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doc_page	Native Index Tasks

Native Index Tasks

Apache Druid (incubating) currently has two types of native batch indexing tasks, index_parallel which runs tasks in parallel on multiple MiddleManager processes, and index which will run a single indexing task locally on a single MiddleManager.

Please check Hadoop-based Batch Ingestion VS Native Batch Ingestion for differences between native batch ingestion and Hadoop-based ingestion.

To run either kind of native batch indexing task, write an ingestion spec as specified below. Then POST it to the /druid/indexer/v1/task endpoint on the Overlord, or use the post-index-task script included with Druid.

Parallel Index Task

The Parallel Index Task is a task for parallel batch indexing. This task only uses Druid's resource and doesn't depend on other external systems like Hadoop. This task currently works in a single phase without shuffling intermediate data. index_parallel task is a supervisor task which basically generates multiple worker tasks and submits them to Overlords. Each worker task reads input data and makes segments. Once they successfully generate segments for all input, they report the generated segment list to the supervisor task. The supervisor task periodically checks the worker task statuses. If one of them fails, it retries the failed task until the retrying number reaches the configured limit. If all worker tasks succeed, then it collects the reported list of generated segments and publishes those segments at once.

To use this task, the firehose in ioConfig should be splittable. If it's not, this task runs sequentially. The current splittable fireshoses are LocalFirehose, IngestSegmentFirehose, HttpFirehose , StaticS3Firehose, StaticAzureBlobStoreFirehose , StaticGoogleBlobStoreFirehose, and StaticCloudFilesFirehose.

The splittable firehose is responsible for generating splits. The supervisor task generates worker task specs each of which specifies a split and submits worker tasks using those specs. As a result, the number of worker tasks depends on the implementation of splittable firehoses. Please note that multiple tasks can be created for the same worker task spec if one of them fails.

You may want to consider the below points:

Since this task doesn't shuffle intermediate data, it isn't available for perfect rollup.
The number of tasks for parallel ingestion is decided by maxNumSubTasks in the tuningConfig. Since the supervisor task creates up to maxNumSubTasks worker tasks regardless of the available task slots, it may affect to other ingestion performance. As a result, it's important to set maxNumSubTasks properly. See the below Capacity Planning section for more details.
By default, batch ingestion replaces all data in any segment that it writes to. If you'd like to add to the segment instead, set the appendToExisting flag in ioConfig. Note that it only replaces data in segments where it actively adds data: if there are segments in your granularitySpec's intervals that have no data written by this task, they will be left alone.

An example ingestion spec is:

{
  "type": "index_parallel",
  "spec": {
    "dataSchema": {
      "dataSource": "wikipedia_parallel_index_test",
      "metricsSpec": [
        {
          "type": "count",
              "name": "count"
            },
            {
              "type": "doubleSum",
              "name": "added",
              "fieldName": "added"
            },
            {
              "type": "doubleSum",
              "name": "deleted",
              "fieldName": "deleted"
            },
            {
              "type": "doubleSum",
              "name": "delta",
              "fieldName": "delta"
            }
        ],
        "granularitySpec": {
          "segmentGranularity": "DAY",
          "queryGranularity": "second",
          "intervals" : [ "2013-08-31/2013-09-02" ]
        },
        "parser": {
          "parseSpec": {
            "format" : "json",
            "timestampSpec": {
              "column": "timestamp"
            },
            "dimensionsSpec": {
              "dimensions": [
                "page",
                "language",
                "user",
                "unpatrolled",
                "newPage",
                "robot",
                "anonymous",
                "namespace",
                "continent",
                "country",
                "region",
                "city"
              ]
            }
          }
        }
    },
    "ioConfig": {
        "type": "index_parallel",
        "firehose": {
          "type": "local",
          "baseDir": "examples/indexing/",
          "filter": "wikipedia_index_data*"
        }
    },
    "tuningconfig": {
        "type": "index_parallel",
        "maxNumSubTasks": 2
    }
  }
}

Task Properties

property	description	required?
type	The task type, this should always be `index_parallel`.	yes
id	The task ID. If this is not explicitly specified, Druid generates the task ID using task type, data source name, interval, and date-time stamp.	no
spec	The ingestion spec including the data schema, IOConfig, and TuningConfig. See below for more details.	yes
context	Context containing various task configuration parameters. See below for more details.	no

DataSchema

This field is required.

