druid/docs/content/ingestion/tasks.md

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Tasks

Tasks are run on middle managers and always operate on a single data source. Tasks are submitted using POST requests.

There are several different types of tasks.

Segment Creation Tasks

Hadoop Index Task

See batch ingestion.

Index Task

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:

{
  "type" : "index",
  "spec" : {
    "dataSchema" : {
      "dataSource" : "wikipedia",
      "parser" : {
        "type" : "string",
        "parseSpec" : {
          "format" : "json",
          "timestampSpec" : {
            "column" : "timestamp",
            "format" : "auto"
          },
          "dimensionsSpec" : {
            "dimensions": ["page","language","user","unpatrolled","newPage","robot","anonymous","namespace","continent","country","region","city"],
            "dimensionExclusions" : [],
            "spatialDimensions" : []
          }
        }
      },
      "metricsSpec" : [
        {
          "type" : "count",
          "name" : "count"
        },
        {
          "type" : "doubleSum",
          "name" : "added",
          "fieldName" : "added"
        },
        {
          "type" : "doubleSum",
          "name" : "deleted",
          "fieldName" : "deleted"
        },
        {
          "type" : "doubleSum",
          "name" : "delta",
          "fieldName" : "delta"
        }
      ],
      "granularitySpec" : {
        "type" : "uniform",
        "segmentGranularity" : "DAY",
        "queryGranularity" : "NONE",
        "intervals" : [ "2013-08-31/2013-09-01" ]
      }
    },
    "ioConfig" : {
      "type" : "index",
      "firehose" : {
        "type" : "local",
        "baseDir" : "examples/indexing/",
        "filter" : "wikipedia_data.json"
       }
    },
    "tuningConfig" : {
      "type" : "index",
      "targetPartitionSize" : -1,
      "rowFlushBoundary" : 0,
      "numShards": 1
    }
  }
}

Task Properties

property description required?
type The task type, this should always be "index". yes
id The task ID. If this is not explicitly specified, Druid generates the task ID using the name of the task file and date-time stamp. no
spec The ingestion spec. See below for more details. yes

DataSchema

This field is required.

See Ingestion

IOConfig

This field is required. You can specify a type of Firehose here.

TuningConfig

The tuningConfig is optional and default parameters will be used if no tuningConfig is specified. See below for more details.

property description default required?
type The task type, this should always be "index". None. yes
targetPartitionSize Used in sharding. Determines how many rows are in each segment. Set this to -1 to use numShards instead for sharding. 5000000 no
rowFlushBoundary Used in determining when intermediate persist should occur to disk. 75000 no
numShards Directly specify the number of shards to create. You can skip the intermediate persist step if you specify the number of shards you want and set targetPartitionSize=-1. null no
indexSpec defines segment storage format options to be used at indexing time, see IndexSpec null no
buildV9Directly Whether to build a v9 index directly instead of first building a v8 index and then converting it to v9 format. true no
forceExtendableShardSpecs Forces use of extendable shardSpecs. Experimental feature intended for use with the Kafka indexing service extension. false no

IndexSpec

The indexSpec defines segment storage format options to be used at indexing time, such as bitmap type and column compression formats. The indexSpec is optional and default parameters will be used if not specified.

Field Type Description Required
bitmap Object Compression format for bitmap indexes. Should be a JSON object; see below for options. no (defaults to Concise)
dimensionCompression String Compression format for dimension columns. Choose from LZ4, LZF, or uncompressed. no (default == LZ4)
metricCompression String Compression format for metric columns. Choose from LZ4, LZF, uncompressed, or none. no (default == LZ4)
longEncoding String Encoding format for metric and dimension columns with type long. Choose from auto or longs. auto encodes the values using offset or lookup table depending on column cardinality, and store them with variable size. longs stores the value as is with 8 bytes each. no (default == longs)
Bitmap types

For Concise bitmaps:

Field Type Description Required
type String Must be concise. yes

For Roaring bitmaps:

Field Type Description Required
type String Must be roaring. yes
compressRunOnSerialization Boolean Use a run-length encoding where it is estimated as more space efficient. no (default == true)

Segment Merging Tasks

Append Task

Append tasks append a list of segments together into a single segment (one after the other). The grammar is:

{
    "type": "append",
    "id": <task_id>,
    "dataSource": <task_datasource>,
    "segments": <JSON list of DataSegment objects to append>,
    "aggregations": <optional list of aggregators>
}

Merge Task

Merge tasks merge a list of segments together. Any common timestamps are merged. If rollup is disabled as part of ingestion, common timestamps are not merged and rows are reordered by their timestamp.

