2018-12-13 14:47:20 -05:00
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---
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2019-08-21 00:48:59 -04:00
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id: having
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2020-04-15 19:12:20 -04:00
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title: "Having filters (groupBy)"
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2018-12-13 14:47:20 -05:00
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---
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2018-11-13 12:38:37 -05:00
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<!--
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~ Licensed to the Apache Software Foundation (ASF) under one
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~ regarding copyright ownership. The ASF licenses this file
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~ to you under the Apache License, Version 2.0 (the
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~ "License"); you may not use this file except in compliance
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~ with the License. You may obtain a copy of the License at
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~
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~ http://www.apache.org/licenses/LICENSE-2.0
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~
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~ Unless required by applicable law or agreed to in writing,
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~ software distributed under the License is distributed on an
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~ "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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~ specific language governing permissions and limitations
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~ under the License.
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-->
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2020-04-15 19:12:20 -04:00
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> Apache Druid supports two query languages: [Druid SQL](sql.md) and [native queries](querying.md).
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> This document describes the native
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> language. For information about functions available in SQL, refer to the
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2022-02-11 17:43:30 -05:00
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> [SQL documentation](sql-scalar.md).
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2018-12-12 23:42:12 -05:00
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2015-05-05 17:07:32 -04:00
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A having clause is a JSON object identifying which rows from a groupBy query should be returned, by specifying conditions on aggregated values.
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It is essentially the equivalent of the HAVING clause in SQL.
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2020-01-03 12:33:19 -05:00
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Apache Druid supports the following types of having clauses.
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2016-12-02 13:04:30 -05:00
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### Query filters
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2020-12-17 16:37:43 -05:00
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Query filter HavingSpecs allow all [Druid query filters](filters.md) to be used in the Having part of the query.
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The grammar for a query filter HavingSpec is:
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```json
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{
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"queryType": "groupBy",
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"dataSource": "sample_datasource",
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...
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"having":
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{
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"type" : "filter",
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"filter" : <any Druid query filter>
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}
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2016-12-02 13:04:30 -05:00
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}
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```
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For example, to use a selector filter:
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```json
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{
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"queryType": "groupBy",
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"dataSource": "sample_datasource",
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...
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"having":
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{
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"type" : "filter",
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"filter" : {
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"type": "selector",
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"dimension" : "<dimension>",
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"value" : "<dimension_value>"
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}
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}
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2016-12-02 13:04:30 -05:00
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}
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```
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2017-03-15 13:59:09 -04:00
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You can use "filter" HavingSpecs to filter on the timestamp of result rows by applying a filter to the "\_\_time"
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column.
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2015-05-05 17:07:32 -04:00
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### Numeric filters
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The simplest having clause is a numeric filter.
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Numeric filters can be used as the base filters for more complex boolean expressions of filters.
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Here's an example of a having-clause numeric filter:
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```json
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{
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"queryType": "groupBy",
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"dataSource": "sample_datasource",
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...
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"having":
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{
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"type": "greaterThan",
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"aggregation": "<aggregate_metric>",
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"value": <numeric_value>
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}
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}
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```
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#### Equal To
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The equalTo filter will match rows with a specific aggregate value.
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The grammar for an `equalTo` filter is as follows:
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```json
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{
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"queryType": "groupBy",
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"dataSource": "sample_datasource",
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...
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"having":
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{
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"type": "equalTo",
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"aggregation": "<aggregate_metric>",
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"value": <numeric_value>
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}
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}
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```
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This is the equivalent of `HAVING <aggregate> = <value>`.
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#### Greater Than
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The greaterThan filter will match rows with aggregate values greater than the given value.
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The grammar for a `greaterThan` filter is as follows:
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```json
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{
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"queryType": "groupBy",
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"dataSource": "sample_datasource",
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...
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"having":
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{
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"type": "greaterThan",
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"aggregation": "<aggregate_metric>",
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"value": <numeric_value>
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}
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}
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```
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This is the equivalent of `HAVING <aggregate> > <value>`.
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#### Less Than
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The lessThan filter will match rows with aggregate values less than the specified value.
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The grammar for a `greaterThan` filter is as follows:
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```json
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{
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"queryType": "groupBy",
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"dataSource": "sample_datasource",
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...
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"having":
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{
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"type": "lessThan",
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"aggregation": "<aggregate_metric>",
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"value": <numeric_value>
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}
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2015-05-05 17:07:32 -04:00
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}
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```
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This is the equivalent of `HAVING <aggregate> < <value>`.
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2015-11-24 09:22:37 -05:00
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### Dimension Selector Filter
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#### dimSelector
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The dimSelector filter will match rows with dimension values equal to the specified value.
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The grammar for a `dimSelector` filter is as follows:
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```json
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{
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"queryType": "groupBy",
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"dataSource": "sample_datasource",
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...
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"having":
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{
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"type": "dimSelector",
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"dimension": "<dimension>",
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"value": <dimension_value>
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}
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2015-11-24 09:22:37 -05:00
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}
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```
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2015-05-05 17:07:32 -04:00
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### Logical expression filters
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#### AND
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The grammar for an AND filter is as follows:
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```json
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{
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"queryType": "groupBy",
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"dataSource": "sample_datasource",
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...
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"having":
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{
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"type": "and",
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"havingSpecs": [
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{
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"type": "greaterThan",
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"aggregation": "<aggregate_metric>",
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"value": <numeric_value>
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},
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{
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"type": "lessThan",
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"aggregation": "<aggregate_metric>",
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"value": <numeric_value>
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}
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]
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}
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}
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```
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#### OR
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The grammar for an OR filter is as follows:
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```json
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{
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"queryType": "groupBy",
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"dataSource": "sample_datasource",
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...
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"having":
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{
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"type": "or",
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"havingSpecs": [
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{
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"type": "greaterThan",
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"aggregation": "<aggregate_metric>",
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"value": <numeric_value>
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},
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{
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"type": "equalTo",
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"aggregation": "<aggregate_metric>",
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"value": <numeric_value>
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}
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]
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}
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2015-05-05 17:07:32 -04:00
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}
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```
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#### NOT
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The grammar for a NOT filter is as follows:
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```json
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{
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"queryType": "groupBy",
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"dataSource": "sample_datasource",
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...
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"having":
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{
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"type": "not",
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"havingSpec":
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{
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"type": "equalTo",
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"aggregation": "<aggregate_metric>",
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"value": <numeric_value>
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}
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}
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2015-05-05 17:07:32 -04:00
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}
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```
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