See Ingestion Spec DataSchema

If you specify intervals explicitly in your dataSchema's granularitySpec, batch ingestion will lock the full intervals specified when it starts up, and you will learn quickly if the specified interval overlaps with locks held by other tasks (eg, Kafka ingestion). Otherwise, batch ingestion will lock each interval as it is discovered, so you may only learn that the task overlaps with a higher-priority task later in ingestion. If you specify intervals explicitly, any rows outside the specified intervals will be thrown away. We recommend setting intervals explicitly if you know the time range of the data so that locking failure happens faster, and so that you don't accidentally replace data outside that range if there's some stray data with unexpected timestamps.

IOConfig

property	description	default	required?
type	The task type, this should always be `index_parallel`.	none	yes
firehose	Specify a Firehose here.	none	yes
appendToExisting	Creates segments as additional shards of the latest version, effectively appending to the segment set instead of replacing it. This will only work if the existing segment set has extendable-type shardSpecs.	false	no

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_parallel`.	none	yes
maxRowsInMemory	Used in determining when intermediate persists to disk should occur. Normally user does not need to set this, but depending on the nature of data, if rows are short in terms of bytes, user may not want to store a million rows in memory and this value should be set.	1000000	no
maxBytesInMemory	Used in determining when intermediate persists to disk should occur. Normally this is computed internally and user does not need to set it. This value represents number of bytes to aggregate in heap memory before persisting. This is based on a rough estimate of memory usage and not actual usage. The maximum heap memory usage for indexing is maxBytesInMemory * (2 + maxPendingPersists)	1/6 of max JVM memory	no
partitionsSpec	Defines how to partition the segments in timeChunk, see PartitionsSpec	`dynamic_partitions`	no
indexSpec	Defines segment storage format options to be used at indexing time, see IndexSpec	null	no
indexSpecForIntermediatePersists	Defines segment storage format options to be used at indexing time for intermediate persisted temporary segments. this can be used to disable dimension/metric compression on intermediate segments to reduce memory required for final merging. however, disabling compression on intermediate segments might increase page cache use while they are used before getting merged into final segment published, see IndexSpec for possible values.	same as indexSpec	no
maxPendingPersists	Maximum number of persists that can be pending but not started. If this limit would be exceeded by a new intermediate persist, ingestion will block until the currently-running persist finishes. Maximum heap memory usage for indexing scales with maxRowsInMemory * (2 + maxPendingPersists).	0 (meaning one persist can be running concurrently with ingestion, and none can be queued up)	no
reportParseExceptions	If true, exceptions encountered during parsing will be thrown and will halt ingestion; if false, unparseable rows and fields will be skipped.	false	no
pushTimeout	Milliseconds to wait for pushing segments. It must be >= 0, where 0 means to wait forever.	0	no
segmentWriteOutMediumFactory	Segment write-out medium to use when creating segments. See SegmentWriteOutMediumFactory.	Not specified, the value from `druid.peon.defaultSegmentWriteOutMediumFactory.type` is used	no
maxNumSubTasks	Maximum number of tasks which can be run at the same time. The supervisor task would spawn worker tasks up to `maxNumSubTasks` regardless of the available task slots. If this value is set to 1, the supervisor task processes data ingestion on its own instead of spawning worker tasks. If this value is set to too large, too many worker tasks can be created which might block other ingestion. Check Capacity Planning for more details.	1	no
maxRetry	Maximum number of retries on task failures.	3	no
taskStatusCheckPeriodMs	Polling period in milleseconds to check running task statuses.	1000	no
chatHandlerTimeout	Timeout for reporting the pushed segments in worker tasks.	PT10S	no
chatHandlerNumRetries	Retries for reporting the pushed segments in worker tasks.	5	no

