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layout: doc_page
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---
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# Aggregation Granularity
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The granularity field determines how data gets bucketed across the time dimension, i.e how it gets aggregated by hour, day, minute, etc.
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The granularity field determines how data gets bucketed across the time dimension, or how it gets aggregated by hour, day, minute, etc.
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It can be specified either as a string for simple granularities or as an object for arbitrary granularities.
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### Simple Granularities
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Simple granularities are specified as a string and bucket timestamps by their UTC time (i.e. days start at 00:00 UTC).
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Simple granularities are specified as a string and bucket timestamps by their UTC time (e.g., days start at 00:00 UTC).
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Supported granularity strings are: `all`, `none`, `minute`, `fifteen_minute`, `thirty_minute`, `hour` and `day`
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@ -35,25 +35,21 @@ This chunks up every hour on the half-hour.
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### Period Granularities
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Period granularities are specified as arbitrary period combinations of years, months, weeks, hours, minutes and seconds (e.g. P2W, P3M, PT1H30M, PT0.750S) in ISO8601 format.
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Period granularities are specified as arbitrary period combinations of years, months, weeks, hours, minutes and seconds (e.g. P2W, P3M, PT1H30M, PT0.750S) in ISO8601 format. They support specifying a time zone which determines where period boundaries start as well as the timezone of the returned timestamps. By default, years start on the first of January, months start on the first of the month and weeks start on Mondays unless an origin is specified.
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They support specifying a time zone which determines where period boundaries start and also determines the timezone of the returned timestamps.
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By default years start on the first of January, months start on the first of the month and weeks start on Mondays unless an origin is specified.
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Time zone is optional (defaults to UTC)
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Origin is optional (defaults to 1970-01-01T00:00:00 in the given time zone)
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Time zone is optional (defaults to UTC). Origin is optional (defaults to 1970-01-01T00:00:00 in the given time zone).
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```
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{"type": "period", "period": "P2D", "timeZone": "America/Los_Angeles"}
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```
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This will bucket by two day chunks in the Pacific timezone.
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This will bucket by two-day chunks in the Pacific timezone.
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```
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{"type": "period", "period": "P3M", "timeZone": "America/Los_Angeles", "origin": "2012-02-01T00:00:00-08:00"}
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```
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This will bucket by 3 month chunks in the Pacific timezone where the three-month quarters are defined as starting from February.
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This will bucket by 3-month chunks in the Pacific timezone where the three-month quarters are defined as starting from February.
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Supported time zones: timezone support is provided by the [Joda Time library](http://www.joda.org), which uses the standard IANA time zones. [Joda Time supported timezones](http://joda-time.sourceforge.net/timezones.html)
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#### Supported Time Zones
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Timezone support is provided by the [Joda Time library](http://www.joda.org), which uses the standard IANA time zones. See the [Joda Time supported timezones](http://joda-time.sourceforge.net/timezones.html).
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@ -22,7 +22,7 @@ druid.storage.baseKey=sample
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```
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## I don't see my Druid segments on my historical nodes
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You can check the coordinator console located at <COORDINATOR_IP>:<PORT>/cluster.html. Make sure that your segments have actually loaded on [historical nodes](Historical.html). If your segments are not present, check the coordinator logs for messages about capacity of replication errors. One reason that segments are not downloaded is because historical nodes have maxSizes that are too small, making them incapable of downloading more data. You can change that with (for example):
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You can check the coordinator console located at `<COORDINATOR_IP>:<PORT>/cluster.html`. Make sure that your segments have actually loaded on [historical nodes](Historical.html). If your segments are not present, check the coordinator logs for messages about capacity of replication errors. One reason that segments are not downloaded is because historical nodes have maxSizes that are too small, making them incapable of downloading more data. You can change that with (for example):
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```
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-Ddruid.segmentCache.locations=[{"path":"/tmp/druid/storageLocation","maxSize":"500000000000"}]
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## My queries are returning empty results
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You can check <BROKER_IP>:<PORT>/druid/v2/datasources/<YOUR_DATASOURCE> for the dimensions and metrics that have been created for your datasource. Make sure that the name of the aggregators you use in your query match one of these metrics. Also make sure that the query interval you specify match a valid time range where data exists.
