Contributing Moving-Average Query to open source. (#6430)

* Contributing Moving-Average Query to open source.

* Fix failing code inspections.

* See if explicit types will invoke the correct comparison function.

* Explicitly remove support for druid.generic.useDefaultValueForNull configuration parameter.

* Update styling and headers for complience.

* Refresh code with latest master changes:

* Remove NullDimensionSelector.
* Apply changes of RequestLogger.
* Apply changes of TimelineServerView.

* Small checkstyle fix.

* Checkstyle fixes.

* Fixing rat errors; Teamcity errors.

* Removing support theta sketches. Will be added back in this pr or a following once DI conflicts with datasketches are resolved.

* Implements some of the review fixes.

* Contributing Moving-Average Query to open source.

* Fix failing code inspections.

* See if explicit types will invoke the correct comparison function.

* Explicitly remove support for druid.generic.useDefaultValueForNull configuration parameter.

* Update styling and headers for complience.

* Refresh code with latest master changes:

* Remove NullDimensionSelector.
* Apply changes of RequestLogger.
* Apply changes of TimelineServerView.

* Small checkstyle fix.

* Checkstyle fixes.

* Fixing rat errors; Teamcity errors.

* Removing support theta sketches. Will be added back in this pr or a following once DI conflicts with datasketches are resolved.

* Implements some of the review fixes.

* More fixes for review.

* More fixes from review.

* MapBasedRow is Unmodifiable. Create new rows instead of modifying existing ones.

* Remove more changes related to datasketches support.

* Refactor BaseAverager startFrom field and add a comment.

* fakeEvents field: Refactor initialization and add comment.

* Rename parameters (tiny change).

* Fix variable name typo in test (JAN_4).

* Fix styling of non camelCase fields.

* Fix Preconditions.checkArgument for cycleSize.

* Add more documentation to RowBucketIterable and other classes.

* key/value comment on in MovingAverageIterable.

* Fix anonymous makeColumnValueSelector returning null.

* Replace IdentityYieldingAccumolator with Yielders.each().

* * internalNext() should return null instead of throwing exception.
* Remove unused variables/prarameters.

* Harden MovingAverageIterableTest (Switch anyOf to exact match).

* Change internalNext() from recursion to iteration; Simplify next() and hasNext().

* Remove unused imports.

* Address review comments.

* Rename fakeEvents to emptyEvents.

* Remove redundant parameter key from computeMovingAverage.

* Check yielder as well in RowBucketIterable#hasNext()

* Fix javadoc.

distribution/pom.xml

@@ -333,7 +333,8 @@
                                         <argument>org.apache.druid.extensions.contrib:druid-time-min-max</argument>
                                         <argument>-c</argument>
                                         <argument>org.apache.druid.extensions.contrib:druid-virtual-columns</argument>
-                                    </arguments>
+                                        <argument>-c</argument>
+                                        <argument>org.apache.druid.extensions.contrib:druid-moving-average-query</argument>                                    </arguments>
                                 </configuration>
                             </execution>
                         </executions>

docs/content/development/extensions-contrib/moving-average-query.md

@@ -0,0 +1,337 @@
+---
+layout: doc_page
+---
+
+<!--
+  ~ Licensed to the Apache Software Foundation (ASF) under one
+  ~ or more contributor license agreements.  See the NOTICE file
+  ~ distributed with this work for additional information
+  ~ regarding copyright ownership.  The ASF licenses this file
+  ~ to you under the Apache License, Version 2.0 (the
+  ~ "License"); you may not use this file except in compliance
+  ~ with the License.  You may obtain a copy of the License at
+  ~
+  ~   http://www.apache.org/licenses/LICENSE-2.0
+  ~
+  ~ Unless required by applicable law or agreed to in writing,
+  ~ software distributed under the License is distributed on an
+  ~ "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+  ~ KIND, either express or implied.  See the License for the
+  ~ specific language governing permissions and limitations
+  ~ under the License.
+  -->
+
+# Moving Average Queries
+
+## Overview
+**Moving Average Query** is an extension which provides support for [Moving Average](https://en.wikipedia.org/wiki/Moving_average) and other Aggregate [Window Functions](https://en.wikibooks.org/wiki/Structured_Query_Language/Window_functions) in Druid queries.
+
+These Aggregate Window Functions consume standard Druid Aggregators and outputs additional windowed aggregates called [Averagers](#averagers).
+
+#### High level algorithm 
+
+Moving Average encapsulates the [groupBy query](../../querying/groupbyquery.html) (Or [timeseries](../../querying/timeseriesquery.html) in case of no dimensions) in order to rely on the maturity of these query types.
+
+It runs the query in two main phases:
+1. Runs an inner [groupBy](../../querying/groupbyquery.html) or [timeseries](../../querying/timeseriesquery.html) query to compute Aggregators (i.e. daily count of events).
+2. Passes over aggregated results in Broker, in order to compute Averagers (i.e. moving 7 day average of the daily count).
+
+#### Main enhancements provided by this extension:
+1. Functionality: Extending druid query functionality (i.e. initial introduction of Window Functions).
+2. Performance: Improving performance of such moving aggregations by eliminating multiple segment scans.
+
+#### Further reading
+[Moving Average](https://en.wikipedia.org/wiki/Moving_average)
+
+[Window Functions](https://en.wikibooks.org/wiki/Structured_Query_Language/Window_functions)
+
+[Analytic Functions](https://cloud.google.com/bigquery/docs/reference/standard-sql/analytic-function-concepts)
+
+
+## Operations
+To use this extension, make sure to [load](../../operations/including-extensions.html) `druid-moving-average-query` only to the Broker.
+
+## Configuration
+There are currently no configuration properties specific to Moving Average.
+
+## Limitations
+* movingAverage is missing support for the following groupBy properties: `subtotalsSpec`, `virtualColumns`.
+* movingAverage is missing support for the following timeseries properties: `descending`.
+* movingAverage is missing support for [SQL-compatible null handling](https://github.com/apache/incubator-druid/issues/4349) (So setting druid.generic.useDefaultValueForNull in configuration will give an error). 
+
+##Query spec:
+* Most properties in the query spec derived from  [groupBy query](../../querying/groupbyquery.html) / [timeseries](../../querying/timeseriesquery.html), see documentation for these query types.
+
+|property|description|required?|
+|--------|-----------|---------|
+|queryType|This String should always be "movingAverage"; this is the first thing Druid looks at to figure out how to interpret the query.|yes|
+|dataSource|A String or Object defining the data source to query, very similar to a table in a relational database. See [DataSource](../../querying/datasource.html) for more information.|yes|
+|dimensions|A JSON list of [DimensionSpec](../../querying/dimensionspecs.html) (Notice that property is optional)|no|
+|limitSpec|See [LimitSpec](../../querying/limitspec.html)|no|
+|having|See [Having](../../querying/having.html)|no|
+|granularity|A period granilarity; See [Period Granularities](../../querying/granularities.html#period-granularities)|yes|
+|filter|See [Filters](../../querying/filters.html)|no|
+|aggregations|Aggregations forms the input to Averagers; See [Aggregations](../../querying/aggregations.html)|yes|
+|postAggregations|Supports only aggregations as input; See [Post Aggregations](../../querying/post-aggregations.html)|no|
+|intervals|A JSON Object representing ISO-8601 Intervals. This defines the time ranges to run the query over.|yes|
+|context|An additional JSON Object which can be used to specify certain flags.|no|
+|averagers|Defines the moving average function; See [Averagers](#averagers)|yes|
+|postAveragers|Support input of both averagers and aggregations; Syntax is identical to postAggregations (See [Post Aggregations](../../querying/post-aggregations.html))|no|
+
+## Averagers
+
+Averagers are used to define the Moving-Average function. Averagers are not limited to an average - they can also provide other types of window functions such as MAX()/MIN().
+
+### Properties
+
+These are properties which are common to all Averagers:
+
+|property|description|required?|
+|--------|-----------|---------|
+|type|Averager type; See [Averager types](#averager-types)|yes|
+|name|Averager name|yes|
+|fieldName|Input name (An aggregation name)|yes|
+|buckets|Number of lookback buckets (time periods), including current one. Must be >0|yes|
+|cycleSize|Cycle size; Used to calculate day-of-week option; See [Cycle size (Day of Week)](#cycle-size-day-of-week)|no, defaults to 1|
+
+
+### Averager types:
+
+* [Standard averagers](#standard-averagers):
+  * doubleMean
+  * doubleMeanNoNulls
+  * doubleMax
+  * doubleMin
+  * longMean
+  * longMeanNoNulls
+  * longMax
+  * longMin
+
+#### Standard averagers
+
+These averagers offer four functions:
+* Mean (Average)
+* MeanNoNulls (Ignores empty buckets).
+* Max
+* Min
+
+**Ignoring nulls**:
+Using a MeanNoNulls averager is useful when the interval starts at the dataset beginning time. 
+In that case, the first records will ignore missing buckets and average won't be artificially low.
+However, this also means that empty days in a sparse dataset will also be ignored.
+
+Example of usage:
+```json
+{ "type" : "doubleMean", "name" : <output_name>, "fieldName": <input_name> }
+```
+
+### Cycle size (Day of Week)
+This optional parameter is used to calculate over a single bucket within each cycle instead of all buckets. 
+A prime example would be weekly buckets, resulting in a Day of Week calculation. (Other examples: Month of year, Hour of day).
+
+I.e. when using these parameters:
+* *granularity*: period=P1D (daily)
+* *buckets*: 28
+* *cycleSize*: 7
+
+Within each output record, the averager will compute the result over the following buckets: current (#0), #7, #14, #21. 
+Whereas without specifying cycleSize it would have computed over all 28 buckets.
+
+## Examples
+
+All examples are based on the Wikipedia dataset provided in the Druid [tutorials](../../tutorials/index.html).
+
+### Basic example
+
+Calculating a 7-buckets moving average for Wikipedia edit deltas.
+
+Query syntax:
+```json
+{
+  "queryType": "movingAverage",
+  "dataSource": "wikipedia",
+  "granularity": {
+    "type": "period",
+    "period": "PT30M"
+  },
+  "intervals": [
+    "2015-09-12T00:00:00Z/2015-09-13T00:00:00Z"
+  ],
+  "aggregations": [
+    {
+      "name": "delta30Min",
+      "fieldName": "delta",
+      "type": "longSum"
+    }
+  ],
+  "averagers": [
+    {
+      "name": "trailing30MinChanges",
+      "fieldName": "delta30Min",
+      "type": "longMean",
+      "buckets": 7
+    }
+  ]
+}
+```
+
+Result:
+```json
+[ {
+   "version" : "v1",
+   "timestamp" : "2015-09-12T00:30:00.000Z",
+   "event" : {
+     "delta30Min" : 30490,
+     "trailing30MinChanges" : 4355.714285714285
+   }
+ }, {
+   "version" : "v1",
+   "timestamp" : "2015-09-12T01:00:00.000Z",
+   "event" : {
+     "delta30Min" : 96526,
+     "trailing30MinChanges" : 18145.14285714286
+   }
+ }, {
+...
+...
+... 
+}, {
+  "version" : "v1",
+  "timestamp" : "2015-09-12T23:00:00.000Z",
+  "event" : {
+    "delta30Min" : 119100,
+    "trailing30MinChanges" : 198697.2857142857
+  }
+}, {
+  "version" : "v1",
+  "timestamp" : "2015-09-12T23:30:00.000Z",
+  "event" : {
+    "delta30Min" : 177882,
+    "trailing30MinChanges" : 193890.0
+  }
+}
+```
+
+### Post averager example
+
+Calculating a 7-buckets moving average for Wikipedia edit deltas, plus a ratio between the current period and the moving average.
+
+Query syntax:
+```json
+{
+  "queryType": "movingAverage",
+  "dataSource": "wikipedia",
+  "granularity": {
+    "type": "period",
+    "period": "PT30M"
+  },
+  "intervals": [
+    "2015-09-12T22:00:00Z/2015-09-13T00:00:00Z"
+  ],
+  "aggregations": [
+    {
+      "name": "delta30Min",
+      "fieldName": "delta",
+      "type": "longSum"
+    }
+  ],
+  "averagers": [
+    {
+      "name": "trailing30MinChanges",
+      "fieldName": "delta30Min",
+      "type": "longMean",
+      "buckets": 7
+    }
+  ],
+  "postAveragers" : [
+    {
+      "name": "ratioTrailing30MinChanges",
+      "type": "arithmetic",
+      "fn": "/",
+      "fields": [
+        {
+          "type": "fieldAccess",
+          "fieldName": "delta30Min"
+        },
+        {
+          "type": "fieldAccess",
+          "fieldName": "trailing30MinChanges"
+        }
+      ]
+    }
+  ]
+}
+```
+
+Result:
+```json
+[ {
+  "version" : "v1",
+  "timestamp" : "2015-09-12T22:00:00.000Z",
+  "event" : {
+    "delta30Min" : 144269,
+    "trailing30MinChanges" : 204088.14285714287,
+    "ratioTrailing30MinChanges" : 0.7068955500319539
+  }
+}, {
+  "version" : "v1",
+  "timestamp" : "2015-09-12T22:30:00.000Z",
+  "event" : {
+    "delta30Min" : 242860,
+    "trailing30MinChanges" : 214031.57142857142,
+    "ratioTrailing30MinChanges" : 1.134692411867141
+  }
+}, {
+  "version" : "v1",
+  "timestamp" : "2015-09-12T23:00:00.000Z",
+  "event" : {
+    "delta30Min" : 119100,
+    "trailing30MinChanges" : 198697.2857142857,
+    "ratioTrailing30MinChanges" : 0.5994042624782422
+  }
+}, {
+  "version" : "v1",
+  "timestamp" : "2015-09-12T23:30:00.000Z",
+  "event" : {
+    "delta30Min" : 177882,
+    "trailing30MinChanges" : 193890.0,
+    "ratioTrailing30MinChanges" : 0.9174377224199288
+  }
+} ]
+```
+
+
+### Cycle size example
+
+Calculating an average of every first 10-minutes of the last 3 hours:
+
+Query syntax:
+```json
+{
+  "queryType": "movingAverage",
+  "dataSource": "wikipedia",
+  "granularity": {
+    "type": "period",
+    "period": "PT10M"
+  },
+  "intervals": [
+    "2015-09-12T00:00:00Z/2015-09-13T00:00:00Z"
+  ],
+  "aggregations": [
+    {
+      "name": "delta10Min",
+      "fieldName": "delta",
+      "type": "doubleSum"
+    }
+  ],
+  "averagers": [
+    {
+      "name": "trailing10MinPerHourChanges",
+      "fieldName": "delta10Min",
+      "type": "doubleMeanNoNulls",
+      "buckets": 18,
+      "cycleSize": 6
+    }
+  ]
+}
+```

docs/content/development/extensions.md

@@ -95,6 +95,7 @@ All of these community extensions can be downloaded using *pull-deps* with the c
 |kafka-emitter|Kafka metrics emitter|[link](../development/extensions-contrib/kafka-emitter.html)|
 |druid-thrift-extensions|Support thrift ingestion |[link](../development/extensions-contrib/thrift.html)|
 |druid-opentsdb-emitter|OpenTSDB metrics emitter |[link](../development/extensions-contrib/opentsdb-emitter.html)|
+|druid-moving-average-query|Support for [Moving Average](https://en.wikipedia.org/wiki/Moving_average) and other Aggregate [Window Functions](https://en.wikibooks.org/wiki/Structured_Query_Language/Window_functions) in Druid queries.|[link](../development/extensions-contrib/moving-average-query.html)|
 
 ## Promoting Community Extension to Core Extension
 

extensions-contrib/moving-average-query/README.md

@@ -0,0 +1,29 @@
+<!--
+  ~ Licensed to the Apache Software Foundation (ASF) under one
+  ~ or more contributor license agreements.  See the NOTICE file
+  ~ distributed with this work for additional information
+  ~ regarding copyright ownership.  The ASF licenses this file
+  ~ to you under the Apache License, Version 2.0 (the
+  ~ "License"); you may not use this file except in compliance
+  ~ with the License.  You may obtain a copy of the License at
+  ~
+  ~   http://www.apache.org/licenses/LICENSE-2.0
+  ~
+  ~ Unless required by applicable law or agreed to in writing,
+  ~ software distributed under the License is distributed on an
+  ~ "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+  ~ KIND, either express or implied.  See the License for the
+  ~ specific language governing permissions and limitations
+  ~ under the License.
+  -->
+
+druid-moving-average-query
+=============
+
+Overview
+=============
+**Moving Average Query** is an extension which provides support for [Moving Average](https://en.wikipedia.org/wiki/Moving_average) and other Aggregate [Window Functions](https://en.wikibooks.org/wiki/Structured_Query_Language/Window_functions) in Druid queries.
+
+Documentation 
+=============
+See the druid.io website or under [Druid Github Repo](https://github.com/apache/incubator-druid/tree/master/docs/content/development/extensions-contrib/moving-average-query.md).

extensions-contrib/moving-average-query/pom.xml

@@ -0,0 +1,83 @@
+<?xml version="1.0"?>
+<!--
+  ~ Licensed to the Apache Software Foundation (ASF) under one
+  ~ or more contributor license agreements.  See the NOTICE file
+  ~ distributed with this work for additional information
+  ~ regarding copyright ownership.  The ASF licenses this file
+  ~ to you under the Apache License, Version 2.0 (the
+  ~ "License"); you may not use this file except in compliance
+  ~ with the License.  You may obtain a copy of the License at
+  ~
+  ~   http://www.apache.org/licenses/LICENSE-2.0
+  ~
+  ~ Unless required by applicable law or agreed to in writing,
+  ~ software distributed under the License is distributed on an
+  ~ "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+  ~ KIND, either express or implied.  See the License for the
+  ~ specific language governing permissions and limitations
+  ~ under the License.
+  -->
+<project xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd" xmlns="http://maven.apache.org/POM/4.0.0"
+         xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
+  <modelVersion>4.0.0</modelVersion>
+
+
+  <parent>
+    <groupId>org.apache.druid</groupId>
+    <artifactId>druid</artifactId>
+    <version>0.15.0-incubating-SNAPSHOT</version>
+    <relativePath>../../pom.xml</relativePath>
+  </parent>
+
+  <groupId>org.apache.druid.extensions.contrib</groupId>
+  <artifactId>druid-moving-average-query</artifactId>
+  <name>druid-moving-average-query</name>
+
+  <properties>
+    <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
+  </properties>
+
+  <dependencies>
+    <dependency>
+      <groupId>org.jmockit</groupId>
+      <artifactId>jmockit</artifactId>
+      <version>1.25</version>
+      <scope>test</scope>
+    </dependency>
+    <dependency>
+      <groupId>junit</groupId>
+      <artifactId>junit</artifactId>
+      <scope>test</scope>
+    </dependency>
+    <dependency>
+      <groupId>org.hamcrest</groupId>
+      <artifactId>hamcrest-library</artifactId>
+      <version>1.3</version>
+      <scope>test</scope>
+    </dependency>
+    <dependency>
+      <groupId>com.fasterxml.jackson.dataformat</groupId>
+      <artifactId>jackson-dataformat-yaml</artifactId>
+      <version>2.8.3</version>
+      <scope>test</scope>
+    </dependency>
+    <dependency>
+      <groupId>org.apache.druid</groupId>
+      <artifactId>druid-core</artifactId>
+      <version>${project.parent.version}</version>
+      <scope>provided</scope>
+    </dependency>
+    <dependency>
+      <groupId>org.apache.druid</groupId>
+      <artifactId>druid-processing</artifactId>
+      <version>${project.parent.version}</version>
+      <scope>provided</scope>
+    </dependency>
+    <dependency>
+      <groupId>org.apache.druid</groupId>
+      <artifactId>druid-server</artifactId>
+      <version>${project.parent.version}</version>
+      <scope>provided</scope>
+    </dependency>
+  </dependencies>
+</project>

extensions-contrib/moving-average-query/src/main/java/org/apache/druid/query/movingaverage/AveragerFactoryWrapper.java

@@ -0,0 +1,179 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage;
+
+import org.apache.druid.query.aggregation.Aggregator;
+import org.apache.druid.query.aggregation.AggregatorFactory;
+import org.apache.druid.query.aggregation.BufferAggregator;
+import org.apache.druid.query.movingaverage.averagers.AveragerFactory;
+import org.apache.druid.segment.ColumnSelectorFactory;
+
+import java.util.Comparator;
+import java.util.List;
+
+/**
+ * A wrapper around averagers that makes them appear to be aggregators.
+ * This is necessary purely to allow existing common druid code that only knows
+ * about aggregators to work with the MovingAverageQuery query as well.
+ *
+ * NOTE: The {@link AggregatorFactory} abstract class is only partially extended.
+ * Most methods are not implemented and throw {@link UnsupportedOperationException} if called.
+ * This is becsuse these methods are invalid for the AveragerFactoryWrapper.
+ *
+ * @param <T> Result type
+ * @param <R> Finalized Result type
+ */
+public class AveragerFactoryWrapper<T, R> extends AggregatorFactory
+{
+
+  private final AveragerFactory<T, R> af;
+  private final String prefix;
+
+  /**
+   * Simple constructor
+   *
+   * @param af
+   * @param prefix
+   */
+  public AveragerFactoryWrapper(AveragerFactory<T, R> af, String prefix)
+  {
+    this.af = af;
+    this.prefix = prefix;
+  }
+
+  /**
+   * Not implemented. Throws UnsupportedOperationException.
+   */
+  @Override
+  public Aggregator factorize(ColumnSelectorFactory metricFactory) throws UnsupportedOperationException
+  {
+    throw new UnsupportedOperationException("Invalid operation for AveragerFactoryWrapper.");
+  }
+
+  /**
+   * Not implemented. Throws UnsupportedOperationException.
+   */
+  @Override
+  public BufferAggregator factorizeBuffered(ColumnSelectorFactory metricFactory)
+  {
+    throw new UnsupportedOperationException("Invalid operation for AveragerFactoryWrapper.");
+  }
+
+  /* (non-Javadoc)
+   * @see org.apache.druid.query.aggregation.AggregatorFactory#getComparator()
+   */
+  @Override
+  public Comparator<?> getComparator()
+  {
+    return af.getComparator();
+  }
+
+  /**
+   * Not implemented. Throws UnsupportedOperationException.
+   */
+  @Override
+  public Object combine(Object lhs, Object rhs)
+  {
+    throw new UnsupportedOperationException("Invalid operation for AveragerFactoryWrapper.");
+  }
+
+  /**
+   * Not implemented. Throws UnsupportedOperationException.
+   */
+  @Override
+  public AggregatorFactory getCombiningFactory()
+  {
+    throw new UnsupportedOperationException("Invalid operation for AveragerFactoryWrapper.");
+  }
+
+  /**
+   * Not implemented. Throws UnsupportedOperationException.
+   */
+  @Override
+  public List<AggregatorFactory> getRequiredColumns()
+  {
+    throw new UnsupportedOperationException("Invalid operation for AveragerFactoryWrapper.");
+  }
+
+  /**
+   * Not implemented. Throws UnsupportedOperationException.
+   */
+  @Override
+  public Object deserialize(Object object)
+  {
+    throw new UnsupportedOperationException("Invalid operation for AveragerFactoryWrapper.");
+  }
+
+  /**
+   * Not implemented. Throws UnsupportedOperationException.
+   */
+  @SuppressWarnings("unchecked")
+  @Override
+  public Object finalizeComputation(Object object)
+  {
+    return af.finalizeComputation((T) object);
+  }
+
+  /* (non-Javadoc)
+   * @see org.apache.druid.query.aggregation.AggregatorFactory#getName()
+   */
+  @Override
+  public String getName()
+  {
+    return prefix + af.getName();
+  }
+
+  /**
+   * Not implemented. Throws UnsupportedOperationException.
+   */
+  @Override
+  public List<String> requiredFields()
+  {
+    throw new UnsupportedOperationException("Invalid operation for AveragerFactoryWrapper.");
+  }
+
+  /**
+   * Not implemented. Throws UnsupportedOperationException.
+   */
+  @Override
+  public byte[] getCacheKey()
+  {
+    throw new UnsupportedOperationException("Invalid operation for AveragerFactoryWrapper.");
+  }
+
+  /**
+   * Not implemented. Throws UnsupportedOperationException.
+   */
+  @Override
+  public String getTypeName()
+  {
+    throw new UnsupportedOperationException("Invalid operation for AveragerFactoryWrapper.");
+  }
+
+  /**
+   * Not implemented. Throws UnsupportedOperationException.
+   */
+  @Override
+  public int getMaxIntermediateSize()
+  {
+    throw new UnsupportedOperationException("Invalid operation for AveragerFactoryWrapper.");
+  }
+
+}

extensions-contrib/moving-average-query/src/main/java/org/apache/druid/query/movingaverage/BucketingAccumulator.java

@@ -0,0 +1,68 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage;
+
+import org.apache.druid.data.input.Row;
+import org.apache.druid.java.util.common.guava.YieldingAccumulator;
+
+import java.util.ArrayList;
+import java.util.List;
+
+/**
+ * Groups all the rows for a specific period together.
+ * Rows of each period are placed in a single {@link RowBucket} (timed through the dateTime field).
+ * (Assumpltion: Input arrives sorted by timestamp).
+ */
+public class BucketingAccumulator extends YieldingAccumulator<RowBucket, Row>
+{
+
+  /* (non-Javadoc)
+   * @see YieldingAccumulator#accumulate(java.lang.Object, java.lang.Object)
+   */
+  @Override
+  public RowBucket accumulate(RowBucket accumulated, Row in)
+  {
+    List<Row> rows;
+
+    if (accumulated == null) {
+      // first row, initializing
+      rows = new ArrayList<>();
+      accumulated = new RowBucket(in.getTimestamp(), rows);
+    } else if (accumulated.getNextBucket() != null) {
+      accumulated = accumulated.getNextBucket();
+    }
+
+    if (!accumulated.getDateTime().equals(in.getTimestamp())) {
+      // day change detected
+      rows = new ArrayList<>();
+      rows.add(in);
+      RowBucket nextBucket = new RowBucket(in.getTimestamp(), rows);
+      accumulated.setNextBucket(nextBucket);
+      yield();
+    } else {
+      // still on the same day
+      rows = accumulated.getRows();
+      rows.add(in);
+    }
+
+    return accumulated;
+  }
+
+}

extensions-contrib/moving-average-query/src/main/java/org/apache/druid/query/movingaverage/DefaultMovingAverageQueryMetrics.java

@@ -0,0 +1,62 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage;
+
+import com.fasterxml.jackson.databind.ObjectMapper;
+import org.apache.druid.query.DefaultQueryMetrics;
+import org.apache.druid.query.DruidMetrics;
+
+public class DefaultMovingAverageQueryMetrics extends DefaultQueryMetrics<MovingAverageQuery> implements
+    MovingAverageQueryMetrics
+{
+
+  public DefaultMovingAverageQueryMetrics(ObjectMapper jsonMapper)
+  {
+    super(jsonMapper);
+  }
+
+  @Override
+  public void query(MovingAverageQuery query)
+  {
+    super.query(query);
+    numDimensions(query);
+    numMetrics(query);
+    numComplexMetrics(query);
+  }
+
+  @Override
+  public void numDimensions(MovingAverageQuery query)
+  {
+    setDimension("numDimensions", String.valueOf(query.getDimensions().size()));
+  }
+
+  @Override
+  public void numMetrics(MovingAverageQuery query)
+  {
+    setDimension("numMetrics", String.valueOf(query.getAggregatorSpecs().size()));
+  }
+
+  @Override
+  public void numComplexMetrics(MovingAverageQuery query)
+  {
+    int numComplexAggs = DruidMetrics.findNumComplexAggs(query.getAggregatorSpecs());
+    setDimension("numComplexMetrics", String.valueOf(numComplexAggs));
+  }
+}

extensions-contrib/moving-average-query/src/main/java/org/apache/druid/query/movingaverage/DefaultMovingAverageQueryMetricsFactory.java

@@ -0,0 +1,59 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage;
+
+import com.fasterxml.jackson.databind.ObjectMapper;
+import com.google.common.annotations.VisibleForTesting;
+import com.google.inject.Inject;
+import org.apache.druid.guice.LazySingleton;
+import org.apache.druid.guice.annotations.Json;
+import org.apache.druid.jackson.DefaultObjectMapper;
+
+@LazySingleton
+public class DefaultMovingAverageQueryMetricsFactory implements MovingAverageQueryMetricsFactory
+{
+
+  private static final MovingAverageQueryMetricsFactory INSTANCE =
+      new DefaultMovingAverageQueryMetricsFactory(new DefaultObjectMapper());
+
+  /**
+   * Should be used only in tests, directly or indirectly (via {@link
+   * MovingAverageQueryToolChest#MovingAverageQueryToolChest}).
+   */
+  @VisibleForTesting
+  public static MovingAverageQueryMetricsFactory instance()
+  {
+    return INSTANCE;
+  }
+
+  private final ObjectMapper jsonMapper;
+
+  @Inject
+  public DefaultMovingAverageQueryMetricsFactory(@Json ObjectMapper jsonMapper)
+  {
+    this.jsonMapper = jsonMapper;
+  }
+
+  @Override
+  public MovingAverageQueryMetrics makeMetrics()
+  {
+    return new DefaultMovingAverageQueryMetrics(jsonMapper);
+  }
+}

extensions-contrib/moving-average-query/src/main/java/org/apache/druid/query/movingaverage/MovingAverageHelper.java

