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new 33a5cda Docs: Splits Kafka topic. Adds detailed example for kafka
inputFormat (#11912)
33a5cda is described below
commit 33a5cda061234028241f2eb341524eca3646881e
Author: Charles Smith <[email protected]>
AuthorDate: Fri Nov 12 13:02:23 2021 -0800
Docs: Splits Kafka topic. Adds detailed example for kafka inputFormat
(#11912)
* Splits Kafka topic according to function. Adds detailed example for kafka
inputFormat
* Apply suggestions from code review
accept suggestions from review
Co-authored-by: sthetland <[email protected]>
Co-authored-by: Katya Macedo <[email protected]>
* Apply suggestions from code review
accept suggestions
Co-authored-by: sthetland <[email protected]>
Co-authored-by: Katya Macedo <[email protected]>
* accept suggestions
* accept suggestions
* final typos and clarifications
* bringing forward some syntax fixes
Co-authored-by: sthetland <[email protected]>
Co-authored-by: Katya Macedo <[email protected]>
---
.../development/extensions-core/kafka-ingestion.md | 542 ++++++---------------
.../extensions-core/kafka-supervisor-operations.md | 215 ++++++++
...-ingestion.md => kafka-supervisor-reference.md} | 332 +------------
docs/ingestion/data-formats.md | 4 +-
docs/ingestion/ingestion-spec.md | 2 +-
docs/operations/api-reference.md | 4 +-
docs/operations/dynamic-config-provider.md | 4 +-
docs/querying/sql.md | 2 +-
website/sidebars.json | 2 +
9 files changed, 392 insertions(+), 715 deletions(-)
diff --git a/docs/development/extensions-core/kafka-ingestion.md
b/docs/development/extensions-core/kafka-ingestion.md
index ad3c9c0..c3b592f 100644
--- a/docs/development/extensions-core/kafka-ingestion.md
+++ b/docs/development/extensions-core/kafka-ingestion.md
@@ -1,7 +1,8 @@
---
id: kafka-ingestion
title: "Apache Kafka ingestion"
-sidebar_label: "Apache Kafka"
+sidebar_label: "Apache Kafka ingestion"
+description: "Overview of the Kafka indexing service for Druid. Includes
example supervisor specs to help you get started."
---
<!--
@@ -23,14 +24,18 @@ sidebar_label: "Apache Kafka"
~ under the License.
-->
-When you enable the Kafka indexing service, you can configure *supervisors* on
the Overlord to manage the creation and lifetime of Kafka indexing tasks. These
indexing tasks read events using Kafka's own partition and offset mechanism to
guarantee exactly-once ingestion. The supervisor oversees the state of the
indexing tasks to:
+When you enable the Kafka indexing service, you can configure supervisors on
the Overlord to manage the creation and lifetime of Kafka indexing tasks.
+
+Kafka indexing tasks read events using Kafka's own partition and offset
mechanism to guarantee exactly-once ingestion. The supervisor oversees the
state of the indexing tasks to:
- coordinate handoffs
- manage failures
- ensure that scalability and replication requirements are maintained.
-To use the Kafka indexing service, load the `druid-kafka-indexing-service`
core Apache Druid extension. See [Including
Extensions](../../development/extensions.md#loading-extensions)).
-This topic covers the ingestion spec for Kafka. For a general `ingestionSpec`
reference, see [Ingestion specs](../../ingestion/ingestion-spec.md). For a
walk-through, check out the [Loading from Apache
Kafka](../../tutorials/tutorial-kafka.md) tutorial.
+This topic covers how to submit a supervisor spec to ingest event data, also
known as message data, from Kafka. See the following for more information:
+- For a reference of Kafka supervisor spec configuration options, see the
[Kafka supervisor reference](./kafka-supervisor-reference.md).
+- For operations reference information to help run and maintain Apache Kafka
supervisors, see [Kafka supervisor
operations](./kafka-supervisor-operations.md).
+- For a walk-through, see the [Loading from Apache
Kafka](../../tutorials/tutorial-kafka.md) tutorial.
## Kafka support
The Kafka indexing service supports transactional topics introduced in Kafka
0.11.x by default. The consumer for Kafka indexing service is incompatible with
older Kafka brokers. If you are using an older version, refer to the [Kafka
upgrade guide](https://kafka.apache.org/documentation/#upgrade).
@@ -41,19 +46,22 @@ Additionally, you can set `isolation.level` to
`read_uncommitted` in `consumerPr
If your Kafka cluster enables consumer-group based ACLs, you can set
`group.id` in `consumerProperties` to override the default auto generated group
id.
-## Submitting a Supervisor Spec
+## Load the Kafka indexing service
-To use the Kafka indexing service, load the `druid-kafka-indexing-service`
extension on both the Overlord and the MiddleManagers. Druid starts a
supervisor for a dataSource when you submit a supervisor spec. You can use the
following endpoint:
+To use the Kafka indexing service, load the `druid-kafka-indexing-service`
extension on both the Overlord and the MiddleManagers. See [Loading
extensions](../extensions.md#loading-extensions) for instructions on how to
configure extensions.
