Table

Top-level fields

Property Description

Property	Description
tableName	Specifies the name of the table. Should only contain alpha-numeric characters, hyphens (‘-‘), or underscores (‘_’). (Using a double-underscore (‘__’) is not allowed and reserved for other features within Pinot)
tableType	Defines the table type - `OFFLINE` for offline table, `REALTIME` for realtime table. A hybrid table is essentially 2 table configs one of each type, with the same table name.
isDimTable	Boolean field to indicate whether the table is a dimension table.
quota	This section defines properties related to quotas, such as storage quota and query quota. For more details scroll down to quota.
task	This section defines the enabled minion tasks for the table. See Minion for more details.
routing	This section defines the properties related to configuring how the broker selects the servers to route, and how segments can be pruned by the broker based on segment metadata. For more details, scroll down to routing.
query	This section defines the properties related to query execution. For more details scroll down to query.
segmentsConfig	This section defines the properties related to the segments of the table, such as segment push frequency, type, retention, schema, time column etc. For more details scroll down to segmentsConfig.
tableIndexConfig	This section defines the indexing related information for the Pinot table. For more details head over to Table indexing config.
fieldConfigList	This section specifies the columns and the type of indices to be created on those columns. Currently, only Text search columns can be specified using this property. We will be migrating the rest of the indices to this field in future releases. See Field config list for sub-properties.
tenants	Define the server and broker tenant used for this table. More details about tenant can be found in Tenant.
ingestionConfig	This section defines the configs needed for ingestion level transformations. More details in Ingestion Level Transformations and Ingestion Level Aggregations.
upsertConfig	This section defines the configs related to the upsert feature.
dedupConfig	This section defines the configs related to the dedup feature.
tierConfigs	This section defines configs needed to setup tiered storage. More details in Tiered Storage.
metadata	This section is for keeping custom configs, which are expressed as key-value pairs.

tableName

Specifies the name of the table. Should only contain alpha-numeric characters, hyphens (‘-‘), or underscores (‘_’). (Using a double-underscore (‘__’) is not allowed and reserved for other features within Pinot)

tableType

Defines the table type - OFFLINE for offline table, REALTIME for realtime table. A hybrid table is essentially 2 table configs one of each type, with the same table name.

isDimTable

Boolean field to indicate whether the table is a dimension table.

quota

This section defines properties related to quotas, such as storage quota and query quota. For more details scroll down to quota.

task

This section defines the enabled minion tasks for the table. See Minion for more details.

routing

This section defines the properties related to configuring how the broker selects the servers to route, and how segments can be pruned by the broker based on segment metadata. For more details, scroll down to routing.

query

This section defines the properties related to query execution. For more details scroll down to query.

segmentsConfig

This section defines the properties related to the segments of the table, such as segment push frequency, type, retention, schema, time column etc. For more details scroll down to segmentsConfig.

tableIndexConfig

This section defines the indexing related information for the Pinot table. For more details head over to Table indexing config.

fieldConfigList

This section specifies the columns and the type of indices to be created on those columns. Currently, only Text search columns can be specified using this property. We will be migrating the rest of the indices to this field in future releases. See Field config list for sub-properties.

tenants

Define the server and broker tenant used for this table. More details about tenant can be found in Tenant.

ingestionConfig

This section defines the configs needed for ingestion level transformations. More details in Ingestion Level Transformations and Ingestion Level Aggregations.

upsertConfig

This section defines the configs related to the upsert feature.

dedupConfig

This section defines the configs related to the dedup feature.

tierConfigs

This section defines configs needed to setup tiered storage. More details in Tiered Storage.

metadata

This section is for keeping custom configs, which are expressed as key-value pairs.

Second level fields

The following properties can be nested inside the top-level configs.

