The tables below shows the properties available to set at the table level.
tableName
Specifies the name of the table. Should only contain alpha-numeric characters, hyphens (‘-‘), or underscores (‘_’). (Two notes: While the hyphen is allowed in table names, it is also a reserved character in SQL, so if you use it you must remember to double quote the table name in your queries. Using a double-underscore (‘__’) is not allowed as it is reserved for other features within Pinot.)
tableType
Defines the table type: OFFLINE for offline tables or REALTIME for real-time tables. A hybrid table is essentially two table configurations: one of each type, with the same table name.
isDimTable
Boolean field to indicate whether the table is a .
quota
Defines properties related to quotas, such as storage quota and query quota. For details, see the table below.
task
Defines the enabled minion tasks for the table. See for more details.
routing
Defines the properties that determine how the broker selects the servers to route, and how segments can be pruned by the broker based on segment metadata. For details, see the table below.
query
Defines the properties related to query execution. For details, see the table below.
segmentsConfig
Defines the properties related to the segments of the table, such as segment push frequency, type, retention, schema, time column etc. For details, see the table below.
tableIndexConfig
Defines the indexing related information for the Pinot table. For details, see below.
fieldConfigList
Specifies the columns and the type of indices to be created on those columns. See for sub-properties.
tenants
Defines the server and broker tenant used for this table. For details, see below.
ingestionConfig
Defines the configurations needed for ingestion level transformations. For details, see and .
upsertConfig
Set upset configurations. For details, see .
dedupConfig
Set deduplication configurations. For details, see .
dimensionTableConfig
Set disablePreload to true to save memory if the table is a .
tierConfigs
Defines configurations for tiered storage. For details, see .
metadata
Contains other metadata of the table. There is a string to string map field "customConfigs" under it which is expressed as key-value pairs to hold the custom configurations.
The following properties can be nested inside the top-level configurations.
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, so the maximum storage the table is allowed to use is 140G x 3 = 420G. The space the table uses 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.
Find details on configuring routing here.
segmentPrunerTypes
The list of segment pruners to be enabled.
The segment pruner prunes the selected segments based on the query.
Supported values:
partition: Prunes segments based on the partition metadata stored in zookeeper. By default, there is no pruner.
time: Prune segments for queries filtering on timeColumnName that do not contain data in the query's time range.
instanceSelectorType
The server instances to serve the query based on selected segments. Supported values:
balanced: Balances the number of segments served by each selected instance. Default.
replicaGroup: Instance selector for replica group routing strategy.
timeoutMs
Query timeout in milliseconds
disableGroovy
Whether to disable groovy in query. This overrides the broker instance level config (pinot.broker.disable.query.groovy) if configured.
useApproximateFunction
Whether to automatically use approximate function for expensive aggregates, such as DISTINCT_COUNT OR DISTINCT_COUNT_MV will be converted to DISTINCT_COUNT_SMARTHLL and PERCENTILE to PERCENTILE_SMART_TDIGEST .This overrides the broker instance level config (pinot.broker.use.approximate.function) if configured.
expressionOverrideMap
A map that configures the expressions to override in the query. This can be useful when users cannot control the queries sent to Pinot (e.g. queries auto-generated by some other tools), but want to override the expressions within the query (e.g. override a transform function to a derived column). Example: {"myFunc(a)": "b"}.
maxQueryResponseSizeBytes
Long value config indicating the maximum serialized response size across all servers for a query. This value is // equally divided across all servers processing the query.
maxServerResponseSizeBytes
Long value config indicating the maximum length of the serialized response per server for a query.
schemaName
Deprecated: schema name should always match the table name (without the type suffix, e.g. myTable), and this field should not be configured.
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 real-time.
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, such as HOURS or DAYS. This, in combination with retentionTimeValue decides the duration for which to retain the segments.
For example, 365 DAYS means that segments containing data older than 365 days will be deleted periodically by the RetentionManager Controller periodic task. By default, there is no set retention.
retentionTimeValue
A numeric value for the retention. This, in combination with retentionTimeUnit, determines the duration for which to retain the segments
segmentPushType
(Deprecated starting 0.7.0 or commit 9eaea9. Use IngestionConfig -> BatchIngestionConfig -> segmentPushType )
Can be either:
APPEND: New data segments pushed periodically, to append to the existing data eg. daily or hourly
REFRESH: 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, such as HOURLY or DAILY
This section is used to specify some general index configuration and multi-column indexes like Star-tree.
createInvertedIndexDuringSegmentGeneration
Boolean to indicate whether to create inverted indexes when segments are created. By default, false, which means indexes are created when the segments are loaded on the server. Learn more about this setting in .
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.
starTreeIndexConfigs
The list of StarTree indexing configs for creating StarTree indexes. For details on how to configure this, see .
enableDefaultStarTree
Boolean to indicate whether to create a default StarTree index for the segment. For details, see.
enableDynamicStarTreeCreation
Boolean to indicate whether to allow creating StarTree when server loads the segment. StarTree 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 StarTree.
segmentPartitionConfig
Use segmentPartitionConfig.columnPartitionMap along with to enable partitioning. For each column, configure the following options:
functionName: Specify one of the supported functions:
Murmur:MurmurHash 2
Modulo: Modulo on integer values
HashCode: Java hashCode()
ByteArray: Java hashCode() on deserialized byte array
numPartitions: Number of partitions you want per segment. Controls how data is divided within each segment.