-`http://<OVERLORD_IP>:<OVERLORD_PORT>/druid/indexer/v1/supervisor`
+## Define a supervisor spec
+Similar to the ingestion spec for batch ingestion, the supervisor spec
configures the data ingestion for Kafka streaming ingestion. A supervisor spec
has the following sections:
+- `dataSchema` to specify the Druid datasource name, primary timestamp,
dimensions, metrics, transforms, and any necessary filters.
+- `ioConfig` to configure Kafka connection settings and configure how Druid
parses the data. Kafka-specific connection details go in the
`consumerProperties`. The `ioConfig` is also where you define the input format
(`inputFormat`) of your Kafka data. For supported formats for Kafka and
information on how to configure the input format, see [Data
formats](../../ingestion/data-formats.md).
+- `tuningConfig` to control various tuning parameters specific to each
ingestion method.
+For a full description of all the fields and parameters in a Kafka supervisor
spec, see the [Kafka supervisor reference](./kafka-supervisor-reference.md).
-For example:
-```
-curl -X POST -H 'Content-Type: application/json' -d @supervisor-spec.json
http://localhost:8090/druid/indexer/v1/supervisor
-```
+The following sections contain examples to help you get started with
supervisor specs.
-Where the file `supervisor-spec.json` contains a Kafka supervisor spec:
+### JSON input format supervisor spec example
+The following example demonstrates a supervisor spec for Kafka that uses the
`JSON` input format. In this case Druid parses the event contents in JSON
format:
```json
{
@@ -119,403 +127,143 @@ Where the file `supervisor-spec.json` contains a Kafka
supervisor spec:
}
```
-## Supervisor Configuration
-
-|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](#kafkasupervisorioconfig).|yes|
-|`tuningConfig`|A KafkaSupervisorTuningConfig object to define
performance-related settings for the supervisor and indexing tasks. See
[KafkaSupervisorTuningConfig](#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](#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](#more-on-consumerproperties).|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](#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 [...]
-|`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 an [...]
-|`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 earlyMessageReject [...]
-|`autoScalerConfig`|Object|Defines auto scaling behavior for Kafka ingest
tasks. See [Tasks Autoscaler Properties](#task-autoscaler-properties).|no
(default == null)|
-
-#### Task Autoscaler Properties
-
-> Note that Task AutoScaler is currently designated as experimental.
-
-| 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](#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) |
-
-The following example demonstrates supervisor spec with `lagBased` autoScaler
enabled:
-```json
+### Kafka input format supervisor spec example
+If you want to ingest data from other fields in addition to the Kafka message
contents, you can use the `kafka` input format. The `kafka` input format lets
you ingest:
+- the event key field
+- event headers
+- the Kafka event timestamp
+- the Kafka event value that stores the payload.
+
+> The Kafka inputFormat is currently designated as experimental.
+
+For example, consider the following structure for a message that represents a
fictitious wiki edit in a development environment:
+- **Event headers**: {"environment": "development"}
+- **Event key**: {"key: "wiki-edit"}
+- **Event value**: \<JSON object with event payload containing the change
details\>
+- **Event timestamp**: "Nov. 10, 2021 at 14:06"
+
+When you use the `kafka` input format, you configure the way that Druid names
the dimensions created from the Kafka message:
+- `headerLabelPrefix`: Supply a prefix to the Kafka headers to avoid any
conflicts with named dimensions. The default is `kafka.header`. Considering the
header from the example, Druid maps the header to the following column:
`kafka.header.environment`.
+- `timestampColumnName`: Supply a custom name for the Kafka timestamp in the
Druid schema to avoid conflicts with other time columns. The default is
`kafka.timestamp`.
+- `keyColumnName`: Supply the name for the Kafka key column in Druid. The
default is `kafka.key`.
+Additionally, you must provide information about how Druid should parse the
data in the Kafka message:
+- `headerFormat`: The default "string" decodes UTF8-encoded strings from the
Kafka header. If you need another format, you can implement your own parser.
+- `keyFormat`: Takes a Druid `inputFormat` and uses the value for the first
key it finds. According to the example the value is "wiki-edit". It discards
the key name in this case. If you store the key as a string, use the `CSV`
input format. For example, if you have simple string for the the key
`wiki-edit`, you can use the following to parse the key:
+ ```
+ "keyFormat": {
+ "type": "csv",
+ "hasHeaderRow": false,
+ "findColumnsFromHeader": false,
+ "columns": ["key"]
+ }
+ ```
+- `valueFormat`: Define how to parse the message contents. You can use any of
the Druid input formats that work for Kafka.
+
+For more information on data formats, see [Data
formats](../../ingestion/data-formats.md).