Quota

Property Description

Property	Description
storage	The maximum storage space the table is allowed to use, before replication. For example, in the above table, the storage is 140G and replication is 3. Therefore, the maximum storage the table is allowed to use is 140*3=420G. The space used by the table is calculated by adding up the sizes of all segments from every server hosting this table. Once this limit is reached, offline segment push throws a `403` exception with message, `Quota check failed for segment: segment_0 of table: pinotTable`.
maxQueriesPerSecond	The maximum queries per second allowed to execute on this table. If query volume exceeds this, a `429` exception with message `Request 123 exceeds query quota for table:pinotTable, query:select count(*) from pinotTable` will be sent, and a BrokerMetric `QUERY_QUOTA_EXCEEDED` will be recorded. The application should build an exponential backoff and retry mechanism to react to this exception.

storage

The maximum storage space the table is allowed to use, before replication. For example, in the above table, the storage is 140G and replication is 3. Therefore, the maximum storage the table is allowed to use is 140*3=420G. The space used by the table is calculated by adding up the sizes of all segments from every server hosting this table. Once this limit is reached, offline segment push throws a 403 exception with message, Quota check failed for segment: segment_0 of table: pinotTable.

maxQueriesPerSecond

The maximum queries per second allowed to execute on this table. If query volume exceeds this, a 429 exception with message Request 123 exceeds query quota for table:pinotTable, query:select count(*) from pinotTable will be sent, and a BrokerMetric QUERY_QUOTA_EXCEEDED will be recorded. The application should build an exponential backoff and retry mechanism to react to this exception.

Routing

Property Description

Property	Description
segmentPrunerTypes	The list of segment pruners to be enabled. The segment pruner prunes the selected segments based on the query. Supported values currently are `partition` - prunes segments based on the partition metadata stored in zookeeper. By default, there is no pruner. For more details on how to configure this check out Querying All Segments `time` - prunes segments for queries filtering on `timeColumnName` that do not contain data in the query's time range
instanceSelectorType	The instance selector selects server instances to serve the query based on selected segments. Supported values are `balanced` - balances the number of segments served by each selected instance. Default. `replicaGroup` - instance selector for replica group routing strategy. For more details on how to configure this check out Querying All Servers

segmentPrunerTypes

The list of segment pruners to be enabled.

The segment pruner prunes the selected segments based on the query. Supported values currently are partition - prunes segments based on the partition metadata stored in zookeeper. By default, there is no pruner. For more details on how to configure this check out Querying All Segments time - prunes segments for queries filtering on timeColumnName that do not contain data in the query's time range

instanceSelectorType

The instance selector selects server instances to serve the query based on selected segments. Supported values are balanced - balances the number of segments served by each selected instance. Default. replicaGroup - instance selector for replica group routing strategy. For more details on how to configure this check out Querying All Servers

Query

Property	Description
timeoutMs	Query timeout in milliseconds

Property

Description

timeoutMs

Query timeout in milliseconds

Segments Config

Property Description

Property	Description
schemaName	Name of the schema associated with the table
timeColumnName	The name of the time column for this table. This must match with the time column name in the schema. This is mandatory for tables with push type `APPEND`, optional for `REFRESH.` timeColumnName along with timeColumnType is used to manage segment retention and time boundary for offline vs realtime.
replication	Number of replicas for the tables. A replication value of 1 means segments won't be replicated across servers.
retentionTimeUnit	Unit for the retention. e.g. HOURS, DAYS. This in combination with retentionTimeValue decides the duration for which to retain the segments e.g. `365 DAYS` in the example means that segments containing data older than 365 days will be deleted periodically. This is done by the `RetentionManager` Controller periodic task. By default, no retention is set.
retentionTimeValue	A numeric value for the retention. This in combination with retentionTimeUnit decides the duration for which to retain the segments
segmentPushType (Deprecated starting 0.7.0 or commit 9eaea9. Use IngestionConfig -> BatchIngestionConfig -> segmentPushType )	This can be either `APPEND` - new data segments pushed periodically, to append to the existing data eg. daily or hourly `REFRESH` - the entire data is replaced every time during a data push. Refresh tables have no retention.
segmentPushFrequency (Deprecated starting 0.7.0 or commit 9eaea9. Use IngestionConfig -> BatchIngestionConfig -> segmentPushFrequency )	The cadence at which segments are pushed eg. `HOURLY`, `DAILY`

schemaName

Name of the schema associated with the table

timeColumnName

The name of the time column for this table. This must match with the time column name in the schema. This is mandatory for tables with push type APPEND, optional for REFRESH. timeColumnName along with timeColumnType is used to manage segment retention and time boundary for offline vs realtime.