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You can check `<BROKER_IP>:<PORT>/druid/v2/datasources/<YOUR_DATASOURCE>` for the dimensions and metrics that have been created for your datasource. Make sure that the name of the aggregators you use in your query match one of these metrics. Also make sure that the query interval you specify match a valid time range where data exists.
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## More information
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@ -9,7 +9,7 @@ There are several different types of tasks.
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Segment Creation Tasks
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----------------------
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#### Index Task
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### Index Task
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The Index Task is a simpler variation of the Index Hadoop task that is designed to be used for smaller data sets. The task executes within the indexing service and does not require an external Hadoop setup to use. The grammar of the index task is as follows:
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|--------|-----------|---------|
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|type|The task type, this should always be "index".|yes|
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|id|The task ID.|no|
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|granularitySpec|See [granularitySpec](Tasks.html)|yes|
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|spatialDimensions|Dimensions to build spatial indexes over. See [Spatial-Indexing](Spatial-Indexing.html)|no|
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|granularitySpec|Specifies the segment chunks that the task will process. `type` is always "uniform"; `gran` sets the granularity of the chunks ("DAY" means all segments containing timestamps in the same day, while `intervals` sets the interval that the chunks will cover.|yes|
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|spatialDimensions|Dimensions to build spatial indexes over. See [Geographic Queries](GeographicQueries.html).|no|
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|aggregators|The metrics to aggregate in the data set. For more info, see [Aggregations](Aggregations.html)|yes|
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|indexGranularity|The rollup granularity for timestamps.|no|
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|targetPartitionSize|Used in sharding. Determines how many rows are in each segment.|no|
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|firehose|The input source of data. For more info, see [Firehose](Firehose.html)|yes|
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|rowFlushBoundary|Used in determining when intermediate persist should occur to disk.|no|
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#### Index Hadoop Task
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### Index Hadoop Task
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The Hadoop Index Task is used to index larger data sets that require the parallelization and processing power of a Hadoop cluster.
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The Hadoop Index Config submitted as part of an Hadoop Index Task is identical to the Hadoop Index Config used by the `HadoopBatchIndexer` except that three fields must be omitted: `segmentOutputPath`, `workingPath`, `updaterJobSpec`. The Indexing Service takes care of setting these fields internally.
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##### Using your own Hadoop distribution
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#### Using your own Hadoop distribution
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Druid is compiled against Apache hadoop-core 1.0.3. However, if you happen to use a different flavor of hadoop that is API compatible with hadoop-core 1.0.3, you should only have to change the hadoopCoordinates property to point to the maven artifact used by your distribution.
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##### Resolving dependency conflicts running HadoopIndexTask
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#### Resolving dependency conflicts running HadoopIndexTask
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Currently, the HadoopIndexTask creates a single classpath to run the HadoopDruidIndexerJob, which can lead to version conflicts between various dependencies of Druid, extension modules, and Hadoop's own dependencies.
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If you are having trouble with any extensions in HadoopIndexTask, it may be the case that Druid, or one of its dependencies, depends on a different version of a library than what you are using as part of your extensions, but Druid's version overrides the one in your extension. In that case you probably want to build your own Druid version and override the offending library by adding an explicit dependency to the pom.xml of each druid sub-module that depends on it.
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#### Realtime Index Task
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### Realtime Index Task
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The indexing service can also run real-time tasks. These tasks effectively transform a middle manager into a real-time node. We introduced real-time tasks as a way to programmatically add new real-time data sources without needing to manually add nodes. The grammar for the real-time task is as follows:
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Segment Merging Tasks
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---------------------
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#### Append Task
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### Append Task
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Append tasks append a list of segments together into a single segment (one after the other). The grammar is:
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}
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```
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#### Merge Task
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### Merge Task
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Merge tasks merge a list of segments together. Any common timestamps are merged. The grammar is:
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Segment Destroying Tasks
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------------------------
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#### Delete Task
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### Delete Task
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Delete tasks create empty segments with no data. The grammar is:
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}
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```
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#### Kill Task
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### Kill Task
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Kill tasks delete all information about a segment and removes it from deep storage. Killable segments must be disabled (used==0) in the Druid segment table. The available grammar is:
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Misc. Tasks
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-----------
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#### Version Converter Task
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### Version Converter Task
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These tasks convert segments from an existing older index version to the latest index version. The available grammar is:
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}
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```
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#### Noop Task
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### Noop Task
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These tasks start, sleep for a time and are used only for testing. The available grammar is:
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