PartitionsSpec

PartitionsSpec is to describe the secondary partitioning method. Parallel Index Task supports only the best-effort rollup mode, and thus dynamic_partitions is only available option currently.

property	description	default	required?
type	This should always be `dynamic_partitions`	none	yes
maxRowsPerSegment	Used in sharding. Determines how many rows are in each segment.	5000000	no
maxTotalRows	Total number of rows in segments waiting for being pushed. Used in determining when intermediate segment push should occur.	20000000	no

HTTP Endpoints

The supervisor task provides some HTTP endpoints to get running status.

http://{PEON_IP}:{PEON_PORT}/druid/worker/v1/chat/{SUPERVISOR_TASK_ID}/mode

Returns 'parallel' if the indexing task is running in parallel. Otherwise, it returns 'sequential'.

http://{PEON_IP}:{PEON_PORT}/druid/worker/v1/chat/{SUPERVISOR_TASK_ID}/progress

Returns the current progress if the supervisor task is running in the parallel mode.

An example of the result is

{
  "running":10,
  "succeeded":0,
  "failed":0,
  "complete":0,
  "total":10,
  "expectedSucceeded":10
}

http://{PEON_IP}:{PEON_PORT}/druid/worker/v1/chat/{SUPERVISOR_TASK_ID}/subtasks/running

Returns the task IDs of running worker tasks, or an empty list if the supervisor task is running in the sequential mode.

http://{PEON_IP}:{PEON_PORT}/druid/worker/v1/chat/{SUPERVISOR_TASK_ID}/subtaskspecs

Returns all worker task specs, or an empty list if the supervisor task is running in the sequential mode.

http://{PEON_IP}:{PEON_PORT}/druid/worker/v1/chat/{SUPERVISOR_TASK_ID}/subtaskspecs/running

Returns running worker task specs, or an empty list if the supervisor task is running in the sequential mode.

http://{PEON_IP}:{PEON_PORT}/druid/worker/v1/chat/{SUPERVISOR_TASK_ID}/subtaskspecs/complete

Returns complete worker task specs, or an empty list if the supervisor task is running in the sequential mode.

http://{PEON_IP}:{PEON_PORT}/druid/worker/v1/chat/{SUPERVISOR_TASK_ID}/subtaskspec/{SUB_TASK_SPEC_ID}

Returns the worker task spec of the given id, or HTTP 404 Not Found error if the supervisor task is running in the sequential mode.

http://{PEON_IP}:{PEON_PORT}/druid/worker/v1/chat/{SUPERVISOR_TASK_ID}/subtaskspec/{SUB_TASK_SPEC_ID}/state

Returns the state of the worker task spec of the given id, or HTTP 404 Not Found error if the supervisor task is running in the sequential mode. The returned result contains the worker task spec, a current task status if exists, and task attempt history.

