druid/docs/development/extensions-core/kafka-supervisor-reference.md

id	title	sidebar_label	description
kafka-supervisor-reference	Apache Kafka supervisor reference	Apache Kafka supervisor	Reference topic for Apache Kafka supervisors

This topic contains configuration reference information for the Apache Kafka supervisor for Apache Druid. The following table outlines the high-level configuration options:

Field	Description	Required
type	Supervisor type. For Kafka streaming, set to kafka.	yes
spec	Container object for the supervisor configuration.	yes
dataSchema	Schema for the Kafka indexing task to use during ingestion.	yes
ioConfig	A KafkaSupervisorIOConfig object to define the Kafka connection and I/O-related settings for the supervisor and indexing task. See KafkaSupervisorIOConfig.	yes
tuningConfig	A KafkaSupervisorTuningConfig object to define performance-related settings for the supervisor and indexing tasks. See KafkaSupervisorTuningConfig.	no

KafkaSupervisorIOConfig

Field	Type	Description	Required
topic	String	The Kafka topic to read from. Must be a specific topic. Topic patterns are not supported.	yes
inputFormat	Object	inputFormat to define input data parsing. See Specifying data format for details about specifying the input format.	yes
consumerProperties	Map<String, Object>	A map of properties to pass to the Kafka consumer. See More on consumer properties.	yes
pollTimeout	Long	The length of time to wait for the Kafka consumer to poll records, in milliseconds	no (default == 100)
replicas	Integer	The number of replica sets. "1" means a single set of tasks without replication. Druid always assigns replica tasks to different workers to provide resiliency against worker failure.	no (default == 1)
taskCount	Integer	The maximum number of reading tasks in a replica set. The maximum number of reading tasks equals taskCount * replicas. Therefore, the total number of tasks, reading + publishing, is greater than this count. See Capacity Planning for more details. When taskCount > {numKafkaPartitions}, the actual number of reading tasks is less than the taskCount value.	no (default == 1)
taskDuration	ISO8601 Period	The length of time before tasks stop reading and begin publishing segments.	no (default == PT1H)
startDelay	ISO8601 Period	The period to wait before the supervisor starts managing tasks.	no (default == PT5S)
period	ISO8601 Period	Frequency at which the supervisor executes its management logic. The supervisor also runs in response to certain events. For example, task success, task failure, and tasks reaching their taskDuration. The period value specifies the maximum time between iterations.	no (default == PT30S)
useEarliestOffset	Boolean	If a supervisor manages a dataSource for the first time, it obtains a set of starting offsets from Kafka. This flag determines whether it retrieves the earliest or latest offsets in Kafka. Under normal circumstances, subsequent tasks will start from where the previous segments ended. Therefore Druid only uses useEarliestOffset on first run.	no (default == false)
completionTimeout	ISO8601 Period	The length of time to wait before declaring a publishing task as failed and terminating it. If the value is too low, your tasks may never publish. The publishing clock for a task begins roughly after taskDuration elapses.	no (default == PT30M)
lateMessageRejectionStartDateTime	ISO8601 DateTime	Configure tasks to reject messages with timestamps earlier than this date time; for example if this is set to 2016-01-01T11:00Z and the supervisor creates a task at 2016-01-01T12:00Z, Druid drops messages with timestamps earlier than 2016-01-01T11:00Z. This can prevent concurrency issues if your data stream has late messages and you have multiple pipelines that need to operate on the same segments (e.g. a realtime and a nightly batch ingestion pipeline).	no (default == none)
lateMessageRejectionPeriod	ISO8601 Period	Configure tasks to reject messages with timestamps earlier than this period before the task was created; for example if this is set to PT1H and the supervisor creates a task at 2016-01-01T12:00Z, messages with timestamps earlier than 2016-01-01T11:00Z will be dropped. This may help prevent concurrency issues if your data stream has late messages and you have multiple pipelines that need to operate on the same segments (e.g. a realtime and a nightly batch ingestion pipeline). Please note that only one of lateMessageRejectionPeriod or lateMessageRejectionStartDateTime can be specified.	no (default == none)
earlyMessageRejectionPeriod	ISO8601 Period	Configure tasks to reject messages with timestamps later than this period after the task reached its taskDuration; for example if this is set to PT1H, the taskDuration is set to PT1H and the supervisor creates a task at 2016-01-01T12:00Z, messages with timestamps later than 2016-01-01T14:00Z will be dropped. Note: Tasks sometimes run past their task duration, for example, in cases of supervisor failover. Setting earlyMessageRejectionPeriod too low may cause messages to be dropped unexpectedly whenever a task runs past its originally configured task duration.	no (default == none)
autoScalerConfig	Object	Defines auto scaling behavior for Kafka ingest tasks. See Tasks Autoscaler Properties.	no (default == null)
idleConfig	Object	Defines how and when Kafka Supervisor can become idle. See Idle Supervisor Configuration for more details.	no (default == null)