@@ -0,0 +1,53 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage;
+
+import org.apache.druid.data.input.MapBasedRow;
+import org.apache.druid.data.input.Row;
+import org.apache.druid.query.dimension.DimensionSpec;
+
+import java.util.Collection;
+import java.util.HashMap;
+import java.util.Map;
+
+public class MovingAverageHelper
+{
+
+  /**
+   * @param dimensions A list of DimensionSpec in the specified in the query
+   * @param row        The Row to be used for looking up dimension values
+   *
+   * @return A Map of dimension/value from the row
+   */
+
+  public static Map<String, Object> getDimKeyFromRow(Collection<DimensionSpec> dimensions, Row row)
+  {
+
+    Map<String, Object> key = new HashMap<>();
+    Map<String, Object> event = ((MapBasedRow) row).getEvent();
+
+    for (DimensionSpec dimension : dimensions) {
+      key.put(dimension.getOutputName(), event.get(dimension.getOutputName()));
+    }
+
+    return key;
+  }
+
+}

extensions-contrib/moving-average-query/src/main/java/org/apache/druid/query/movingaverage/MovingAverageIterable.java

@@ -0,0 +1,312 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage;
+
+import org.apache.druid.data.input.MapBasedRow;
+import org.apache.druid.data.input.Row;
+import org.apache.druid.java.util.common.guava.Sequence;
+import org.apache.druid.java.util.common.guava.Yielder;
+import org.apache.druid.java.util.common.guava.Yielders;
+import org.apache.druid.query.aggregation.Aggregator;
+import org.apache.druid.query.aggregation.AggregatorFactory;
+import org.apache.druid.query.aggregation.PostAggregator;
+import org.apache.druid.query.dimension.DimensionSpec;
+import org.apache.druid.query.movingaverage.averagers.Averager;
+import org.apache.druid.query.movingaverage.averagers.AveragerFactory;
+import org.apache.druid.segment.ColumnSelectorFactory;
+import org.apache.druid.segment.ColumnValueSelector;
+import org.apache.druid.segment.DimensionSelector;
+import org.apache.druid.segment.NilColumnValueSelector;
+import org.apache.druid.segment.column.ColumnCapabilities;
+
+import javax.annotation.Nonnull;
+import javax.annotation.Nullable;
+import java.util.HashMap;
+import java.util.HashSet;
+import java.util.Iterator;
+import java.util.LinkedHashMap;
+import java.util.List;
+import java.util.Map;
+import java.util.NoSuchElementException;
+import java.util.Set;
+import java.util.stream.Collectors;
+
+/**
+ * {@link MovingAverageIterable} iterates over days {@link RowBucket}, producing rows for each dimension combination,
+ * filling in missing entries with "empty" rows so that the averaging buckets have enough data to operate on.
+ * It then computes the moving average on the buckets and returns the row.
+ * See computeMovingAverage for more details.
+ */
+public class MovingAverageIterable implements Iterable<Row>
+{
+
+  private final Sequence<RowBucket> seq;
+  private final List<DimensionSpec> dims;
+  private final List<AveragerFactory<?, ?>> factories;
+  private final Map<String, PostAggregator> postAggMap;
+  private final Map<String, AggregatorFactory> aggMap;
+  private final Map<String, Object> emptyEvents;
+
+  public MovingAverageIterable(
+      Sequence<RowBucket> buckets,
+      List<DimensionSpec> dims,
+      List<AveragerFactory<?, ?>> factories,
+      List<PostAggregator> postAggList,
+      List<AggregatorFactory> aggList
+  )
+  {
+    this.dims = dims;
+    this.factories = factories;
+    this.seq = buckets;
+
+    postAggMap = postAggList.stream().collect(Collectors.toMap(postAgg -> postAgg.getName(), postAgg -> postAgg));
+    aggMap = aggList.stream().collect(Collectors.toMap(agg -> agg.getName(), agg -> agg));
+    emptyEvents = generateEmptyEventsFromAggregators(aggMap, postAggMap);
+  }
+
+  // Build a list of empty events from Aggregators/PostAggregators to be used by Iterator to build fake rows.
+  // These fake rows will be used by computeMovingAverage() in skip=true mode.
+  // See emptyEventsCopy in internalNext() and computeMovingAverage() documentation.
+  private Map<String, Object> generateEmptyEventsFromAggregators(Map<String, AggregatorFactory> aggMap,
+                                                                 Map<String, PostAggregator> postAggMap)
+  {
+    Map<String, Object> emptyEvents = new LinkedHashMap<>();
+    aggMap.values().forEach(agg -> {
+      Aggregator aggFactorized = agg.factorize(getEmptyColumnSelectorFactory());
+      emptyEvents.put(agg.getName(), aggFactorized.get());
+    });
+    postAggMap.values().forEach(postAgg -> emptyEvents.put(postAgg.getName(), postAgg.compute(emptyEvents)));
+    return emptyEvents;
+  }
+
+  @Nonnull
+  private ColumnSelectorFactory getEmptyColumnSelectorFactory()
+  {
+    return new ColumnSelectorFactory()
+    {
+      @Override
+      public DimensionSelector makeDimensionSelector(DimensionSpec dimensionSpec)
+      {
+        // Generating empty records while aggregating on Filtered aggregators requires a dimension selector
+        // for initialization.  This dimension selector is not actually used for generating values
+        return DimensionSelector.constant(null);
+      }
+
+      @Override
+      public ColumnValueSelector makeColumnValueSelector(String s)
+      {
+        return NilColumnValueSelector.instance();
+      }
+
+      @Override
+      public ColumnCapabilities getColumnCapabilities(String s)
+      {
+        return null;
+      }
+    };
+  }
+
+  /* (non-Javadoc)
+   * @see java.lang.Iterable#iterator()
+   */
+  @Override
+  public Iterator<Row> iterator()
+  {
+    return new MovingAverageIterator(seq, dims, factories, emptyEvents, aggMap);
+  }
+
+  static class MovingAverageIterator implements Iterator<Row>
+  {
+
+    private final List<DimensionSpec> dims;
+    // Key: Row's dimension set. Value: Averager. See MovingAverageIterator#computeMovingAverage for more details.
+    private final Map<Map<String, Object>, List<Averager<?>>> averagers = new HashMap<>();
+    private final List<AveragerFactory<?, ?>> averagerFactories;
+
+    private Yielder<RowBucket> yielder;
+    private RowBucket cache = null;
+    private Iterator<Row> cacheIter;
+    private Iterator<Map<String, Object>> averagersKeysIter;
+    private Set<Map<String, Object>> seenKeys = new HashSet<>();
+    private Row saveNext;
+    private Map<String, AggregatorFactory> aggMap;
+    private Map<String, Object> emptyEvents;
+
+    public MovingAverageIterator(
+        Sequence<RowBucket> rows,
+        List<DimensionSpec> dims,
+        List<AveragerFactory<?, ?>> averagerFactories,
+        Map<String, Object> emptyEvents,
+        Map<String, AggregatorFactory> aggMap
+    )
+    {
+      this.dims = dims;
+      this.averagerFactories = averagerFactories;
+      this.emptyEvents = emptyEvents;
+      this.aggMap = aggMap;
+
+      yielder = Yielders.each(rows);
+    }
+
+    /* (non-Javadoc)
+     * @see java.util.Iterator#hasNext()
+     */
+    @Override
+    public boolean hasNext()
+    {
+      if (saveNext != null) {
+        return true;
+      }
+
+      saveNext = internalNext();
+      return (saveNext != null);
+    }
+
+    /* (non-Javadoc)
+     * @see java.util.Iterator#next()
+     */
+    @Override
+    public Row next()
+    {
+      if (!hasNext()) {
+        throw new NoSuchElementException();
+      }
+
+      Row retVal = saveNext;
+      saveNext = null;
+      return retVal;
+    }
+
+    private Row internalNext()
+    {
+      // Iterate until there is a row to return or Yielder is exahusted, in such a case return null.
+      // This is used in order to skip empty buckets (iterate to the next one).
+      while (true) {
+        if (cache == null && !yielder.isDone()) {
+          cache = yielder.get();
+          yielder = yielder.next(cache);
+
+          cacheIter = cache.getRows().iterator();
+        }
+
+        Row r;
+
+        // return rows from the cached RowBucket
+        if (cacheIter != null) {
+          if (cacheIter.hasNext()) {
+            r = cacheIter.next();
+            // Convert full event (key + metrics) to key
+            Map<String, Object> key = MovingAverageHelper.getDimKeyFromRow(dims, r);
+            seenKeys.add(key);
+            r = computeMovingAverage((MapBasedRow) r, false);
+            if (r != null) {
+              return r;
+            } else {
+              throw new NoSuchElementException();
+            }
+          } else {
+            Set<Map<String, Object>> averagerKeys = new HashSet<>(averagers.keySet());
+            averagerKeys.removeAll(seenKeys);
+            averagersKeysIter = averagerKeys.iterator();
+            cacheIter = null;
+          }
+        }
+
+        // return empty rows for unseen dimension combinations
+        if (averagersKeysIter != null) {
+          while (averagersKeysIter.hasNext()) {
+            Map<String, Object> dims = averagersKeysIter.next();
+            Map<String, Object> emptyEventsCopy = new HashMap<>(emptyEvents);
+
+            // Convert key to a full dummy event (key + dummy metrics).
+            dims.forEach((dim, value) -> emptyEventsCopy.put(dim, value));
+
+            r = computeMovingAverage(new MapBasedRow(cache.getDateTime(), emptyEventsCopy), true);
+            if (r != null) {
+              return r;
+            }
+          }
+
+          seenKeys.clear();
+          averagersKeysIter = null;
+          cache = null;
+        }
+
+        if (cacheIter == null && yielder.isDone()) {
+          // we should never get here. For some reason, there is
+          // no more work to do, so continuing to iterate will infinite loop
+          return null;
+        }
+      }
+    }
+
+    /**
+     * Compute and add any moving average columns.
+     *
+     * <p>Normally, the row passed in will be added to all the {@link Averager}'s and then results pulled
+     * from each averager. If skip is true, then the incoming row is actually a dummy value due to
+     * no data being present for this dimension combination in the current bucket. When this happens,
+     * {@link Averager#skip()} should be called instead of {@link Averager#addElement(Map, Map)}()} to force proper
+     * decaying of the average values.
+     *
+     * <p>Usually, the contents of key will be contained by the row R being passed in, but in the case of a
+     * dummy row, it's possible that the dimensions will be known but the row empty. Hence, the values are
+     * passed as two separate arguments.
+     *
+     * @param r    The Row to operate on
+     * @param skip Indicates whether skip or add should be called
+     *
+     * @return The updated row containing averager results, or null if no averagers computed a result
+     */
+    @Nullable
+    private Row computeMovingAverage(MapBasedRow r, boolean skip)
+    {
+      Map<String, Object> event = r.getEvent();
+      Map<String, Object> result = new HashMap<>(event);
+      Map<String, Object> key = MovingAverageHelper.getDimKeyFromRow(dims, r);
+
+      List<Averager<?>> avg = averagers.get(key);
+
+      // Initialize key's averagers.
+      if (avg == null) {
+        avg = averagerFactories.stream().map(af -> af.createAverager()).collect(Collectors.toList());
+        averagers.put(key, avg);
+      }
+
+      if (!skip) {
+        avg.forEach(af -> af.addElement(event, aggMap));
+      } else {
+        avg.forEach(af -> af.skip());
+      }
+
+      avg.forEach(af -> result.put(af.getName(), af.getResult()));
+
+      // At least one non-dimension value must be in the record for it to be valid.
+      if (result.entrySet().stream().anyMatch(e -> !key.containsKey(e.getKey()) && e.getValue() != null)) {
+        result.putAll(event);
+        return new MapBasedRow(r.getTimestamp(), result);
+      } else {
+        // No averagers returned anything. All buckets must be empty.
+        // skip this row.
+        return null;
+      }
+    }
+  }
+}

extensions-contrib/moving-average-query/src/main/java/org/apache/druid/query/movingaverage/MovingAverageQuery.java

@@ -0,0 +1,378 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage;
+
+
+import com.fasterxml.jackson.annotation.JsonCreator;
+import com.fasterxml.jackson.annotation.JsonIgnore;
+import com.fasterxml.jackson.annotation.JsonProperty;
+import com.fasterxml.jackson.annotation.JsonTypeName;
+import com.google.common.base.Function;
+import com.google.common.base.Functions;
+import com.google.common.base.Preconditions;
+import com.google.common.base.Predicate;
+import com.google.common.collect.ImmutableList;
+import org.apache.druid.common.config.NullHandling;
+import org.apache.druid.data.input.Row;
+import org.apache.druid.java.util.common.IAE;
+import org.apache.druid.java.util.common.granularity.Granularity;
+import org.apache.druid.java.util.common.guava.Sequence;
+import org.apache.druid.java.util.common.guava.Sequences;
+import org.apache.druid.query.BaseQuery;
+import org.apache.druid.query.DataSource;
+import org.apache.druid.query.Query;
+import org.apache.druid.query.aggregation.AggregatorFactory;
+import org.apache.druid.query.aggregation.PostAggregator;
+import org.apache.druid.query.dimension.DimensionSpec;
+import org.apache.druid.query.filter.DimFilter;
+import org.apache.druid.query.groupby.having.HavingSpec;
+import org.apache.druid.query.groupby.orderby.LimitSpec;
+import org.apache.druid.query.groupby.orderby.NoopLimitSpec;
+import org.apache.druid.query.movingaverage.averagers.AveragerFactory;
+import org.apache.druid.query.spec.QuerySegmentSpec;
+
+import java.util.ArrayList;
+import java.util.HashSet;
+import java.util.List;
+import java.util.Map;
+import java.util.Set;
+
+/**
+ * Class that defines druid MovingAverage query fields
+ */
+@JsonTypeName("movingAverage")
+public class MovingAverageQuery extends BaseQuery<Row>
+{
+
+  public static final String MOVING_AVG_QUERY_TYPE = "movingAverage";
+  public static final String CTX_KEY_SORT_BY_DIMS_FIRST = "sortByDimsFirst";
+
+  private final LimitSpec limitSpec;
+  private final HavingSpec havingSpec;
+  private final DimFilter dimFilter;
+  private final Function<Sequence<Row>, Sequence<Row>> limitFn;
+  private final Granularity granularity;
+  private final List<DimensionSpec> dimensions;
+  private final List<AggregatorFactory> aggregatorSpecs;
+  private final List<PostAggregator> postAggregatorSpecs;
+  private final List<AveragerFactory<?, ?>> averagerSpecs;
+  private final List<PostAggregator> postAveragerSpecs;
+
+  @JsonCreator
+  public MovingAverageQuery(
+      @JsonProperty("dataSource") DataSource dataSource,
+      @JsonProperty("intervals") QuerySegmentSpec querySegmentSpec,
+      @JsonProperty("filter") DimFilter dimFilter,
+      @JsonProperty("granularity") Granularity granularity,
+      @JsonProperty("dimensions") List<DimensionSpec> dimensions,
+      @JsonProperty("aggregations") List<AggregatorFactory> aggregatorSpecs,
+      @JsonProperty("postAggregations") List<PostAggregator> postAggregatorSpecs,
+      @JsonProperty("having") HavingSpec havingSpec,
+      @JsonProperty("averagers") List<AveragerFactory<?, ?>> averagerSpecs,
+      @JsonProperty("postAveragers") List<PostAggregator> postAveragerSpecs,
+      @JsonProperty("limitSpec") LimitSpec limitSpec,
+      @JsonProperty("context") Map<String, Object> context
+  )
+  {
+    super(dataSource, querySegmentSpec, false, context);
+
+    //TBD: Implement null awareness to respect the contract of this flag.
+    Preconditions.checkArgument(NullHandling.replaceWithDefault(), "movingAverage does not support druid.generic.useDefaultValueForNull=false");
+
+    this.dimFilter = dimFilter;
+    this.granularity = granularity;
+    this.dimensions = dimensions == null ? ImmutableList.of() : dimensions;
+    for (DimensionSpec spec : this.dimensions) {
+      Preconditions.checkArgument(spec != null, "dimensions has null DimensionSpec");
+    }
+    this.aggregatorSpecs = aggregatorSpecs == null ? ImmutableList.of() : aggregatorSpecs;
+    this.postAggregatorSpecs = postAggregatorSpecs == null ? ImmutableList.of() : postAggregatorSpecs;
+    this.averagerSpecs = averagerSpecs == null ? ImmutableList.of() : averagerSpecs;
+    this.postAveragerSpecs = postAveragerSpecs == null ? ImmutableList.of() : postAveragerSpecs;
+    this.havingSpec = havingSpec;
+    this.limitSpec = (limitSpec == null) ? NoopLimitSpec.INSTANCE : limitSpec;
+
+    Preconditions.checkNotNull(this.granularity, "Must specify a granularity");
+
+    verifyOutputNames(this.dimensions, this.aggregatorSpecs, this.postAggregatorSpecs);
+
+    // build combined list of aggregators and averagers so that limit spec building is happy
+    List<AggregatorFactory> combinedAggregatorSpecs = new ArrayList<>();
+    combinedAggregatorSpecs.addAll(this.aggregatorSpecs);
+    for (AveragerFactory<?, ?> avg : this.averagerSpecs) {
+      combinedAggregatorSpecs.add(new AveragerFactoryWrapper(avg, ""));
+    }
+
+    Function<Sequence<Row>, Sequence<Row>> postProcFn =
+        this.limitSpec.build(
+            this.dimensions,
+            combinedAggregatorSpecs,
+            this.postAggregatorSpecs,
+            this.granularity,
+            getContextSortByDimsFirst()
+        );
+
+    if (havingSpec != null) {
+      postProcFn = Functions.compose(
+          postProcFn,
+          new Function<Sequence<Row>, Sequence<Row>>()
+          {
+            @Override
+            public Sequence<Row> apply(Sequence<Row> input)
+            {
+              return Sequences.filter(
+                  input,
+                  new Predicate<Row>()
+                  {
+                    @Override
+                    public boolean apply(Row input)
+                    {
+                      return MovingAverageQuery.this.havingSpec.eval(input);
+                    }
+                  }
+              );
+            }
+          }
+      );
+    }
+
+    this.limitFn = postProcFn;
+
+  }
+
+  private static void verifyOutputNames(
+      List<DimensionSpec> dimensions,
+      List<AggregatorFactory> aggregators,
+      List<PostAggregator> postAggregators
+  )
+  {
+
+    final Set<String> outputNames = new HashSet<>();
+    for (DimensionSpec dimension : dimensions) {
+      if (!outputNames.add(dimension.getOutputName())) {
+        throw new IAE("Duplicate output name[%s]", dimension.getOutputName());
+      }
+    }
+
+    for (AggregatorFactory aggregator : aggregators) {
+      if (!outputNames.add(aggregator.getName())) {
+        throw new IAE("Duplicate output name[%s]", aggregator.getName());
+      }
+    }
+
+    for (PostAggregator postAggregator : postAggregators) {
+      if (!outputNames.add(postAggregator.getName())) {
+        throw new IAE("Duplicate output name[%s]", postAggregator.getName());
+      }
+    }
+  }
+
+  /**
+   * A private constructor that avoids all of the various state checks.  Used by the with*() methods where the checks
+   * have already passed in order for the object to exist.
+   */
+  private MovingAverageQuery(
+      DataSource dataSource,
+      QuerySegmentSpec querySegmentSpec,
+      DimFilter dimFilter,
+      Granularity granularity,
+      List<DimensionSpec> dimensions,
+      List<AggregatorFactory> aggregatorSpecs,
+      List<AveragerFactory<?, ?>> averagerSpecs,
+      List<PostAggregator> postAggregatorSpecs,
+      List<PostAggregator> postAveragerSpecs,
+      HavingSpec havingSpec,
+      LimitSpec orderBySpec,
+      Function<Sequence<Row>, Sequence<Row>> limitFn,
+      Map<String, Object> context
+  )
+  {
+    super(dataSource, querySegmentSpec, false, context);
+
+    this.dimFilter = dimFilter;
+    this.granularity = granularity;
+    this.dimensions = dimensions;
+    this.aggregatorSpecs = aggregatorSpecs;
+    this.averagerSpecs = averagerSpecs;
+    this.postAggregatorSpecs = postAggregatorSpecs;
+    this.postAveragerSpecs = postAveragerSpecs;
+    this.havingSpec = havingSpec;
+    this.limitSpec = orderBySpec;
+    this.limitFn = limitFn;
+  }
+
+  @Override
+  public boolean hasFilters()
+  {
+    return dimFilter != null;
+  }
+
+  @Override
+  public String getType()
+  {
+    return MOVING_AVG_QUERY_TYPE;
+  }
+
+  @JsonIgnore
+  public boolean getContextSortByDimsFirst()
+  {
+    return getContextBoolean(CTX_KEY_SORT_BY_DIMS_FIRST, false);
+  }
+
+  @Override
+  @JsonProperty
+  public DimFilter getFilter()
+  {
+    return dimFilter;
+  }
+
+  @Override
+  @JsonProperty
+  public Granularity getGranularity()
+  {
+    return granularity;
+  }
+
+  @JsonProperty
+  public List<DimensionSpec> getDimensions()
+  {
+    return dimensions;
+  }
+
+  @JsonProperty("aggregations")
+  public List<AggregatorFactory> getAggregatorSpecs()
+  {
+    return aggregatorSpecs;
+  }
+
+  @JsonProperty("averagers")
+  public List<AveragerFactory<?, ?>> getAveragerSpecs()
+  {
+    return averagerSpecs;
+  }
+
+  @JsonProperty("postAggregations")
+  public List<PostAggregator> getPostAggregatorSpecs()
+  {
+    return postAggregatorSpecs;
+  }
+
+  @JsonProperty("postAveragers")
+  public List<PostAggregator> getPostAveragerSpecs()
+  {
+    return postAveragerSpecs;
+  }
+
+  @JsonProperty("having")
+  public HavingSpec getHavingSpec()
+  {
+    return havingSpec;
+  }
+
+  @JsonProperty
+  public LimitSpec getLimitSpec()
+  {
+    return limitSpec;
+  }
+
+  @Override
+  public MovingAverageQuery withOverriddenContext(Map contextOverride)
+  {
+    return new MovingAverageQuery(
+        getDataSource(),
+        getQuerySegmentSpec(),
+        dimFilter,
+        granularity,
+        dimensions,
+        aggregatorSpecs,
+        averagerSpecs,
+        postAggregatorSpecs,
+        postAveragerSpecs,
+        havingSpec,
+        limitSpec,
+        limitFn,
+        computeOverridenContext(contextOverride)
+    );
+  }
+
+  @Override
+  public MovingAverageQuery withQuerySegmentSpec(QuerySegmentSpec spec)
+  {
+    return new MovingAverageQuery(
+        getDataSource(),
+        spec,
+        dimFilter,
+        granularity,
+        dimensions,
+        aggregatorSpecs,
+        averagerSpecs,
+        postAggregatorSpecs,
+        postAveragerSpecs,
+        havingSpec,
+        limitSpec,
+        limitFn,
+        getContext()
+    );
+  }
+
+  @Override
+  public Query<Row> withDataSource(DataSource dataSource)
+  {
+    return new MovingAverageQuery(
+        dataSource,
+        getQuerySegmentSpec(),
+        dimFilter,
+        granularity,
+        dimensions,
+        aggregatorSpecs,
+        averagerSpecs,
+        postAggregatorSpecs,
+        postAveragerSpecs,
+        havingSpec,
+        limitSpec,
+        limitFn,
+        getContext()
+    );
+  }
+
+  public Query<Row> withPostAveragers(List<PostAggregator> postAveragerSpecs)
+  {
+    return new MovingAverageQuery(
+        getDataSource(),
+        getQuerySegmentSpec(),
+        dimFilter,
+        granularity,
+        dimensions,
+        aggregatorSpecs,
+        averagerSpecs,
+        postAggregatorSpecs,
+        postAveragerSpecs,
+        havingSpec,
+        limitSpec,
+        limitFn,
+        getContext()
+    );
+  }
+
+  public Sequence<Row> applyLimit(Sequence<Row> results)
+  {
+    return limitFn.apply(results);
+  }
+}

extensions-contrib/moving-average-query/src/main/java/org/apache/druid/query/movingaverage/MovingAverageQueryMetrics.java

@@ -0,0 +1,42 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage;
+
+import org.apache.druid.query.QueryMetrics;
+
+public interface MovingAverageQueryMetrics extends QueryMetrics<MovingAverageQuery>
+{
+  /**
+   * Sets the size of {@link MovingAverageQuery#getDimensions()} of the given query as dimension.
+   */
+  void numDimensions(MovingAverageQuery query);
+
+  /**
+   * Sets the number of metrics of the given groupBy query as dimension.
+   */
+  void numMetrics(MovingAverageQuery query);
+
+  /**
+   * Sets the number of "complex" metrics of the given groupBy query as dimension. By default it is assumed that
+   * "complex" metric is a metric of not long or double type, but it could be redefined in the implementation of this
+   * method.
+   */
+  void numComplexMetrics(MovingAverageQuery query);
+}

extensions-contrib/moving-average-query/src/main/java/org/apache/druid/query/movingaverage/MovingAverageQueryMetricsFactory.java

@@ -0,0 +1,36 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage;
+
+/**
+ * Implementations could be injected using
+ * <p>
+ * PolyBind
+ * .optionBinder(binder, Key.get(MovingAverageQueryMetricsFactory.class))
+ * .addBinding("myCustomMovingAverageQueryMetricsFactory")
+ * .to(MyCustomMovingAverageQueryMetricsFactory.class);
+ * <p>
+ * And then setting property:
+ * druid.query.movingavgquery.queryMetricsFactory=myCustomMovingAverageQueryMetricsFactory
+ */
+public interface MovingAverageQueryMetricsFactory
+{
+  MovingAverageQueryMetrics makeMetrics();
+}

extensions-contrib/moving-average-query/src/main/java/org/apache/druid/query/movingaverage/MovingAverageQueryModule.java

@@ -0,0 +1,61 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage;
+
+import com.fasterxml.jackson.databind.Module;
+import com.fasterxml.jackson.databind.jsontype.NamedType;
+import com.fasterxml.jackson.databind.module.SimpleModule;
+import com.google.inject.Binder;
+import com.google.inject.multibindings.MapBinder;
+import org.apache.druid.guice.DruidBinders;
+import org.apache.druid.guice.LazySingleton;
+import org.apache.druid.initialization.DruidModule;
+import org.apache.druid.query.Query;
+import org.apache.druid.query.QueryToolChest;
+
+import java.util.Collections;
+import java.util.List;
+
+public class MovingAverageQueryModule implements DruidModule
+{
+
+  @Override
+  public void configure(Binder binder)
+  {
+    MapBinder<Class<? extends Query>, QueryToolChest> toolChests = DruidBinders.queryToolChestBinder(binder);
+
+    //Bind the query toolchest to the query class and add the binding to toolchest
+    toolChests.addBinding(MovingAverageQuery.class).to(MovingAverageQueryToolChest.class);
+
+    //Bind the query toolchest to binder
+    binder.bind(MovingAverageQueryToolChest.class).in(LazySingleton.class);
+  }
+
+  @Override
+  public List<? extends Module> getJacksonModules()
+  {
+    return Collections.<Module>singletonList(new SimpleModule("MovingAverageQueryModule")
+                                                 .registerSubtypes(new NamedType(
+                                                     MovingAverageQuery.class,
+                                                     "movingAverage"
+                                                 )));
+  }
+
+}

extensions-contrib/moving-average-query/src/main/java/org/apache/druid/query/movingaverage/MovingAverageQueryRunner.java