+
+Finally, add the Kafka message columns to the `dimensionsSpec`. For the key
and timestamp, you can use the dimension names you defined for `keyColumnName`
and `timestampColumnName`. For header dimensions, append the header key to the
`headerLabelPrefix`. For example `kafka.header.environment`.
+
+The following supervisor spec demonstrates how to ingest the Kafka header,
key, and timestamp into Druid dimensions:
+```
{
- "type": "kafka",
- "spec": {
- "dataSchema": {
- ...
+ "type": "kafka",
+ "spec": {
+ "ioConfig": {
+ "type": "kafka",
+ "consumerProperties": {
+ "bootstrap.servers": "localhost:9092"
},
- "ioConfig": {
- "topic": "metrics",
- "inputFormat": {
- "type": "json"
- },
- "consumerProperties": {
- "bootstrap.servers": "localhost:9092"
+ "topic": "wiki-edits",
+ "inputFormat": {
+ "type": "kafka",
+ "headerLabelPrefix": "kafka.header.",
+ "timestampColumnName": "kafka.timestamp",
+ "keyColumnName": "kafka.key",
+ "headerFormat": {
+ "type": "string"
+ },
+ "keyFormat": {
+ "type": "json"
+ },
+ "valueFormat": {
+ "type": "json"
+ },
+ "findColumnsFromHeader": false
+ },
+ "useEarliestOffset": true
+ },
+ "tuningConfig": {
+ "type": "kafka"
+ },
+ "dataSchema": {
+ "dataSource": "wikiticker",
+ "timestampSpec": {
+ "column": "timestamp",
+ "format": "posix"
+ },
+ "dimensionsSpec": {
+ "dimensions": [
+ {
+ "type": "string",
+ "name": "kafka.key"
+ },
+ {
+ "type": "string",
+ "name": "kafka.timestamp"
},
- "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"
+ {
+ "type": "string",
+ "name": "kafka.header.environment"
+ },
+ "$schema",
+ {
+ "type": "long",
+ "name": "id"
+ },
+ "type",
+ {
+ "type": "long",
+ "name": "namespace"
+ },
+ "title",
+ "comment",
+ "user",]
+ ]
},
- "tuningConfig":{
- ...
- }
+ "granularitySpec": {
+ "queryGranularity": "none",
+ "rollup": false,
+ "segmentGranularity": "day"
+ }
}
+ },
+ "tuningConfig": {
+ "type": "kafka"
+ }
}
```
-
-#### 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](../../operations/dynamic-config-pro [...]
-
-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"
- }
- }
- }
+After Druid ingests the data, you can query the Kafka message columns as
follows:
+```unix
+SELECT
+ "kafka.header.environment",
+ "kafka.key",
+ "kafka.timestamp"
+FROM "wikiticker"
+
+kafka.header.environment kafka.key kafka.timestamp
+development wiki-edit 1636399229823
```
-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 Druid console. When connecting to Kafka, Druid replaces the
environment variables with their corresponding values.
-
-Note: You can provide SSL connections with [Password
Provider](../../operations/password-provider.md) interface to define the
`keystore`, `truststore`, and `key`, but this feature is deprecated.
-
-#### Specifying data format
-
-Kafka indexing service supports both
[`inputFormat`](../../ingestion/data-formats.md#input-format) and
[`parser`](../../ingestion/data-formats.md#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 `inputFormat`s include:
-- `csv`
-- `delimited`
-- `json`
-- `kafka`
-- `avro_stream`
-- `protobuf`
-
-For more information, see [Data formats](../../ingestion/data-formats.md). You
can also read [`thrift`](../extensions-contrib/thrift.md) formats using
`parser`.
-
-<a name="tuningconfig"></a>
+For more information, see [`kafka` data
format](../../ingestion/data-formats.md#kafka).
+## Submit a supervisor spec
-### KafkaSupervisorTuningConfig
+Druid starts a supervisor for a dataSource when you submit a supervisor spec.
You can use the data loader in the Druid console or you can submit a supervisor
spec to the following endpoint:
-The tuningConfig is optional and default parameters will be used if no
tuningConfig is specified.
-
-| Field | Type | Description
[...]
-|-----------------------------------|----------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
[...]
-| `type` | String | The indexing task type,
this should always be `kafka`.
[...]
-| `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 [...]
-| `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).
[...]
-| `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.
[...]
-| `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.
[...]
-| `intermediatePersistPeriod` | ISO8601 Period | The period that
determines the rate at which intermediate persists occur.
[...]
-| `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).
[...]
-| `indexSpec` | Object | Tune how data is
indexed. See [IndexSpec](#indexspec) for more information.
[...]
-| `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](#indexspec) for possib [...]
-| `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. [...]
-| `handoffConditionTimeout` | Long | Milliseconds to wait
for segment handoff. It must be >= 0, where 0 means to wait forever.
[...]