The grammar is:

{
    "type": "merge",
    "id": <task_id>,
    "dataSource": <task_datasource>,
    "aggregations": <list of aggregators>,
    "rollup": <whether or not to rollup data during a merge>,
    "segments": <JSON list of DataSegment objects to merge>
}

Segment Destroying Tasks

Kill Task

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:

{
    "type": "kill",
    "id": <task_id>,
    "dataSource": <task_datasource>,
    "interval" : <all_segments_in_this_interval_will_die!>
}

Misc. Tasks

Version Converter Task

The convert task suite takes active segments and will recompress them using a new IndexSpec. This is handy when doing activities like migrating from Concise to Roaring, or adding dimension compression to old segments.

Upon success the new segments will have the same version as the old segment with _converted appended. A convert task may be run against the same interval for the same datasource multiple times. Each execution will append another _converted to the version for the segments

There are two types of conversion tasks. One is the Hadoop convert task, and the other is the indexing service convert task. The Hadoop convert task runs on a hadoop cluster, and simply leaves a task monitor on the indexing service (similar to the hadoop batch task). The indexing service convert task runs the actual conversion on the indexing service.

Hadoop Convert Segment Task

{
  "type": "hadoop_convert_segment",
  "dataSource":"some_datasource",
  "interval":"2013/2015",
  "indexSpec":{"bitmap":{"type":"concise"},"dimensionCompression":"lz4","metricCompression":"lz4"},
  "force": true,
  "validate": false,
  "distributedSuccessCache":"hdfs://some-hdfs-nn:9000/user/jobrunner/cache",
  "jobPriority":"VERY_LOW",
  "segmentOutputPath":"s3n://somebucket/somekeyprefix"
}

The values are described below.

Field Type Description Required
type String Convert task identifier Yes: hadoop_convert_segment
dataSource String The datasource to search for segments Yes
interval Interval string The interval in the datasource to look for segments Yes
indexSpec json The compression specification for the index Yes
force boolean Forces the convert task to continue even if binary versions indicate it has been updated recently (you probably want to do this) No
validate boolean Runs validation between the old and new segment before reporting task success No
distributedSuccessCache URI A location where hadoop should put intermediary files. Yes
jobPriority org.apache.hadoop.mapred.JobPriority as String The priority to set for the hadoop job No
segmentOutputPath URI A base uri for the segment to be placed. Same format as other places a segment output path is needed Yes

Indexing Service Convert Segment Task

{
  "type": "convert_segment",
  "dataSource":"some_datasource",
  "interval":"2013/2015",
  "indexSpec":{"bitmap":{"type":"concise"},"dimensionCompression":"lz4","metricCompression":"lz4"},
  "force": true,
  "validate": false
}
Field Type Description Required (default)
type String Convert task identifier Yes: convert_segment
dataSource String The datasource to search for segments Yes
interval Interval string The interval in the datasource to look for segments Yes
indexSpec json The compression specification for the index Yes
force boolean Forces the convert task to continue even if binary versions indicate it has been updated recently (you probably want to do this) No (false)
validate boolean Runs validation between the old and new segment before reporting task success No (true)

Unlike the hadoop convert task, the indexing service task draws its output path from the indexing service's configuration.

Noop Task

These tasks start, sleep for a time and are used only for testing. The available grammar is:

{
    "type": "noop",
    "id": <optional_task_id>,
    "interval" : <optional_segment_interval>,
    "runTime" : <optional_millis_to_sleep>,
    "firehose": <optional_firehose_to_test_connect>
}

Locking

Once an overlord node accepts a task, a lock is created for the data source and interval specified in the task. Tasks do not need to explicitly release locks, they are released upon task completion. Tasks may potentially release locks early if they desire. Tasks ids are unique by naming them using UUIDs or the timestamp in which the task was created. Tasks are also part of a "task group", which is a set of tasks that can share interval locks.