@@ -0,0 +1,235 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage;
+
+import com.google.common.base.Function;
+import com.google.common.base.Throwables;
+import com.google.common.collect.ImmutableMap;
+import org.apache.druid.data.input.MapBasedRow;
+import org.apache.druid.data.input.Row;
+import org.apache.druid.java.util.common.DateTimes;
+import org.apache.druid.java.util.common.ISE;
+import org.apache.druid.java.util.common.granularity.PeriodGranularity;
+import org.apache.druid.java.util.common.guava.Sequence;
+import org.apache.druid.java.util.common.guava.Sequences;
+import org.apache.druid.query.DataSource;
+import org.apache.druid.query.QueryContexts;
+import org.apache.druid.query.QueryDataSource;
+import org.apache.druid.query.QueryPlus;
+import org.apache.druid.query.QueryRunner;
+import org.apache.druid.query.QuerySegmentWalker;
+import org.apache.druid.query.Result;
+import org.apache.druid.query.TableDataSource;
+import org.apache.druid.query.UnionDataSource;
+import org.apache.druid.query.groupby.GroupByQuery;
+import org.apache.druid.query.movingaverage.averagers.AveragerFactory;
+import org.apache.druid.query.spec.MultipleIntervalSegmentSpec;
+import org.apache.druid.query.timeseries.TimeseriesQuery;
+import org.apache.druid.query.timeseries.TimeseriesResultValue;
+import org.apache.druid.server.QueryStats;
+import org.apache.druid.server.RequestLogLine;
+import org.apache.druid.server.log.RequestLogger;
+import org.joda.time.Interval;
+import org.joda.time.Period;
+
+import javax.annotation.Nullable;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+import java.util.Optional;
+import java.util.concurrent.atomic.AtomicLong;
+import java.util.stream.Collectors;
+
+/**
+ * The QueryRunner for MovingAverage query.
+ * High level flow:
+ * 1. Invokes an inner groupBy query (Or timeseries for no dimensions scenario) to get Aggregations/PostAggregtions.
+ * 2. Result is passed to {@link RowBucketIterable}, which groups rows of all dimension combinations into period-based (e.g. daily) buckets of rows ({@link RowBucket}).
+ * 3. The sequence is passed to {@link MovingAverageIterable}, which performs the main part of the query of adding Averagers computation into the records.
+ * 4. Finishes up by applying post averagers, removing redundant dates, and applying post phases (having, sorting, limits).
+ */
+public class MovingAverageQueryRunner implements QueryRunner<Row>
+{
+
+  public static final String QUERY_FAIL_TIME = "queryFailTime";
+  public static final String QUERY_TOTAL_BYTES_GATHERED = "queryTotalBytesGathered";
+
+  private final QuerySegmentWalker walker;
+  private final RequestLogger requestLogger;
+
+  public MovingAverageQueryRunner(
+      @Nullable QuerySegmentWalker walker,
+      RequestLogger requestLogger
+  )
+  {
+    this.walker = walker;
+    this.requestLogger = requestLogger;
+  }
+
+  @Override
+  public Sequence<Row> run(QueryPlus<Row> query, Map<String, Object> responseContext)
+  {
+
+    MovingAverageQuery maq = (MovingAverageQuery) query.getQuery();
+    List<Interval> intervals;
+    final Period period;
+
+    // Get the largest bucket from the list of averagers
+    Optional<Integer> opt =
+        maq.getAveragerSpecs().stream().map(AveragerFactory::getNumBuckets).max(Integer::compare);
+    int buckets = opt.orElse(0);
+
+    //Extend the interval beginning by specified bucket - 1
+    if (maq.getGranularity() instanceof PeriodGranularity) {
+      period = ((PeriodGranularity) maq.getGranularity()).getPeriod();
+      int offset = buckets <= 0 ? 0 : (1 - buckets);
+      intervals = maq.getIntervals()
+                     .stream()
+                     .map(i -> new Interval(i.getStart().withPeriodAdded(period, offset), i.getEnd()))
+                     .collect(Collectors.toList());
+    } else {
+      throw new ISE("Only PeriodGranulaity is supported for movingAverage queries");
+    }
+
+    Sequence<Row> resultsSeq;
+    DataSource dataSource = maq.getDataSource();
+    if (maq.getDimensions() != null && !maq.getDimensions().isEmpty() &&
+        (dataSource instanceof TableDataSource || dataSource instanceof UnionDataSource ||
+         dataSource instanceof QueryDataSource)) {
+      // build groupBy query from movingAverage query
+      GroupByQuery.Builder builder = GroupByQuery.builder()
+                                                 .setDataSource(dataSource)
+                                                 .setInterval(intervals)
+                                                 .setDimFilter(maq.getFilter())
+                                                 .setGranularity(maq.getGranularity())
+                                                 .setDimensions(maq.getDimensions())
+                                                 .setAggregatorSpecs(maq.getAggregatorSpecs())
+                                                 .setPostAggregatorSpecs(maq.getPostAggregatorSpecs())
+                                                 .setContext(maq.getContext());
+      GroupByQuery gbq = builder.build();
+
+      HashMap<String, Object> gbqResponse = new HashMap<>();
+      gbqResponse.put(QUERY_FAIL_TIME, System.currentTimeMillis() + QueryContexts.getTimeout(gbq));
+      gbqResponse.put(QUERY_TOTAL_BYTES_GATHERED, new AtomicLong());
+
+      Sequence<Row> results = gbq.getRunner(walker).run(QueryPlus.wrap(gbq), gbqResponse);
+      try {
+        // use localhost for remote address
+        requestLogger.logNativeQuery(RequestLogLine.forNative(
+            gbq,
+            DateTimes.nowUtc(),
+            "127.0.0.1",
+            new QueryStats(
+                ImmutableMap.of(
+                    "query/time", 0,
+                    "query/bytes", 0,
+                    "success", true
+                ))
+        ));
+      }
+      catch (Exception e) {
+        throw Throwables.propagate(e);
+      }
+
+      resultsSeq = results;
+    } else {
+      // no dimensions, so optimize this as a TimeSeries
+      TimeseriesQuery tsq = new TimeseriesQuery(
+          dataSource,
+          new MultipleIntervalSegmentSpec(intervals),
+          false,
+          null,
+          maq.getFilter(),
+          maq.getGranularity(),
+          maq.getAggregatorSpecs(),
+          maq.getPostAggregatorSpecs(),
+          0,
+          maq.getContext()
+      );
+      HashMap<String, Object> tsqResponse = new HashMap<>();
+      tsqResponse.put(QUERY_FAIL_TIME, System.currentTimeMillis() + QueryContexts.getTimeout(tsq));
+      tsqResponse.put(QUERY_TOTAL_BYTES_GATHERED, new AtomicLong());
+
+      Sequence<Result<TimeseriesResultValue>> results = tsq.getRunner(walker).run(QueryPlus.wrap(tsq), tsqResponse);
+      try {
+        // use localhost for remote address
+        requestLogger.logNativeQuery(RequestLogLine.forNative(
+            tsq,
+            DateTimes.nowUtc(),
+            "127.0.0.1",
+            new QueryStats(
+                ImmutableMap.of(
+                    "query/time", 0,
+                    "query/bytes", 0,
+                    "success", true
+                ))
+        ));
+      }
+      catch (Exception e) {
+        throw Throwables.propagate(e);
+      }
+
+      resultsSeq = Sequences.map(results, new TimeseriesResultToRow());
+    }
+
+    // Process into period buckets
+    Sequence<RowBucket> bucketedMovingAvgResults =
+        Sequences.simple(new RowBucketIterable(resultsSeq, intervals, period));
+
+    // Apply the windows analysis functions
+    Sequence<Row> movingAvgResults = Sequences.simple(
+        new MovingAverageIterable(
+            bucketedMovingAvgResults,
+            maq.getDimensions(),
+            maq.getAveragerSpecs(),
+            maq.getPostAggregatorSpecs(),
+            maq.getAggregatorSpecs()
+        ));
+
+    // Apply any postAveragers
+    Sequence<Row> movingAvgResultsWithPostAveragers =
+        Sequences.map(movingAvgResults, new PostAveragerAggregatorCalculator(maq));
+
+    // remove rows outside the reporting window
+    List<Interval> reportingIntervals = maq.getIntervals();
+    movingAvgResults =
+        Sequences.filter(
+            movingAvgResultsWithPostAveragers,
+            row -> reportingIntervals.stream().anyMatch(i -> i.contains(row.getTimestamp()))
+        );
+
+    // Apply any having, sorting, and limits
+    movingAvgResults = ((MovingAverageQuery) maq).applyLimit(movingAvgResults);
+
+    return movingAvgResults;
+
+  }
+
+  static class TimeseriesResultToRow implements Function<Result<TimeseriesResultValue>, Row>
+  {
+    @Override
+    public Row apply(Result<TimeseriesResultValue> lookbackResult)
+    {
+      Map<String, Object> event = lookbackResult.getValue().getBaseObject();
+      MapBasedRow row = new MapBasedRow(lookbackResult.getTimestamp(), event);
+      return row;
+    }
+  }
+}

extensions-contrib/moving-average-query/src/main/java/org/apache/druid/query/movingaverage/MovingAverageQueryToolChest.java

@@ -0,0 +1,135 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage;
+
+import com.fasterxml.jackson.core.type.TypeReference;
+import com.google.common.base.Function;
+import com.google.common.base.Functions;
+import com.google.inject.Inject;
+import com.google.inject.Provider;
+import org.apache.druid.data.input.MapBasedRow;
+import org.apache.druid.data.input.Row;
+import org.apache.druid.query.QueryMetrics;
+import org.apache.druid.query.QueryRunner;
+import org.apache.druid.query.QuerySegmentWalker;
+import org.apache.druid.query.QueryToolChest;
+import org.apache.druid.query.aggregation.AggregatorFactory;
+import org.apache.druid.query.aggregation.MetricManipulationFn;
+import org.apache.druid.query.movingaverage.averagers.AveragerFactory;
+import org.apache.druid.server.log.RequestLogger;
+
+import java.util.HashMap;
+import java.util.Map;
+
+/**
+ * The QueryToolChest for MovingAverage Query
+ */
+public class MovingAverageQueryToolChest extends QueryToolChest<Row, MovingAverageQuery>
+{
+
+  private final QuerySegmentWalker walker;
+  private final RequestLogger requestLogger;
+
+  private final MovingAverageQueryMetricsFactory movingAverageQueryMetricsFactory;
+
+  /**
+   * Construct a MovingAverageQueryToolChest for processing moving-average queries.
+   * MovingAverage queries are expected to be processed on broker nodes and never hit historical nodes.
+   *
+   * @param walker
+   * @param requestLogger
+   */
+  @Inject
+  public MovingAverageQueryToolChest(Provider<QuerySegmentWalker> walker, RequestLogger requestLogger)
+  {
+
+    this.walker = walker.get();
+    this.requestLogger = requestLogger;
+    this.movingAverageQueryMetricsFactory = DefaultMovingAverageQueryMetricsFactory.instance();
+  }
+
+  @Override
+  public QueryRunner<Row> mergeResults(QueryRunner<Row> runner)
+  {
+    return new MovingAverageQueryRunner(walker, requestLogger);
+  }
+
+  @Override
+  public QueryMetrics<? super MovingAverageQuery> makeMetrics(MovingAverageQuery query)
+  {
+    MovingAverageQueryMetrics movingAverageQueryMetrics = movingAverageQueryMetricsFactory.makeMetrics();
+    movingAverageQueryMetrics.query(query);
+    return movingAverageQueryMetrics;
+  }
+
+  @Override
+  public Function<Row, Row> makePostComputeManipulatorFn(MovingAverageQuery query, MetricManipulationFn fn)
+  {
+
+    return new Function<Row, Row>()
+    {
+
+      @Override
+      public Row apply(Row result)
+      {
+        MapBasedRow mRow = (MapBasedRow) result;
+        final Map<String, Object> values = new HashMap<>(mRow.getEvent());
+
+        for (AggregatorFactory agg : query.getAggregatorSpecs()) {
+          Object aggVal = values.get(agg.getName());
+          if (aggVal != null) {
+            values.put(agg.getName(), fn.manipulate(agg, aggVal));
+          } else {
+            values.put(agg.getName(), null);
+          }
+        }
+
+        for (AveragerFactory<?, ?> avg : query.getAveragerSpecs()) {
+          Object aggVal = values.get(avg.getName());
+          if (aggVal != null) {
+            values.put(avg.getName(), fn.manipulate(new AveragerFactoryWrapper<>(avg, avg.getName() + "_"), aggVal));
+          } else {
+            values.put(avg.getName(), null);
+          }
+        }
+
+        return new MapBasedRow(result.getTimestamp(), values);
+
+      }
+    };
+
+  }
+
+
+  @Override
+  public TypeReference<Row> getResultTypeReference()
+  {
+    return new TypeReference<Row>()
+    {
+    };
+  }
+
+  @Override
+  public Function<Row, Row> makePreComputeManipulatorFn(MovingAverageQuery query, MetricManipulationFn fn)
+  {
+    return Functions.identity();
+  }
+
+}

extensions-contrib/moving-average-query/src/main/java/org/apache/druid/query/movingaverage/PostAveragerAggregatorCalculator.java

@@ -0,0 +1,63 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage;
+
+import com.google.common.base.Function;
+import com.google.common.collect.Maps;
+import org.apache.druid.data.input.MapBasedRow;
+import org.apache.druid.data.input.Row;
+import org.apache.druid.query.aggregation.PostAggregator;
+
+import java.util.List;
+import java.util.Map;
+
+/**
+ * Function that can be applied to a Sequence to calculate PostAverager results
+ */
+public class PostAveragerAggregatorCalculator implements Function<Row, Row>
+{
+
+  private final List<PostAggregator> postAveragers;
+
+  public PostAveragerAggregatorCalculator(MovingAverageQuery maq)
+  {
+    this.postAveragers = maq.getPostAveragerSpecs();
+  }
+
+  @Override
+  public Row apply(final Row row)
+  {
+    if (postAveragers.isEmpty()) {
+      return row;
+    }
+
+    final Map<String, Object> newMap;
+
+    newMap = Maps.newLinkedHashMap(((MapBasedRow) row).getEvent());
+
+    for (PostAggregator postAverager : postAveragers) {
+      boolean allColsPresent = postAverager.getDependentFields().stream().allMatch(c -> newMap.get(c) != null);
+      newMap.put(postAverager.getName(), allColsPresent ? postAverager.compute(newMap) : null);
+    }
+
+    return new MapBasedRow(row.getTimestamp(), newMap);
+  }
+
+}

extensions-contrib/moving-average-query/src/main/java/org/apache/druid/query/movingaverage/RowBucket.java

@@ -0,0 +1,62 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage;
+
+import org.apache.druid.data.input.Row;
+import org.joda.time.DateTime;
+
+import java.util.List;
+
+/**
+ * Represents a set of rows for a specific date
+ * Each RowBucket is an element in a list (holds a pointer to the next RowBucket)
+ */
+public class RowBucket
+{
+  private final DateTime dateTime;
+  private final List<Row> rows;
+  private RowBucket nextBucket = null;
+
+  public RowBucket(DateTime dateTime, List<Row> rows)
+  {
+    this.dateTime = dateTime;
+    this.rows = rows;
+  }
+
+  public DateTime getDateTime()
+  {
+    return dateTime;
+  }
+
+  public List<Row> getRows()
+  {
+    return rows;
+  }
+
+  public RowBucket getNextBucket()
+  {
+    return nextBucket;
+  }
+
+  public void setNextBucket(RowBucket nextRow)
+  {
+    this.nextBucket = nextRow;
+  }
+}

extensions-contrib/moving-average-query/src/main/java/org/apache/druid/query/movingaverage/RowBucketIterable.java

@@ -0,0 +1,155 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage;
+
+import org.apache.druid.data.input.Row;
+import org.apache.druid.java.util.common.guava.Sequence;
+import org.apache.druid.java.util.common.guava.Yielder;
+import org.joda.time.DateTime;
+import org.joda.time.Interval;
+import org.joda.time.Period;
+
+import java.util.Collections;
+import java.util.Iterator;
+import java.util.List;
+import java.util.NoSuchElementException;
+
+/**
+ * An iterator which takes list of rows ({@link Sequence<Row>}) and generates a new list of {@link RowBucket}s from it.
+ *
+ * It calls {@link BucketingAccumulator} for naive bucketing to buckets of periods,
+ * But does more subtle logic to cover edge cases, such as:
+ * - Handling periods with no rows.
+ * - Handling last record.
+ *
+ * Please notice this is being called by {@link MovingAverageIterable.MovingAverageIterator#internalNext()}
+ * and the logic for skipping records is comprised by the interaction between the two classes.
+ */
+public class RowBucketIterable implements Iterable<RowBucket>
+{
+
+  public final Sequence<Row> seq;
+  private List<Interval> intervals;
+  private Period period;
+
+  public RowBucketIterable(Sequence<Row> seq, List<Interval> intervals, Period period)
+  {
+    this.seq = seq;
+    this.period = period;
+    this.intervals = intervals;
+  }
+
+  /* (non-Javadoc)
+   * @see java.lang.Iterable#iterator()
+   */
+  @Override
+  public Iterator<RowBucket> iterator()
+  {
+    return new RowBucketIterator(seq, intervals, period);
+  }
+
+  static class RowBucketIterator implements Iterator<RowBucket>
+  {
+    private Yielder<RowBucket> yielder;
+    private DateTime endTime;
+    private DateTime expectedBucket;
+    private Period period;
+    private int intervalIndex = 0;
+    private List<Interval> intervals;
+    private boolean processedLastRow = false;
+    private boolean processedExtraRow = false;
+
+    public RowBucketIterator(Sequence<Row> rows, List<Interval> intervals, Period period)
+    {
+      this.period = period;
+      this.intervals = intervals;
+      expectedBucket = intervals.get(intervalIndex).getStart();
+      endTime = intervals.get(intervals.size() - 1).getEnd();
+      yielder = rows.toYielder(null, new BucketingAccumulator());
+    }
+
+    /* (non-Javadoc)
+     * @see java.util.Iterator#hasNext()
+     */
+    @Override
+    public boolean hasNext()
+    {
+      return expectedBucket.compareTo(endTime) < 0 || !this.yielder.isDone();
+    }
+
+    /* (non-Javadoc)
+     * @see java.util.Iterator#next()
+     */
+    @Override
+    public RowBucket next()
+    {
+      RowBucket currentBucket = yielder.get();
+
+      // Iterate to next interval
+      if (expectedBucket.compareTo(intervals.get(intervalIndex).getEnd()) >= 0) {
+        intervalIndex++;
+        if (intervalIndex < intervals.size()) {
+          expectedBucket = intervals.get(intervalIndex).getStart();
+        }
+      }
+      // currentBucket > expectedBucket (No rows found for period). Iterate to next period.
+      if (currentBucket != null && currentBucket.getDateTime().compareTo(expectedBucket) > 0) {
+        currentBucket = new RowBucket(expectedBucket, Collections.emptyList());
+        expectedBucket = expectedBucket.plus(period);
+        return currentBucket;
+      }
+
+      if (!yielder.isDone()) {
+        // standard case. return regular row
+        yielder = yielder.next(currentBucket);
+        expectedBucket = expectedBucket.plus(period);
+        return currentBucket;
+      } else if (!processedLastRow && yielder.get() != null && yielder.get().getNextBucket() == null) {
+        // yielder.isDone, processing last row
+        processedLastRow = true;
+        expectedBucket = expectedBucket.plus(period);
+        return currentBucket;
+      } else if (!processedExtraRow && yielder.get() != null && yielder.get().getNextBucket() != null) {
+        RowBucket lastRow = yielder.get().getNextBucket();
+
+        if (lastRow.getDateTime().compareTo(expectedBucket) > 0) {
+          lastRow = new RowBucket(expectedBucket, Collections.emptyList());
+          expectedBucket = expectedBucket.plus(period);
+          return lastRow;
+        }
+
+        // yielder is done, processing newBucket
+        processedExtraRow = true;
+        expectedBucket = expectedBucket.plus(period);
+        return lastRow;
+      } else if (expectedBucket.compareTo(endTime) < 0) {
+        // add any trailing blank rows
+        currentBucket = new RowBucket(expectedBucket, Collections.emptyList());
+        expectedBucket = expectedBucket.plus(period);
+        return currentBucket;
+      } else {
+        // we should never get here
+        throw new NoSuchElementException();
+      }
+
+    }
+  }
+
+}

extensions-contrib/moving-average-query/src/main/java/org/apache/druid/query/movingaverage/averagers/Averager.java

@@ -0,0 +1,57 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage.averagers;
+
+import org.apache.druid.query.aggregation.AggregatorFactory;
+
+import java.util.Map;
+
+/**
+ * Interface for an averager
+ *
+ * @param <R> The return type of the averager
+ */
+public interface Averager<R>
+{
+  /**
+   * Add a row to the window being operated on
+   *
+   * @param e      The row to add
+   * @param aggMap The Map of AggregatorFactory used to determine if the metric should to be finalized
+   */
+  void addElement(Map<String, Object> e, Map<String, AggregatorFactory> aggMap);
+
+  /**
+   * There is a missing row, so record a missing entry in the window
+   */
+  void skip();
+
+  /**
+   * Compute the resulting "average" over the collected window
+   *
+   * @return the "average" over the window of buckets
+   */
+  R getResult();
+
+  /**
+   * @return the name
+   */
+  String getName();
+}

extensions-contrib/moving-average-query/src/main/java/org/apache/druid/query/movingaverage/averagers/AveragerFactory.java

@@ -0,0 +1,106 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage.averagers;
+
+import com.fasterxml.jackson.annotation.JsonSubTypes;
+import com.fasterxml.jackson.annotation.JsonTypeInfo;
+
+import java.util.Comparator;
+import java.util.List;
+
+/**
+ * Interface representing Averager in the movingAverage query.
+ *
+ * @param <R> Type returned by the underlying averager.
+ * @param <F> Type of finalized value.
+ */
+@JsonTypeInfo(use = JsonTypeInfo.Id.NAME, property = "type")
+@JsonSubTypes(value = {
+    @JsonSubTypes.Type(name = "constant", value = ConstantAveragerFactory.class),
+    @JsonSubTypes.Type(name = "doubleMean", value = DoubleMeanAveragerFactory.class),
+    @JsonSubTypes.Type(name = "doubleMeanNoNulls", value = DoubleMeanNoNullAveragerFactory.class),
+    @JsonSubTypes.Type(name = "doubleMax", value = DoubleMaxAveragerFactory.class),
+    @JsonSubTypes.Type(name = "doubleMin", value = DoubleMinAveragerFactory.class),
+    @JsonSubTypes.Type(name = "longMean", value = LongMeanAveragerFactory.class),
+    @JsonSubTypes.Type(name = "longMeanNoNulls", value = LongMeanNoNullAveragerFactory.class),
+    @JsonSubTypes.Type(name = "longMax", value = LongMaxAveragerFactory.class),
+    @JsonSubTypes.Type(name = "longMin", value = LongMinAveragerFactory.class)
+})
+public interface AveragerFactory<R, F>
+{
+  int DEFAULT_PERIOD = 1;
+
+  /**
+   * Gets the column name that will be populated by the Averager
+   *
+   * @return The column name
+   */
+  String getName();
+
+  /**
+   * Returns the window size over which the averaging calculations will be
+   * performed. Size is computed in terms of buckets rather than absolute time.
+   *
+   * @return The window size
+   */
+  int getNumBuckets();
+
+  /**
+   * Returns the cycle size (number of periods to skip during averaging calculations).
+   *
+   * @return The cycle size
+   */
+  int getCycleSize();
+
+  /**
+   * Create an Averager for a specific dimension combination.
+   *
+   * @return The {@link Averager}
+   */
+  Averager<R> createAverager();
+
+  /**
+   * Gets the list of dependent fields that will be used by this Averager. Most
+   * {@link Averager}s depend on only a single field from the underlying query, but
+   * that is not required. This method allow the required fields to be communicated
+   * back to the main query so that validation to enforce the fields presence can
+   * be accomplished.
+   *
+   * @return A list of field names
+   */
+  List<String> getDependentFields();
+
+  /**
+   * Returns a {@link Comparator} that can be used to compare result values for
+   * purposes of sorting the end result of the query.
+   *
+   * @return A {@link Comparator}
+   */
+  Comparator<R> getComparator();
+
+  /**
+   * Finalize result value.
+   *
+   * @param val the value to finalize.
+   *
+   * @return The finalized value.
+   */
+  F finalizeComputation(R val);
+}

extensions-contrib/moving-average-query/src/main/java/org/apache/druid/query/movingaverage/averagers/BaseAverager.java

@@ -0,0 +1,192 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage.averagers;
+
+import org.apache.druid.query.aggregation.AggregatorFactory;
+
+import java.lang.reflect.Array;
+import java.util.Map;
+
+/**
+ * Common base class available for use by averagers. The base class implements methods that
+ * capture incoming and skipped rows and store them in an array, to be used later for
+ * calculating the actual value.
+ *
+ * @param <I> The type of intermediate value to be retrieved from the row and stored
+ * @param <R> The type of result the averager is expected to produce
+ */
+public abstract class BaseAverager<I, R extends Object> implements Averager<R>
+{
+
+  final int numBuckets;
+  final int cycleSize;
+  private final String name;
+  private final String fieldName;
+  final I[] buckets;
+  private int index;
+
+  /**
+   * {@link BaseAverager#startFrom} is needed because `buckets` field is a fixed array, not a list.
+   * It makes computeResults() start from the correct bucket in the array.
+   */
+  int startFrom = 0;
+
+  /**
+   * @param storageType    The class to use for storing intermediate values
+   * @param numBuckets     The number of buckets to include in the window being aggregated
+   * @param name           The name of the resulting metric
+   * @param fieldName      The field to extra from incoming rows and stored in the window cache
+   * @param cycleSize      Cycle group size. Used to calculate day-of-week option. Default=1 (single element in group).
+   */
+  public BaseAverager(Class<I> storageType, int numBuckets, String name, String fieldName, int cycleSize)
+  {
+    this.numBuckets = numBuckets;
+    this.name = name;
+    this.fieldName = fieldName;
+    this.index = 0;
+    @SuppressWarnings("unchecked")
+    final I[] array = (I[]) Array.newInstance(storageType, numBuckets);
+    this.buckets = array;
+    this.cycleSize = cycleSize;
+  }
+
+
+  /* (non-Javadoc)
+   * @see Averager#addElement(java.util.Map, java.util.Map)
+   */
+  @SuppressWarnings("unchecked")
+  @Override
+  public void addElement(Map<String, Object> e, Map<String, AggregatorFactory> a)
+  {
+    Object metric = e.get(fieldName);
+    I finalMetric;
+    if (a.containsKey(fieldName)) {
+      AggregatorFactory af = a.get(fieldName);
+      finalMetric = metric != null ? (I) af.finalizeComputation(metric) : null;
+    } else {
+      finalMetric = (I) metric;
+    }
+    buckets[index++] = finalMetric;
+    index %= numBuckets;
+  }
+
+  /* (non-Javadoc)
+   * @see Averager#skip()
+   */
+  @Override
+  public void skip()
+  {
+    buckets[index++] = null;
+    index %= numBuckets;
+  }
+
+  /* (non-Javadoc)
+   * @see Averager#getResult()
+   */
+  @Override
+  public R getResult()
+  {
+    if (!hasData()) {
+      return null;
+    }
+    return computeResult();
+  }
+
+  /**
+   * Compute the result value to be returned by getResult.
+   *
+   * <p>This routine will only be called when there is valid data within the window
+   * and doesn't need to worry about detecting the case where no data should be returned.
+   *
+   * <p>
+   * The method typically should use {@link #getBuckets()} to retrieve the set of buckets
+   * within the window and then compute a value based on those. It should expect nulls within
+   * the array, indicating buckets where no row was found for the dimension combination. It is
+   * up to the actual implementation to determin how to evaluate those nulls.
+   *
+   * <p>
+   * The type returned is NOT required to be the same type as the intermediary value. For example,
+   * the intermediate value could be a Sketch, but the result a Long.
+   *
+   * @return the computed result
+   */
+  protected abstract R computeResult();
+
+  /* (non-Javadoc)
+   * @see Averager#getName()
+   */
+  @Override
+  public String getName()
+  {
+    return name;
+  }
+
+  /**
+   * Returns the fieldname to be extracted from any event rows passed in and stored
+   * for use computing the windowed function.
+   *
+   * @return the fieldName
+   */
+  public String getFieldName()
+  {
+    return fieldName;
+  }
+
+  /**
+   * @return the numBuckets
+   */
+  public int getNumBuckets()
+  {
+    return numBuckets;
+  }
+
+  /**
+   * @return the cycleSize
+   */
+  public int getCycleSize()
+  {
+    return cycleSize;
+  }
+
+  /**
+   * @return the array of buckets
+   */
+  protected I[] getBuckets()
+  {
+    return buckets;
+  }
+
+  /**
+   * Determines wheter any data is present. If all the buckets are empty (not "0"), then
+   * no value should be returned from the Averager, as there were not valid rows within the window.
+   *
+   * @return true if any non-null values available
+   */
+  protected boolean hasData()
+  {
+    for (Object b : buckets) {
+      if (b != null) {
+        return true;
+      }
+    }
+    return false;
+  }
+
+}

extensions-contrib/moving-average-query/src/main/java/org/apache/druid/query/movingaverage/averagers/BaseAveragerFactory.java