-| `resetOffsetAutomatically` | Boolean | Controls behavior when
Druid needs to read Kafka messages that are no longer available (i.e. when
OffsetOutOfRangeException is encountered).<br/><br/>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](../../operations/api-reference.md#supervisors). This mode is useful f [...]
-| `workerThreads` | Integer | The number of threads
that the supervisor uses to handle requests/responses for worker tasks, along
with any other internal asynchronous operation.
[...]
-| `chatThreads` | Integer | The number of threads
that will be used for communicating with indexing tasks.
[...]
-| `chatRetries` | Integer | The number of times
HTTP requests to indexing tasks will be retried before considering tasks
unresponsive.
[...]
-| `httpTimeout` | ISO8601 Period | How long to wait for a
HTTP response from an indexing task.
[...]
-| `shutdownTimeout` | ISO8601 Period | How long to wait for
the supervisor to attempt a graceful shutdown of tasks before exiting.
[...]
-| `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.
[...]
-| `segmentWriteOutMediumFactory` | Object | Segment write-out
medium to use when creating segments. See below for more information.
[...]
-| `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.
[...]
-| `logParseExceptions` | Boolean | If true, log an error
message when a parsing exception occurs, containing information about the row
where the error occurred.
[...]
-| `maxParseExceptions` | Integer | The maximum number of
parse exceptions that can occur before the task halts ingestion and fails.
Overridden if `reportParseExceptions` is set.
[...]
-| `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](../../ingestion/tasks.md#reports). Overridden if
`reportParseExceptions` is set.
[...]
-
-#### IndexSpec
-
-|Field|Type|Description|Required|
-|-----|----|-----------|--------|
-|bitmap|Object|Compression format for bitmap indexes. Should be a JSON object.
See [Bitmap types](#bitmap-types) below for options.|no (defaults to Roaring)|
-|dimensionCompression|String|Compression format for dimension columns. Choose
from `LZ4`, `LZF`, or `uncompressed`.|no (default == `LZ4`)|
-|metricCompression|String|Compression format for primitive type 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 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`)|
-
-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](../../configuration/index.md#segmentwriteoutmediumfactory)
for explanation and available options.|yes|
-
-## Operations
-
-This section gives descriptions of how some supervisor APIs work specifically
in Kafka Indexing Service.
-For all supervisor APIs, please check [Supervisor
APIs](../../operations/api-reference.md#supervisors).
-
-### Getting Supervisor Status Report
-
-`GET /druid/indexer/v1/supervisor/<supervisorId>/status` returns a snapshot
report of the current state of the tasks managed by the given supervisor. This
includes the latest
-offsets as reported by Kafka, the consumer lag per partition, as well as the
aggregate lag of all partitions. The
-consumer lag per partition may be reported as negative values if the
supervisor has not received a recent latest offset
-response from Kafka. The aggregate lag value will always be >= 0.
-
-The status report also contains the supervisor's state and a list of recently
thrown exceptions (reported as
-`recentErrors`, whose max size can be controlled using the
`druid.supervisor.maxStoredExceptionEvents` configuration).
-There are two fields related to the supervisor's state - `state` and
`detailedState`. The `state` field will always be
-one of a small number of generic states that are applicable to any type of
supervisor, while the `detailedState` field
-will contain a more descriptive, implementation-specific state that may
provide more insight into the supervisor's
-activities than the generic `state` field.
-
-The list of possible `state` values are: [`PENDING`, `RUNNING`, `SUSPENDED`,
`STOPPING`, `UNHEALTHY_SUPERVISOR`, `UNHEALTHY_TASKS`]
-
-The list of `detailedState` values and their corresponding `state` mapping is
as follows:
-
-|Detailed State|Corresponding State|Description|
-|--------------|-------------------|-----------|
-|UNHEALTHY_SUPERVISOR|UNHEALTHY_SUPERVISOR|The supervisor has encountered
errors on the past `druid.supervisor.unhealthinessThreshold` iterations|
-|UNHEALTHY_TASKS|UNHEALTHY_TASKS|The last
`druid.supervisor.taskUnhealthinessThreshold` tasks have all failed|
-|UNABLE_TO_CONNECT_TO_STREAM|UNHEALTHY_SUPERVISOR|The supervisor is
encountering connectivity issues with Kafka and has not successfully connected
in the past|
-|LOST_CONTACT_WITH_STREAM|UNHEALTHY_SUPERVISOR|The supervisor is encountering
connectivity issues with Kafka but has successfully connected in the past|
-|PENDING (first iteration only)|PENDING|The supervisor has been initialized
and hasn't started connecting to the stream|
-|CONNECTING_TO_STREAM (first iteration only)|RUNNING|The supervisor is trying
to connect to the stream and update partition data|
-|DISCOVERING_INITIAL_TASKS (first iteration only)|RUNNING|The supervisor is
discovering already-running tasks|
-|CREATING_TASKS (first iteration only)|RUNNING|The supervisor is creating
tasks and discovering state|
-|RUNNING|RUNNING|The supervisor has started tasks and is waiting for
taskDuration to elapse|
-|SUSPENDED|SUSPENDED|The supervisor has been suspended|
-|STOPPING|STOPPING|The supervisor is stopping|
-
-On each iteration of the supervisor's run loop, the supervisor completes the
following tasks in sequence:
- 1) Fetch the list of partitions from Kafka and determine the starting offset
for each partition (either based on the
- last processed offset if continuing, or starting from the beginning or
ending of the stream if this is a new topic).