replication

Number of replicas for the tables. A replication value of 1 means segments won't be replicated across servers.

retentionTimeUnit

Unit for the retention. e.g. HOURS, DAYS. This in combination with retentionTimeValue decides the duration for which to retain the segments e.g. 365 DAYS in the example means that segments containing data older than 365 days will be deleted periodically. This is done by the RetentionManager Controller periodic task. By default, no retention is set.

retentionTimeValue

A numeric value for the retention. This in combination with retentionTimeUnit decides the duration for which to retain the segments

segmentPushType

(Deprecated starting 0.7.0 or commit 9eaea9. Use IngestionConfig -> BatchIngestionConfig -> segmentPushType )

This can be either APPEND - new data segments pushed periodically, to append to the existing data eg. daily or hourly REFRESH - the entire data is replaced every time during a data push. Refresh tables have no retention.

segmentPushFrequency

(Deprecated starting 0.7.0 or commit 9eaea9. Use IngestionConfig -> BatchIngestionConfig -> segmentPushFrequency )

The cadence at which segments are pushed eg. HOURLY, DAILY

Table Index Config

Property Description

Property	Description
invertedIndexColumns	The list of columns that inverted index should be created on. The name of columns should match the schema. e.g. in the table above, inverted index has been created on 3 columns `foo`, `bar`, `moo`
createInvertedIndexDuringSegmentGeneration	Boolean to indicate whether to create inverted indexes during the segment creation. By default, false i.e. inverted indexes are created when the segments are loaded on the server
sortedColumn	The column which is sorted in the data and hence will have a sorted index. This does not need to be specified for the offline table, as the segment generation job will automatically detect the sorted column in the data and create a sorted index for it.
bloomFilterColumns	The list of columns to apply bloom filter on. The names of the columns should match the schema. For more details about using bloom filters refer to Bloom Filter.
bloomFilterConfigs	The map from the column to the bloom filter config. The names of the columns should match the schema. For more details about using bloom filters refer to Bloom Filter.
rangeIndexColumns	The list of columns that range index should be created on. Typically used for numeric columns and mostly on metrics. e.g. `select count() from T where latency > 3000` will be faster if you enable range index for latency*
rangeIndexVersion	Version of the range index, 2 (latest) by default.
starTreeIndexConfigs	The list of star-tree indexing configs for creating star-tree indexes. For more details on how to configure this, go to Star-tree
enableDefaultStarTree	Boolean to indicate whether to create a default star-tree index for the segment. For more details about this, go to Star-tree
enableDynamicStarTreeCreation	Boolean to indicate whether to allow creating star-tree when server loads the segment. Star-tree creation could potentially consume a lot of system resources, so this config should be enabled when the servers have the free system resources to create the star-tree.
noDictionaryColumns	The set of columns that should not be dictionary encoded. The name of columns should match the schema. NoDictionary dimension columns are LZ4 compressed, while the metrics are not compressed.
onHeapDictionaryColumns	The list of columns for which the dictionary should be created on heap
varLengthDictionaryColumns	The list of columns for which the variable length dictionary needs to be enabled in offline segments. This is only valid for string and bytes columns and has no impact for columns of other data types.
jsonIndexColumns	The list of columns to create the JSON index. See JSON Index for more details.
jsonIndexConfigs	The map from column to JSON index config. See JSON Index for more details.
segmentPartitionConfig	The map from column to partition function, which indicates how the segment is partitioned. Currently 4 types of partition functions are supported: `Murmur` - murmur2 hash function `Modulo` - modulo on integer values `HashCode` - java hashCode() function `ByteArray` - java hashCode() on deserialized byte array Example: `{` `"foo": {` `"functionName": "Murmur",` `"numPartitions": 32` `}` `}`
loadMode	Indicates how the segments will be loaded onto the server `heap` - load data directly into direct memory `mmap` - load data segments to off-heap memory
columnMinMaxValueGeneratorMode	Generate min max values for columns. Supported values are `NONE` - do not generate for any columns `ALL` - generate for all columns `TIME` - generate for only time column `NON_METRIC` - generate for time and dimension columns
nullHandlingEnabled	Boolean to indicate whether to keep track of null values as part of the segment generation. This is required when using `IS NULL` or `IS NOT NULL` predicates in the query. Enabling this will lead to additional memory and storage usage per segment. By default, this is set to false.
aggregateMetrics	(depreciated, use Ingestion Aggregation) (only applicable for stream) set to `true` to pre-aggregate the metrics
optimizeDictionaryForMetrics	Set to `true` if you want to disable dictionaries for single valued metric columns. Only applicable to single-valued metric columns. If a column is specified Default `false`
noDictionarySizeRatioThreshold	If `optimizeDictionaryForMetrics` enabled, dictionary is not created for the metric columns for which `noDictionaryIndexSize/ indexWithDictionarySize` is less than the `noDictionarySizeRatioThreshold` `Default: 0.85`
segmentNameGeneratorType	Type of segmentNameGenerator, default is `SimpleSegmentNameGenerator.` See more on