Task Autoscaler Properties

Property	Description	Required
enableTaskAutoScaler	Enable or disable autoscaling. false or blank disables the autoScaler even when autoScalerConfig is not null	no (default == false)
taskCountMax	Maximum number of ingestion tasks. Set taskCountMax >= taskCountMin. If taskCountMax > {numKafkaPartitions}, Druid only scales reading tasks up to the {numKafkaPartitions}. In this case taskCountMax is ignored.	yes
taskCountMin	Minimum number of ingestion tasks. When you enable autoscaler, Druid ignores the value of taskCount in IOConfig and starts with the taskCountMin number of tasks.	yes
minTriggerScaleActionFrequencyMillis	Minimum time interval between two scale actions.	no (default == 600000)
autoScalerStrategy	The algorithm of autoScaler. Only supports lagBased. See Lag Based AutoScaler Strategy Related Properties for details.	no (default == lagBased)

Lag Based AutoScaler Strategy Related Properties

Property	Description	Required
lagCollectionIntervalMillis	Period of lag points collection.	no (default == 30000)
lagCollectionRangeMillis	The total time window of lag collection. Use with lagCollectionIntervalMillis，it means that in the recent lagCollectionRangeMillis, collect lag metric points every lagCollectionIntervalMillis.	no (default == 600000)
scaleOutThreshold	The threshold of scale out action	no (default == 6000000)
triggerScaleOutFractionThreshold	If triggerScaleOutFractionThreshold percent of lag points are higher than scaleOutThreshold, then do scale out action.	no (default == 0.3)
scaleInThreshold	The Threshold of scale in action	no (default == 1000000)
triggerScaleInFractionThreshold	If triggerScaleInFractionThreshold percent of lag points are lower than scaleOutThreshold, then do scale in action.	no (default == 0.9)
scaleActionStartDelayMillis	Number of milliseconds after supervisor starts when first check scale logic.	no (default == 300000)
scaleActionPeriodMillis	The frequency of checking whether to do scale action in millis	no (default == 60000)
scaleInStep	How many tasks to reduce at a time	no (default == 1)
scaleOutStep	How many tasks to add at a time	no (default == 2)

Idle Supervisor Configuration

Note that Idle state transitioning is currently designated as experimental.

Property	Description	Required
enabled	If true, Kafka supervisor will become idle if there is no data on input stream/topic for some time.	no (default == false)
inactiveAfterMillis	Supervisor is marked as idle if all existing data has been read from input topic and no new data has been published for inactiveAfterMillis milliseconds.	no (default == 600_000)

When the supervisor enters the idle state, no new tasks will be launched subsequent to the completion of the currently executing tasks. This strategy may lead to reduced costs for cluster operators while using topics that get sporadic data.

The following example demonstrates supervisor spec with lagBased autoScaler and idle config enabled:

{
    "type": "kafka",
    "spec": {
      "dataSchema": {
        ...
      },
      "ioConfig": {
         "topic": "metrics",
         "inputFormat": {
             "type": "json"
         },
          "consumerProperties": {
             "bootstrap.servers": "localhost:9092"
          },
         "autoScalerConfig": {
             "enableTaskAutoScaler": true,
              "taskCountMax": 6,
              "taskCountMin": 2,
             "minTriggerScaleActionFrequencyMillis": 600000,
             "autoScalerStrategy": "lagBased",
              "lagCollectionIntervalMillis": 30000,
              "lagCollectionRangeMillis": 600000,
              "scaleOutThreshold": 6000000,
              "triggerScaleOutFractionThreshold": 0.3,
             "scaleInThreshold": 1000000,
             "triggerScaleInFractionThreshold": 0.9,
              "scaleActionStartDelayMillis": 300000,
              "scaleActionPeriodMillis": 60000,
              "scaleInStep": 1,
             "scaleOutStep": 2
         },
         "taskCount":1,
         "replicas":1,
         "taskDuration":"PT1H",
         "idleConfig": {
           "enabled": true,
           "inactiveAfterMillis": 600000 
         }
      },
     "tuningConfig":{
        ...
     }
    }
}