@@ -0,0 +1,103 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage.averagers;
+
+import com.fasterxml.jackson.annotation.JsonProperty;
+import com.google.common.base.Preconditions;
+
+import java.util.Collections;
+import java.util.List;
+
+/**
+ * Common base class for AveragerFactories
+ *
+ * @param <R> Base type that the averager should return as a result
+ * @param <F> Type that that is returned from finalization
+ */
+public abstract class BaseAveragerFactory<R, F> implements AveragerFactory<R, F>
+{
+
+  protected String name;
+  protected String fieldName;
+  protected int numBuckets;
+  protected int cycleSize;
+
+  /**
+   * Constructor.
+   *
+   * @param name       Name of the Averager
+   * @param numBuckets Number of buckets in the analysis window
+   * @param fieldName  Field from incoming events to include in the analysis
+   * @param cycleSize  Cycle group size. Used to calculate day-of-week option. Default=1 (single element in group).
+   */
+  public BaseAveragerFactory(String name, int numBuckets, String fieldName, Integer cycleSize)
+  {
+    this.name = name;
+    this.numBuckets = numBuckets;
+    this.fieldName = fieldName;
+    this.cycleSize = (cycleSize != null) ? cycleSize : DEFAULT_PERIOD;
+    Preconditions.checkNotNull(name, "Must have a valid, non-null averager name");
+    Preconditions.checkNotNull(fieldName, "Must have a valid, non-null field name");
+    Preconditions.checkArgument(this.cycleSize > 0, "Cycle size must be greater than zero");
+    Preconditions.checkArgument(numBuckets > 0, "Bucket size must be greater than zero");
+    Preconditions.checkArgument(!(this.cycleSize > numBuckets), "Cycle size must be less than the bucket size");
+    Preconditions.checkArgument(numBuckets % this.cycleSize == 0, "cycleSize must devide numBuckets without a remainder");
+  }
+
+  @Override
+  @JsonProperty
+  public String getName()
+  {
+    return name;
+  }
+
+  @JsonProperty
+  public String getFieldName()
+  {
+    return fieldName;
+  }
+
+  @Override
+  @JsonProperty("buckets")
+  public int getNumBuckets()
+  {
+    return numBuckets;
+  }
+
+  @Override
+  @JsonProperty("cycleSize")
+  public int getCycleSize()
+  {
+    return cycleSize;
+  }
+
+  @Override
+  public List<String> getDependentFields()
+  {
+    return Collections.singletonList(fieldName);
+  }
+
+  @SuppressWarnings("unchecked")
+  @Override
+  public F finalizeComputation(R val)
+  {
+    return (F) val;
+  }
+}

extensions-contrib/moving-average-query/src/main/java/org/apache/druid/query/movingaverage/averagers/ComparableAveragerFactory.java

@@ -0,0 +1,51 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage.averagers;
+
+import java.util.Comparator;
+
+/**
+ * Base averager factory that adds a default comparable method.
+ *
+ * @param <R> return type
+ * @param <F> finalized type
+ */
+public abstract class ComparableAveragerFactory<R extends Comparable<R>, F> extends BaseAveragerFactory<R, F>
+{
+  /**
+   * Constructor.
+   *
+   * @param name       Name of the Averager
+   * @param numBuckets Number of buckets in the analysis window
+   * @param fieldName  Field from incoming events to include in the analysis
+   * @param cycleSize  Cycle group size. Used to calculate day-of-week option. Default=1 (single element in group).
+   */
+  public ComparableAveragerFactory(String name, int numBuckets, String fieldName, Integer cycleSize)
+  {
+    super(name, numBuckets, fieldName, cycleSize);
+  }
+
+  @Override
+  public Comparator<R> getComparator()
+  {
+    return Comparator.naturalOrder();
+  }
+
+}

extensions-contrib/moving-average-query/src/main/java/org/apache/druid/query/movingaverage/averagers/ConstantAverager.java

@@ -0,0 +1,81 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage.averagers;
+
+import org.apache.druid.query.aggregation.AggregatorFactory;
+
+import java.util.Map;
+
+/**
+ * The constant averager.Created soley for incremental development and wiring things up.
+ */
+public class ConstantAverager implements Averager<Float>
+{
+
+  private String name;
+  private float retval;
+
+  /**
+   * @param n
+   * @param name
+   * @param retval
+   */
+  public ConstantAverager(int n, String name, float retval)
+  {
+    this.name = name;
+    this.retval = retval;
+  }
+
+  /* (non-Javadoc)
+   * @see Averager#getResult()
+   */
+  @Override
+  public Float getResult()
+  {
+    return retval;
+  }
+
+  /* (non-Javadoc)
+   * @see Averager#getName()
+   */
+  @Override
+  public String getName()
+  {
+    return name;
+  }
+
+  /* (non-Javadoc)
+   * @see Averager#addElement(java.util.Map, java.util.Map)
+   */
+  @Override
+  public void addElement(Map<String, Object> e, Map<String, AggregatorFactory> a)
+  {
+    // since we return a constant, no need to read from the event
+  }
+
+  /* (non-Javadoc)
+   * @see Averager#skip()
+   */
+  @Override
+  public void skip()
+  {
+  }
+
+}

extensions-contrib/moving-average-query/src/main/java/org/apache/druid/query/movingaverage/averagers/ConstantAveragerFactory.java

@@ -0,0 +1,101 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage.averagers;
+
+import com.fasterxml.jackson.annotation.JsonCreator;
+import com.fasterxml.jackson.annotation.JsonProperty;
+
+import java.util.Collections;
+import java.util.Comparator;
+import java.util.List;
+
+/**
+ * Implementation of AveragerFacvtory created solely for incremental development
+ */
+
+public class ConstantAveragerFactory implements AveragerFactory<Float, Float>
+{
+
+  private String name;
+  private int numBuckets;
+  private float retval;
+
+  @JsonCreator
+  public ConstantAveragerFactory(
+      @JsonProperty("name") String name,
+      @JsonProperty("buckets") int numBuckets,
+      @JsonProperty("retval") float retval
+  )
+  {
+    this.name = name;
+    this.numBuckets = numBuckets;
+    this.retval = retval;
+  }
+
+  @Override
+  @JsonProperty
+  public String getName()
+  {
+    return name;
+  }
+
+  @Override
+  @JsonProperty("buckets")
+  public int getNumBuckets()
+  {
+    return numBuckets;
+  }
+
+  @JsonProperty
+  public float getRetval()
+  {
+    return retval;
+  }
+
+  @Override
+  public Averager<Float> createAverager()
+  {
+    return new ConstantAverager(numBuckets, name, retval);
+  }
+
+  @Override
+  public List<String> getDependentFields()
+  {
+    return Collections.emptyList();
+  }
+
+  @Override
+  public Comparator<Float> getComparator()
+  {
+    return Comparator.naturalOrder();
+  }
+
+  @Override
+  public int getCycleSize()
+  {
+    return 1;
+  }
+
+  @Override
+  public Float finalizeComputation(Float val)
+  {
+    return val;
+  }
+}

extensions-contrib/moving-average-query/src/main/java/org/apache/druid/query/movingaverage/averagers/DoubleMaxAverager.java

@@ -0,0 +1,44 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage.averagers;
+
+public class DoubleMaxAverager extends BaseAverager<Number, Double>
+{
+
+  public DoubleMaxAverager(int numBuckets, String name, String fieldName, int cycleSize)
+  {
+    super(Number.class, numBuckets, name, fieldName, cycleSize);
+  }
+
+  @Override
+  protected Double computeResult()
+  {
+    double result = Double.NEGATIVE_INFINITY;
+
+    for (int i = 0; i < numBuckets; i += cycleSize) {
+      if (buckets[(i + startFrom) % numBuckets] != null) {
+        result = Double.max(result, (buckets[(i + startFrom) % numBuckets]).doubleValue());
+      }
+    }
+
+    startFrom++;
+    return result;
+  }
+}

extensions-contrib/moving-average-query/src/main/java/org/apache/druid/query/movingaverage/averagers/DoubleMaxAveragerFactory.java

@@ -0,0 +1,44 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage.averagers;
+
+import com.fasterxml.jackson.annotation.JsonCreator;
+import com.fasterxml.jackson.annotation.JsonProperty;
+
+public class DoubleMaxAveragerFactory extends ComparableAveragerFactory<Double, Double>
+{
+
+  @JsonCreator
+  public DoubleMaxAveragerFactory(
+      @JsonProperty("name") String name,
+      @JsonProperty("buckets") int numBuckets,
+      @JsonProperty("cycleSize") Integer cycleSize,
+      @JsonProperty("fieldName") String fieldName
+  )
+  {
+    super(name, numBuckets, fieldName, cycleSize);
+  }
+
+  @Override
+  public Averager<Double> createAverager()
+  {
+    return new DoubleMaxAverager(numBuckets, name, fieldName, cycleSize);
+  }
+}

extensions-contrib/moving-average-query/src/main/java/org/apache/druid/query/movingaverage/averagers/DoubleMeanAverager.java

@@ -0,0 +1,48 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage.averagers;
+
+public class DoubleMeanAverager extends BaseAverager<Number, Double>
+{
+
+  public DoubleMeanAverager(int numBuckets, String name, String fieldName, int cycleSize)
+  {
+    super(Number.class, numBuckets, name, fieldName, cycleSize);
+  }
+
+  @Override
+  protected Double computeResult()
+  {
+    double result = 0.0;
+    int validBuckets = 0;
+
+    for (int i = 0; i < numBuckets; i += cycleSize) {
+      if (buckets[(i + startFrom) % numBuckets] != null) {
+        result += (buckets[(i + startFrom) % numBuckets]).doubleValue();
+      } else {
+        result += 0.0;
+      }
+      validBuckets++;
+    }
+
+    startFrom++;
+    return result / validBuckets;
+  }
+}

extensions-contrib/moving-average-query/src/main/java/org/apache/druid/query/movingaverage/averagers/DoubleMeanAveragerFactory.java

@@ -0,0 +1,44 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage.averagers;
+
+import com.fasterxml.jackson.annotation.JsonCreator;
+import com.fasterxml.jackson.annotation.JsonProperty;
+
+public class DoubleMeanAveragerFactory extends ComparableAveragerFactory<Double, Double>
+{
+
+  @JsonCreator
+  public DoubleMeanAveragerFactory(
+      @JsonProperty("name") String name,
+      @JsonProperty("buckets") int numBuckets,
+      @JsonProperty("cycleSize") Integer cycleSize,
+      @JsonProperty("fieldName") String fieldName
+  )
+  {
+    super(name, numBuckets, fieldName, cycleSize);
+  }
+
+  @Override
+  public Averager<Double> createAverager()
+  {
+    return new DoubleMeanAverager(numBuckets, name, fieldName, cycleSize);
+  }
+}

extensions-contrib/moving-average-query/src/main/java/org/apache/druid/query/movingaverage/averagers/DoubleMeanNoNullAverager.java

@@ -0,0 +1,46 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage.averagers;
+
+public class DoubleMeanNoNullAverager extends BaseAverager<Number, Double>
+{
+
+  public DoubleMeanNoNullAverager(int numBuckets, String name, String fieldName, int cycleSize)
+  {
+    super(Number.class, numBuckets, name, fieldName, cycleSize);
+  }
+
+  @Override
+  protected Double computeResult()
+  {
+    double result = 0.0;
+    int validBuckets = 0;
+
+    for (int i = 0; i < numBuckets; i += cycleSize) {
+      if (buckets[(i + startFrom) % numBuckets] != null) {
+        result += (buckets[(i + startFrom) % numBuckets]).doubleValue();
+        validBuckets++;
+      }
+    }
+
+    startFrom++;
+    return result / validBuckets;
+  }
+}

extensions-contrib/moving-average-query/src/main/java/org/apache/druid/query/movingaverage/averagers/DoubleMeanNoNullAveragerFactory.java

@@ -0,0 +1,43 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage.averagers;
+
+import com.fasterxml.jackson.annotation.JsonCreator;
+import com.fasterxml.jackson.annotation.JsonProperty;
+
+public class DoubleMeanNoNullAveragerFactory extends ComparableAveragerFactory<Double, Double>
+{
+  @JsonCreator
+  public DoubleMeanNoNullAveragerFactory(
+      @JsonProperty("name") String name,
+      @JsonProperty("buckets") int numBuckets,
+      @JsonProperty("cycleSize") Integer cycleSize,
+      @JsonProperty("fieldName") String fieldName
+  )
+  {
+    super(name, numBuckets, fieldName, cycleSize);
+  }
+
+  @Override
+  public Averager<Double> createAverager()
+  {
+    return new DoubleMeanNoNullAverager(numBuckets, name, fieldName, cycleSize);
+  }
+}

extensions-contrib/moving-average-query/src/main/java/org/apache/druid/query/movingaverage/averagers/DoubleMinAverager.java

@@ -0,0 +1,44 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage.averagers;
+
+public class DoubleMinAverager extends BaseAverager<Number, Double>
+{
+
+  public DoubleMinAverager(int numBuckets, String name, String fieldName, int cycleSize)
+  {
+    super(Number.class, numBuckets, name, fieldName, cycleSize);
+  }
+
+  @Override
+  protected Double computeResult()
+  {
+    double result = Double.POSITIVE_INFINITY;
+
+    for (int i = 0; i < numBuckets; i += cycleSize) {
+      if (buckets[(i + startFrom) % numBuckets] != null) {
+        result = Double.min(result, (buckets[(i + startFrom) % numBuckets]).doubleValue());
+      }
+    }
+
+    startFrom++;
+    return result;
+  }
+}

extensions-contrib/moving-average-query/src/main/java/org/apache/druid/query/movingaverage/averagers/DoubleMinAveragerFactory.java

@@ -0,0 +1,43 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage.averagers;
+
+import com.fasterxml.jackson.annotation.JsonCreator;
+import com.fasterxml.jackson.annotation.JsonProperty;
+
+public class DoubleMinAveragerFactory extends ComparableAveragerFactory<Double, Double>
+{
+  @JsonCreator
+  public DoubleMinAveragerFactory(
+      @JsonProperty("name") String name,
+      @JsonProperty("buckets") int numBuckets,
+      @JsonProperty("cycleSize") Integer cycleSize,
+      @JsonProperty("fieldName") String fieldName
+  )
+  {
+    super(name, numBuckets, fieldName, cycleSize);
+  }
+
+  @Override
+  public Averager<Double> createAverager()
+  {
+    return new DoubleMinAverager(numBuckets, name, fieldName, cycleSize);
+  }
+}

extensions-contrib/moving-average-query/src/main/java/org/apache/druid/query/movingaverage/averagers/LongMaxAverager.java

@@ -0,0 +1,44 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage.averagers;
+
+public class LongMaxAverager extends BaseAverager<Number, Long>
+{
+
+  public LongMaxAverager(int numBuckets, String name, String fieldName, int cycleSize)
+  {
+    super(Number.class, numBuckets, name, fieldName, cycleSize);
+  }
+
+  @Override
+  protected Long computeResult()
+  {
+    long result = Long.MIN_VALUE;
+
+    for (int i = 0; i < numBuckets; i += cycleSize) {
+      if (buckets[(i + startFrom) % numBuckets] != null) {
+        result = Long.max(result, (buckets[(i + startFrom) % numBuckets]).longValue());
+      }
+    }
+
+    startFrom++;
+    return result;
+  }
+}

extensions-contrib/moving-average-query/src/main/java/org/apache/druid/query/movingaverage/averagers/LongMaxAveragerFactory.java

@@ -0,0 +1,43 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage.averagers;
+
+import com.fasterxml.jackson.annotation.JsonCreator;
+import com.fasterxml.jackson.annotation.JsonProperty;
+
+public class LongMaxAveragerFactory extends ComparableAveragerFactory<Long, Long>
+{
+  @JsonCreator
+  public LongMaxAveragerFactory(
+      @JsonProperty("name") String name,
+      @JsonProperty("buckets") int numBuckets,
+      @JsonProperty("cycleSize") Integer cycleSize,
+      @JsonProperty("fieldName") String fieldName
+  )
+  {
+    super(name, numBuckets, fieldName, cycleSize);
+  }
+
+  @Override
+  public Averager<Long> createAverager()
+  {
+    return new LongMaxAverager(numBuckets, name, fieldName, cycleSize);
+  }
+}

extensions-contrib/moving-average-query/src/main/java/org/apache/druid/query/movingaverage/averagers/LongMeanAverager.java

@@ -0,0 +1,48 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage.averagers;
+
+public class LongMeanAverager extends BaseAverager<Number, Double>
+{
+
+  public LongMeanAverager(int numBuckets, String name, String fieldName, int cycleSize)
+  {
+    super(Number.class, numBuckets, name, fieldName, cycleSize);
+  }
+
+  @Override
+  protected Double computeResult()
+  {
+    long result = 0;
+    int validBuckets = 0;
+
+    for (int i = 0; i < numBuckets; i += cycleSize) {
+      if (buckets[(i + startFrom) % numBuckets] != null) {
+        result += (buckets[(i + startFrom) % numBuckets]).longValue();
+      } else {
+        result += 0;
+      }
+      validBuckets++;
+    }
+
+    startFrom++;
+    return ((double) result) / validBuckets;
+  }
+}

extensions-contrib/moving-average-query/src/main/java/org/apache/druid/query/movingaverage/averagers/LongMeanAveragerFactory.java

@@ -0,0 +1,44 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage.averagers;
+
+import com.fasterxml.jackson.annotation.JsonCreator;
+import com.fasterxml.jackson.annotation.JsonProperty;
+
+public class LongMeanAveragerFactory extends ComparableAveragerFactory<Double, Double>
+{
+
+  @JsonCreator
+  public LongMeanAveragerFactory(
+      @JsonProperty("name") String name,
+      @JsonProperty("buckets") int numBuckets,
+      @JsonProperty("cycleSize") Integer cycleSize,
+      @JsonProperty("fieldName") String fieldName
+  )
+  {
+    super(name, numBuckets, fieldName, cycleSize);
+  }
+
+  @Override
+  public Averager<Double> createAverager()
+  {
+    return new LongMeanAverager(numBuckets, name, fieldName, cycleSize);
+  }
+}

extensions-contrib/moving-average-query/src/main/java/org/apache/druid/query/movingaverage/averagers/LongMeanNoNullAverager.java

@@ -0,0 +1,46 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage.averagers;
+
+public class LongMeanNoNullAverager extends BaseAverager<Number, Double>
+{
+
+  public LongMeanNoNullAverager(int numBuckets, String name, String fieldName, int cycleSize)
+  {
+    super(Number.class, numBuckets, name, fieldName, cycleSize);
+  }
+
+  @Override
+  protected Double computeResult()
+  {
+    long result = 0;
+    int validBuckets = 0;
+
+    for (int i = 0; i < numBuckets; i += cycleSize) {
+      if (buckets[(i + startFrom) % numBuckets] != null) {
+        result += (buckets[(i + startFrom) % numBuckets]).longValue();
+        validBuckets++;
+      }
+    }
+
+    startFrom++;
+    return ((double) result) / validBuckets;
+  }
+}

extensions-contrib/moving-average-query/src/main/java/org/apache/druid/query/movingaverage/averagers/LongMeanNoNullAveragerFactory.java

@@ -0,0 +1,44 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage.averagers;
+
+import com.fasterxml.jackson.annotation.JsonCreator;
+import com.fasterxml.jackson.annotation.JsonProperty;
+
+public class LongMeanNoNullAveragerFactory extends ComparableAveragerFactory<Double, Double>
+{
+
+  @JsonCreator
+  public LongMeanNoNullAveragerFactory(
+      @JsonProperty("name") String name,
+      @JsonProperty("buckets") int numBuckets,
+      @JsonProperty("cycleSize") Integer cycleSize,
+      @JsonProperty("fieldName") String fieldName
+  )
+  {
+    super(name, numBuckets, fieldName, cycleSize);
+  }
+
+  @Override
+  public Averager<Double> createAverager()
+  {
+    return new LongMeanNoNullAverager(numBuckets, name, fieldName, cycleSize);
+  }
+}

extensions-contrib/moving-average-query/src/main/java/org/apache/druid/query/movingaverage/averagers/LongMinAverager.java

@@ -0,0 +1,45 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage.averagers;
+
+public class LongMinAverager extends BaseAverager<Number, Long>
+{
+
+  public LongMinAverager(int numBuckets, String name, String fieldName, int cycleSize)
+  {
+    super(Number.class, numBuckets, name, fieldName, cycleSize);
+  }
+
+  @Override
+  protected Long computeResult()
+  {
+    long result = Long.MAX_VALUE;
+
+    for (int i = 0; i < numBuckets; i += cycleSize) {
+      if (buckets[(i + startFrom) % numBuckets] != null) {
+        result = Long.min(result, (buckets[(i + startFrom) % numBuckets]).longValue());
+      }
+    }
+
+    startFrom++;
+    return result;
+  }
+
+}

extensions-contrib/moving-average-query/src/main/java/org/apache/druid/query/movingaverage/averagers/LongMinAveragerFactory.java

@@ -0,0 +1,44 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage.averagers;
+
+import com.fasterxml.jackson.annotation.JsonCreator;
+import com.fasterxml.jackson.annotation.JsonProperty;
+
+public class LongMinAveragerFactory extends ComparableAveragerFactory<Long, Long>
+{
+
+  @JsonCreator
+  public LongMinAveragerFactory(
+      @JsonProperty("name") String name,
+      @JsonProperty("buckets") int numBuckets,
+      @JsonProperty("cycleSize") int cycleSize,
+      @JsonProperty("fieldName") String fieldName
+  )
+  {
+    super(name, numBuckets, fieldName, cycleSize);
+  }
+
+  @Override
+  public Averager<Long> createAverager()
+  {
+    return new LongMinAverager(numBuckets, name, fieldName, cycleSize);
+  }
+}

extensions-contrib/moving-average-query/src/main/resources/META-INF/services/org.apache.druid.initialization.DruidModule

@@ -0,0 +1,16 @@
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+org.apache.druid.query.movingaverage.MovingAverageQueryModule

extensions-contrib/moving-average-query/src/test/java/org/apache/druid/query/movingaverage/MovingAverageIterableTest.java