invertedIndexColumns

The list of columns that inverted index should be created on. The name of columns should match the schema. e.g. in the table above, inverted index has been created on 3 columns foo, bar, moo

createInvertedIndexDuringSegmentGeneration

Boolean to indicate whether to create inverted indexes during the segment creation. By default, false i.e. inverted indexes are created when the segments are loaded on the server

sortedColumn

The column which is sorted in the data and hence will have a sorted index. This does not need to be specified for the offline table, as the segment generation job will automatically detect the sorted column in the data and create a sorted index for it.

bloomFilterColumns

The list of columns to apply bloom filter on. The names of the columns should match the schema. For more details about using bloom filters refer to Bloom Filter.

bloomFilterConfigs

The map from the column to the bloom filter config. The names of the columns should match the schema. For more details about using bloom filters refer to Bloom Filter.

rangeIndexColumns

The list of columns that range index should be created on. Typically used for numeric columns and mostly on metrics. e.g. select count(*) from T where latency > 3000 will be faster if you enable range index for latency

rangeIndexVersion

Version of the range index, 2 (latest) by default.

starTreeIndexConfigs

The list of star-tree indexing configs for creating star-tree indexes. For more details on how to configure this, go to Star-tree

enableDefaultStarTree

Boolean to indicate whether to create a default star-tree index for the segment. For more details about this, go to Star-tree

enableDynamicStarTreeCreation

Boolean to indicate whether to allow creating star-tree when server loads the segment. Star-tree creation could potentially consume a lot of system resources, so this config should be enabled when the servers have the free system resources to create the star-tree.

noDictionaryColumns

The set of columns that should not be dictionary encoded. The name of columns should match the schema. NoDictionary dimension columns are LZ4 compressed, while the metrics are not compressed.

onHeapDictionaryColumns

The list of columns for which the dictionary should be created on heap

varLengthDictionaryColumns

The list of columns for which the variable length dictionary needs to be enabled in offline segments. This is only valid for string and bytes columns and has no impact for columns of other data types.

jsonIndexColumns

The list of columns to create the JSON index. See JSON Index for more details.

jsonIndexConfigs

The map from column to JSON index config. See JSON Index for more details.

segmentPartitionConfig

The map from column to partition function, which indicates how the segment is partitioned.