More on consumerProperties

Consumer properties must contain a property bootstrap.servers with a list of Kafka brokers in the form: <BROKER_1>:<PORT_1>,<BROKER_2>:<PORT_2>,.... By default, isolation.level is set to read_committed. If you use older versions of Kafka servers without transactions support or don't want Druid to consume only committed transactions, set isolation.level to read_uncommitted.

In some cases, you may need to fetch consumer properties at runtime. For example, when bootstrap.servers is not known upfront, or is not static. To enable SSL connections, you must provide passwords for keystore, truststore and key secretly. You can provide configurations at runtime with a dynamic config provider implementation like the environment variable config provider that comes with Druid. For more information, see DynamicConfigProvider.

For example, if you are using SASL and SSL with Kafka, set the following environment variables for the Druid user on the machines running the Overlord and the Peon services:

export KAFKA_JAAS_CONFIG="org.apache.kafka.common.security.plain.PlainLoginModule required username='admin_user' password='admin_password';"
export SSL_KEY_PASSWORD=mysecretkeypassword
export SSL_KEYSTORE_PASSWORD=mysecretkeystorepassword
export SSL_TRUSTSTORE_PASSWORD=mysecrettruststorepassword

        "druid.dynamic.config.provider": {
          "type": "environment",
          "variables": {
            "sasl.jaas.config": "KAFKA_JAAS_CONFIG",
            "ssl.key.password": "SSL_KEY_PASSWORD",
            "ssl.keystore.password": "SSL_KEYSTORE_PASSWORD",
            "ssl.truststore.password": "SSL_TRUSTSTORE_PASSWORD"
          }
        }
      }

Verify that you've changed the values for all configurations to match your own environment. You can use the environment variable config provider syntax in the Consumer properties field on the Connect tab in the Load Data UI in the web console. When connecting to Kafka, Druid replaces the environment variables with their corresponding values.

Note: You can provide SSL connections with Password Provider interface to define the keystore, truststore, and key, but this feature is deprecated.

Specifying data format

Kafka indexing service supports both inputFormat and parser to specify the data format. Use the inputFormat to specify the data format for Kafka indexing service unless you need a format only supported by the legacy parser.

Supported inputFormats include:

• csv
• delimited
• json
• kafka
• avro_stream
• avro_ocf
• protobuf

For more information, see Data formats. You can also read thrift formats using parser.

KafkaSupervisorTuningConfig

The tuningConfig is optional and default parameters will be used if no tuningConfig is specified.