An example of the result is

{
  "spec": {
    "id": "index_parallel_lineitem_2018-04-20T22:12:43.610Z_2",
    "groupId": "index_parallel_lineitem_2018-04-20T22:12:43.610Z",
    "supervisorTaskId": "index_parallel_lineitem_2018-04-20T22:12:43.610Z",
    "context": null,
    "inputSplit": {
      "split": "/path/to/data/lineitem.tbl.5"
    },
    "ingestionSpec": {
      "dataSchema": {
        "dataSource": "lineitem",
        "parser": {
          "type": "hadoopyString",
          "parseSpec": {
            "format": "tsv",
            "delimiter": "|",
            "timestampSpec": {
              "column": "l_shipdate",
              "format": "yyyy-MM-dd"
            },
            "dimensionsSpec": {
              "dimensions": [
                "l_orderkey",
                "l_partkey",
                "l_suppkey",
                "l_linenumber",
                "l_returnflag",
                "l_linestatus",
                "l_shipdate",
                "l_commitdate",
                "l_receiptdate",
                "l_shipinstruct",
                "l_shipmode",
                "l_comment"
              ]
            },
            "columns": [
              "l_orderkey",
              "l_partkey",
              "l_suppkey",
              "l_linenumber",
              "l_quantity",
              "l_extendedprice",
              "l_discount",
              "l_tax",
              "l_returnflag",
              "l_linestatus",
              "l_shipdate",
              "l_commitdate",
              "l_receiptdate",
              "l_shipinstruct",
              "l_shipmode",
              "l_comment"
            ]
          }
        },
        "metricsSpec": [
          {
            "type": "count",
            "name": "count"
          },
          {
            "type": "longSum",
            "name": "l_quantity",
            "fieldName": "l_quantity",
            "expression": null
          },
          {
            "type": "doubleSum",
            "name": "l_extendedprice",
            "fieldName": "l_extendedprice",
            "expression": null
          },
          {
            "type": "doubleSum",
            "name": "l_discount",
            "fieldName": "l_discount",
            "expression": null
          },
          {
            "type": "doubleSum",
            "name": "l_tax",
            "fieldName": "l_tax",
            "expression": null
          }
        ],
        "granularitySpec": {
          "type": "uniform",
          "segmentGranularity": "YEAR",
          "queryGranularity": {
            "type": "none"
          },
          "rollup": true,
          "intervals": [
            "1980-01-01T00:00:00.000Z/2020-01-01T00:00:00.000Z"
          ]
        },
        "transformSpec": {
          "filter": null,
          "transforms": []
        }
      },
      "ioConfig": {
        "type": "index_parallel",
        "firehose": {
          "type": "local",
          "baseDir": "/path/to/data/",
          "filter": "lineitem.tbl.5",
          "parser": null
        },
        "appendToExisting": false
      },
      "tuningConfig": {
        "type": "index_parallel",
        "maxRowsPerSegment": 5000000,
        "maxRowsInMemory": 1000000,
        "maxTotalRows": 20000000,
        "numShards": null,
        "indexSpec": {
          "bitmap": {
            "type": "concise"
          },
          "dimensionCompression": "lz4",
          "metricCompression": "lz4",
          "longEncoding": "longs"
        },
        "indexSpecForIntermediatePersists": {
          "bitmap": {
            "type": "concise"
          },
          "dimensionCompression": "lz4",
          "metricCompression": "lz4",
          "longEncoding": "longs"
        },
        "maxPendingPersists": 0,
        "reportParseExceptions": false,
        "pushTimeout": 0,
        "segmentWriteOutMediumFactory": null,
        "maxNumSubTasks": 4,
        "maxRetry": 3,
        "taskStatusCheckPeriodMs": 1000,
        "chatHandlerTimeout": "PT10S",
        "chatHandlerNumRetries": 5,
        "logParseExceptions": false,
        "maxParseExceptions": 2147483647,
        "maxSavedParseExceptions": 0,
        "forceGuaranteedRollup": false,
        "buildV9Directly": true
      }
    }
  },
  "currentStatus": {
    "id": "index_sub_lineitem_2018-04-20T22:16:29.922Z",
    "type": "index_sub",
    "createdTime": "2018-04-20T22:16:29.925Z",
    "queueInsertionTime": "2018-04-20T22:16:29.929Z",
    "statusCode": "RUNNING",
    "duration": -1,
    "location": {
      "host": null,
      "port": -1,
      "tlsPort": -1
    },
    "dataSource": "lineitem",
    "errorMsg": null
  },
  "taskHistory": []
}

http://{PEON_IP}:{PEON_PORT}/druid/worker/v1/chat/{SUPERVISOR_TASK_ID}/subtaskspec/{SUB_TASK_SPEC_ID}/history

Returns the task attempt history of the worker task spec of the given id, or HTTP 404 Not Found error if the supervisor task is running in the sequential mode.

Capacity Planning

The supervisor task can create up to maxNumSubTasks worker tasks no matter how many task slots are currently available. As a result, total number of tasks which can be run at the same time is (maxNumSubTasks + 1) (including the supervisor task). Please note that this can be even larger than total number of task slots (sum of the capacity of all workers). If maxNumSubTasks is larger than n (available task slots), then maxNumSubTasks tasks are created by the supervisor task, but only n tasks would be started. Others will wait in the pending state until any running task is finished.