Currently 4 types of partition functions are supported:

Murmur - murmur2 hash function

Modulo - modulo on integer values

HashCode - java hashCode() function

ByteArray - java hashCode() on deserialized byte array

Example:

{ "foo": { "functionName": "Murmur", "numPartitions": 32 } }

loadMode

Indicates how the segments will be loaded onto the server heap - load data directly into direct memory mmap - load data segments to off-heap memory

columnMinMaxValueGeneratorMode

Generate min max values for columns. Supported values are NONE - do not generate for any columns ALL - generate for all columns TIME - generate for only time column NON_METRIC - generate for time and dimension columns

nullHandlingEnabled

Boolean to indicate whether to keep track of null values as part of the segment generation. This is required when using IS NULL or IS NOT NULL predicates in the query. Enabling this will lead to additional memory and storage usage per segment. By default, this is set to false.

aggregateMetrics

(depreciated, use Ingestion Aggregation) (only applicable for stream) set to true to pre-aggregate the metrics

optimizeDictionaryForMetrics

Set to true if you want to disable dictionaries for single valued metric columns. Only applicable to single-valued metric columns. If a column is specified Default false

noDictionarySizeRatioThreshold

If optimizeDictionaryForMetrics enabled, dictionary is not created for the metric columns for which noDictionaryIndexSize/ indexWithDictionarySize is less than the noDictionarySizeRatioThreshold Default: 0.85

segmentNameGeneratorType

Type of segmentNameGenerator, default is SimpleSegmentNameGenerator.

See more on

Field Config List

Specify the columns and the type of indices to be created on those columns. Currently, only Text search columns can be specified using this property. We will be migrating the rest of the indices to this field in future releases.

Property

Property
name	name of the column
encodingType	Should be one of `RAW` or `DICTIONARY`
indexType	index to create on this column. currently only `TEXT` is supported.
properties	JSON of key-value pairs containing additional properties associated with the index. The following properties are supported currently - `enableQueryCacheForTextIndex` - set to `true` to enable caching for text index in Lucene `rawIndexWriterVersion` `deriveNumDocsPerChunkForRawIndex` `forwardIndexDisabled` - set to `true` to disable the forward index, defaults to `false`

name

name of the column

encodingType

Should be one of RAW or DICTIONARY

indexType

index to create on this column. currently only TEXT is supported.

properties

JSON of key-value pairs containing additional properties associated with the index. The following properties are supported currently -

enableQueryCacheForTextIndex - set to true to enable caching for text index in Lucene
rawIndexWriterVersion
deriveNumDocsPerChunkForRawIndex
forwardIndexDisabled - set to true to disable the forward index, defaults to false

Warning:

If removing the forwardIndexDisabled property above to regenerate the forward index for multi-value (MV) columns note that the following invariants cannot be maintained after regenerating the forward index for a forward index disabled column:

Ordering guarantees of the MV values within a row
If entries within an MV row are duplicated, the duplicates will be lost. Please regenerate the segments via your offline jobs and re-push / refresh the data to get back the original MV data with duplicates.

We will work on removing the second invariant in the future.

Realtime Table Config

We will now discuss the sections that are only applicable to realtime tables.

segmentsConfig

Property Description

Property	Description
replicasPerPartition	The number of replicas per partition for the stream
completionMode	determines if segment should be downloaded from other server or built in memory. can be `DOWNLOAD` or empty
peerSegmentDownloadScheme	protocol to use to download segments from server. can be on of `http` or `https`

replicasPerPartition

The number of replicas per partition for the stream

completionMode

determines if segment should be downloaded from other server or built in memory. can be DOWNLOAD or empty

peerSegmentDownloadScheme

protocol to use to download segments from server. can be on of http or https

Indexing config

Below is the list of fields in streamConfigs section.

IndexingConfig -> streamConfig has been deprecated starting 0.7.0 or commit 9eaea9. Use IngestionConfig -> StreamIngestionConfig -> streamConfigMaps instead.

