35 KiB
layout | title |
---|---|
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. index_parallel
task is a supervisor task which basically generates
multiple worker tasks and submits them to the Overlord. Each worker task reads input data and creates segments. Once they
successfully generate segments for all input data, they report the generated segment list to the supervisor task.
The supervisor task periodically checks the status of worker tasks. If one of them fails, it retries the failed task
until the number of retries reaches the configured limit. If all worker tasks succeed, then it publishes the reported segments at once.
The parallel Index Task can run in two different modes depending on forceGuaranteedRollup
in tuningConfig
.
If forceGuaranteedRollup
= false, it's executed in a single phase. In this mode,
each sub task creates segments individually and reports them to the supervisor task.
If forceGuaranteedRollup
= true, it's executed in two phases with data shuffle which is similar to MapReduce.
In the first phase, each sub task partitions input data based on segmentGranularity
(primary partition key) in granularitySpec
and partitionDimensions
(secondary partition key) in partitionsSpec
. The partitioned data is served by
the middleManager or the indexer
where the first phase tasks ran. In the second phase, each sub task fetches
partitioned data from middleManagers or indexers and merges them to create the final segments.
As in the single phase execution, the created segments are reported to the supervisor task to publish at once.
To use this task, the firehose
in ioConfig
should be splittable and maxNumSubTasks
should be set something larger than 1 in tuningConfig
.
Otherwise, this task runs sequentially. Here is the list of currently splittable fireshoses.
LocalFirehose
IngestSegmentFirehose
HttpFirehose
StaticS3Firehose
StaticAzureBlobStoreFirehose
StaticGoogleBlobStoreFirehose
StaticCloudFilesFirehose
The splittable firehose is responsible for generating splits. The supervisor task generates worker task specs containing 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 things:
- The number of concurrent tasks run in parallel ingestion is determined by
maxNumSubTasks
in thetuningConfig
. The supervisor task checks the number of current running sub tasks and creates more if it's smaller thanmaxNumSubTasks
no matter how many task slots are currently available. This may affect to other ingestion performance. 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 inioConfig
. 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.
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 a timeChunk, see PartitionsSpec | dynamic if forceGuaranteedRollup = false, hashed 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, numShards in tuningConfig and intervals in granularitySpec must be set. Note that the result segments would be hash-partitioned. This flag cannot be used with appendToExisting of IOConfig. For more details, see the below Segment pushing modes section. |
false | 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 current 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 |
maxNumSegmentsToMerge | Max limit for the number of segments that a single task can merge at the same time in the second phase. Used only forceGuaranteedRollup is set. |
100 | no |
totalNumMergeTasks | Total number of tasks to merge segments in the second phase when forceGuaranteedRollup is set. |
10 | 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.
You should use different partitionsSpec depending on the rollup mode you want.
For perfect rollup, you should use hashed
.
property | description | default | required? |
---|---|---|---|
type | This should always be hashed |
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
.
property | description | default | required? |
---|---|---|---|
type | This should always be dynamic |
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}/phase
Returns the name of the current phase if the task running in the parallel mode.
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.
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 a timeChunk, see PartitionsSpec | dynamic if forceGuaranteedRollup = false, hashed 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. 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
.
property | description | default | required? |
---|---|---|---|
type | This should always be hashed |
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
.
property | description | default | required? |
---|---|---|---|
type | This should always be dynamic |
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.