If you are using the Parallel Index Task with stream ingestion together, we would recommend to limit the max capacity for batch ingestion to prevent stream ingestion from being blocked by batch ingestion. Suppose you have t Parallel Index Tasks to run at the same time, but want to limit the max number of tasks for batch ingestion to b. Then, (sum of maxNumSubTasks of all Parallel Index Tasks + t (for supervisor tasks)) must be smaller than b.

If you have some tasks of a higher priority than others, you may set their maxNumSubTasks to a higher value than lower priority tasks. This may help the higher priority tasks to finish earlier than lower priority tasks by assigning more task slots to them.

Local Index Task

The Local Index Task is designed to be used for smaller data sets. The task executes within the indexing service. 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",
      "maxRowsPerSegment" : 5000000,
      "maxRowsInMemory" : 1000000
    }
  }
}

By default, batch ingestion replaces all data in any segment that it writes to. If you'd like to add to the segment instead, set the appendToExisting flag in ioConfig. Note that it only replaces data in segments where it actively adds data: if there are segments in your granularitySpec's intervals that have no data written by this task, they will be left alone.

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 task type, data source name, interval, and date-time stamp.	no
spec	The ingestion spec including the data schema, IOConfig, and TuningConfig. See below for more details.	yes
context	Context containing various task configuration parameters. See below for more details.	no

DataSchema

This field is required.

See Ingestion Spec DataSchema

If you do not specify intervals explicitly in your dataSchema's granularitySpec, the Local Index Task will do an extra pass over the data to determine the range to lock when it starts up. If you specify intervals explicitly, any rows outside the specified intervals will be thrown away. We recommend setting intervals explicitly if you know the time range of the data because it allows the task to skip the extra pass, and so that you don't accidentally replace data outside that range if there's some stray data with unexpected timestamps.

IOConfig

property	description	default	required?
type	The task type, this should always be "index".	none	yes
firehose	Specify a Firehose here.	none	yes
appendToExisting	Creates segments as additional shards of the latest version, effectively appending to the segment set instead of replacing it. This will only work if the existing segment set has extendable-type shardSpecs.	false	no

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
maxRowsInMemory	Used in determining when intermediate persists to disk should occur. Normally user does not need to set this, but depending on the nature of data, if rows are short in terms of bytes, user may not want to store a million rows in memory and this value should be set.	1000000	no
maxBytesInMemory	Used in determining when intermediate persists to disk should occur. Normally this is computed internally and user does not need to set it. This value represents number of bytes to aggregate in heap memory before persisting. This is based on a rough estimate of memory usage and not actual usage. The maximum heap memory usage for indexing is maxBytesInMemory * (2 + maxPendingPersists)	1/6 of max JVM memory	no
partitionsSpec	Defines how to partition the segments in timeChunk, see PartitionsSpec	`dynamic_partitions` if `forceGuaranteedRollup` = false, `hashed_partitions` if `forceGuaranteedRollup` = true	no
indexSpec	Defines segment storage format options to be used at indexing time, see IndexSpec	null	no
indexSpecForIntermediatePersists	Defines segment storage format options to be used at indexing time for intermediate persisted temporary segments. this can be used to disable dimension/metric compression on intermediate segments to reduce memory required for final merging. however, disabling compression on intermediate segments might increase page cache use while they are used before getting merged into final segment published, see IndexSpec for possible values.	same as indexSpec	no
maxPendingPersists	Maximum number of persists that can be pending but not started. If this limit would be exceeded by a new intermediate persist, ingestion will block until the currently-running persist finishes. Maximum heap memory usage for indexing scales with maxRowsInMemory * (2 + maxPendingPersists).	0 (meaning one persist can be running concurrently with ingestion, and none can be queued up)	no
forceGuaranteedRollup	Forces guaranteeing the perfect rollup. The perfect rollup optimizes the total size of generated segments and querying time while indexing time will be increased. If this is set to true, the index task will read the entire input data twice: one for finding the optimal number of partitions per time chunk and one for generating segments. Note that the result segments would be hash-partitioned. You can set `forceExtendableShardSpecs` if you plan to append more data to the same time range in the future. This flag cannot be used with `appendToExisting` of IOConfig. For more details, see the below Segment pushing modes section.	false	no
reportParseExceptions	DEPRECATED. If true, exceptions encountered during parsing will be thrown and will halt ingestion; if false, unparseable rows and fields will be skipped. Setting `reportParseExceptions` to true will override existing configurations for `maxParseExceptions` and `maxSavedParseExceptions`, setting `maxParseExceptions` to 0 and limiting `maxSavedParseExceptions` to no more than 1.	false	no
pushTimeout	Milliseconds to wait for pushing segments. It must be >= 0, where 0 means to wait forever.	0	no
segmentWriteOutMediumFactory	Segment write-out medium to use when creating segments. See SegmentWriteOutMediumFactory.	Not specified, the value from `druid.peon.defaultSegmentWriteOutMediumFactory.type` is used	no
logParseExceptions	If true, log an error message when a parsing exception occurs, containing information about the row where the error occurred.	false	no
maxParseExceptions	The maximum number of parse exceptions that can occur before the task halts ingestion and fails. Overridden if `reportParseExceptions` is set.	unlimited	no
maxSavedParseExceptions	When a parse exception occurs, Druid can keep track of the most recent parse exceptions. "maxSavedParseExceptions" limits how many exception instances will be saved. These saved exceptions will be made available after the task finishes in the task completion report. Overridden if `reportParseExceptions` is set.	0	no