- 2) Discover any running indexing tasks that are writing to the supervisor's
datasource and adopt them if they match
- the supervisor's configuration, else signal them to stop.
- 3) Send a status request to each supervised task to update our view of the
state of the tasks under our supervision.
- 4) Handle tasks that have exceeded `taskDuration` and should transition from
the reading to publishing state.
- 5) Handle tasks that have finished publishing and signal redundant replica
tasks to stop.
- 6) Handle tasks that have failed and clean up the supervisor's internal
state.
- 7) Compare the list of healthy tasks to the requested `taskCount` and
`replicas` configurations and create additional tasks if required.
-
-The `detailedState` field will show additional values (those marked with
"first iteration only") the first time the
-supervisor executes this run loop after startup or after resuming from a
suspension. This is intended to surface
-initialization-type issues, where the supervisor is unable to reach a stable
state (perhaps because it can't connect to
-Kafka, it can't read from the Kafka topic, or it can't communicate with
existing tasks). Once the supervisor is stable -
-that is, once it has completed a full execution without encountering any
issues - `detailedState` will show a `RUNNING`
-state until it is stopped, suspended, or hits a task failure threshold and
transitions to an unhealthy state.
-
-### Getting Supervisor Ingestion Stats Report
-
-`GET /druid/indexer/v1/supervisor/<supervisorId>/stats` returns a snapshot of
the current ingestion row counters for each task being managed by the
supervisor, along with moving averages for the row counters.
-
-See [Task Reports: Row Stats](../../ingestion/tasks.md#row-stats) for more
information.
-
-### Supervisor Health Check
-
-`GET /druid/indexer/v1/supervisor/<supervisorId>/health` returns `200 OK` if
the supervisor is healthy and
-`503 Service Unavailable` if it is unhealthy. Healthiness is determined by the
supervisor's `state` (as returned by the
-`/status` endpoint) and the `druid.supervisor.*` Overlord configuration
thresholds.
-
-### Updating Existing Supervisors
-
-`POST /druid/indexer/v1/supervisor` can be used to update existing supervisor
spec.
-Calling this endpoint when there is already an existing supervisor for the
same dataSource will cause:
-
-- The running supervisor to signal its managed tasks to stop reading and begin
publishing.
-- The running supervisor to exit.
-- A new supervisor to be created using the configuration provided in the
request body. This supervisor will retain the
-existing publishing tasks and will create new tasks starting at the offsets
the publishing tasks ended on.
-
-Seamless schema migrations can thus be achieved by simply submitting the new
schema using this endpoint.
-
-### Suspending and Resuming Supervisors
-
-You can suspend and resume a supervisor using `POST
/druid/indexer/v1/supervisor/<supervisorId>/suspend` and `POST
/druid/indexer/v1/supervisor/<supervisorId>/resume`, respectively.
-
-Note that the supervisor itself will still be operating and emitting logs and
metrics,
-it will just ensure that no indexing tasks are running until the supervisor is
resumed.
-
-### Resetting Supervisors
-
-The `POST /druid/indexer/v1/supervisor/<supervisorId>/reset` operation clears
stored
-offsets, causing the supervisor to start reading offsets from either the
earliest or latest
-offsets in Kafka (depending on the value of `useEarliestOffset`). After
clearing stored
-offsets, the supervisor kills and recreates any active tasks, so that tasks
begin reading
-from valid offsets.
-
-Use care when using this operation! Resetting the supervisor may cause Kafka
messages
-to be skipped or read twice, resulting in missing or duplicate data.
-
-The reason for using this operation is to recover from a state in which the
supervisor
-ceases operating due to missing offsets. The indexing service keeps track of
the latest
-persisted Kafka offsets in order to provide exactly-once ingestion guarantees
across
-tasks. Subsequent tasks must start reading from where the previous task
completed in
-order for the generated segments to be accepted. If the messages at the
expected
-starting offsets are no longer available in Kafka (typically because the
message retention
-period has elapsed or the topic was removed and re-created) the supervisor
will refuse
-to start and in flight tasks will fail. This operation enables you to recover
from this condition.
-
-Note that the supervisor must be running for this endpoint to be available.