Example:
{
"columnPartitionMap": {
"column_memberID": {
"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:
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
(deprecated, use enableColumnBasedNullHandling in ) For more information, see the .
aggregateMetrics
(deprecated, use ) (only applicable for stream) set to true to pre-aggregate the metrics
optimizeDictionary
Set to true if you want to disable dictionaries for single valued metric columns. Only applicable to single-valued columns. Applies other modifications to dictionary indexes. Read to get more info. Defaults to false.
optimizeDictionaryForMetrics
Set to true if you want to disable dictionaries for single valued metric columns. Only applicable to single-valued metric columns. Defaults to 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
Specify the columns and the type of indices to be created on those columns.
name
Name of the column
encodingType
Should be one of RAW or DICTIONARY
indexes
An object whose keys identify indexes. Values are interpreted as the configuration for each index. See each index section to learn more about them
timestampConfig
An object that defines the granularities used in indexes
properties
JSON of key-value pairs containing additional properties associated with the index.
There are several deprecated configuration options in Pinot that are still supported but recommended for migration to newer ways of configuration. Here's a summary of these options:
indexTypes
Description: An older way to define indexes enabled for a column.
Supported Index Types: Text, FST, Timestamp, H3 (also known as geospatial).
Note: Some index types required additional properties for configuration.
indexType
Description: Similar to indexTypes, but only supports a single index type as a string.
Note: If both indexTypes and indexType are present, the latter is ignored.
compressionCodec
Description: An older way to specify compression for indexes.
Recommendation: It's now recommended to specify compression in the forward index config.
Deprecated properties
Description: Before Pinot 0.13, certain indexes were configured using properties within this section.
Migration: Since Pinot 0.13, each index can be configured in a type-safe manner within its dedicated section in the indexes object. The documentation for each index type lists the properties that were previously used.
Notable Properties:
Text Index Properties: enableQueryCacheForTextIndex (used to enable/disable the cache, with values specified as strings, e.g., "true" or "false").
Forward Index Properties: rawIndexWriterVersion, deriveNumDocsPerChunkForRawIndex, forwardIndexDisabled.
It's strongly recommended to migrate from these deprecated options to the new, more structured configuration methods introduced in Pinot 0.13 for better maintainability and compatibility.
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. 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.
The sections below apply to real-time tables only.
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
The streamConfigs section has been deprecated as of release 0.7.0. See streamConfigMaps instead.
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": "brokerTenantName",
"server": "serverTenantName",
"tagOverrideConfig" : {
"realtimeConsuming" : "serverTenantName_REALTIME"
"realtimeCompleted" : "serverTenantName_OFFLINE"
}
}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": {}
}
},
...
}"OFFLINE": {
"tableName": "pinotTable",
"tableType": "OFFLINE",
"quota": {
"maxQueriesPerSecond": 300,
"storage": "140G"
},
"routing": {
"segmentPrunerTypes": ["partition"],
"instanceSelectorType": "replicaGroup"
},
"segmentsConfig": {
"timeColumnName": "daysSinceEpoch",
"timeType": "DAYS",
"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": {
"columnPartitionMap": {
"column_foo": {
"functionName": "Murmur",
"numPartitions": 32
}
}
},
"loadMode": "MMAP",
"columnMinMaxValueGeneratorMode": null,
"nullHandlingEnabled": false
},
"ingestionConfig": {
"filterConfig": {
"filterFunction": "Groovy({foo == \"VALUE1\"}, foo)"
},
"transformConfigs": [
{
"columnName": "bar",
"transformFunction": "lower(moo)"
},
{
"columnName": "hoursSinceEpoch",
"transformFunction": "toEpochHours(millis)"
}]
},
"tenants": {
"broker": "myBrokerTenant",
"server": "myServerTenant"
},
"metadata": {
"customConfigs": {
"key": "value",
"key": "value"
}
}
}Here's an example table config for a real-time table. All the fields from the offline table config are valid for the real-time table. Additionally, real-time tables use some extra fields.
"REALTIME": {
"tableName": "pinotTable",
"tableType": "REALTIME",
"segmentsConfig": {
"timeColumnName": "daysSinceEpoch",
"timeType": "DAYS",
"replication": "3",
"retentionTimeUnit": "DAYS",
"retentionTimeValue": "5",
"completionConfig": {
"completionMode": "DOWNLOAD"
}
},
"tableIndexConfig": {
"invertedIndexColumns": ["foo", "bar", "moo"],
"sortedColumn": ["column1"],
"noDictionaryColumns": ["metric1", "metric2"],
"loadMode": "MMAP",
"nullHandlingEnabled": false
},
"ingestionConfig:" {
"streamIngestionConfig": {
"streamConfigMaps": [
{
"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": {}
}