@@ -0,0 +1,803 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage;
+
+import org.apache.druid.data.input.MapBasedRow;
+import org.apache.druid.data.input.Row;
+import org.apache.druid.java.util.common.guava.Sequence;
+import org.apache.druid.java.util.common.guava.Sequences;
+import org.apache.druid.query.aggregation.AggregatorFactory;
+import org.apache.druid.query.aggregation.FilteredAggregatorFactory;
+import org.apache.druid.query.aggregation.LongSumAggregatorFactory;
+import org.apache.druid.query.dimension.DefaultDimensionSpec;
+import org.apache.druid.query.dimension.DimensionSpec;
+import org.apache.druid.query.filter.DimFilter;
+import org.apache.druid.query.filter.SelectorDimFilter;
+import org.apache.druid.query.movingaverage.averagers.AveragerFactory;
+import org.apache.druid.query.movingaverage.averagers.ConstantAveragerFactory;
+import org.apache.druid.query.movingaverage.averagers.LongMeanAveragerFactory;
+import org.joda.time.DateTime;
+import org.joda.time.chrono.ISOChronology;
+import org.junit.Test;
+
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.Collections;
+import java.util.HashMap;
+import java.util.Iterator;
+import java.util.List;
+import java.util.Map;
+
+import static org.hamcrest.CoreMatchers.equalTo;
+import static org.hamcrest.CoreMatchers.not;
+import static org.junit.Assert.assertEquals;
+import static org.junit.Assert.assertFalse;
+import static org.junit.Assert.assertThat;
+import static org.junit.Assert.assertTrue;
+
+/**
+ *
+ */
+public class MovingAverageIterableTest
+{
+  private static final DateTime JAN_1 = new DateTime(2017, 1, 1, 0, 0, 0, 0, ISOChronology.getInstanceUTC());
+  private static final DateTime JAN_2 = new DateTime(2017, 1, 2, 0, 0, 0, 0, ISOChronology.getInstanceUTC());
+  private static final DateTime JAN_3 = new DateTime(2017, 1, 3, 0, 0, 0, 0, ISOChronology.getInstanceUTC());
+  private static final DateTime JAN_4 = new DateTime(2017, 1, 4, 0, 0, 0, 0, ISOChronology.getInstanceUTC());
+  private static final DateTime JAN_5 = new DateTime(2017, 1, 5, 0, 0, 0, 0, ISOChronology.getInstanceUTC());
+  private static final DateTime JAN_6 = new DateTime(2017, 1, 6, 0, 0, 0, 0, ISOChronology.getInstanceUTC());
+
+  private static final String GENDER = "gender";
+  private static final String AGE = "age";
+  private static final String COUNTRY = "country";
+
+  private static final Map<String, Object> dims1 = new HashMap<>();
+  private static final Map<String, Object> dims2 = new HashMap<>();
+  private static final Map<String, Object> dims3 = new HashMap<>();
+
+  static {
+    dims1.put(GENDER, "m");
+    dims1.put(AGE, "10");
+    dims1.put(COUNTRY, "US");
+
+    dims2.put(GENDER, "f");
+    dims2.put(AGE, "8");
+    dims2.put(COUNTRY, "US");
+
+    dims3.put(GENDER, "u");
+    dims3.put(AGE, "5");
+    dims3.put(COUNTRY, "UK");
+  }
+
+  @Test
+  public void testNext()
+  {
+
+    List<DimensionSpec> dims = Arrays.asList(
+        new DefaultDimensionSpec(GENDER, GENDER),
+        new DefaultDimensionSpec(AGE, AGE),
+        new DefaultDimensionSpec(COUNTRY, COUNTRY)
+    );
+
+    Sequence<RowBucket> dayBuckets = Sequences.simple(Arrays.asList(
+        new RowBucket(JAN_1, Arrays.asList(
+            new MapBasedRow(JAN_1, dims1),
+            new MapBasedRow(JAN_1, dims2)
+        )),
+        new RowBucket(JAN_2, Collections.singletonList(
+            new MapBasedRow(JAN_2, dims1)
+        )),
+        new RowBucket(JAN_3, Collections.emptyList()),
+        new RowBucket(JAN_4, Arrays.asList(
+            new MapBasedRow(JAN_4, dims2),
+            new MapBasedRow(JAN_4, dims3)
+        ))
+    ));
+
+    Iterable<Row> iterable = new MovingAverageIterable(
+        dayBuckets,
+        dims,
+        Collections.singletonList(new ConstantAveragerFactory("noop", 1, 1.1f)),
+        Collections.emptyList(),
+        Collections.emptyList()
+    );
+
+    Iterator<Row> iter = iterable.iterator();
+
+    assertTrue(iter.hasNext());
+    Row r = iter.next();
+    assertEquals(JAN_1, r.getTimestamp());
+    assertEquals("m", r.getRaw(GENDER));
+
+    assertTrue(iter.hasNext());
+    r = iter.next();
+    assertEquals(JAN_1, r.getTimestamp());
+    assertEquals("f", r.getRaw(GENDER));
+
+    assertTrue(iter.hasNext());
+    r = iter.next();
+    assertEquals(JAN_2, r.getTimestamp());
+    assertEquals("m", r.getRaw(GENDER));
+
+    assertTrue(iter.hasNext());
+    r = iter.next();
+    assertEquals(JAN_2, r.getTimestamp());
+    assertEquals("f", r.getRaw(GENDER));
+
+    assertTrue(iter.hasNext());
+    r = iter.next();
+    Row r2 = r;
+    assertEquals(JAN_3, r.getTimestamp());
+    assertEquals("US", r.getRaw(COUNTRY));
+
+    assertTrue(iter.hasNext());
+    r = iter.next();
+    assertEquals(JAN_3, r.getTimestamp());
+    assertEquals("US", r.getRaw(COUNTRY));
+    assertThat(r.getRaw(AGE), not(equalTo(r2.getRaw(AGE))));
+
+    assertTrue(iter.hasNext());
+    r = iter.next();
+    assertEquals(JAN_4, r.getTimestamp());
+    assertEquals("f", r.getRaw(GENDER));
+
+    assertTrue(iter.hasNext());
+    r = iter.next();
+    assertEquals(JAN_4, r.getTimestamp());
+    assertEquals("u", r.getRaw(GENDER));
+
+    assertTrue(iter.hasNext());
+    r = iter.next();
+    assertEquals(JAN_4, r.getTimestamp());
+    assertEquals("m", r.getRaw(GENDER));
+
+    assertFalse(iter.hasNext());
+  }
+
+  @Test
+  public void testAveraging()
+  {
+
+    Map<String, Object> event1 = new HashMap<>();
+    Map<String, Object> event2 = new HashMap<>();
+    Map<String, Object> event3 = new HashMap<>();
+    Map<String, Object> event4 = new HashMap<>();
+
+    List<DimensionSpec> ds = new ArrayList<>();
+    ds.add(new DefaultDimensionSpec("gender", "gender"));
+
+    event1.put("gender", "m");
+    event1.put("pageViews", 10L);
+    Row row1 = new MapBasedRow(JAN_1, event1);
+
+    event2.put("gender", "m");
+    event2.put("pageViews", 20L);
+    Row row2 = new MapBasedRow(JAN_2, event2);
+
+    event3.put("gender", "m");
+    event3.put("pageViews", 30L);
+    Row row3 = new MapBasedRow(JAN_3, event3);
+
+    event4.put("gender", "f");
+    event4.put("pageViews", 40L);
+    Row row4 = new MapBasedRow(JAN_3, event4);
+
+    float retval = 14.5f;
+
+    Sequence<RowBucket> seq = Sequences.simple(Arrays.asList(
+        new RowBucket(JAN_1, Collections.singletonList(row1)),
+        new RowBucket(JAN_2, Collections.singletonList(row2)),
+        new RowBucket(JAN_3, Arrays.asList(row3, row4))
+    ));
+
+    Iterator<Row> iter = new MovingAverageIterable(seq, ds, Arrays.asList(
+        new ConstantAveragerFactory("costPageViews", 7, retval),
+        new LongMeanAveragerFactory("movingAvgPageViews", 7, 1, "pageViews")
+    ),
+                                                   Collections.emptyList(),
+                                                   Collections.singletonList(new LongSumAggregatorFactory("pageViews",
+                                                                                                          "pageViews"
+                                                   ))
+    ).iterator();
+
+    assertTrue(iter.hasNext());
+    Row caResult = iter.next();
+
+    assertEquals(JAN_1, caResult.getTimestamp());
+    assertEquals("m", (caResult.getDimension("gender")).get(0));
+    assertEquals(retval, caResult.getMetric("costPageViews").floatValue(), 0.0f);
+    assertEquals(1.4285715f, caResult.getMetric("movingAvgPageViews").floatValue(), 0.0f);
+
+    assertTrue(iter.hasNext());
+    caResult = iter.next();
+    assertEquals("m", (caResult.getDimension("gender")).get(0));
+    assertEquals(4.285714f, caResult.getMetric("movingAvgPageViews").floatValue(), 0.0f);
+
+    assertTrue(iter.hasNext());
+    caResult = iter.next();
+    assertEquals("m", (caResult.getDimension("gender")).get(0));
+    assertEquals(8.571428f, caResult.getMetric("movingAvgPageViews").floatValue(), 0.0f);
+
+    assertTrue(iter.hasNext());
+    caResult = iter.next();
+    assertEquals("f", (caResult.getDimension("gender")).get(0));
+    assertEquals(5.714285850f, caResult.getMetric("movingAvgPageViews").floatValue(), 0.0f);
+
+    assertFalse(iter.hasNext());
+
+  }
+
+
+  @Test
+  public void testCompleteData()
+  {
+
+    Map<String, Object> event1 = new HashMap<>();
+    Map<String, Object> event2 = new HashMap<>();
+    Map<String, Object> event3 = new HashMap<>();
+
+    event1.put("gender", "m");
+    event1.put("pageViews", 10L);
+    event2.put("gender", "f");
+    event2.put("pageViews", 20L);
+    event3.put("gender", "u");
+    event3.put("pageViews", 30L);
+
+    List<DimensionSpec> ds = new ArrayList<>();
+    ds.add(new DefaultDimensionSpec("gender", "gender"));
+
+    Row jan1Row1 = new MapBasedRow(JAN_1, event1);
+    Row jan1Row2 = new MapBasedRow(JAN_1, event2);
+    Row jan1Row3 = new MapBasedRow(JAN_1, event3);
+
+    Row jan2Row1 = new MapBasedRow(JAN_2, event1);
+    Row jan2Row2 = new MapBasedRow(JAN_2, event2);
+    Row jan2Row3 = new MapBasedRow(JAN_2, event3);
+
+    Sequence<RowBucket> seq = Sequences.simple(Arrays.asList(
+        new RowBucket(JAN_1, Arrays.asList(jan1Row1, jan1Row2, jan1Row3)),
+        new RowBucket(JAN_2, Arrays.asList(jan2Row1, jan2Row2, jan2Row3))
+    ));
+
+    Iterator<Row> iter = new MovingAverageIterable(seq, ds, Collections.singletonList(
+        new LongMeanAveragerFactory("movingAvgPageViews", 2, 1, "pageViews")),
+                                                   Collections.emptyList(),
+                                                   Collections.singletonList(new LongSumAggregatorFactory("pageViews",
+                                                                                                          "pageViews"
+                                                   ))
+    ).iterator();
+
+    assertTrue(iter.hasNext());
+    Row result = iter.next();
+    assertEquals("m", (result.getDimension("gender")).get(0));
+    assertEquals(JAN_1, (result.getTimestamp()));
+
+    assertTrue(iter.hasNext());
+    result = iter.next();
+    assertEquals("f", (result.getDimension("gender")).get(0));
+    assertEquals(JAN_1, (result.getTimestamp()));
+
+    assertTrue(iter.hasNext());
+    result = iter.next();
+    assertEquals("u", (result.getDimension("gender")).get(0));
+    assertEquals(JAN_1, (result.getTimestamp()));
+
+    assertTrue(iter.hasNext());
+    result = iter.next();
+    assertEquals("m", (result.getDimension("gender")).get(0));
+    assertEquals(JAN_2, (result.getTimestamp()));
+
+    assertTrue(iter.hasNext());
+    result = iter.next();
+    assertEquals("f", (result.getDimension("gender")).get(0));
+    assertEquals(JAN_2, (result.getTimestamp()));
+
+    assertTrue(iter.hasNext());
+    result = iter.next();
+    assertEquals("u", (result.getDimension("gender")).get(0));
+    assertEquals(JAN_2, (result.getTimestamp()));
+
+    assertFalse(iter.hasNext());
+
+  }
+
+  // no injection if the data missing at the begining
+  @Test
+  public void testMissingDataAtBeginning()
+  {
+
+    Map<String, Object> event1 = new HashMap<>();
+    Map<String, Object> event2 = new HashMap<>();
+    Map<String, Object> event3 = new HashMap<>();
+
+    event1.put("gender", "m");
+    event1.put("pageViews", 10L);
+    event2.put("gender", "f");
+    event2.put("pageViews", 20L);
+    event3.put("gender", "u");
+    event3.put("pageViews", 30L);
+
+    List<DimensionSpec> ds = new ArrayList<>();
+    ds.add(new DefaultDimensionSpec("gender", "gender"));
+
+    Row jan1Row1 = new MapBasedRow(JAN_1, event1);
+
+    Row jan2Row1 = new MapBasedRow(JAN_2, event1);
+    Row jan2Row2 = new MapBasedRow(JAN_2, event2);
+    Row jan2Row3 = new MapBasedRow(JAN_2, event3);
+
+    Sequence<RowBucket> seq = Sequences.simple(Arrays.asList(
+        new RowBucket(JAN_1, Collections.singletonList(jan1Row1)),
+        new RowBucket(JAN_2, Arrays.asList(jan2Row1, jan2Row2, jan2Row3))
+    ));
+
+    Iterator<Row> iter = new MovingAverageIterable(seq, ds, Collections.singletonList(
+        new LongMeanAveragerFactory("movingAvgPageViews", 2, 1, "pageViews")),
+                                                   Collections.emptyList(),
+                                                   Collections.singletonList(new LongSumAggregatorFactory("pageViews",
+                                                                                                          "pageViews"
+                                                   ))
+    ).iterator();
+
+    assertTrue(iter.hasNext());
+    Row result = iter.next();
+    assertEquals("m", (result.getDimension("gender")).get(0));
+    assertEquals(JAN_1, (result.getTimestamp()));
+
+    assertTrue(iter.hasNext());
+    result = iter.next();
+    assertEquals("m", (result.getDimension("gender")).get(0));
+    assertEquals(JAN_2, (result.getTimestamp()));
+
+    assertTrue(iter.hasNext());
+    result = iter.next();
+    assertEquals("f", (result.getDimension("gender")).get(0));
+    assertEquals(JAN_2, (result.getTimestamp()));
+
+    assertTrue(iter.hasNext());
+    result = iter.next();
+    assertEquals("u", (result.getDimension("gender")).get(0));
+    assertEquals(JAN_2, (result.getTimestamp()));
+
+    assertFalse(iter.hasNext());
+  }
+
+  // test injection when the data is missing at the end
+  @Test
+  public void testMissingDataAtTheEnd()
+  {
+
+    Map<String, Object> event1 = new HashMap<>();
+    Map<String, Object> event2 = new HashMap<>();
+    Map<String, Object> event3 = new HashMap<>();
+
+    event1.put("gender", "m");
+    event1.put("pageViews", 10L);
+    event2.put("gender", "f");
+    event2.put("pageViews", 20L);
+    event3.put("gender", "u");
+    event3.put("pageViews", 30L);
+
+    List<DimensionSpec> ds = new ArrayList<>();
+    ds.add(new DefaultDimensionSpec("gender", "gender"));
+
+    Row jan1Row1 = new MapBasedRow(JAN_1, event1);
+    Row jan1Row2 = new MapBasedRow(JAN_1, event2);
+    Row jan1Row3 = new MapBasedRow(JAN_1, event3);
+    Row jan2Row1 = new MapBasedRow(JAN_2, event1);
+
+    Sequence<RowBucket> seq = Sequences.simple(Arrays.asList(
+        new RowBucket(JAN_1, Arrays.asList(jan1Row1, jan1Row2, jan1Row3)),
+        new RowBucket(JAN_2, Collections.singletonList(jan2Row1))
+    ));
+
+    Iterator<Row> iter = new MovingAverageIterable(seq, ds, Collections.singletonList(
+        new LongMeanAveragerFactory("movingAvgPageViews", 2, 1, "pageViews")),
+                                                   Collections.emptyList(),
+                                                   Collections.singletonList(new LongSumAggregatorFactory("pageViews",
+                                                                                                          "pageViews"
+                                                   ))
+    ).iterator();
+
+    assertTrue(iter.hasNext());
+    Row result = iter.next();
+    assertEquals("m", (result.getDimension("gender")).get(0));
+    assertEquals(JAN_1, (result.getTimestamp()));
+
+    assertTrue(iter.hasNext());
+    result = iter.next();
+    assertEquals("f", (result.getDimension("gender")).get(0));
+    assertEquals(JAN_1, (result.getTimestamp()));
+
+    assertTrue(iter.hasNext());
+    result = iter.next();
+    assertEquals("u", (result.getDimension("gender")).get(0));
+    assertEquals(JAN_1, (result.getTimestamp()));
+
+    assertTrue(iter.hasNext());
+    result = iter.next();
+    assertEquals("m", (result.getDimension("gender")).get(0));
+    assertEquals(JAN_2, (result.getTimestamp()));
+
+    assertTrue(iter.hasNext());
+    result = iter.next();
+    assertEquals("u", (result.getDimension("gender")).get(0));
+    assertEquals(JAN_2, (result.getTimestamp()));
+
+    assertTrue(iter.hasNext());
+    result = iter.next();
+    assertEquals("f", (result.getDimension("gender")).get(0));
+    assertEquals(JAN_2, (result.getTimestamp()));
+
+    assertFalse(iter.hasNext());
+  }
+
+  // test injection when the data is missing in the middle
+  @Test
+  public void testMissingDataAtMiddle()
+  {
+
+    Map<String, Object> eventM = new HashMap<>();
+    Map<String, Object> eventF = new HashMap<>();
+    Map<String, Object> eventU = new HashMap<>();
+    Map<String, Object> event4 = new HashMap<>();
+
+    eventM.put("gender", "m");
+    eventM.put("pageViews", 10L);
+    eventF.put("gender", "f");
+    eventF.put("pageViews", 20L);
+    eventU.put("gender", "u");
+    eventU.put("pageViews", 30L);
+
+    List<DimensionSpec> ds = new ArrayList<>();
+    ds.add(new DefaultDimensionSpec("gender", "gender"));
+
+    Row jan1Row1M = new MapBasedRow(JAN_1, eventM);
+    Row jan1Row2F = new MapBasedRow(JAN_1, eventF);
+    Row jan1Row3U = new MapBasedRow(JAN_1, eventU);
+    Row jan2Row1M = new MapBasedRow(JAN_2, eventM);
+    Row jan3Row1M = new MapBasedRow(JAN_3, eventM);
+    Row jan3Row2F = new MapBasedRow(JAN_3, eventF);
+    Row jan3Row3U = new MapBasedRow(JAN_3, eventU);
+    Row jan4Row1M = new MapBasedRow(JAN_4, eventM);
+
+    Sequence<RowBucket> seq = Sequences.simple(Arrays.asList(
+        new RowBucket(JAN_1, Arrays.asList(jan1Row1M, jan1Row2F, jan1Row3U)),
+        new RowBucket(JAN_2, Collections.singletonList(jan2Row1M)),
+        new RowBucket(JAN_3, Arrays.asList(jan3Row1M, jan3Row2F, jan3Row3U)),
+        new RowBucket(JAN_4, Collections.singletonList(jan4Row1M))
+    ));
+
+    Iterator<Row> iter = new MovingAverageIterable(seq, ds, Collections.singletonList(
+        new LongMeanAveragerFactory("movingAvgPageViews", 3, 1, "pageViews")),
+                                                   Collections.emptyList(),
+                                                   Collections.singletonList(new LongSumAggregatorFactory("pageViews",
+                                                                                                          "pageViews"
+                                                   ))
+    ).iterator();
+
+    // Jan 1
+    assertTrue(iter.hasNext());
+    Row result = iter.next();
+    assertEquals("m", (result.getDimension("gender")).get(0));
+    assertEquals(JAN_1, (result.getTimestamp()));
+
+    assertTrue(iter.hasNext());
+    result = iter.next();
+    assertEquals("f", (result.getDimension("gender")).get(0));
+    assertEquals(JAN_1, (result.getTimestamp()));
+
+    assertTrue(iter.hasNext());
+    result = iter.next();
+    assertEquals("u", (result.getDimension("gender")).get(0));
+    assertEquals(JAN_1, (result.getTimestamp()));
+
+    // Jan 2
+    assertTrue(iter.hasNext());
+    result = iter.next();
+    assertEquals("m", (result.getDimension("gender")).get(0));
+    assertEquals(JAN_2, (result.getTimestamp()));
+
+    assertTrue(iter.hasNext());
+    result = iter.next();
+    assertEquals("u", (result.getDimension("gender")).get(0));
+    assertEquals(JAN_2, (result.getTimestamp()));
+
+    assertTrue(iter.hasNext());
+    result = iter.next();
+    assertEquals("f", (result.getDimension("gender")).get(0));
+    assertEquals(JAN_2, (result.getTimestamp()));
+
+    // Jan 3
+    assertTrue(iter.hasNext());
+    result = iter.next();
+    assertEquals("m", (result.getDimension("gender")).get(0));
+    assertEquals(JAN_3, (result.getTimestamp()));
+
+    assertTrue(iter.hasNext());
+    result = iter.next();
+    assertEquals("f", (result.getDimension("gender")).get(0));
+    assertEquals(JAN_3, (result.getTimestamp()));
+
+    assertTrue(iter.hasNext());
+    result = iter.next();
+    assertEquals("u", (result.getDimension("gender")).get(0));
+    assertEquals(JAN_3, (result.getTimestamp()));
+
+    // Jan 4
+    assertTrue(iter.hasNext());
+    result = iter.next();
+    assertEquals("m", (result.getDimension("gender")).get(0));
+    assertEquals(JAN_4, (result.getTimestamp()));
+
+    assertTrue(iter.hasNext());
+    result = iter.next();
+    assertEquals("u", (result.getDimension("gender")).get(0));
+    assertEquals(JAN_4, (result.getTimestamp()));
+
+    assertTrue(iter.hasNext());
+    result = iter.next();
+    assertEquals("f", (result.getDimension("gender")).get(0));
+    assertEquals(JAN_4, (result.getTimestamp()));
+
+    assertFalse(iter.hasNext());
+  }
+
+  @Test
+  public void testMissingDaysAtBegining()
+  {
+
+    Map<String, Object> event1 = new HashMap<>();
+    Map<String, Object> event2 = new HashMap<>();
+
+    List<DimensionSpec> ds = new ArrayList<>();
+    ds.add(new DefaultDimensionSpec("gender", "gender"));
+
+    event1.put("gender", "m");
+    event1.put("pageViews", 10L);
+    Row row1 = new MapBasedRow(JAN_3, event1);
+
+    event2.put("gender", "m");
+    event2.put("pageViews", 20L);
+    Row row2 = new MapBasedRow(JAN_4, event2);
+
+    Sequence<RowBucket> seq = Sequences.simple(Arrays.asList(
+        new RowBucket(JAN_1, Collections.emptyList()),
+        new RowBucket(JAN_2, Collections.emptyList()),
+        new RowBucket(JAN_3, Collections.singletonList(row1)),
+        new RowBucket(JAN_4, Collections.singletonList(row2))
+    ));
+
+    Iterator<Row> iter = new MovingAverageIterable(seq, ds, Collections.singletonList(
+        new LongMeanAveragerFactory("movingAvgPageViews", 4, 1, "pageViews")),
+                                                   Collections.emptyList(),
+                                                   Collections.singletonList(new LongSumAggregatorFactory("pageViews",
+                                                                                                          "pageViews"
+                                                   ))
+    ).iterator();
+
+    assertTrue(iter.hasNext());
+    Row result = iter.next();
+    assertEquals("m", (result.getDimension("gender")).get(0));
+    assertEquals(2.5f, result.getMetric("movingAvgPageViews").floatValue(), 0.0f);
+
+    assertTrue(iter.hasNext());
+    result = iter.next();
+    assertEquals("m", (result.getDimension("gender")).get(0));
+    assertEquals(7.5f, result.getMetric("movingAvgPageViews").floatValue(), 0.0f);
+
+    assertFalse(iter.hasNext());
+  }
+
+  @Test
+  public void testMissingDaysInMiddle()
+  {
+    System.setProperty("druid.generic.useDefaultValueForNull", "true");
+
+    Map<String, Object> event1 = new HashMap<>();
+    Map<String, Object> event2 = new HashMap<>();
+
+    List<DimensionSpec> ds = new ArrayList<>();
+    ds.add(new DefaultDimensionSpec("gender", "gender"));
+
+    event1.put("gender", "m");
+    event1.put("pageViews", 10L);
+    Row row1 = new MapBasedRow(JAN_1, event1);
+
+    event2.put("gender", "m");
+    event2.put("pageViews", 20L);
+    Row row2 = new MapBasedRow(JAN_4, event2);
+
+    Sequence<RowBucket> seq = Sequences.simple(Arrays.asList(
+        new RowBucket(JAN_1, Collections.singletonList(row1)),
+        new RowBucket(JAN_2, Collections.emptyList()),
+        new RowBucket(JAN_3, Collections.emptyList()),
+        new RowBucket(JAN_4, Collections.singletonList(row2))
+    ));
+
+    Iterator<Row> iter = new MovingAverageIterable(seq, ds, Collections.singletonList(
+        new LongMeanAveragerFactory("movingAvgPageViews", 4, 1, "pageViews")),
+                                                   Collections.emptyList(),
+                                                   Collections.singletonList(new LongSumAggregatorFactory("pageViews",
+                                                                                                          "pageViews"
+                                                   ))
+    ).iterator();
+
+    assertTrue(iter.hasNext());
+    Row result = iter.next();
+    assertEquals("m", (result.getDimension("gender")).get(0));
+    assertEquals(2.5f, result.getMetric("movingAvgPageViews").floatValue(), 0.0f);
+
+    assertTrue(iter.hasNext());
+    result = iter.next();
+    assertEquals("m", (result.getDimension("gender")).get(0));
+    assertEquals(2.5f, result.getMetric("movingAvgPageViews").floatValue(), 0.0f);
+
+    assertTrue(iter.hasNext());
+    result = iter.next();
+    assertEquals("m", (result.getDimension("gender")).get(0));
+    assertEquals(2.5f, result.getMetric("movingAvgPageViews").floatValue(), 0.0f);
+
+    assertTrue(iter.hasNext());
+    result = iter.next();
+    assertEquals("m", (result.getDimension("gender")).get(0));
+    assertEquals(7.5f, result.getMetric("movingAvgPageViews").floatValue(), 0.0f);
+
+    assertFalse(iter.hasNext());
+  }
+
+  @Test
+  public void testWithFilteredAggregation()
+  {
+
+    Map<String, Object> event1 = new HashMap<>();
+    Map<String, Object> event2 = new HashMap<>();
+
+    List<DimensionSpec> ds = new ArrayList<>();
+    ds.add(new DefaultDimensionSpec("gender", "gender"));
+
+    event1.put("gender", "m");
+    event1.put("pageViews", 10L);
+    Row row1 = new MapBasedRow(JAN_1, event1);
+
+    event2.put("gender", "m");
+    event2.put("pageViews", 20L);
+    Row row2 = new MapBasedRow(JAN_4, event2);
+
+    Sequence<RowBucket> seq = Sequences.simple(Arrays.asList(
+        new RowBucket(JAN_1, Collections.singletonList(row1)),
+        new RowBucket(JAN_2, Collections.emptyList()),
+        new RowBucket(JAN_3, Collections.emptyList()),
+        new RowBucket(JAN_4, Collections.singletonList(row2))
+    ));
+
+    AveragerFactory averagerfactory = new LongMeanAveragerFactory("movingAvgPageViews", 4, 1, "pageViews");
+    AggregatorFactory aggregatorFactory = new LongSumAggregatorFactory("pageViews", "pageViews");
+    DimFilter filter = new SelectorDimFilter("gender", "m", null);
+    FilteredAggregatorFactory filteredAggregatorFactory = new FilteredAggregatorFactory(aggregatorFactory, filter);
+
+    Iterator<Row> iter = new MovingAverageIterable(seq, ds, Collections.singletonList(
+        averagerfactory),
+                                                   Collections.emptyList(),
+                                                   Collections.singletonList(
+                                                       filteredAggregatorFactory)
+    ).iterator();
+
+    assertTrue(iter.hasNext());
+    Row result = iter.next();
+    assertEquals("m", (result.getDimension("gender")).get(0));
+    assertEquals(2.5f, result.getMetric("movingAvgPageViews").floatValue(), 0.0f);
+
+    assertTrue(iter.hasNext());
+    result = iter.next();
+    assertEquals("m", (result.getDimension("gender")).get(0));
+    assertEquals(2.5f, result.getMetric("movingAvgPageViews").floatValue(), 0.0f);
+
+    assertTrue(iter.hasNext());
+    result = iter.next();
+    assertEquals("m", (result.getDimension("gender")).get(0));
+    assertEquals(2.5f, result.getMetric("movingAvgPageViews").floatValue(), 0.0f);
+
+    assertTrue(iter.hasNext());
+    result = iter.next();
+    assertEquals("m", (result.getDimension("gender")).get(0));
+    assertEquals(7.5f, result.getMetric("movingAvgPageViews").floatValue(), 0.0f);
+
+    assertFalse(iter.hasNext());
+  }
+
+  @Test
+  public void testMissingDaysAtEnd()
+  {
+    System.setProperty("druid.generic.useDefaultValueForNull", "true");
+
+    Map<String, Object> event1 = new HashMap<>();
+    Map<String, Object> event2 = new HashMap<>();
+
+    List<DimensionSpec> ds = new ArrayList<>();
+    ds.add(new DefaultDimensionSpec("gender", "gender"));
+
+    event1.put("gender", "m");
+    event1.put("pageViews", 10L);
+    Row row1 = new MapBasedRow(JAN_1, event1);
+
+    event2.put("gender", "m");
+    event2.put("pageViews", 20L);
+    Row row2 = new MapBasedRow(JAN_2, event2);
+
+    Sequence<RowBucket> seq = Sequences.simple(Arrays.asList(
+        new RowBucket(JAN_1, Collections.singletonList(row1)),
+        new RowBucket(JAN_2, Collections.singletonList(row2)),
+        new RowBucket(JAN_3, Collections.emptyList()),
+        new RowBucket(JAN_4, Collections.emptyList()),
+        new RowBucket(JAN_5, Collections.emptyList()),
+        new RowBucket(JAN_6, Collections.emptyList())
+    ));
+
+    Iterator<Row> iter = new MovingAverageIterable(seq, ds, Collections.singletonList(
+        new LongMeanAveragerFactory("movingAvgPageViews", 4, 1, "pageViews")),
+                                                   Collections.emptyList(),
+                                                   Collections.singletonList(new LongSumAggregatorFactory("pageViews",
+                                                                                                          "pageViews"
+                                                   ))
+    ).iterator();
+
+    assertTrue(iter.hasNext());
+    Row result = iter.next();
+
+    assertEquals(JAN_1, result.getTimestamp());
+    assertEquals("m", (result.getDimension("gender")).get(0));
+    assertEquals(2.5f, result.getMetric("movingAvgPageViews").floatValue(), 0.0f);
+
+    assertTrue(iter.hasNext());
+    result = iter.next();
+    assertEquals(JAN_2, result.getTimestamp());
+    assertEquals("m", (result.getDimension("gender")).get(0));
+    assertEquals(7.5f, result.getMetric("movingAvgPageViews").floatValue(), 0.0f);
+
+    assertTrue(iter.hasNext());
+    result = iter.next();
+    assertEquals(JAN_3, result.getTimestamp());
+    assertEquals("m", (result.getDimension("gender")).get(0));
+    assertEquals(7.5f, result.getMetric("movingAvgPageViews").floatValue(), 0.0f);
+
+    assertTrue(iter.hasNext());
+    result = iter.next();
+    assertEquals(JAN_4, result.getTimestamp());
+    assertEquals("m", (result.getDimension("gender")).get(0));
+    assertEquals(7.5f, result.getMetric("movingAvgPageViews").floatValue(), 0.0f);
+
+    assertTrue(iter.hasNext());
+    result = iter.next();
+    assertEquals(JAN_5, result.getTimestamp());
+    assertEquals("m", (result.getDimension("gender")).get(0));
+    assertEquals(5.0f, result.getMetric("movingAvgPageViews").floatValue(), 0.0f);
+
+    assertTrue(iter.hasNext());
+    result = iter.next();
+    assertEquals(JAN_6, result.getTimestamp());
+    assertEquals("m", (result.getDimension("gender")).get(0));
+    assertEquals(0.0f, result.getMetric("movingAvgPageViews").floatValue(), 0.0f);
+
+    assertFalse(iter.hasNext());
+
+  }
+
+}

extensions-contrib/moving-average-query/src/test/java/org/apache/druid/query/movingaverage/MovingAverageQueryTest.java