-
-### Terminating Supervisors
-
-The `POST /druid/indexer/v1/supervisor/<supervisorId>/terminate` operation
terminates a supervisor and causes all
-associated indexing tasks managed by this supervisor to immediately stop and
begin
-publishing their segments. This supervisor will still exist in the metadata
store and it's history may be retrieved
-with the supervisor history API, but will not be listed in the 'get
supervisors' API response nor can it's configuration
-or status report be retrieved. The only way this supervisor can start again is
by submitting a functioning supervisor
-spec to the create API.
-
-### Capacity Planning
-
-Kafka indexing tasks run on MiddleManagers and are thus limited by the
resources available in the MiddleManager
-cluster. In particular, you should make sure that you have sufficient worker
capacity (configured using the
-`druid.worker.capacity` property) to handle the configuration in the
supervisor spec. Note that worker capacity is
-shared across all types of indexing tasks, so you should plan your worker
capacity to handle your total indexing load
-(e.g. batch processing, realtime tasks, merging tasks, etc.). If your workers
run out of capacity, Kafka indexing tasks
-will queue and wait for the next available worker. This may cause queries to
return partial results but will not result
-in data loss (assuming the tasks run before Kafka purges those offsets).
-
-A running task will normally be in one of two states: *reading* or
*publishing*. A task will remain in reading state for
-`taskDuration`, at which point it will transition to publishing state. A task
will remain in publishing state for as long
-as it takes to generate segments, push segments to deep storage, and have them
be loaded and served by a Historical process
-(or until `completionTimeout` elapses).
+`http://<OVERLORD_IP>:<OVERLORD_PORT>/druid/indexer/v1/supervisor`
-The number of reading tasks is controlled by `replicas` and `taskCount`. In
general, there will be `replicas * taskCount`
-reading tasks, the exception being if taskCount > {numKafkaPartitions} in
which case {numKafkaPartitions} tasks will
-be used instead. When `taskDuration` elapses, these tasks will transition to
publishing state and `replicas * taskCount`
-new reading tasks will be created. Therefore to allow for reading tasks and
publishing tasks to run concurrently, there
-should be a minimum capacity of:
+For example:
```
-workerCapacity = 2 * replicas * taskCount
+curl -X POST -H 'Content-Type: application/json' -d @supervisor-spec.json
http://localhost:8090/druid/indexer/v1/supervisor
```
-This value is for the ideal situation in which there is at most one set of
tasks publishing while another set is reading.
-In some circumstances, it is possible to have multiple sets of tasks
publishing simultaneously. This would happen if the
-time-to-publish (generate segment, push to deep storage, loaded on Historical)
> `taskDuration`. This is a valid
-scenario (correctness-wise) but requires additional worker capacity to
support. In general, it is a good idea to have
-`taskDuration` be large enough that the previous set of tasks finishes
publishing before the current set begins.
-
-### Supervisor Persistence
-
-When a supervisor spec is submitted via the `POST
/druid/indexer/v1/supervisor` endpoint, it is persisted in the
-configured metadata database. There can only be a single supervisor per
dataSource, and submitting a second spec for
-the same dataSource will overwrite the previous one.
-
-When an Overlord gains leadership, either by being started or as a result of
another Overlord failing, it will spawn
-a supervisor for each supervisor spec in the metadata database. The supervisor
will then discover running Kafka indexing
-tasks and will attempt to adopt them if they are compatible with the
supervisor's configuration. If they are not
-compatible because they have a different ingestion spec or partition
allocation, the tasks will be killed and the
-supervisor will create a new set of tasks. In this way, the supervisors are
persistent across Overlord restarts and
-fail-overs.
-
-A supervisor is stopped via the `POST
/druid/indexer/v1/supervisor/<supervisorId>/terminate` endpoint. This places a
-tombstone marker in the database (to prevent the supervisor from being
reloaded on a restart) and then gracefully
-shuts down the currently running supervisor. When a supervisor is shut down in
this way, it will instruct its
-managed tasks to stop reading and begin publishing their segments immediately.
The call to the shutdown endpoint will
-return after all tasks have been signaled to stop but before the tasks finish
publishing their segments.
-
-### Schema/Configuration Changes
-
-Schema and configuration changes are handled by submitting the new supervisor
spec via the same
-`POST /druid/indexer/v1/supervisor` endpoint used to initially create the
supervisor. The Overlord will initiate a
-graceful shutdown of the existing supervisor which will cause the tasks being
managed by that supervisor to stop reading
-and begin publishing their segments. A new supervisor will then be started
which will create a new set of tasks that
-will start reading from the offsets where the previous now-publishing tasks
left off, but using the updated schema.
-In this way, configuration changes can be applied without requiring any pause
in ingestion.
-
-### Deployment Notes on Kafka partitions and Druid segments
-
-Druid assigns each Kafka indexing task Kafka partitions. A task writes the
events it consumes from Kafka into a single segment for the segment granularity
interval until it reaches one of the following: `maxRowsPerSegment`,
`maxTotalRows` or `intermediateHandoffPeriod` limit. At this point, the task
creates a new partition for this segment granularity to contain subsequent
events.