Property Description

Property	Description
streamType	only `kafka` is supported at the moment
stream.[streamType].consumer.type	should be one of `lowLevel` or `highLevel` . See Stream ingestion for more details
stream.[streamType].topic.name	topic or equivalent datasource from which to consume data
stream[streamType].consumer.prop.auto.offset.reset	offset to start consuming data from. Should be one of `smallest` , `largest`, timestamp in format 'yyyy-MM-dd'T'HH:mm:ss.SSSZ' or Valid Datetime interval Eg., '2d', '1m' etc,.
(0.6.0 onwards) realtime.segment.flush.threshold.rows (0.5.0 and prior) (deprecated) ~~realtime.segment.flush.threshold.size~~	The maximum number of rows to consume before persisting the consuming segment. Default is 5,000,000
realtime.segment.flush.threshold.time	Maximum elapsed time after which a consuming segment should be persisted. The value can be set as a human readable string, such as `1d`, `4h30m` Default is 6 hours.
(0.6.0 onwards) realtime.segment.flush.threshold.segment.size (0.5.0 and prior) (deprecated) ~~realtime.segment.flush.desired.size~~	Desired size of the completed segments. This value can be set as a human readable string such as `150M`, or `1.1G`, etc. This value is used when `realtime.segment.flush.threshold.rows` is set to 0. Default is `200M` i.e. 200 MegaBytes
realtime.segment.flush.autotune.initialRows	Initial number of rows for learning. This value is used only if `realtime.segment.flush.threshold.rows` is set o 0 and the consumer type is `LowLevel`. Default is `100000 (ie 100K).`

streamType

only kafka is supported at the moment

stream.[streamType].consumer.type

should be one of lowLevel or highLevel . See Stream ingestion for more details

stream.[streamType].topic.name

topic or equivalent datasource from which to consume data

stream[streamType].consumer.prop.auto.offset.reset

offset to start consuming data from. Should be one of smallest , largest, timestamp in format 'yyyy-MM-dd'T'HH:mm:ss.SSSZ' or Valid Datetime interval Eg., '2d', '1m' etc,.

(0.6.0 onwards) realtime.segment.flush.threshold.rows

(0.5.0 and prior) (deprecated) ~~realtime.segment.flush.threshold.size~~

The maximum number of rows to consume before persisting the consuming segment. Default is 5,000,000

realtime.segment.flush.threshold.time

Maximum elapsed time after which a consuming segment should be persisted. The value can be set as a human readable string, such as 1d, 4h30m Default is 6 hours.

(0.6.0 onwards) realtime.segment.flush.threshold.segment.size

(0.5.0 and prior) (deprecated)

~~realtime.segment.flush.desired.size~~

Desired size of the completed segments. This value can be set as a human readable string such as 150M, or 1.1G, etc. This value is used when realtime.segment.flush.threshold.rows is set to 0. Default is 200M i.e. 200 MegaBytes

realtime.segment.flush.autotune.initialRows

Initial number of rows for learning.

This value is used only if realtime.segment.flush.threshold.rows is set o 0 and the consumer type is LowLevel.

Default is 100000 (ie 100K).

When specifying realtime.segment.flush.threshold.rows, the actual number of rows per segment is computed using the following formula: `` realtime.segment.flush.threshold.rows / partitionsConsumedByServer

This means that if we set realtime.segment.flush.threshold.rows=1000 and each server consumes 10 partitions, the rows per segment will be:1000/10 = 100

Any additional properties set here will be directly available to the stream consumers. For example, in case of Kafka stream, you could put any of the configs described in Kafka configuraton page, and it will be automatically passed to the KafkaConsumer.

Some of the properties you might want to set:

Config	Description	Values
auto.offset.reset	If Kafka Consumer encounters an offset which is not in range (resulting in Kafka OffsetOutOfRange), the strategy to use to reset the offset Default value is latest, as a result of which, if the consumer seeks for an offset which has already expired, the consumer will reset to latest, resulting in data loss.	earliest - reset to earliest available offset latest - reset to latest available offset.