@@ -0,0 +1,420 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage;
+
+import com.fasterxml.jackson.core.JsonParseException;
+import com.fasterxml.jackson.core.type.TypeReference;
+import com.fasterxml.jackson.databind.JsonMappingException;
+import com.fasterxml.jackson.databind.ObjectMapper;
+import com.fasterxml.jackson.databind.node.ArrayNode;
+import com.fasterxml.jackson.dataformat.yaml.YAMLFactory;
+import com.google.common.collect.Maps;
+import com.google.inject.Injector;
+import com.google.inject.Module;
+import com.google.inject.name.Names;
+import com.google.inject.util.Providers;
+import mockit.Mock;
+import mockit.MockUp;
+import org.apache.druid.client.CachingClusteredClient;
+import org.apache.druid.client.DruidServer;
+import org.apache.druid.client.ImmutableDruidServer;
+import org.apache.druid.client.TimelineServerView;
+import org.apache.druid.client.cache.CacheConfig;
+import org.apache.druid.client.cache.CachePopulatorStats;
+import org.apache.druid.client.cache.ForegroundCachePopulator;
+import org.apache.druid.client.cache.MapCache;
+import org.apache.druid.client.selector.ServerSelector;
+import org.apache.druid.data.input.MapBasedRow;
+import org.apache.druid.data.input.Row;
+import org.apache.druid.guice.DruidProcessingModule;
+import org.apache.druid.guice.GuiceInjectors;
+import org.apache.druid.guice.QueryRunnerFactoryModule;
+import org.apache.druid.guice.QueryableModule;
+import org.apache.druid.guice.http.DruidHttpClientConfig;
+import org.apache.druid.initialization.Initialization;
+import org.apache.druid.java.util.common.guava.Accumulators;
+import org.apache.druid.java.util.common.guava.Sequence;
+import org.apache.druid.java.util.common.guava.Sequences;
+import org.apache.druid.java.util.emitter.core.Event;
+import org.apache.druid.java.util.emitter.service.ServiceEmitter;
+import org.apache.druid.query.DataSource;
+import org.apache.druid.query.Query;
+import org.apache.druid.query.QueryPlus;
+import org.apache.druid.query.QueryRunner;
+import org.apache.druid.query.QuerySegmentWalker;
+import org.apache.druid.query.QueryToolChestWarehouse;
+import org.apache.druid.query.Result;
+import org.apache.druid.query.RetryQueryRunnerConfig;
+import org.apache.druid.query.groupby.GroupByQuery;
+import org.apache.druid.query.movingaverage.test.TestConfig;
+import org.apache.druid.query.timeseries.TimeseriesQuery;
+import org.apache.druid.query.timeseries.TimeseriesResultValue;
+import org.apache.druid.server.ClientQuerySegmentWalker;
+import org.apache.druid.server.initialization.ServerConfig;
+import org.apache.druid.timeline.TimelineLookup;
+import org.hamcrest.core.IsInstanceOf;
+import org.junit.Test;
+import org.junit.runner.RunWith;
+import org.junit.runners.Parameterized;
+import org.junit.runners.Parameterized.Parameters;
+
+import java.io.BufferedReader;
+import java.io.IOException;
+import java.io.InputStream;
+import java.io.InputStreamReader;
+import java.nio.charset.StandardCharsets;
+import java.util.ArrayList;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+import java.util.concurrent.Executor;
+
+import static org.junit.Assert.assertEquals;
+import static org.junit.Assert.assertNotNull;
+import static org.junit.Assert.assertThat;
+
+/**
+ * Base class for implementing MovingAverageQuery tests
+ */
+@RunWith(Parameterized.class)
+public class MovingAverageQueryTest
+{
+  private final ObjectMapper jsonMapper;
+  private final Injector injector;
+  private final QueryToolChestWarehouse warehouse;
+  private final RetryQueryRunnerConfig retryConfig;
+  private final ServerConfig serverConfig;
+
+  private final List<Row> groupByResults = new ArrayList<>();
+  private final List<Result<TimeseriesResultValue>> timeseriesResults = new ArrayList<>();
+
+  private final TestConfig config;
+  private final String yamlFile;
+
+  @Parameters(name = "{0}")
+  public static Iterable<String[]> data() throws IOException
+  {
+    BufferedReader testReader = new BufferedReader(
+        new InputStreamReader(MovingAverageQueryTest.class.getResourceAsStream("/queryTests"), StandardCharsets.UTF_8));
+    List<String[]> tests = new ArrayList<>();
+
+    for (String line = testReader.readLine(); line != null; line = testReader.readLine()) {
+      tests.add(new String[] {line});
+    }
+
+    return tests;
+  }
+
+  public MovingAverageQueryTest(String yamlFile) throws IOException
+  {
+    this.yamlFile = yamlFile;
+
+    List<Module> modules = getRequiredModules();
+    modules.add(
+        binder -> {
+          binder.bindConstant().annotatedWith(Names.named("serviceName")).to("queryTest");
+          binder.bindConstant().annotatedWith(Names.named("servicePort")).to(0);
+          binder.bindConstant().annotatedWith(Names.named("tlsServicePort")).to(1);
+          binder.bind(QuerySegmentWalker.class).toProvider(Providers.of(null));
+        }
+    );
+
+    System.setProperty("druid.generic.useDefaultValueForNull", "true");
+    System.setProperty("druid.processing.buffer.sizeBytes", "655360");
+    Injector baseInjector = GuiceInjectors.makeStartupInjector();
+    injector = Initialization.makeInjectorWithModules(baseInjector, modules);
+
+    jsonMapper = injector.getInstance(ObjectMapper.class);
+    warehouse = injector.getInstance(QueryToolChestWarehouse.class);
+    retryConfig = injector.getInstance(RetryQueryRunnerConfig.class);
+    serverConfig = injector.getInstance(ServerConfig.class);
+
+    InputStream is = getClass().getResourceAsStream("/queryTests/" + yamlFile);
+    ObjectMapper reader = new ObjectMapper(new YAMLFactory());
+    config = reader.readValue(is, TestConfig.class);
+  }
+
+  /**
+   * Returns the JSON query that should be used in the test.
+   *
+   * @return The JSON query
+   */
+  protected String getQueryString()
+  {
+    return config.query.toString();
+  }
+
+  /**
+   * Returns the JSON result that should be expected from the query.
+   *
+   * @return The JSON result
+   */
+  protected String getExpectedResultString()
+  {
+    return config.expectedOutput.toString();
+  }
+
+  /**
+   * Returns the JSON result that the nested groupby query should produce.
+   * Either this method or {@link #getTimeseriesResultJson()} must be defined
+   * by the subclass.
+   *
+   * @return The JSON result from the groupby query
+   */
+  protected String getGroupByResultJson()
+  {
+    ArrayNode node = config.intermediateResults.get("groupBy");
+    return node == null ? null : node.toString();
+  }
+
+  /**
+   * Returns the JSON result that the nested timeseries query should produce.
+   * Either this method or {@link #getGroupByResultJson()} must be defined
+   * by the subclass.
+   *
+   * @return The JSON result from the timeseries query
+   */
+  protected String getTimeseriesResultJson()
+  {
+    ArrayNode node = config.intermediateResults.get("timeseries");
+    return node == null ? null : node.toString();
+  }
+
+  /**
+   * Returns the expected query type.
+   *
+   * @return The Query type
+   */
+  protected Class<?> getExpectedQueryType()
+  {
+    return MovingAverageQuery.class;
+  }
+
+  protected TypeReference<?> getExpectedResultType()
+  {
+    return new TypeReference<List<Row>>()
+    {
+    };
+  }
+
+  /**
+   * Returns a list of any additional Druid Modules necessary to run the test.
+   *
+   * @return List of Druid Modules
+   */
+  protected List<Module> getRequiredModules()
+  {
+    List<Module> list = new ArrayList<>();
+
+    list.add(new QueryRunnerFactoryModule());
+    list.add(new QueryableModule());
+    list.add(new DruidProcessingModule());
+
+    return list;
+  }
+
+  /**
+   * Set up any needed mocks to stub out backend query behavior.
+   *
+   * @throws IOException
+   * @throws JsonMappingException
+   * @throws JsonParseException
+   */
+  protected void defineMocks() throws IOException
+  {
+    groupByResults.clear();
+    timeseriesResults.clear();
+
+    if (getGroupByResultJson() != null) {
+      groupByResults.addAll(jsonMapper.readValue(getGroupByResultJson(), new TypeReference<List<Row>>()
+      {
+      }));
+    }
+
+    if (getTimeseriesResultJson() != null) {
+      timeseriesResults.addAll(jsonMapper.readValue(
+          getTimeseriesResultJson(),
+          new TypeReference<List<Result<TimeseriesResultValue>>>()
+          {
+          }
+      ));
+    }
+  }
+
+  /**
+   * converts Int to Long, Float to Double in the actual and expected result
+   *
+   * @param result
+   */
+  protected List<MapBasedRow> consistentTypeCasting(List<MapBasedRow> result)
+  {
+    List<MapBasedRow> newResult = new ArrayList<>();
+    for (MapBasedRow row : result) {
+      final Map<String, Object> event = Maps.newLinkedHashMap((row).getEvent());
+      event.forEach((key, value) -> {
+        if (Integer.class.isInstance(value)) {
+          event.put(key, ((Integer) value).longValue());
+        }
+        if (Float.class.isInstance(value)) {
+          event.put(key, ((Float) value).doubleValue());
+        }
+      });
+      newResult.add(new MapBasedRow(row.getTimestamp(), event));
+    }
+    
+    return newResult;
+  }
+
+  /**
+   * Validate that the specified query behaves correctly.
+   *
+   * @throws IOException
+   * @throws JsonMappingException
+   * @throws JsonParseException
+   */
+  @SuppressWarnings({"unchecked", "rawtypes"})
+  @Test
+  public void testQuery() throws IOException
+  {
+
+
+    // create mocks for nested queries
+    @SuppressWarnings("unused")
+
+    MockUp<GroupByQuery> groupByQuery = new MockUp<GroupByQuery>()
+    {
+      @Mock
+      public QueryRunner getRunner(QuerySegmentWalker walker)
+      {
+        return new QueryRunner()
+        {
+          @Override
+          public Sequence run(QueryPlus queryPlus, Map responseContext)
+          {
+            return Sequences.simple(groupByResults);
+          }
+        };
+      }
+    };
+
+
+    @SuppressWarnings("unused")
+    MockUp<TimeseriesQuery> timeseriesQuery = new MockUp<TimeseriesQuery>()
+    {
+      @Mock
+      public QueryRunner getRunner(QuerySegmentWalker walker)
+      {
+        return new QueryRunner()
+        {
+          @Override
+          public Sequence run(QueryPlus queryPlus, Map responseContext)
+          {
+            return Sequences.simple(timeseriesResults);
+          }
+        };
+      }
+    };
+
+
+    Query<?> query = jsonMapper.readValue(getQueryString(), Query.class);
+    assertThat(query, IsInstanceOf.instanceOf(getExpectedQueryType()));
+
+    List<MapBasedRow> expectedResults = jsonMapper.readValue(getExpectedResultString(), getExpectedResultType());
+    assertNotNull(expectedResults);
+    assertThat(expectedResults, IsInstanceOf.instanceOf(List.class));
+
+    CachingClusteredClient baseClient = new CachingClusteredClient(
+        warehouse,
+        new TimelineServerView()
+        {
+          @Override
+          public TimelineLookup<String, ServerSelector> getTimeline(DataSource dataSource)
+          {
+            return null;
+          }
+
+          @Override
+          public List<ImmutableDruidServer> getDruidServers()
+          {
+            return null;
+          }
+
+          @Override
+          public <T> QueryRunner<T> getQueryRunner(DruidServer server)
+          {
+            return null;
+          }
+
+          @Override
+          public void registerTimelineCallback(Executor exec, TimelineCallback callback)
+          {
+
+          }
+
+          @Override
+          public void registerSegmentCallback(Executor exec, SegmentCallback callback)
+          {
+
+          }
+
+          @Override
+          public void registerServerRemovedCallback(Executor exec, ServerRemovedCallback callback)
+          {
+
+          }
+        },
+        MapCache.create(100000),
+        jsonMapper,
+        new ForegroundCachePopulator(jsonMapper, new CachePopulatorStats(), -1),
+        new CacheConfig(),
+        new DruidHttpClientConfig()
+        {
+          @Override
+          public long getMaxQueuedBytes()
+          {
+            return 0L;
+          }
+        }
+    );
+
+    ClientQuerySegmentWalker walker = new ClientQuerySegmentWalker(
+        new ServiceEmitter("", "", null)
+        {
+          @Override
+          public void emit(Event event) {}
+        },
+        baseClient, warehouse, retryConfig, jsonMapper, serverConfig, null, new CacheConfig()
+    );
+    final Map<String, Object> responseContext = new HashMap<>();
+
+    defineMocks();
+
+    QueryPlus queryPlus = QueryPlus.wrap(query);
+    final Sequence<?> res = query.getRunner(walker).run(queryPlus, responseContext);
+
+    List actualResults = new ArrayList();
+    actualResults = (List<MapBasedRow>) res.accumulate(actualResults, Accumulators.list());
+
+    expectedResults = consistentTypeCasting(expectedResults);
+    actualResults = consistentTypeCasting(actualResults);
+
+    assertEquals(expectedResults, actualResults);
+  }
+}

extensions-contrib/moving-average-query/src/test/java/org/apache/druid/query/movingaverage/PostAveragerAggregatorCalculatorTest.java

@@ -0,0 +1,109 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage;
+
+import org.apache.druid.data.input.MapBasedRow;
+import org.apache.druid.data.input.Row;
+import org.apache.druid.java.util.common.granularity.Granularities;
+import org.apache.druid.query.TableDataSource;
+import org.apache.druid.query.aggregation.CountAggregatorFactory;
+import org.apache.druid.query.aggregation.post.ArithmeticPostAggregator;
+import org.apache.druid.query.aggregation.post.FieldAccessPostAggregator;
+import org.apache.druid.query.movingaverage.averagers.DoubleMeanAveragerFactory;
+import org.apache.druid.query.spec.MultipleIntervalSegmentSpec;
+import org.joda.time.DateTime;
+import org.joda.time.Interval;
+import org.joda.time.chrono.ISOChronology;
+import org.junit.Before;
+import org.junit.Test;
+
+import java.util.Arrays;
+import java.util.Collections;
+import java.util.HashMap;
+import java.util.Map;
+
+import static org.junit.Assert.assertEquals;
+import static org.junit.Assert.assertNull;
+
+
+/**
+ * Unit tests for PostAveragerCalcualtor
+ */
+public class PostAveragerAggregatorCalculatorTest
+{
+
+  private MovingAverageQuery query;
+  private PostAveragerAggregatorCalculator pac;
+  private Map<String, Object> event;
+  private MapBasedRow row;
+
+  @Before
+  public void setup()
+  {
+    System.setProperty("druid.generic.useDefaultValueForNull", "true");
+    query = new MovingAverageQuery(
+        new TableDataSource("d"),
+        new MultipleIntervalSegmentSpec(Collections.singletonList(new Interval("2017-01-01/2017-01-01", ISOChronology.getInstanceUTC()))),
+        null,
+        Granularities.DAY,
+        null,
+        Collections.singletonList(new CountAggregatorFactory("count")),
+        Collections.emptyList(),
+        null,
+        Collections.singletonList(new DoubleMeanAveragerFactory("avgCount", 7, 1, "count")),
+        Collections.singletonList(new ArithmeticPostAggregator(
+            "avgCountRatio",
+            "/",
+            Arrays.asList(
+                new FieldAccessPostAggregator("count", "count"),
+                new FieldAccessPostAggregator("avgCount", "avgCount")
+            )
+        )),
+        null,
+        null
+    );
+
+    pac = new PostAveragerAggregatorCalculator(query);
+    event = new HashMap<>();
+    row = new MapBasedRow(new DateTime(ISOChronology.getInstanceUTC()), event);
+  }
+
+  @Test
+  public void testApply()
+  {
+    event.put("count", new Double(10.0));
+    event.put("avgCount", new Double(12.0));
+
+    Row result = pac.apply(row);
+
+    assertEquals(result.getMetric("avgCountRatio").floatValue(), 10.0f / 12.0f, 0.0);
+  }
+
+  @Test
+  public void testApplyMissingColumn()
+  {
+    event.put("count", new Double(10.0));
+
+    Row result = pac.apply(row);
+
+    assertEquals(result.getMetric("avgCountRatio").floatValue(), 0.0, 0.0);
+    assertNull(result.getRaw("avgCountRatio"));
+  }
+}

extensions-contrib/moving-average-query/src/test/java/org/apache/druid/query/movingaverage/RowBucketIterableTest.java

@@ -0,0 +1,670 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage;
+
+import org.apache.druid.data.input.MapBasedRow;
+import org.apache.druid.data.input.Row;
+import org.apache.druid.java.util.common.guava.Sequence;
+import org.apache.druid.java.util.common.guava.Sequences;
+import org.joda.time.DateTime;
+import org.joda.time.Interval;
+import org.joda.time.Period;
+import org.joda.time.chrono.ISOChronology;
+import org.junit.BeforeClass;
+import org.junit.Test;
+
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.Collections;
+import java.util.HashMap;
+import java.util.Iterator;
+import java.util.List;
+import java.util.Map;
+
+import static org.junit.Assert.assertEquals;
+import static org.junit.Assert.assertTrue;
+
+public class RowBucketIterableTest
+{
+
+  private static final DateTime JAN_1 = new DateTime(2017, 1, 1, 0, 0, 0, 0, ISOChronology.getInstanceUTC());
+  private static final DateTime JAN_2 = new DateTime(2017, 1, 2, 0, 0, 0, 0, ISOChronology.getInstanceUTC());
+  private static final DateTime JAN_3 = new DateTime(2017, 1, 3, 0, 0, 0, 0, ISOChronology.getInstanceUTC());
+  private static final DateTime JAN_4 = new DateTime(2017, 1, 4, 0, 0, 0, 0, ISOChronology.getInstanceUTC());
+  private static final DateTime JAN_5 = new DateTime(2017, 1, 5, 0, 0, 0, 0, ISOChronology.getInstanceUTC());
+  private static final DateTime JAN_6 = new DateTime(2017, 1, 6, 0, 0, 0, 0, ISOChronology.getInstanceUTC());
+  private static final DateTime JAN_9 = new DateTime(2017, 1, 9, 0, 0, 0, 0, ISOChronology.getInstanceUTC());
+
+  private static final Map<String, Object> EVENT_M_10 = new HashMap<>();
+  private static final Map<String, Object> EVENT_F_20 = new HashMap<>();
+  private static final Map<String, Object> EVENT_U_30 = new HashMap<>();
+
+  private static final Row JAN_1_M_10 = new MapBasedRow(new DateTime(2017, 1, 1, 0, 0, 0, 0, ISOChronology.getInstanceUTC()), EVENT_M_10);
+  private static final Row JAN_1_F_20 = new MapBasedRow(new DateTime(2017, 1, 1, 0, 0, 0, 0, ISOChronology.getInstanceUTC()), EVENT_F_20);
+  private static final Row JAN_1_U_30 = new MapBasedRow(new DateTime(2017, 1, 1, 0, 0, 0, 0, ISOChronology.getInstanceUTC()), EVENT_U_30);
+  private static final Row JAN_2_M_10 = new MapBasedRow(new DateTime(2017, 1, 2, 0, 0, 0, 0, ISOChronology.getInstanceUTC()), EVENT_M_10);
+  private static final Row JAN_3_M_10 = new MapBasedRow(new DateTime(2017, 1, 3, 0, 0, 0, 0, ISOChronology.getInstanceUTC()), EVENT_M_10);
+  private static final Row JAN_3_F_20 = new MapBasedRow(new DateTime(2017, 1, 3, 0, 0, 0, 0, ISOChronology.getInstanceUTC()), EVENT_F_20);
+  private static final Row JAN_4_M_10 = new MapBasedRow(new DateTime(2017, 1, 4, 0, 0, 0, 0, ISOChronology.getInstanceUTC()), EVENT_M_10);
+  private static final Row JAN_4_F_20 = new MapBasedRow(new DateTime(2017, 1, 4, 0, 0, 0, 0, ISOChronology.getInstanceUTC()), EVENT_F_20);
+  private static final Row JAN_4_U_30 = new MapBasedRow(new DateTime(2017, 1, 4, 0, 0, 0, 0, ISOChronology.getInstanceUTC()), EVENT_U_30);
+  private static final Row JAN_5_M_10 = new MapBasedRow(new DateTime(2017, 1, 5, 0, 0, 0, 0, ISOChronology.getInstanceUTC()), EVENT_M_10);
+  private static final Row JAN_6_M_10 = new MapBasedRow(new DateTime(2017, 1, 6, 0, 0, 0, 0, ISOChronology.getInstanceUTC()), EVENT_M_10);
+  private static final Row JAN_7_F_20 = new MapBasedRow(new DateTime(2017, 1, 7, 0, 0, 0, 0, ISOChronology.getInstanceUTC()), EVENT_F_20);
+  private static final Row JAN_8_U_30 = new MapBasedRow(new DateTime(2017, 1, 8, 0, 0, 0, 0, ISOChronology.getInstanceUTC()), EVENT_U_30);
+
+  private static final Interval INTERVAL_JAN_1_1 = new Interval(JAN_1, JAN_2);
+  private static final Interval INTERVAL_JAN_1_2 = new Interval(JAN_1, JAN_3);
+  private static final Interval INTERVAL_JAN_1_4 = new Interval(JAN_1, JAN_5);
+  private static final Interval INTERVAL_JAN_1_5 = new Interval(JAN_1, JAN_6);
+  private static final Interval INTERVAL_JAN_6_8 = new Interval(JAN_6, JAN_9);
+  private static final Period ONE_DAY = Period.days(1);
+
+  private List<Row> rows = null;
+  private List<Interval> intervals = new ArrayList<>();
+
+  @BeforeClass
+  public static void setupClass()
+  {
+    EVENT_M_10.put("gender", "m");
+    EVENT_M_10.put("pageViews", 10L);
+    EVENT_F_20.put("gender", "f");
+    EVENT_F_20.put("pageViews", 20L);
+    EVENT_U_30.put("gender", "u");
+    EVENT_U_30.put("pageViews", 30L);
+  }
+
+  // normal case. data for all the days present
+  @Test
+  public void testCompleteData()
+  {
+
+    intervals = new ArrayList<>();
+    intervals.add(INTERVAL_JAN_1_4);
+
+    rows = new ArrayList<>();
+    rows.add(JAN_1_M_10);
+    rows.add(JAN_2_M_10);
+    rows.add(JAN_3_M_10);
+    rows.add(JAN_4_M_10);
+
+    List<Row> expectedDay1 = Collections.singletonList(JAN_1_M_10);
+    List<Row> expectedDay2 = Collections.singletonList(JAN_2_M_10);
+    List<Row> expectedDay3 = Collections.singletonList(JAN_3_M_10);
+    List<Row> expectedDay4 = Collections.singletonList(JAN_4_M_10);
+
+    Sequence<Row> seq = Sequences.simple(rows);
+    RowBucketIterable rbi = new RowBucketIterable(seq, intervals, ONE_DAY);
+    Iterator<RowBucket> iter = rbi.iterator();
+
+    RowBucket actual = iter.next();
+    assertEquals(JAN_1, actual.getDateTime());
+    assertEquals(expectedDay1, actual.getRows());
+
+    actual = iter.next();
+    assertEquals(JAN_2, actual.getDateTime());
+    assertEquals(expectedDay2, actual.getRows());
+
+    actual = iter.next();
+    assertEquals(JAN_3, actual.getDateTime());
+    assertEquals(expectedDay3, actual.getRows());
+
+    actual = iter.next();
+    assertEquals(JAN_4, actual.getDateTime());
+    assertEquals(expectedDay4, actual.getRows());
+  }
+
+  // all days present and last day only has one row
+  @Test
+  public void testApplyLastDaySingleRow()
+  {
+
+    intervals = new ArrayList<>();
+    intervals.add(INTERVAL_JAN_1_4);
+
+    List<Row> expectedDay1 = Arrays.asList(JAN_1_M_10, JAN_1_F_20);
+    List<Row> expectedDay2 = Collections.singletonList(JAN_2_M_10);
+    List<Row> expectedDay3 = Collections.singletonList(JAN_3_F_20);
+    List<Row> expectedDay4 = Collections.singletonList(JAN_4_M_10);
+
+    rows = new ArrayList<>();
+    rows.add(JAN_1_M_10);
+    rows.add(JAN_1_F_20);
+    rows.add(JAN_2_M_10);
+    rows.add(JAN_3_F_20);
+    rows.add(JAN_4_M_10);
+
+    Sequence<Row> seq = Sequences.simple(rows);
+    RowBucketIterable rbi = new RowBucketIterable(seq, intervals, ONE_DAY);
+    Iterator<RowBucket> iter = rbi.iterator();
+
+    RowBucket actual = iter.next();
+    assertEquals(expectedDay1, actual.getRows());
+
+    actual = iter.next();
+    assertEquals(expectedDay2, actual.getRows());
+
+    actual = iter.next();
+    assertEquals(expectedDay3, actual.getRows());
+
+    actual = iter.next();
+    assertEquals(expectedDay4, actual.getRows());
+  }
+
+  // all days present and last day has multiple rows
+  @Test
+  public void testApplyLastDayMultipleRows()
+  {
+
+    intervals = new ArrayList<>();
+    intervals.add(INTERVAL_JAN_1_4);
+
+    List<Row> expectedDay1 = Arrays.asList(JAN_1_M_10, JAN_1_F_20);
+    List<Row> expectedDay2 = Collections.singletonList(JAN_2_M_10);
+    List<Row> expectedDay3 = Collections.singletonList(JAN_3_F_20);
+    List<Row> expectedDay4 = Arrays.asList(JAN_4_M_10, JAN_4_F_20, JAN_4_U_30);
+
+    rows = new ArrayList<>();
+    rows.add(JAN_1_M_10);
+    rows.add(JAN_1_F_20);
+    rows.add(JAN_2_M_10);
+    rows.add(JAN_3_F_20);
+    rows.add(JAN_4_M_10);
+    rows.add(JAN_4_F_20);
+    rows.add(JAN_4_U_30);
+
+    Sequence<Row> seq = Sequences.simple(rows);
+    RowBucketIterable rbi = new RowBucketIterable(seq, intervals, ONE_DAY);
+    Iterator<RowBucket> iter = rbi.iterator();
+
+    RowBucket actual = iter.next();
+    assertEquals(expectedDay1, actual.getRows());
+
+    actual = iter.next();
+    assertEquals(expectedDay2, actual.getRows());
+
+    actual = iter.next();
+    assertEquals(expectedDay3, actual.getRows());
+
+    actual = iter.next();
+    assertEquals(expectedDay4, actual.getRows());
+  }
+
+  // test single day with single row
+  @Test
+  public void testSingleDaySingleRow()
+  {
+
+    intervals = new ArrayList<>();
+    intervals.add(INTERVAL_JAN_1_1);
+
+    rows = new ArrayList<>();
+    rows.add(JAN_1_M_10);
+
+    List<Row> expectedDay1 = Collections.singletonList(JAN_1_M_10);
+
+    Sequence<Row> seq = Sequences.simple(rows);
+    RowBucketIterable rbi = new RowBucketIterable(seq, intervals, ONE_DAY);
+    Iterator<RowBucket> iter = rbi.iterator();
+
+    RowBucket actual = iter.next();
+    assertEquals(expectedDay1, actual.getRows());
+    assertEquals(JAN_1, actual.getDateTime());
+
+  }
+
+  // test single day with multiple rows
+  @Test
+  public void testSingleDayMultipleRow()
+  {
+
+    intervals = new ArrayList<>();
+    intervals.add(INTERVAL_JAN_1_1);
+
+    rows = new ArrayList<>();
+    rows.add(JAN_1_M_10);
+    rows.add(JAN_1_F_20);
+    rows.add(JAN_1_U_30);
+
+    List<Row> expectedDay1 = Arrays.asList(JAN_1_M_10, JAN_1_F_20, JAN_1_U_30);
+
+    Sequence<Row> seq = Sequences.simple(rows);
+    RowBucketIterable rbi = new RowBucketIterable(seq, intervals, ONE_DAY);
+    Iterator<RowBucket> iter = rbi.iterator();
+
+    RowBucket actual = iter.next();
+    assertEquals(JAN_1, actual.getDateTime());
+    assertEquals(expectedDay1, actual.getRows());
+
+  }
+
+  //  missing day at the beginning followed by single row
+  @Test
+  public void testMissingDaysAtBegining()
+  {
+
+    List<Row> expectedDay1 = Collections.emptyList();
+    List<Row> expectedDay2 = Collections.singletonList(JAN_2_M_10);
+
+    intervals = new ArrayList<>();
+    intervals.add(INTERVAL_JAN_1_2);
+
+    rows = new ArrayList<>();
+    rows.add(JAN_2_M_10);
+
+    Sequence<Row> seq = Sequences.simple(rows);
+    RowBucketIterable rbi = new RowBucketIterable(seq, intervals, ONE_DAY);
+    Iterator<RowBucket> iter = rbi.iterator();
+
+    RowBucket actual = iter.next();
+    assertEquals(JAN_1, actual.getDateTime());
+    assertEquals(expectedDay1, actual.getRows());
+
+    actual = iter.next();
+    assertEquals(JAN_2, actual.getDateTime());
+    assertEquals(expectedDay2, actual.getRows());
+
+  }
+
+  //  missing day at the beginning followed by multiple row
+  @Test
+  public void testMissingDaysAtBeginingFollowedByMultipleRow()
+  {
+
+    List<Row> expectedDay1 = Collections.emptyList();
+    List<Row> expectedDay2 = Collections.singletonList(JAN_2_M_10);
+    List<Row> expectedDay3 = Collections.singletonList(JAN_3_M_10);
+    List<Row> expectedDay4 = Collections.singletonList(JAN_4_M_10);
+
+    intervals = new ArrayList<>();
+    intervals.add(INTERVAL_JAN_1_4);
+
+    rows = new ArrayList<>();
+    rows.add(JAN_2_M_10);
+    rows.add(JAN_3_M_10);
+    rows.add(JAN_4_M_10);
+
+    Sequence<Row> seq = Sequences.simple(rows);
+    RowBucketIterable rbi = new RowBucketIterable(seq, intervals, ONE_DAY);
+    Iterator<RowBucket> iter = rbi.iterator();
+
+    RowBucket actual = iter.next();
+    assertEquals(JAN_1, actual.getDateTime());
+    assertEquals(expectedDay1, actual.getRows());
+
+    actual = iter.next();
+    assertEquals(JAN_2, actual.getDateTime());
+    assertEquals(expectedDay2, actual.getRows());
+
+    actual = iter.next();
+    assertEquals(JAN_3, actual.getDateTime());
+    assertEquals(expectedDay3, actual.getRows());
+
+    actual = iter.next();
+    assertEquals(JAN_4, actual.getDateTime());
+    assertEquals(expectedDay4, actual.getRows());
+  }
+
+  //  missing day at the beginning and at the end
+  @Test
+  public void testMissingDaysAtBeginingAndAtTheEnd()
+  {
+
+    List<Row> expectedDay1 = Collections.emptyList();
+    List<Row> expectedDay2 = Collections.singletonList(JAN_2_M_10);
+    List<Row> expectedDay3 = Collections.singletonList(JAN_3_M_10);
+    List<Row> expectedDay4 = Collections.emptyList();
+
+    intervals = new ArrayList<>();
+    intervals.add(INTERVAL_JAN_1_4);
+
+    rows = new ArrayList<>();
+    rows.add(JAN_2_M_10);
+    rows.add(JAN_3_M_10);
+
+    Sequence<Row> seq = Sequences.simple(rows);
+    RowBucketIterable rbi = new RowBucketIterable(seq, intervals, ONE_DAY);
+    Iterator<RowBucket> iter = rbi.iterator();
+
+    RowBucket actual = iter.next();
+    assertEquals(JAN_1, actual.getDateTime());
+    assertEquals(expectedDay1, actual.getRows());
+
+    actual = iter.next();
+    assertEquals(JAN_2, actual.getDateTime());
+    assertEquals(expectedDay2, actual.getRows());
+
+    actual = iter.next();
+    assertEquals(JAN_3, actual.getDateTime());
+    assertEquals(expectedDay3, actual.getRows());
+
+    actual = iter.next();
+    assertEquals(JAN_4, actual.getDateTime());
+    assertEquals(expectedDay4, actual.getRows());
+  }
+
+  //  multiple missing days in an interval
+  @Test
+  public void testMultipleMissingDays()
+  {
+
+    List<Row> expectedDay1 = Collections.emptyList();
+    List<Row> expectedDay2 = Collections.singletonList(JAN_2_M_10);
+    List<Row> expectedDay3 = Collections.emptyList();
+    List<Row> expectedDay4 = Collections.singletonList(JAN_4_M_10);
+
+    intervals = new ArrayList<>();
+    intervals.add(INTERVAL_JAN_1_4);
+
+    rows = new ArrayList<>();
+    rows.add(JAN_2_M_10);
+    rows.add(JAN_4_M_10);
+
+    Sequence<Row> seq = Sequences.simple(rows);
+    RowBucketIterable rbi = new RowBucketIterable(seq, intervals, ONE_DAY);
+    Iterator<RowBucket> iter = rbi.iterator();
+
+    RowBucket actual = iter.next();
+    assertEquals(JAN_1, actual.getDateTime());
+    assertEquals(expectedDay1, actual.getRows());
+
+    actual = iter.next();
+    assertEquals(JAN_2, actual.getDateTime());
+    assertEquals(expectedDay2, actual.getRows());
+
+    actual = iter.next();
+    assertEquals(JAN_3, actual.getDateTime());
+    assertEquals(expectedDay3, actual.getRows());
+
+    actual = iter.next();
+    assertEquals(JAN_4, actual.getDateTime());
+    assertEquals(expectedDay4, actual.getRows());
+  }
+
+  //  multiple missing days in an interval followed by multiple row at the end
+  @Test
+  public void testMultipleMissingDaysMultipleRowAtTheEnd()
+  {
+
+    List<Row> expectedDay1 = Collections.emptyList();
+    List<Row> expectedDay2 = Collections.singletonList(JAN_2_M_10);
+    List<Row> expectedDay3 = Collections.emptyList();
+    List<Row> expectedDay4 = Collections.singletonList(JAN_4_M_10);
+    List<Row> expectedDay5 = Collections.singletonList(JAN_5_M_10);
+
+    intervals = new ArrayList<>();
+    intervals.add(INTERVAL_JAN_1_5);
+
+    rows = new ArrayList<>();
+    rows.add(JAN_2_M_10);
+    rows.add(JAN_4_M_10);
+    rows.add(JAN_5_M_10);
+
+    Sequence<Row> seq = Sequences.simple(rows);
+    RowBucketIterable rbi = new RowBucketIterable(seq, intervals, ONE_DAY);
+    Iterator<RowBucket> iter = rbi.iterator();
+
+    RowBucket actual = iter.next();
+    assertEquals(JAN_1, actual.getDateTime());
+    assertEquals(expectedDay1, actual.getRows());
+
+    actual = iter.next();
+    assertEquals(JAN_2, actual.getDateTime());
+    assertEquals(expectedDay2, actual.getRows());
+
+    actual = iter.next();
+    assertEquals(JAN_3, actual.getDateTime());
+    assertEquals(expectedDay3, actual.getRows());
+
+    actual = iter.next();
+    assertEquals(JAN_4, actual.getDateTime());
+    assertEquals(expectedDay4, actual.getRows());
+
+    actual = iter.next();
+    assertEquals(JAN_5, actual.getDateTime());
+    assertEquals(expectedDay5, actual.getRows());
+  }
+
+
+  //  missing day in the middle followed by single row
+  @Test
+  public void testMissingDaysInMiddleOneRow()
+  {
+
+    List<Row> expectedDay1 = Collections.singletonList(JAN_1_M_10);
+    List<Row> expectedDay2 = Collections.singletonList(JAN_2_M_10);
+    List<Row> expectedDay3 = Collections.emptyList();
+    List<Row> expectedDay4 = Collections.singletonList(JAN_4_M_10);
+
+    rows = new ArrayList<>();
+    rows.add(JAN_1_M_10);
+    rows.add(JAN_2_M_10);
+    rows.add(JAN_4_M_10);
+
+    intervals = new ArrayList<>();
+    intervals.add(INTERVAL_JAN_1_4);
+
+    Sequence<Row> seq = Sequences.simple(rows);
+    RowBucketIterable rbi = new RowBucketIterable(seq, intervals, ONE_DAY);
+    Iterator<RowBucket> iter = rbi.iterator();
+
+    RowBucket actual = iter.next();
+    assertEquals(expectedDay1, actual.getRows());
+
+    actual = iter.next();
+    assertEquals(expectedDay2, actual.getRows());
+
+    actual = iter.next();
+    assertEquals(JAN_3, actual.getDateTime());
+    assertEquals(expectedDay3, actual.getRows());
+
+    actual = iter.next();
+    assertEquals(expectedDay4, actual.getRows());
+
+  }
+
+  //  missing day in the middle followed by multiple rows
+  @Test
+  public void testMissingDaysInMiddleMultipleRow()
+  {
+
+    List<Row> expectedDay1 = Collections.singletonList(JAN_1_M_10);
+    List<Row> expectedDay2 = Collections.emptyList();
+    List<Row> expectedDay3 = Collections.singletonList(JAN_3_M_10);
+    List<Row> expectedDay4 = Collections.singletonList(JAN_4_M_10);
+
+    intervals = new ArrayList<>();
+    intervals.add(INTERVAL_JAN_1_4);
+
+    rows = new ArrayList<>();
+    rows.add(JAN_1_M_10);
+    rows.add(JAN_3_M_10);
+    rows.add(JAN_4_M_10);
+
+    Sequence<Row> seq = Sequences.simple(rows);
+    RowBucketIterable rbi = new RowBucketIterable(seq, intervals, ONE_DAY);
+    Iterator<RowBucket> iter = rbi.iterator();
+
+    RowBucket actual = iter.next();
+    assertEquals(JAN_1, actual.getDateTime());
+    assertEquals(expectedDay1, actual.getRows());
+
+    actual = iter.next();
+    assertEquals(JAN_2, actual.getDateTime());
+    assertEquals(expectedDay2, actual.getRows());
+
+    actual = iter.next();
+    assertEquals(JAN_3, actual.getDateTime());
+    assertEquals(expectedDay3, actual.getRows());
+
+    actual = iter.next();
+    assertEquals(JAN_4, actual.getDateTime());
+    assertEquals(expectedDay4, actual.getRows());
+
+  }
+
+  // data missing for last day .
+  @Test
+  public void testApplyLastDayNoRows()
+  {
+
+    intervals = new ArrayList<>();
+    intervals.add(INTERVAL_JAN_1_4);
+
+    List<Row> expectedDay1 = Arrays.asList(JAN_1_M_10, JAN_1_F_20);
+    List<Row> expectedDay2 = Collections.singletonList(JAN_2_M_10);
+    List<Row> expectedDay3 = Collections.singletonList(JAN_3_F_20);
+    List<Row> expectedDay4 = Collections.emptyList();
+
+    rows = new ArrayList<>();
+    rows.add(JAN_1_M_10);
+    rows.add(JAN_1_F_20);
+    rows.add(JAN_2_M_10);
+    rows.add(JAN_3_F_20);
+
+    Sequence<Row> seq = Sequences.simple(rows);
+    RowBucketIterable rbi = new RowBucketIterable(seq, intervals, ONE_DAY);
+    Iterator<RowBucket> iter = rbi.iterator();
+
+    RowBucket actual = iter.next();
+    assertEquals(expectedDay1, actual.getRows());
+
+    actual = iter.next();
+    assertEquals(expectedDay2, actual.getRows());
+
+    actual = iter.next();
+    assertEquals(expectedDay3, actual.getRows());
+
+    actual = iter.next();
+    assertEquals(JAN_4, actual.getDateTime());
+    assertEquals(expectedDay4, actual.getRows());
+  }
+
+  // data missing for last two days
+  @Test
+  public void testApplyLastTwoDayNoRows()
+  {
+
+    List<Row> expectedDay1 = Arrays.asList(JAN_1_M_10, JAN_1_F_20);
+    List<Row> expectedDay2 = Collections.singletonList(JAN_2_M_10);
+    List<Row> expectedDay3 = Collections.emptyList();
+    List<Row> expectedDay4 = Collections.emptyList();
+
+    rows = new ArrayList<>();
+    rows.add(JAN_1_M_10);
+    rows.add(JAN_1_F_20);
+    rows.add(JAN_2_M_10);
+
+    intervals = new ArrayList<>();
+    intervals.add(INTERVAL_JAN_1_4);
+
+    Sequence<Row> seq = Sequences.simple(rows);
+    RowBucketIterable rbi = new RowBucketIterable(seq, intervals, ONE_DAY);
+    Iterator<RowBucket> iter = rbi.iterator();
+
+    RowBucket actual = iter.next();
+    assertEquals(expectedDay1, actual.getRows());
+
+    actual = iter.next();
+    assertEquals(expectedDay2, actual.getRows());
+
+    actual = iter.next();
+    assertEquals(JAN_3, actual.getDateTime());
+    assertEquals(expectedDay3, actual.getRows());
+
+    actual = iter.next();
+    assertEquals(JAN_4, actual.getDateTime());
+    assertEquals(expectedDay4, actual.getRows());
+  }
+
+
+  @Test
+  public void testApplyMultipleInterval()
+  {
+
+    intervals = new ArrayList<>();
+    intervals.add(INTERVAL_JAN_1_4);
+    intervals.add(INTERVAL_JAN_6_8);
+
+    List<Row> expectedDay1 = Arrays.asList(JAN_1_M_10, JAN_1_F_20);
+    List<Row> expectedDay2 = Collections.singletonList(JAN_2_M_10);
+    List<Row> expectedDay3 = Collections.singletonList(JAN_3_F_20);
+    List<Row> expectedDay4 = Arrays.asList(JAN_4_M_10, JAN_4_F_20, JAN_4_U_30);
+    List<Row> expectedDay6 = Collections.singletonList(JAN_6_M_10);
+    List<Row> expectedDay7 = Collections.singletonList(JAN_7_F_20);
+    List<Row> expectedDay8 = Collections.singletonList(JAN_8_U_30);
+
+    rows = new ArrayList<>();
+    rows.add(JAN_1_M_10);
+    rows.add(JAN_1_F_20);
+    rows.add(JAN_2_M_10);
+    rows.add(JAN_3_F_20);
+    rows.add(JAN_4_M_10);
+    rows.add(JAN_4_F_20);
+    rows.add(JAN_4_U_30);
+    rows.add(JAN_6_M_10);
+    rows.add(JAN_7_F_20);
+    rows.add(JAN_8_U_30);
+
+    Sequence<Row> seq = Sequences.simple(rows);
+    RowBucketIterable rbi = new RowBucketIterable(seq, intervals, ONE_DAY);
+    Iterator<RowBucket> iter = rbi.iterator();
+
+    RowBucket actual = iter.next();
+    assertEquals(expectedDay1, actual.getRows());
+
+    actual = iter.next();
+    assertEquals(expectedDay2, actual.getRows());
+
+    actual = iter.next();
+    assertEquals(expectedDay3, actual.getRows());
+
+    actual = iter.next();
+    assertEquals(expectedDay4, actual.getRows());
+
+    actual = iter.next();
+    assertEquals(expectedDay6, actual.getRows());
+
+    actual = iter.next();
+    assertEquals(expectedDay7, actual.getRows());
+
+    actual = iter.next();
+    assertEquals(expectedDay8, actual.getRows());
+  }
+
+  @Test
+  public void testNodata()
+  {
+
+    intervals = new ArrayList<>();
+    intervals.add(INTERVAL_JAN_1_4);
+    intervals.add(INTERVAL_JAN_6_8);
+
+    rows = new ArrayList<>();
+
+    Sequence<Row> seq = Sequences.simple(rows);
+    RowBucketIterable rbi = new RowBucketIterable(seq, intervals, ONE_DAY);
+    Iterator<RowBucket> iter = rbi.iterator();
+
+    assertTrue(iter.hasNext());
+    RowBucket actual = iter.next();
+    assertEquals(Collections.emptyList(), actual.getRows());
+  }
+}