PartitionsSpec

PartitionsSpec is to describe the secondary partitioning method. You should use different partitionsSpec depending on the rollup mode you want. For perfect rollup, you should use hashed_partitions.

property	description	default	required?
type	This should always be `hashed_partitions`	none	yes
maxRowsPerSegment	Used in sharding. Determines how many rows are in each segment.	5000000	no
numShards	Directly specify the number of shards to create. If this is specified and 'intervals' is specified in the granularitySpec, the index task can skip the determine intervals/partitions pass through the data. numShards cannot be specified if maxRowsPerSegment is set.	null	no
partitionDimensions	The dimensions to partition on. Leave blank to select all dimensions.	null	no

For best-effort rollup, you should use dynamic_partitions.

property	description	default	required?
type	This should always be `dynamic_partitions`	none	yes
maxRowsPerSegment	Used in sharding. Determines how many rows are in each segment.	5000000	no
maxTotalRows	Total number of rows in segments waiting for being pushed. Used in determining when intermediate segment push should occur.	20000000	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`)

SegmentWriteOutMediumFactory

Field	Type	Description	Required
type	String	See Additional Peon Configuration: SegmentWriteOutMediumFactory for explanation and available options.	yes

Segment pushing modes

While ingesting data using the Index task, it creates segments from the input data and pushes them. For segment pushing, the Index task supports two segment pushing modes, i.e., bulk pushing mode and incremental pushing mode for perfect rollup and best-effort rollup, respectively.

In the bulk pushing mode, every segment is pushed at the very end of the index task. Until then, created segments are stored in the memory and local storage of the process running the index task. As a result, this mode might cause a problem due to limited storage capacity, and is not recommended to use in production.

On the contrary, in the incremental pushing mode, segments are incrementally pushed, that is they can be pushed in the middle of the index task. More precisely, the index task collects data and stores created segments in the memory and disks of the process running that task until the total number of collected rows exceeds maxTotalRows. Once it exceeds, the index task immediately pushes all segments created until that moment, cleans all pushed segments up, and continues to ingest remaining data.

To enable bulk pushing mode, forceGuaranteedRollup should be set in the TuningConfig. Note that this option cannot be used with appendToExisting of IOConfig.

32 KiB Raw Blame History

Native Index Tasks

Parallel Index Task

Task Properties

DataSchema

IOConfig

TuningConfig

PartitionsSpec

HTTP Endpoints

Capacity Planning

Local Index Task

Task Properties

DataSchema

IOConfig

TuningConfig

PartitionsSpec

IndexSpec

Bitmap types

SegmentWriteOutMediumFactory

Segment pushing modes

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