Config

Description

Values

auto.offset.reset

If Kafka Consumer encounters an offset which is not in range (resulting in Kafka OffsetOutOfRange), the strategy to use to reset the offset Default value is latest, as a result of which, if the consumer seeks for an offset which has already expired, the consumer will reset to latest, resulting in data loss.

earliest - reset to earliest available offset latest - reset to latest available offset.

Example

Here is a minimal example of what the streamConfigs section may look like:

0.6.0 onwards:

"streamConfigs" : {
  "realtime.segment.flush.threshold.rows": "0",
  "realtime.segment.flush.threshold.time": "24h",
  "realtime.segment.flush.threshold.segment.size": "150M",
  "streamType": "kafka",
  "stream.kafka.consumer.type": "LowLevel",
  "stream.kafka.topic.name": "ClickStream",
  "stream.kafka.consumer.prop.auto.offset.reset" : "largest"
}

0.5.0 and prior:

"streamConfigs" : {
  "realtime.segment.flush.threshold.size": "0",
  "realtime.segment.flush.threshold.time": "24h",
  "realtime.segment.flush.desired.size": "150M",
  "streamType": "kafka",
  "stream.kafka.consumer.type": "LowLevel",
  "stream.kafka.topic.name": "ClickStream",
  "stream.kafka.consumer.prop.auto.offset.reset" : "largest"
}

Tenants

Property Description

Property	Description
broker	Broker tenant in which the segment should reside
server	Server tenant in which the segment should reside
tagOverrideConfig	Override the tenant for segment if it fulfills certain conditions. Currently, only support override on `realtimeConsuming` or `realtimeCompleted`

broker

Broker tenant in which the segment should reside

server

Server tenant in which the segment should reside

tagOverrideConfig

Override the tenant for segment if it fulfills certain conditions. Currently, only support override on realtimeConsuming or realtimeCompleted

Example

  "broker": "brokerTenantName",
  "server": "serverTenantName",
  "tagOverrideConfig" : {
    "realtimeConsuming" : "serverTenantName_REALTIME"
    "realtimeCompleted" : "serverTenantName_OFFLINE"
  }
}

Environment Variables Override

Pinot allows users to define environment variables in the format of ${ENV_NAME} or ${ENV_NAME:DEFAULT_VALUE}as field values in table config.

Pinot instance will override it during runtime.

Brackets are required when defining the environment variable."$ENV_NAME"is not supported.

Environment variables used without default value in table config have to be available to all Pinot components - Controller, Broker, Server, and Minion. Otherwise, querying/consumption will be affected depending on the service to which these variables are not available.

Below is an example of setting AWS credential as part of table config using environment variable.

Example:

{
...
  "ingestionConfig": {
    "batchIngestionConfig": {
      "segmentIngestionType": "APPEND",
      "segmentIngestionFrequency": "DAILY",
      "batchConfigMaps": [
        {
          "inputDirURI": "s3://<my-bucket>/baseballStats/rawdata",
          "includeFileNamePattern": "glob:**/*.csv",
          "excludeFileNamePattern": "glob:**/*.tmp",
          "inputFormat": "csv",
          "outputDirURI": "s3://<my-bucket>/baseballStats/segments",
          "input.fs.className": "org.apache.pinot.plugin.filesystem.S3PinotFS",
          "input.fs.prop.region": "us-west-2",
          "input.fs.prop.accessKey": "${AWS_ACCESS_KEY}",
          "input.fs.prop.secretKey": "${AWS_SECRET_KEY}",
          "push.mode": "tar"
        }
      ],
      "segmentNameSpec": {},
      "pushSpec": {}
    }
  },
...
}