extensions-contrib/moving-average-query/src/test/java/org/apache/druid/query/movingaverage/averagers/BaseAveragerFactoryTest.java

@@ -0,0 +1,68 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage.averagers;
+
+import org.junit.Before;
+import org.junit.Test;
+
+import java.util.Comparator;
+import java.util.List;
+
+import static org.junit.Assert.assertEquals;
+
+public class BaseAveragerFactoryTest
+{
+
+  private AveragerFactory<Long, Long> fac;
+
+  @Before
+  public void setup()
+  {
+    fac = new BaseAveragerFactory<Long, Long>("test", 5, "field", 1)
+    {
+      @Override
+      public Averager<Long> createAverager()
+      {
+        return null;
+      }
+
+      @Override
+      public Comparator<Long> getComparator()
+      {
+        return null;
+      }
+    };
+  }
+
+  @Test
+  public void testGetDependentFields()
+  {
+    List<String> dependentFields = fac.getDependentFields();
+    assertEquals(1, dependentFields.size());
+    assertEquals("field", dependentFields.get(0));
+  }
+
+  @Test
+  public void testFinalization()
+  {
+    Long input = Long.valueOf(5L);
+    assertEquals(input, fac.finalizeComputation(input));
+  }
+}

extensions-contrib/moving-average-query/src/test/java/org/apache/druid/query/movingaverage/averagers/BaseAveragerTest.java

@@ -0,0 +1,156 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage.averagers;
+
+import org.junit.Test;
+
+import java.util.Collections;
+
+import static org.junit.Assert.assertEquals;
+import static org.junit.Assert.assertFalse;
+import static org.junit.Assert.assertNotNull;
+import static org.junit.Assert.assertNull;
+import static org.junit.Assert.assertTrue;
+
+/**
+ * Test class for BaseAverager
+ */
+public class BaseAveragerTest
+{
+
+  public static class TestAverager extends BaseAverager<Integer, Integer>
+  {
+    public TestAverager(Class<Integer> clazz, int b, String name, String field, int cycleSize)
+    {
+      super(clazz, b, name, field, cycleSize);
+    }
+
+    @Override
+    protected Integer computeResult()
+    {
+      return 1;
+    }
+  }
+
+  @Test
+  public void testBaseAverager()
+  {
+    BaseAverager<Integer, Integer> avg = new TestAverager(Integer.class, 5, "test", "field", 1);
+
+    assertEquals("test", avg.getName());
+    assertEquals(5, avg.getNumBuckets());
+    assertEquals(5, avg.getBuckets().length);
+    assertTrue(avg.getBuckets().getClass().isArray());
+  }
+
+  @Test
+  public void testAddElement()
+  {
+    BaseAverager<Integer, Integer> avg = new TestAverager(Integer.class, 3, "test", "field", 1);
+    Object[] buckets = avg.getBuckets();
+
+    avg.addElement(Collections.singletonMap("field", 1), Collections.emptyMap());
+    assertEquals(Integer.valueOf(1), buckets[0]);
+    assertNull(buckets[1]);
+    assertNull(buckets[2]);
+
+    avg.addElement(Collections.singletonMap("field", 2), Collections.emptyMap());
+    assertEquals(Integer.valueOf(1), buckets[0]);
+    assertEquals(Integer.valueOf(2), buckets[1]);
+    assertNull(buckets[2]);
+
+    avg.addElement(Collections.singletonMap("field", 3), Collections.emptyMap());
+    assertEquals(Integer.valueOf(1), buckets[0]);
+    assertEquals(Integer.valueOf(2), buckets[1]);
+    assertEquals(Integer.valueOf(3), buckets[2]);
+
+    avg.addElement(Collections.singletonMap("field", 4), Collections.emptyMap());
+    assertEquals(Integer.valueOf(4), buckets[0]);
+    assertEquals(Integer.valueOf(2), buckets[1]);
+    assertEquals(Integer.valueOf(3), buckets[2]);
+  }
+
+  @Test
+  public void testSkip()
+  {
+    BaseAverager<Integer, Integer> avg = new TestAverager(Integer.class, 3, "test", "field", 1);
+    Object[] buckets = avg.getBuckets();
+
+    avg.addElement(Collections.singletonMap("field", 1), Collections.emptyMap());
+    avg.addElement(Collections.singletonMap("field", 1), Collections.emptyMap());
+    avg.addElement(Collections.singletonMap("field", 1), Collections.emptyMap());
+
+    assertEquals(Integer.valueOf(1), buckets[0]);
+    assertEquals(Integer.valueOf(1), buckets[1]);
+    assertEquals(Integer.valueOf(1), buckets[2]);
+
+    avg.skip();
+    assertNull(buckets[0]);
+    assertNotNull(buckets[1]);
+    assertNotNull(buckets[2]);
+
+    avg.skip();
+    assertNull(buckets[0]);
+    assertNull(buckets[1]);
+    assertNotNull(buckets[2]);
+
+    avg.skip();
+    assertNull(buckets[0]);
+    assertNull(buckets[1]);
+    assertNull(buckets[2]);
+
+    // poke some test data into the array
+    buckets[0] = Integer.valueOf(1);
+
+    avg.skip();
+    assertNull(buckets[0]);
+    assertNull(buckets[1]);
+    assertNull(buckets[2]);
+  }
+
+  @Test
+  public void testHasData()
+  {
+    BaseAverager<Integer, Integer> avg = new TestAverager(Integer.class, 3, "test", "field", 1);
+
+    assertFalse(avg.hasData());
+
+    avg.addElement(Collections.singletonMap("field", 1), Collections.emptyMap());
+    assertTrue(avg.hasData());
+
+    avg.skip();
+    avg.skip();
+    avg.skip();
+
+    assertFalse(avg.hasData());
+  }
+
+  @Test
+  public void testGetResult()
+  {
+    BaseAverager<Integer, Integer> avg = new TestAverager(Integer.class, 3, "test", "field", 1);
+
+    assertNull(avg.getResult());
+
+    avg.addElement(Collections.singletonMap("field", 1), Collections.emptyMap());
+    assertEquals(Integer.valueOf(1), avg.getResult());
+  }
+
+}

extensions-contrib/moving-average-query/src/test/java/org/apache/druid/query/movingaverage/averagers/DoubleMaxAveragerFactoryTest.java

@@ -0,0 +1,38 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage.averagers;
+
+import org.junit.Test;
+
+import static org.hamcrest.CoreMatchers.instanceOf;
+import static org.junit.Assert.assertThat;
+
+
+public class DoubleMaxAveragerFactoryTest
+{
+
+  @Test
+  public void testCreateAverager()
+  {
+    AveragerFactory<?, ?> fac = new DoubleMaxAveragerFactory("test", 5, 1, "field");
+    assertThat(fac.createAverager(), instanceOf(DoubleMaxAverager.class));
+  }
+
+}

extensions-contrib/moving-average-query/src/test/java/org/apache/druid/query/movingaverage/averagers/DoubleMaxAveragerTest.java

@@ -0,0 +1,57 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage.averagers;
+
+import org.junit.Test;
+
+import java.util.Collections;
+import java.util.HashMap;
+
+import static org.junit.Assert.assertEquals;
+
+public class DoubleMaxAveragerTest
+{
+
+  @Test
+  public void testComputeResult()
+  {
+    BaseAverager<Number, Double> avg = new DoubleMaxAverager(3, "test", "field", 1);
+
+    assertEquals(Double.NEGATIVE_INFINITY, avg.computeResult(), 0.0);
+
+    avg.addElement(Collections.singletonMap("field", -1.1e100), new HashMap<>());
+    assertEquals(-1.1e100, avg.computeResult(), 0.0);
+
+    avg.addElement(Collections.singletonMap("field", 1.0), new HashMap<>());
+    assertEquals(1.0, avg.computeResult(), 0.0);
+
+    avg.addElement(Collections.singletonMap("field", new Integer(1)), new HashMap<>());
+    assertEquals(1.0, avg.computeResult(), 0.0);
+
+    avg.addElement(Collections.singletonMap("field", 5.0), new HashMap<>());
+    avg.addElement(Collections.singletonMap("field", 3.0), new HashMap<>());
+    avg.addElement(Collections.singletonMap("field", 2.0), new HashMap<>());
+    assertEquals(5.0, avg.computeResult(), 0.0);
+
+    avg.skip();
+    assertEquals(3.0, avg.computeResult(), 0.0);
+  }
+
+}

extensions-contrib/moving-average-query/src/test/java/org/apache/druid/query/movingaverage/averagers/DoubleMeanAveragerFactoryTest.java

@@ -0,0 +1,37 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage.averagers;
+
+import org.junit.Test;
+
+import static org.hamcrest.core.IsInstanceOf.instanceOf;
+import static org.junit.Assert.assertThat;
+
+public class DoubleMeanAveragerFactoryTest
+{
+
+  @Test
+  public void testCreateAverager()
+  {
+    AveragerFactory<?, ?> fac = new DoubleMeanAveragerFactory("test", 5, 1, "field");
+    assertThat(fac.createAverager(), instanceOf(DoubleMeanAverager.class));
+  }
+
+}

extensions-contrib/moving-average-query/src/test/java/org/apache/druid/query/movingaverage/averagers/DoubleMeanAveragerTest.java

@@ -0,0 +1,58 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage.averagers;
+
+import org.junit.Test;
+
+import java.util.Collections;
+import java.util.HashMap;
+
+import static org.junit.Assert.assertEquals;
+
+public class DoubleMeanAveragerTest
+{
+
+  @Test
+  public void testComputeResult()
+  {
+    BaseAverager<Number, Double> avg = new DoubleMeanAverager(3, "test", "field", 1);
+
+    assertEquals(0.0, avg.computeResult(), 0.0);
+
+    avg.addElement(Collections.singletonMap("field", 3.0), new HashMap<>());
+    assertEquals(1.0, avg.computeResult(), 0.0);
+
+    avg.addElement(Collections.singletonMap("field", 3.0), new HashMap<>());
+    assertEquals(2.0, avg.computeResult(), 0.0);
+
+    avg.addElement(Collections.singletonMap("field", new Integer(0)), new HashMap<>());
+    assertEquals(2.0, avg.computeResult(), 0.0);
+
+    avg.addElement(Collections.singletonMap("field", 2.0), new HashMap<>());
+    avg.addElement(Collections.singletonMap("field", 2.0), new HashMap<>());
+    avg.addElement(Collections.singletonMap("field", 2.0), new HashMap<>());
+    assertEquals(2.0, avg.computeResult(), 0.0);
+
+    avg.skip();
+    assertEquals(4.0 / 3, avg.computeResult(), 0.0);
+
+  }
+
+}

extensions-contrib/moving-average-query/src/test/java/org/apache/druid/query/movingaverage/averagers/DoubleMeanAveragerWithPeriodTest.java

@@ -0,0 +1,81 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage.averagers;
+
+import org.junit.Test;
+
+import java.util.Collections;
+import java.util.HashMap;
+
+import static org.junit.Assert.assertEquals;
+
+public class DoubleMeanAveragerWithPeriodTest
+{
+
+  @Test
+  public void testComputeResult()
+  {
+    BaseAverager<Number, Double> averager = new DoubleMeanAverager(14, "test", "field", 7);
+
+    averager.addElement(Collections.singletonMap("field", 7.0), new HashMap<>());
+    averager.addElement(Collections.singletonMap("field", 1.0), new HashMap<>());
+    averager.addElement(Collections.singletonMap("field", 2.0), new HashMap<>());
+    averager.addElement(Collections.singletonMap("field", 3.0), new HashMap<>());
+    averager.addElement(Collections.singletonMap("field", 4.0), new HashMap<>());
+    averager.addElement(Collections.singletonMap("field", 5.0), new HashMap<>());
+    averager.addElement(Collections.singletonMap("field", 6.0), new HashMap<>());
+    averager.addElement(Collections.singletonMap("field", 7.0), new HashMap<>());
+    averager.addElement(Collections.singletonMap("field", 1.0), new HashMap<>());
+    averager.addElement(Collections.singletonMap("field", 2.0), new HashMap<>());
+    averager.addElement(Collections.singletonMap("field", 3.0), new HashMap<>());
+    averager.addElement(Collections.singletonMap("field", 4.0), new HashMap<>());
+    averager.addElement(Collections.singletonMap("field", 5.0), new HashMap<>());
+    averager.addElement(Collections.singletonMap("field", 6.0), new HashMap<>());
+
+    assertEquals(7, averager.computeResult(), 0.0); // (7+7)/2
+
+    averager.addElement(Collections.singletonMap("field", 3.0), new HashMap<>());
+    assertEquals(1, averager.computeResult(), 0.0); // (1+1)/2
+
+    BaseAverager<Number, Double> averager1 = new DoubleMeanAverager(14, "test", "field", 3);
+
+    averager1.addElement(Collections.singletonMap("field", 1.0), new HashMap<>());
+    averager1.addElement(Collections.singletonMap("field", 2.0), new HashMap<>());
+    averager1.addElement(Collections.singletonMap("field", 3.0), new HashMap<>());
+    averager1.addElement(Collections.singletonMap("field", 1.0), new HashMap<>());
+    averager1.addElement(Collections.singletonMap("field", 2.0), new HashMap<>());
+    averager1.addElement(Collections.singletonMap("field", 3.0), new HashMap<>());
+    averager1.addElement(Collections.singletonMap("field", 1.0), new HashMap<>());
+    averager1.addElement(Collections.singletonMap("field", 2.0), new HashMap<>());
+    averager1.addElement(Collections.singletonMap("field", 3.0), new HashMap<>());
+    averager1.addElement(Collections.singletonMap("field", 1.0), new HashMap<>());
+    averager1.addElement(Collections.singletonMap("field", 2.0), new HashMap<>());
+    averager1.addElement(Collections.singletonMap("field", 3.0), new HashMap<>());
+    averager1.addElement(Collections.singletonMap("field", 1.0), new HashMap<>());
+    averager1.addElement(Collections.singletonMap("field", 2.0), new HashMap<>());
+
+    assertEquals(1, averager1.computeResult(), 0.0); // (1+1+1+1+1)/5
+
+    assertEquals(2, averager1.computeResult(), 0.0); // (2+2+2+2+2)/5
+
+    assertEquals(13.0 / 5, averager1.computeResult(), 0.0); // (3+3+3+3+1)/5
+
+  }
+}

extensions-contrib/moving-average-query/src/test/java/org/apache/druid/query/movingaverage/averagers/DoubleMeanNoNullAveragerFactoryTest.java

@@ -0,0 +1,37 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage.averagers;
+
+import org.junit.Test;
+
+import static org.hamcrest.core.IsInstanceOf.instanceOf;
+import static org.junit.Assert.assertThat;
+
+public class DoubleMeanNoNullAveragerFactoryTest
+{
+
+  @Test
+  public void testCreateAverager()
+  {
+    AveragerFactory<?, ?> fac = new DoubleMeanNoNullAveragerFactory("test", 5, 1, "field");
+    assertThat(fac.createAverager(), instanceOf(DoubleMeanNoNullAverager.class));
+  }
+
+}

extensions-contrib/moving-average-query/src/test/java/org/apache/druid/query/movingaverage/averagers/DoubleMeanNoNullAveragerTest.java

@@ -0,0 +1,82 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage.averagers;
+
+import org.junit.Test;
+
+import java.util.Collections;
+import java.util.HashMap;
+
+import static org.junit.Assert.assertEquals;
+
+public class DoubleMeanNoNullAveragerTest
+{
+
+  @Test
+  public void testComputeResult()
+  {
+    BaseAverager<Number, Double> avg = new DoubleMeanNoNullAverager(3, "test", "field", 1);
+
+    assertEquals(Double.NaN, avg.computeResult(), 0.0);
+
+    avg.addElement(Collections.singletonMap("field", 3.0), new HashMap<>());
+    assertEquals(3.0, avg.computeResult(), 0.0);
+
+    avg.addElement(Collections.singletonMap("field", 3.0), new HashMap<>());
+    assertEquals(3.0, avg.computeResult(), 0.0);
+
+    avg.addElement(Collections.singletonMap("field", new Integer(0)), new HashMap<>());
+    assertEquals(2.0, avg.computeResult(), 0.0);
+
+    avg.addElement(Collections.singletonMap("field", 2.0), new HashMap<>());
+    avg.addElement(Collections.singletonMap("field", 2.0), new HashMap<>());
+    avg.addElement(Collections.singletonMap("field", 2.0), new HashMap<>());
+    assertEquals(2.0, avg.computeResult(), 0.0);
+
+    avg.skip();
+    assertEquals(2.0, avg.computeResult(), 0.0);
+
+    // testing cycleSize functionality
+    BaseAverager<Number, Double> averager = new DoubleMeanNoNullAverager(14, "test", "field", 7);
+
+    averager.addElement(Collections.singletonMap("field", 2.0), new HashMap<>());
+    assertEquals(2.0, averager.computeResult(), 0.0);
+
+    averager.addElement(Collections.singletonMap("field", 4.0), new HashMap<>());
+    averager.addElement(Collections.singletonMap("field", 5.0), new HashMap<>());
+    averager.addElement(Collections.singletonMap("field", 6.0), new HashMap<>());
+    averager.addElement(Collections.singletonMap("field", 7.0), new HashMap<>());
+    averager.addElement(Collections.singletonMap("field", 8.0), new HashMap<>());
+    averager.addElement(Collections.singletonMap("field", 9.0), new HashMap<>());
+    averager.addElement(Collections.singletonMap("field", null), new HashMap<>());
+    averager.addElement(Collections.singletonMap("field", 11.0), new HashMap<>());
+    averager.addElement(Collections.singletonMap("field", 12.0), new HashMap<>());
+    averager.addElement(Collections.singletonMap("field", 13.0), new HashMap<>());
+    averager.addElement(Collections.singletonMap("field", 14.0), new HashMap<>());
+    averager.addElement(Collections.singletonMap("field", 15.0), new HashMap<>());
+    averager.addElement(Collections.singletonMap("field", 16.0), new HashMap<>());
+
+    assertEquals(7.5, averager.computeResult(), 0.0);
+
+    averager.addElement(Collections.singletonMap("field", 3.0), new HashMap<>());
+    assertEquals(8.5, averager.computeResult(), 0.0);
+  }
+
+}

extensions-contrib/moving-average-query/src/test/java/org/apache/druid/query/movingaverage/averagers/DoubleMinAveragerFactoryTest.java