Field	Type	Description	Required
type	String	The indexing task type, this should always be kafka.	yes
maxRowsInMemory	Integer	The number of rows to aggregate before persisting. This number is the post-aggregation rows, so it is not equivalent to the number of input events, but the number of aggregated rows that those events result in. This is used to manage the required JVM heap size. Maximum heap memory usage for indexing scales with maxRowsInMemory * (2 + maxPendingPersists). 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.	no (default == 1000000)
maxBytesInMemory	Long	The number of bytes to aggregate in heap memory before persisting. This is based on a rough estimate of memory usage and not actual usage. Normally this is computed internally and user does not need to set it. The maximum heap memory usage for indexing is maxBytesInMemory * (2 + maxPendingPersists).	no (default == One-sixth of max JVM memory)
maxRowsPerSegment	Integer	The number of rows to aggregate into a segment; this number is post-aggregation rows. Handoff will happen either if maxRowsPerSegment or maxTotalRows is hit or every intermediateHandoffPeriod, whichever happens earlier.	no (default == 5000000)
maxTotalRows	Long	The number of rows to aggregate across all segments; this number is post-aggregation rows. Handoff will happen either if maxRowsPerSegment or maxTotalRows is hit or every intermediateHandoffPeriod, whichever happens earlier.	no (default == unlimited)
intermediatePersistPeriod	ISO8601 Period	The period that determines the rate at which intermediate persists occur.	no (default == PT10M)
maxPendingPersists	Integer	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).	no (default == 0, meaning one persist can be running concurrently with ingestion, and none can be queued up)
indexSpec	Object	Tune how data is indexed. See IndexSpec for more information.	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.	no (default = same as indexSpec)
reportParseExceptions	Boolean	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.	no (default == false)
handoffConditionTimeout	Long	Milliseconds to wait for segment handoff. It must be >= 0, where 0 means to wait forever.	no (default == 0)
resetOffsetAutomatically	Boolean	Controls behavior when Druid needs to read Kafka messages that are no longer available (i.e. when OffsetOutOfRangeException is encountered). If false, the exception will bubble up, which will cause your tasks to fail and ingestion to halt. If this occurs, manual intervention is required to correct the situation; potentially using the Reset Supervisor API. This mode is useful for production, since it will make you aware of issues with ingestion. If true, Druid will automatically reset to the earlier or latest offset available in Kafka, based on the value of the useEarliestOffset property (earliest if true, latest if false). Note that this can lead to data being DROPPED (if useEarliestOffset is false) or DUPLICATED (if useEarliestOffset is true) without your knowledge. Messages will be logged indicating that a reset has occurred, but ingestion will continue. This mode is useful for non-production situations, since it will make Druid attempt to recover from problems automatically, even if they lead to quiet dropping or duplicating of data. This feature behaves similarly to the Kafka auto.offset.reset consumer property.	no (default == false)
workerThreads	Integer	The number of threads that the supervisor uses to handle requests/responses for worker tasks, along with any other internal asynchronous operation.	no (default == min(10, taskCount))
chatAsync	Boolean	If true, use asynchronous communication with indexing tasks, and ignore the chatThreads parameter. If false, use synchronous communication in a thread pool of size chatThreads.	no (default == true)
chatThreads	Integer	The number of threads that will be used for communicating with indexing tasks. Ignored if chatAsync is true (the default).	no (default == min(10, taskCount * replicas))
chatRetries	Integer	The number of times HTTP requests to indexing tasks will be retried before considering tasks unresponsive.	no (default == 8)
httpTimeout	ISO8601 Period	How long to wait for a HTTP response from an indexing task.	no (default == PT10S)
shutdownTimeout	ISO8601 Period	How long to wait for the supervisor to attempt a graceful shutdown of tasks before exiting.	no (default == PT80S)
offsetFetchPeriod	ISO8601 Period	How often the supervisor queries Kafka and the indexing tasks to fetch current offsets and calculate lag. If the user-specified value is below the minimum value (PT5S), the supervisor ignores the value and uses the minimum value instead.	no (default == PT30S, min == PT5S)
segmentWriteOutMediumFactory	Object	Segment write-out medium to use when creating segments. See below for more information.	no (not specified by default, the value from druid.peon.defaultSegmentWriteOutMediumFactory.type is used)
intermediateHandoffPeriod	ISO8601 Period	How often the tasks should hand off segments. Handoff will happen either if maxRowsPerSegment or maxTotalRows is hit or every intermediateHandoffPeriod, whichever happens earlier.	no (default == P2147483647D)
logParseExceptions	Boolean	If true, log an error message when a parsing exception occurs, containing information about the row where the error occurred.	no, default == false
maxParseExceptions	Integer	The maximum number of parse exceptions that can occur before the task halts ingestion and fails. Overridden if reportParseExceptions is set.	no, unlimited default
maxSavedParseExceptions	Integer	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.	no, default == 0

IndexSpec

Field	Type	Description	Required
bitmap	Object	Compression format for bitmap indexes. Should be a JSON object. See Bitmap types below for options.	no (defaults to Roaring)
dimensionCompression	String	Compression format for dimension columns. Choose from LZ4, LZF, ZSTD or uncompressed.	no (default == LZ4)
metricCompression	String	Compression format for primitive type metric columns. Choose from LZ4, LZF, ZSTD, 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 Roaring bitmaps:

Field	Type	Description	Required
type	String	Must be roaring.	yes

For Concise bitmaps:

Field	Type	Description	Required
type	String	Must be concise.	yes

SegmentWriteOutMediumFactory

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