Sample Configurations

Offline Table

pinot-table-offline.json

"OFFLINE": {
    "tableName": "pinotTable",
    "tableType": "OFFLINE",
    "quota": {
      "maxQueriesPerSecond": 300,
      "storage": "140G"
    },
    "routing": {
      "segmentPrunerTypes": ["partition"],
      "instanceSelectorType": "replicaGroup"
    },
    "segmentsConfig": {
      "schemaName": "pinotTable",
      "timeColumnName": "daysSinceEpoch",
      "timeType": "DAYS",
      "allowNullTimeValue": false,
      "replication": "3",
      "retentionTimeUnit": "DAYS",
      "retentionTimeValue": "365",
      "segmentPushFrequency": "DAILY",
      "segmentPushType": "APPEND"
    },
    "tableIndexConfig": {
      "invertedIndexColumns": ["foo", "bar", "moo"],
      "createInvertedIndexDuringSegmentGeneration": false,
      "sortedColumn": ["pk"],
      "bloomFilterColumns": [],
      "starTreeIndexConfigs": [],
      "noDictionaryColumns": [],
      "rangeIndexColumns": [],
      "onHeapDictionaryColumns": [],
      "varLengthDictionaryColumns": [],
      "segmentPartitionConfig": {
        "pk": {
          "functionName": "Murmur",
          "numPartitions": 32
        }
      }
      "loadMode": "MMAP",
      "columnMinMaxValueGeneratorMode": null,
      "nullHandlingEnabled": false
    },
    "tenants": {
      "broker": "myBrokerTenant",
      "server": "myServerTenant"
    },
    "ingestionConfig": {
      "filterConfig": {
        "filterFunction": "Groovy({foo == \"VALUE1\"}, foo)"
      },
      "transformConfigs": [{
        "columnName": "bar",
        "transformFunction": "lower(moo)"
      },
      {
        "columnName": "hoursSinceEpoch",
        "transformFunction": "toEpochHours(millis)"
      }]
    }
    "metadata": {
      "customConfigs": {
        "key": "value",
        "key": "value"
      }
    }
  }
}

Realtime Table

Here's an example table config for a realtime table. All the fields from the offline table config are valid for the realtime table. Additionally, realtime tables use some extra fields.

pinot-table-realtime.json

"REALTIME": {
    "tableName": "pinotTable",
    "tableType": "REALTIME",
    "segmentsConfig": {
      "schemaName": "pinotTable",
      "timeColumnName": "daysSinceEpoch",
      "timeType": "DAYS",
      "allowNullTimeValue": true,
      "replicasPerPartition": "3",
      "retentionTimeUnit": "DAYS",
      "retentionTimeValue": "5",
      "segmentPushType": "APPEND",
      "completionConfig": {
        "completionMode": "DOWNLOAD"
      }
    },
    "tableIndexConfig": {
      "invertedIndexColumns": ["foo", "bar", "moo"],
      "sortedColumn": ["column1"],
      "noDictionaryColumns": ["metric1", "metric2"],
      "loadMode": "MMAP",
      "nullHandlingEnabled": false,
      "streamConfigs": {
        "realtime.segment.flush.threshold.rows": "0",
        "realtime.segment.flush.threshold.time": "24h",
        "realtime.segment.flush.threshold.segment.size": "150M",
        "stream.kafka.broker.list": "XXXX",
        "stream.kafka.consumer.factory.class.name": "XXXX",
        "stream.kafka.consumer.prop.auto.offset.reset": "largest",
        "stream.kafka.consumer.type": "XXXX",
        "stream.kafka.decoder.class.name": "XXXX",
        "stream.kafka.decoder.prop.schema.registry.rest.url": "XXXX",
        "stream.kafka.decoder.prop.schema.registry.schema.name": "XXXX",
        "stream.kafka.hlc.zk.connect.string": "XXXX",
        "stream.kafka.topic.name": "XXXX",
        "stream.kafka.zk.broker.url": "XXXX",
        "streamType": "kafka"
      }
    },
    "tenants": {
      "broker": "myBrokerTenant",
      "server": "myServerTenant",
      "tagOverrideConfig": {}
    },
    "metadata": {
    }
}

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