-
-The Kafka Indexing Task also does incremental hand-offs. Therefore segments
become available as they are ready and you do not have to wait for all segments
until the end of the task duration. When the task reaches one of
`maxRowsPerSegment`, `maxTotalRows`, or `intermediateHandoffPeriod`, it hands
off all the segments and creates a new new set of segments will be created for
further events. This allows the task to run for longer durations without
accumulating old segments locally on Mi [...]
-
-The Kafka Indexing Service may still produce some small segments. For example,
consider the following scenario:
-- Task duration is 4 hours
-- Segment granularity is set to an HOUR
-- The supervisor was started at 9:10
-After 4 hours at 13:10, Druid starts a new set of tasks. The events for the
interval 13:00 - 14:00 may be split across existing tasks and the new set of
tasks which could result in small segments. To merge them together into new
segments of an ideal size (in the range of ~500-700 MB per segment), you can
schedule re-indexing tasks, optionally with a different segment granularity.
-
-For more detail, see [Segment size
optimization](../../operations/segment-optimization.md).
-There is also ongoing work to support automatic segment compaction of sharded
segments as well as compaction not requiring
-Hadoop (see [here](https://github.com/apache/druid/pull/5102)).
+Where the file `supervisor-spec.json` contains your Kafka supervisor spec file.
diff --git a/docs/development/extensions-core/kafka-supervisor-operations.md
b/docs/development/extensions-core/kafka-supervisor-operations.md
new file mode 100644
index 0000000..fad3aa6
--- /dev/null
+++ b/docs/development/extensions-core/kafka-supervisor-operations.md
@@ -0,0 +1,215 @@
+---
+id: kafka-supervisor-operations
+title: "Apache Kafka supervisor operations reference"
+sidebar_label: "Apache Kafka operations"
+description: "Refrence topic for running and maintaining Apache Kafka
supervisors"
+---
+
+<!--
+ ~ Licensed to the Apache Software Foundation (ASF) under one
+ ~ or more contributor license agreements. See the NOTICE file
+ ~ distributed with this work for additional information
+ ~ regarding copyright ownership. The ASF licenses this file
+ ~ to you under the Apache License, Version 2.0 (the
+ ~ "License"); you may not use this file except in compliance
+ ~ with the License. You may obtain a copy of the License at
+ ~
+ ~ http://www.apache.org/licenses/LICENSE-2.0
+ ~
+ ~ Unless required by applicable law or agreed to in writing,
+ ~ software distributed under the License is distributed on an
+ ~ "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ ~ KIND, either express or implied. See the License for the
+ ~ specific language governing permissions and limitations
+ ~ under the License.
+ -->
+This topic contains operations reference information to run and maintain
Apache Kafka supervisors for Apache Druid. It includes descriptions of how some
supervisor APIs work within Kafka Indexing Service.
+
+For all supervisor APIs, see [Supervisor
APIs](../../operations/api-reference.md#supervisors).
+
+## Getting Supervisor Status Report
+
+`GET /druid/indexer/v1/supervisor/<supervisorId>/status` returns a snapshot
report of the current state of the tasks managed by the given supervisor. This
includes the latest
+offsets as reported by Kafka, the consumer lag per partition, as well as the
aggregate lag of all partitions. The
+consumer lag per partition may be reported as negative values if the
supervisor has not received a recent latest offset
+response from Kafka. The aggregate lag value will always be >= 0.
+
+The status report also contains the supervisor's state and a list of recently
thrown exceptions (reported as
+`recentErrors`, whose max size can be controlled using the
`druid.supervisor.maxStoredExceptionEvents` configuration).
+There are two fields related to the supervisor's state - `state` and
`detailedState`. The `state` field will always be
+one of a small number of generic states that are applicable to any type of
supervisor, while the `detailedState` field
+will contain a more descriptive, implementation-specific state that may
provide more insight into the supervisor's
+activities than the generic `state` field.