@@ -0,0 +1,37 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage.averagers;
+
+import org.junit.Test;
+
+import static org.hamcrest.core.IsInstanceOf.instanceOf;
+import static org.junit.Assert.assertThat;
+
+public class DoubleMinAveragerFactoryTest
+{
+
+  @Test
+  public void testCreateAverager()
+  {
+    AveragerFactory<?, ?> fac = new DoubleMinAveragerFactory("test", 5, 1, "field");
+    assertThat(fac.createAverager(), instanceOf(DoubleMinAverager.class));
+  }
+
+}

extensions-contrib/moving-average-query/src/test/java/org/apache/druid/query/movingaverage/averagers/DoubleMinAveragerTest.java

@@ -0,0 +1,58 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage.averagers;
+
+import org.junit.Test;
+
+import java.util.Collections;
+import java.util.HashMap;
+
+import static org.junit.Assert.assertEquals;
+
+public class DoubleMinAveragerTest
+{
+
+  @Test
+  public void testComputeResult()
+  {
+    BaseAverager<Number, Double> avg = new DoubleMinAverager(3, "test", "field", 1);
+
+    assertEquals(Double.POSITIVE_INFINITY, avg.computeResult(), 0.0);
+
+    avg.addElement(Collections.singletonMap("field", -1.1e100), new HashMap<>());
+    assertEquals(-1.1e100, avg.computeResult(), 0.0);
+
+    avg.addElement(Collections.singletonMap("field", 1.0), new HashMap<>());
+    assertEquals(-1.1e100, avg.computeResult(), 0.0);
+
+    avg.addElement(Collections.singletonMap("field", new Integer(1)), new HashMap<>());
+    assertEquals(-1.1e100, avg.computeResult(), 0.0);
+
+    avg.addElement(Collections.singletonMap("field", 5.0), new HashMap<>());
+    avg.addElement(Collections.singletonMap("field", 2.0), new HashMap<>());
+    avg.addElement(Collections.singletonMap("field", 3.0), new HashMap<>());
+    assertEquals(2.0, avg.computeResult(), 0.0);
+
+    avg.skip();
+    avg.skip();
+    assertEquals(3.0, avg.computeResult(), 0.0);
+  }
+
+}

extensions-contrib/moving-average-query/src/test/java/org/apache/druid/query/movingaverage/averagers/LongMaxAveragerFactoryTest.java

@@ -0,0 +1,37 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage.averagers;
+
+import org.junit.Test;
+
+import static org.hamcrest.core.IsInstanceOf.instanceOf;
+import static org.junit.Assert.assertThat;
+
+public class LongMaxAveragerFactoryTest
+{
+
+  @Test
+  public void testCreateAverager()
+  {
+    AveragerFactory<?, ?> fac = new LongMaxAveragerFactory("test", 5, 1, "field");
+    assertThat(fac.createAverager(), instanceOf(LongMaxAverager.class));
+  }
+
+}

extensions-contrib/moving-average-query/src/test/java/org/apache/druid/query/movingaverage/averagers/LongMaxAveragerTest.java

@@ -0,0 +1,57 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage.averagers;
+
+import org.junit.Test;
+
+import java.util.Collections;
+import java.util.HashMap;
+
+import static org.junit.Assert.assertEquals;
+
+public class LongMaxAveragerTest
+{
+
+  @Test
+  public void testComputeResult()
+  {
+    BaseAverager<Number, Long> avg = new LongMaxAverager(3, "test", "field", 1);
+
+    assertEquals(Long.MIN_VALUE, (long) avg.computeResult());
+
+    avg.addElement(Collections.singletonMap("field", -1000000L), new HashMap<>());
+    assertEquals(-1000000, (long) avg.computeResult());
+
+    avg.addElement(Collections.singletonMap("field", 1L), new HashMap<>());
+    assertEquals(1, (long) avg.computeResult());
+
+    avg.addElement(Collections.singletonMap("field", new Integer(1)), new HashMap<>());
+    assertEquals(1, (long) avg.computeResult());
+
+    avg.addElement(Collections.singletonMap("field", 5L), new HashMap<>());
+    avg.addElement(Collections.singletonMap("field", 3L), new HashMap<>());
+    avg.addElement(Collections.singletonMap("field", 2L), new HashMap<>());
+    assertEquals(5, (long) avg.computeResult());
+
+    avg.skip();
+    assertEquals(3, (long) avg.computeResult());
+  }
+
+}

extensions-contrib/moving-average-query/src/test/java/org/apache/druid/query/movingaverage/averagers/LongMeanAveragerFactoryTest.java

@@ -0,0 +1,37 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage.averagers;
+
+import org.junit.Test;
+
+import static org.hamcrest.core.IsInstanceOf.instanceOf;
+import static org.junit.Assert.assertThat;
+
+public class LongMeanAveragerFactoryTest
+{
+
+  @Test
+  public void testCreateAverager()
+  {
+    AveragerFactory<?, ?> fac = new LongMeanAveragerFactory("test", 5, 1, "field");
+    assertThat(fac.createAverager(), instanceOf(LongMeanAverager.class));
+  }
+
+}

extensions-contrib/moving-average-query/src/test/java/org/apache/druid/query/movingaverage/averagers/LongMeanAveragerTest.java

@@ -0,0 +1,57 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage.averagers;
+
+import org.junit.Test;
+
+import java.util.Collections;
+import java.util.HashMap;
+
+import static org.junit.Assert.assertEquals;
+
+public class LongMeanAveragerTest
+{
+
+  @Test
+  public void testComputeResult()
+  {
+    BaseAverager<Number, Double> avg = new LongMeanAverager(3, "test", "field", 1);
+
+    assertEquals(0.0, avg.computeResult(), 0.0);
+
+    avg.addElement(Collections.singletonMap("field", 3L), new HashMap<>());
+    assertEquals(1.0, avg.computeResult(), 0.0);
+
+    avg.addElement(Collections.singletonMap("field", 3L), new HashMap<>());
+    assertEquals(2.0, avg.computeResult(), 0.0);
+
+    avg.addElement(Collections.singletonMap("field", 3), new HashMap<>());
+    assertEquals(3.0, avg.computeResult(), 0.0);
+
+    avg.addElement(Collections.singletonMap("field", 2L), new HashMap<>());
+    avg.addElement(Collections.singletonMap("field", 2L), new HashMap<>());
+    avg.addElement(Collections.singletonMap("field", 2L), new HashMap<>());
+    assertEquals(2.0, avg.computeResult(), 0.0);
+
+    avg.skip();
+    assertEquals(4.0 / 3, avg.computeResult(), 0.0);
+  }
+
+}

extensions-contrib/moving-average-query/src/test/java/org/apache/druid/query/movingaverage/averagers/LongMeanNoNullAveragerFactoryTest.java

@@ -0,0 +1,37 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage.averagers;
+
+import org.junit.Test;
+
+import static org.hamcrest.core.IsInstanceOf.instanceOf;
+import static org.junit.Assert.assertThat;
+
+public class LongMeanNoNullAveragerFactoryTest
+{
+
+  @Test
+  public void testCreateAverager()
+  {
+    AveragerFactory<?, ?> fac = new LongMeanNoNullAveragerFactory("test", 5, 1, "field");
+    assertThat(fac.createAverager(), instanceOf(LongMeanNoNullAverager.class));
+  }
+
+}

extensions-contrib/moving-average-query/src/test/java/org/apache/druid/query/movingaverage/averagers/LongMeanNoNullAveragerTest.java

@@ -0,0 +1,57 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage.averagers;
+
+import org.junit.Test;
+
+import java.util.Collections;
+import java.util.HashMap;
+
+import static org.junit.Assert.assertEquals;
+
+public class LongMeanNoNullAveragerTest
+{
+
+  @Test
+  public void testComputeResult()
+  {
+    BaseAverager<Number, Double> avg = new LongMeanNoNullAverager(3, "test", "field", 1);
+
+    assertEquals(Double.NaN, avg.computeResult(), 0.0);
+
+    avg.addElement(Collections.singletonMap("field", 3L), new HashMap<>());
+    assertEquals(3.0, avg.computeResult(), 0.0);
+
+    avg.addElement(Collections.singletonMap("field", 3L), new HashMap<>());
+    assertEquals(3.0, avg.computeResult(), 0.0);
+
+    avg.addElement(Collections.singletonMap("field", new Integer(0)), new HashMap<>());
+    assertEquals(2.0, avg.computeResult(), 0.0);
+
+    avg.addElement(Collections.singletonMap("field", 2L), new HashMap<>());
+    avg.addElement(Collections.singletonMap("field", 2L), new HashMap<>());
+    avg.addElement(Collections.singletonMap("field", 2L), new HashMap<>());
+    assertEquals(2.0, avg.computeResult(), 0.0);
+
+    avg.skip();
+    assertEquals(2.0, avg.computeResult(), 0.0);
+  }
+
+}

extensions-contrib/moving-average-query/src/test/java/org/apache/druid/query/movingaverage/averagers/LongMinAveragerFactoryTest.java

@@ -0,0 +1,37 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage.averagers;
+
+import org.junit.Test;
+
+import static org.hamcrest.core.IsInstanceOf.instanceOf;
+import static org.junit.Assert.assertThat;
+
+public class LongMinAveragerFactoryTest
+{
+
+  @Test
+  public void testCreateAverager()
+  {
+    AveragerFactory<?, ?> fac = new LongMinAveragerFactory("test", 5, 1, "field");
+    assertThat(fac.createAverager(), instanceOf(LongMinAverager.class));
+  }
+
+}

extensions-contrib/moving-average-query/src/test/java/org/apache/druid/query/movingaverage/averagers/LongMinAveragerTest.java

@@ -0,0 +1,58 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage.averagers;
+
+import org.junit.Test;
+
+import java.util.Collections;
+import java.util.HashMap;
+
+import static org.junit.Assert.assertEquals;
+
+public class LongMinAveragerTest
+{
+
+  @Test
+  public void testComputeResult()
+  {
+    BaseAverager<Number, Long> avg = new LongMinAverager(3, "test", "field", 1);
+
+    assertEquals(Long.MAX_VALUE, (long) avg.computeResult());
+
+    avg.addElement(Collections.singletonMap("field", -10000L), new HashMap<>());
+    assertEquals(-10000, (long) avg.computeResult());
+
+    avg.addElement(Collections.singletonMap("field", 1L), new HashMap<>());
+    assertEquals(-10000, (long) avg.computeResult());
+
+    avg.addElement(Collections.singletonMap("field", new Integer(1000)), new HashMap<>());
+    assertEquals(-10000, (long) avg.computeResult());
+
+    avg.addElement(Collections.singletonMap("field", 5L), new HashMap<>());
+    avg.addElement(Collections.singletonMap("field", 2L), new HashMap<>());
+    avg.addElement(Collections.singletonMap("field", 3L), new HashMap<>());
+    assertEquals(2, (long) avg.computeResult());
+
+    avg.skip();
+    avg.skip();
+    assertEquals(3, (long) avg.computeResult());
+  }
+
+}

extensions-contrib/moving-average-query/src/test/java/org/apache/druid/query/movingaverage/test/TestConfig.java

@@ -0,0 +1,35 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.druid.query.movingaverage.test;
+
+import com.fasterxml.jackson.databind.node.ArrayNode;
+import com.fasterxml.jackson.databind.node.ObjectNode;
+
+import java.util.Map;
+
+/**
+ * Configuration for a unit test.
+ */
+public class TestConfig
+{
+  public ObjectNode query;
+  public ArrayNode expectedOutput;
+  public Map<String, ArrayNode> intermediateResults;
+}

extensions-contrib/moving-average-query/src/test/resources/queryTests/basicGroupByMovingAverage.yaml

@@ -0,0 +1,57 @@
+query:
+  queryType: movingAverage
+  dataSource:
+    type: table
+    name: slice_pf_us_pl_dt_os
+  context: {
+  }
+  granularity:
+    type: period
+    period: P1D
+  intervals:
+  - 2017-01-02T00:00Z/2017-01-03T00:00Z
+  dimensions:
+  - gender
+  averagers:
+  - buckets: 2
+    name: trailing7DayAvgTimeSpent
+    fieldName: timeSpent
+    type: doubleMean
+  aggregations:
+  - name: timespent_secs
+    fieldName: timespent
+    type: longSum
+  postAggregations:
+  - type: arithmetic
+    name: timeSpent
+    fn: /
+    fields:
+    - type: fieldAccess
+      fieldName: timespent_secs
+    - type: constant
+      name: seconds_per_minute
+      value: 60.0
+  postAveragers: [
+  ]
+expectedOutput:
+- version: v1
+  timestamp: 2017-01-02T00:00Z
+  event:
+    gender: m
+    timespent_secs: 240.0
+    timeSpent: 4.0
+    trailing7DayAvgTimeSpent: 3.0
+intermediateResults:
+  groupBy:
+  - version: v1
+    timestamp: 2017-01-01T00:00Z
+    event:
+      gender: m
+      timespent_secs: 120.0
+      timeSpent: 2.0
+  - version: v1
+    timestamp: 2017-01-02T00:00Z
+    event:
+      gender: m
+      timespent_secs: 240.0
+      timeSpent: 4.0

extensions-contrib/moving-average-query/src/test/resources/queryTests/basicGroupByMovingAverage2.yaml

@@ -0,0 +1,57 @@
+query:
+  queryType: movingAverage
+  dataSource:
+    type: table
+    name: slice_pf_us_pl_dt_os
+  context: {
+  }
+  granularity:
+    type: period
+    period: P1D
+  intervals:
+  - 2017-01-02T00:00Z/2017-01-03T00:00Z
+  dimensions:
+  - gender
+  averagers:
+  - buckets: 2
+    name: trailing7DayAvgTimeSpent
+    fieldName: timeSpent
+    type: doubleMean
+  aggregations:
+  - name: timespent_secs
+    fieldName: timespent
+    type: longSum
+  postAggregations:
+  - type: arithmetic
+    name: timeSpent
+    fn: /
+    fields:
+    - type: fieldAccess
+      fieldName: timespent_secs
+    - type: constant
+      name: seconds_per_minute
+      value: 60.0
+  postAveragers: [
+  ]
+expectedOutput:
+- version: v1
+  timestamp: 2017-01-02T00:00Z
+  event:
+    gender: m
+    timespent_secs: 240.0
+    timeSpent: 4.0
+    trailing7DayAvgTimeSpent: 3.0
+intermediateResults:
+  groupBy:
+  - version: v1
+    timestamp: 2017-01-01T00:00Z
+    event:
+      gender: m
+      timespent_secs: 120.0
+      timeSpent: 2.0
+  - version: v1
+    timestamp: 2017-01-02T00:00Z
+    event:
+      gender: m
+      timespent_secs: 240.0
+      timeSpent: 4.0

extensions-contrib/moving-average-query/src/test/resources/queryTests/basicTimeseriesMovingAverage.yaml

@@ -0,0 +1,51 @@
+query:
+  queryType: movingAverage
+  dataSource:
+    type: table
+    name: slice_pf_us_pl_dt_os
+  context: {
+  }
+  granularity:
+    type: period
+    period: P1D
+  intervals:
+  - 2017-01-02T00:00Z/2017-01-03T00:00Z
+  dimensions: []
+  averagers:
+  - buckets: 2
+    name: trailing7DayAvgTimeSpent
+    fieldName: timeSpent
+    type: doubleMean
+  aggregations:
+  - name: timespent_secs
+    fieldName: timespent
+    type: longSum
+  postAggregations:
+  - type: arithmetic
+    name: timeSpent
+    fn: /
+    fields:
+    - type: fieldAccess
+      fieldName: timespent_secs
+    - type: constant
+      name: seconds_per_minute
+      value: 60.0
+  postAveragers: [
+  ]
+expectedOutput:
+- version: v1
+  timestamp: 2017-01-02T00:00Z
+  event:
+    timespent_secs: 240.0
+    timeSpent: 4.0
+    trailing7DayAvgTimeSpent: 3.0
+intermediateResults:
+  timeseries:
+  - timestamp: 2017-01-01T00:00Z
+    result:
+      timespent_secs: 120.0
+      timeSpent: 2.0
+  - timestamp: 2017-01-02T00:00Z
+    result:
+      timespent_secs: 240.0
+      timeSpent: 4.0

extensions-contrib/moving-average-query/src/test/resources/queryTests/missingGroupByValues.yaml

@@ -0,0 +1,78 @@
+query:
+  queryType: movingAverage
+  dataSource:
+    type: table
+    name: slice_pf_us_pl_dt_os
+  context: {
+  }
+  granularity:
+    type: period
+    period: P1D
+  intervals:
+  - 2017-01-02T00:00Z/2017-01-03T00:00Z
+  dimensions:
+  - gender
+  averagers:
+  - buckets: 2
+    name: trailing7DayAvgTimeSpent
+    fieldName: timeSpent
+    type: doubleMean
+  aggregations:
+  - name: timespent_secs
+    fieldName: timespent
+    type: longSum
+  - name: someSum
+    fieldName: someSum_field
+    type: doubleSum
+  postAggregations:
+  - type: arithmetic
+    name: timeSpent
+    fn: /
+    fields:
+    - type: fieldAccess
+      fieldName: timespent_secs
+    - type: constant
+      name: seconds_per_minute
+      value: 60.0
+  postAveragers: [
+  ]
+expectedOutput:
+- version: v1
+  timestamp: 2017-01-02T00:00Z
+  event:
+    gender: m
+    timespent_secs: 240
+    timeSpent: 4.0
+    trailing7DayAvgTimeSpent: 3.0
+    someSum: 3.0
+- version: v1
+  timestamp: 2017-01-02T00:00Z
+  event:
+    gender: f
+    timespent_secs: 0
+    timeSpent: 0.0
+    trailing7DayAvgTimeSpent: 1.0
+    someSum: 0.0
+intermediateResults:
+  groupBy:
+  - version: v1
+    timestamp: 2017-01-01T00:00Z
+    event:
+      gender: m
+      timespent_secs: 120
+      timeSpent: 2.0
+      someSum: 5.0
+  - version: v1
+    timestamp: 2017-01-01T00:00Z
+    event:
+      gender: f
+      timespent_secs: 120
+      timeSpent: 2.0
+      someSum: 2.0
+  - version: v1
+    timestamp: 2017-01-02T00:00Z
+    event:
+      gender: m
+      timespent_secs: 240
+      timeSpent: 4.0
+      someSum: 3.0

extensions-contrib/moving-average-query/src/test/resources/queryTests/sortingAveragersAsc.yaml

@@ -0,0 +1,81 @@
+query:
+  queryType: movingAverage
+  dataSource:
+    type: table
+    name: slice_pf_us_pl_dt_os
+  context: {
+  }
+  granularity:
+    type: period
+    period: P1D
+  intervals:
+  - 2017-01-02T00:00Z/2017-01-03T00:00Z
+  dimensions:
+  - gender
+  averagers:
+  - buckets: 2
+    name: trailing7DayAvgTimeSpent
+    fieldName: timeSpent
+    type: doubleMean
+  aggregations:
+  - name: timespent_secs
+    fieldName: timespent
+    type: longSum
+  postAggregations:
+  - type: arithmetic
+    name: timeSpent
+    fn: /
+    fields:
+    - type: fieldAccess
+      fieldName: timespent_secs
+    - type: constant
+      name: seconds_per_minute
+      value: 60.0
+  postAveragers: [
+  ]
+  limitSpec:
+    type: default
+    columns:
+    - dimension: trailing7DayAvgTimeSpent
+expectedOutput:
+- version: v1
+  timestamp: 2017-01-02T00:00Z
+  event:
+    gender: m
+    timespent_secs: 240.0
+    timeSpent: 4.0
+    trailing7DayAvgTimeSpent: 3.0
+- version: v1
+  timestamp: 2017-01-02T00:00Z
+  event:
+    gender: f
+    timespent_secs: 480.0
+    timeSpent: 8.0
+    trailing7DayAvgTimeSpent: 6.0
+intermediateResults:
+  groupBy:
+  - version: v1
+    timestamp: 2017-01-01T00:00Z
+    event:
+      gender: m
+      timespent_secs: 120.0
+      timeSpent: 2.0
+  - version: v1
+    timestamp: 2017-01-01T00:00Z
+    event:
+      gender: f
+      timespent_secs: 240.0
+      timeSpent: 4.0
+  - version: v1
+    timestamp: 2017-01-02T00:00Z
+    event:
+      gender: m
+      timespent_secs: 240.0
+      timeSpent: 4.0
+  - version: v1
+    timestamp: 2017-01-02T00:00Z
+    event:
+      gender: f
+      timespent_secs: 480.0
+      timeSpent: 8.0
+            

extensions-contrib/moving-average-query/src/test/resources/queryTests/sortingAveragersDesc.yaml

@@ -0,0 +1,82 @@
+query:
+  queryType: movingAverage
+  dataSource:
+    type: table
+    name: slice_pf_us_pl_dt_os
+  context: {
+  }
+  granularity:
+    type: period
+    period: P1D
+  intervals:
+  - 2017-01-02T00:00Z/2017-01-03T00:00Z
+  dimensions:
+  - gender
+  averagers:
+  - buckets: 2
+    name: trailing7DayAvgTimeSpent
+    fieldName: timeSpent
+    type: doubleMean
+  aggregations:
+  - name: timespent_secs
+    fieldName: timespent
+    type: longSum
+  postAggregations:
+  - type: arithmetic
+    name: timeSpent
+    fn: /
+    fields:
+    - type: fieldAccess
+      fieldName: timespent_secs
+    - type: constant
+      name: seconds_per_minute
+      value: 60.0
+  postAveragers: [
+  ]
+  limitSpec:
+    type: default
+    columns:
+    - dimension: trailing7DayAvgTimeSpent
+      direction: DESC
+expectedOutput:
+- version: v1
+  timestamp: 2017-01-02T00:00Z
+  event:
+    gender: f
+    timespent_secs: 480.0
+    timeSpent: 8.0
+    trailing7DayAvgTimeSpent: 6.0
+- version: v1
+  timestamp: 2017-01-02T00:00Z
+  event:
+    gender: m
+    timespent_secs: 240.0
+    timeSpent: 4.0
+    trailing7DayAvgTimeSpent: 3.0
+intermediateResults:
+  groupBy:
+  - version: v1
+    timestamp: 2017-01-01T00:00Z
+    event:
+      gender: m
+      timespent_secs: 120.0
+      timeSpent: 2.0
+  - version: v1
+    timestamp: 2017-01-01T00:00Z
+    event:
+      gender: f
+      timespent_secs: 240.0
+      timeSpent: 4.0
+  - version: v1
+    timestamp: 2017-01-02T00:00Z
+    event:
+      gender: m
+      timespent_secs: 240.0
+      timeSpent: 4.0
+  - version: v1
+    timestamp: 2017-01-02T00:00Z
+    event:
+      gender: f
+      timespent_secs: 480.0
+      timeSpent: 8.0
+            

extensions-contrib/moving-average-query/src/test/resources/queryTests/sortingWithNonMovingAndMovingAvgMetric.yaml

@@ -0,0 +1,84 @@
+query:
+  queryType: movingAverage
+  dataSource:
+    type: table
+    name: slice_pf_us_uc_ud
+  context: {
+  }
+  granularity:
+    type: period
+    period: P1D
+  intervals:
+  - 2017-01-02T00:00Z/2017-01-03T00:00Z
+  dimensions:
+  - gender
+  averagers:
+  - buckets: 7
+    name: trailing7DayAvgTotalPageViews
+    fieldName: totalPageViews
+    type: doubleMean
+  aggregations:
+  - name: addPageViews
+    fieldName: additive_page_views
+    type: longSum
+  - name: pageViews
+    fieldName: other_page_views
+    type: longSum
+  postAggregations:
+  - type: arithmetic
+    name: totalPageViews
+    fn: +
+    fields:
+    - type: fieldAccess
+      fieldName: addPageViews
+    - type: fieldAccess
+      fieldName: pageViews
+  postAveragers: [
+  ]
+  limitSpec:
+    type: default
+    columns:
+    - dimension: addPageViews
+      direction: DESC
+      dimension: trailing7DayAvgTotalPageViews
+      direction: DESC
+expectedOutput:
+- version: v1
+  timestamp: 2017-01-02T00:00Z
+  event:
+    gender: f
+    addPageViews: 1.0
+    pageViews: 2.0
+    totalPageViews: 3.0
+    trailing7DayAvgTotalPageViews: 3.0
+- version: v1
+  timestamp: 2017-01-02T00:00Z
+  event:
+    gender: m
+    addPageViews: 0
+    pageViews: 0
+    totalPageViews: 0.0
+    trailing7DayAvgTotalPageViews: 2.142857142857143
+intermediateResults:
+  groupBy:
+  - version: v1
+    timestamp: 2017-01-01T00:00Z
+    event:
+      gender: m
+      addPageViews: 5.0
+      pageViews: 10.0
+      totalPageViews: 15.0
+  - version: v1
+    timestamp: 2017-01-01T00:00Z
+    event:
+      gender: f
+      addPageViews: 6.0
+      pageViews: 12.0
+      totalPageViews: 18.0
+  - version: v1
+    timestamp: 2017-01-02T00:00Z
+    event:
+      gender: f
+      addPageViews: 1.0
+      pageViews: 2.0
+      totalPageViews: 3.0

extensions-contrib/moving-average-query/src/test/resources/queryTests/sortingWithNonMovingAvgMetric.yaml

@@ -0,0 +1,82 @@
+query:
+  queryType: movingAverage
+  dataSource:
+    type: table
+    name: slice_pf_us_uc_ud
+  context: {
+  }
+  granularity:
+    type: period
+    period: P1D
+  intervals:
+  - 2017-01-02T00:00Z/2017-01-03T00:00Z
+  dimensions:
+  - gender
+  averagers:
+  - buckets: 7
+    name: trailing7DayAvgTotalPageViews
+    fieldName: totalPageViews
+    type: doubleMean
+  aggregations:
+  - name: addPageViews
+    fieldName: additive_page_views
+    type: longSum
+  - name: pageViews
+    fieldName: other_page_views
+    type: longSum
+  postAggregations:
+  - type: arithmetic
+    name: totalPageViews
+    fn: +
+    fields:
+    - type: fieldAccess
+      fieldName: addPageViews
+    - type: fieldAccess
+      fieldName: pageViews
+  postAveragers: [
+  ]
+  limitSpec:
+    type: default
+    columns:
+    - dimension: addPageViews
+      direction: DESC
+expectedOutput:
+- version: v1
+  timestamp: 2017-01-02T00:00Z
+  event:
+    gender: f
+    addPageViews: 1.0
+    pageViews: 2.0
+    totalPageViews: 3.0
+    trailing7DayAvgTotalPageViews: 3.0
+- version: v1
+  timestamp: 2017-01-02T00:00Z
+  event:
+    gender: m
+    addPageViews: 0
+    pageViews: 0
+    totalPageViews: 0.0
+    trailing7DayAvgTotalPageViews: 2.142857142857143
+intermediateResults:
+  groupBy:
+  - version: v1
+    timestamp: 2017-01-01T00:00Z
+    event:
+      gender: m
+      addPageViews: 5.0
+      pageViews: 10.0
+      totalPageViews: 15.0
+  - version: v1
+    timestamp: 2017-01-01T00:00Z
+    event:
+      gender: f
+      addPageViews: 6.0
+      pageViews: 12.0
+      totalPageViews: 18.0
+  - version: v1
+    timestamp: 2017-01-02T00:00Z
+    event:
+      gender: f
+      addPageViews: 1.0
+      pageViews: 2.0
+      totalPageViews: 3.0

pom.xml

@@ -173,6 +173,7 @@
         <module>extensions-contrib/materialized-view-maintenance</module>
         <module>extensions-contrib/materialized-view-selection</module>
         <module>extensions-contrib/momentsketch</module>
+        <module>extensions-contrib/moving-average-query</module>
         <!-- distribution packaging -->
         <module>distribution</module>
     </modules>
@@ -1580,4 +1581,4 @@
             </build>
         </profile>
     </profiles>
-</project>
+</project>