+
+The list of possible `state` values are: [`PENDING`, `RUNNING`, `SUSPENDED`,
`STOPPING`, `UNHEALTHY_SUPERVISOR`, `UNHEALTHY_TASKS`]
+
+The list of `detailedState` values and their corresponding `state` mapping is
as follows:
+
+|Detailed State|Corresponding State|Description|
+|--------------|-------------------|-----------|
+|UNHEALTHY_SUPERVISOR|UNHEALTHY_SUPERVISOR|The supervisor has encountered
errors on the past `druid.supervisor.unhealthinessThreshold` iterations|
+|UNHEALTHY_TASKS|UNHEALTHY_TASKS|The last
`druid.supervisor.taskUnhealthinessThreshold` tasks have all failed|
+|UNABLE_TO_CONNECT_TO_STREAM|UNHEALTHY_SUPERVISOR|The supervisor is
encountering connectivity issues with Kafka and has not successfully connected
in the past|
+|LOST_CONTACT_WITH_STREAM|UNHEALTHY_SUPERVISOR|The supervisor is encountering
connectivity issues with Kafka but has successfully connected in the past|
+|PENDING (first iteration only)|PENDING|The supervisor has been initialized
and hasn't started connecting to the stream|
+|CONNECTING_TO_STREAM (first iteration only)|RUNNING|The supervisor is trying
to connect to the stream and update partition data|
+|DISCOVERING_INITIAL_TASKS (first iteration only)|RUNNING|The supervisor is
discovering already-running tasks|
+|CREATING_TASKS (first iteration only)|RUNNING|The supervisor is creating
tasks and discovering state|
+|RUNNING|RUNNING|The supervisor has started tasks and is waiting for
taskDuration to elapse|
+|SUSPENDED|SUSPENDED|The supervisor has been suspended|
+|STOPPING|STOPPING|The supervisor is stopping|
+
+On each iteration of the supervisor's run loop, the supervisor completes the
following tasks in sequence:
+ 1) Fetch the list of partitions from Kafka and determine the starting offset
for each partition (either based on the
+ last processed offset if continuing, or starting from the beginning or
ending of the stream if this is a new topic).
+ 2) Discover any running indexing tasks that are writing to the supervisor's
datasource and adopt them if they match
+ the supervisor's configuration, else signal them to stop.
+ 3) Send a status request to each supervised task to update our view of the
state of the tasks under our supervision.
+ 4) Handle tasks that have exceeded `taskDuration` and should transition from
the reading to publishing state.
+ 5) Handle tasks that have finished publishing and signal redundant replica
tasks to stop.
+ 6) Handle tasks that have failed and clean up the supervisor's internal
state.
+ 7) Compare the list of healthy tasks to the requested `taskCount` and
`replicas` configurations and create additional tasks if required.
+
+The `detailedState` field will show additional values (those marked with
"first iteration only") the first time the
+supervisor executes this run loop after startup or after resuming from a
suspension. This is intended to surface
+initialization-type issues, where the supervisor is unable to reach a stable
state (perhaps because it can't connect to
+Kafka, it can't read from the Kafka topic, or it can't communicate with
existing tasks). Once the supervisor is stable -
+that is, once it has completed a full execution without encountering any
issues - `detailedState` will show a `RUNNING`
+state until it is stopped, suspended, or hits a task failure threshold and
transitions to an unhealthy state.
+
+## Getting Supervisor Ingestion Stats Report
+
+`GET /druid/indexer/v1/supervisor/<supervisorId>/stats` returns a snapshot of
the current ingestion row counters for each task being managed by the
supervisor, along with moving averages for the row counters.
+
+See [Task Reports: Row Stats](../../ingestion/tasks.md#row-stats) for more
information.
+
+## Supervisor Health Check
+
+`GET /druid/indexer/v1/supervisor/<supervisorId>/health` returns `200 OK` if
the supervisor is healthy and
+`503 Service Unavailable` if it is unhealthy. Healthiness is determined by the
supervisor's `state` (as returned by the
+`/status` endpoint) and the `druid.supervisor.*` Overlord configuration
thresholds.
+
+## Updating Existing Supervisors
+
+`POST /druid/indexer/v1/supervisor` can be used to update existing supervisor
spec.
+Calling this endpoint when there is already an existing supervisor for the
same dataSource will cause:
+
+- The running supervisor to signal its managed tasks to stop reading and begin
publishing.
+- The running supervisor to exit.
+- A new supervisor to be created using the configuration provided in the
request body. This supervisor will retain the
+existing publishing tasks and will create new tasks starting at the offsets
the publishing tasks ended on.
+
+Seamless schema migrations can thus be achieved by simply submitting the new
schema using this endpoint.
+
+## Suspending and Resuming Supervisors
+
+You can suspend and resume a supervisor using `POST
/druid/indexer/v1/supervisor/<supervisorId>/suspend` and `POST
/druid/indexer/v1/supervisor/<supervisorId>/resume`, respectively.
+
+Note that the supervisor itself will still be operating and emitting logs and
metrics,
+it will just ensure that no indexing tasks are running until the supervisor is
resumed.
+
+## Resetting Supervisors
+
+The `POST /druid/indexer/v1/supervisor/<supervisorId>/reset` operation clears
stored
+offsets, causing the supervisor to start reading offsets from either the
earliest or latest
+offsets in Kafka (depending on the value of `useEarliestOffset`). After
clearing stored
+offsets, the supervisor kills and recreates any active tasks, so that tasks
begin reading
+from valid offsets.
+
+Use care when using this operation! Resetting the supervisor may cause Kafka
messages
+to be skipped or read twice, resulting in missing or duplicate data.
+
+The reason for using this operation is to recover from a state in which the
supervisor
+ceases operating due to missing offsets. The indexing service keeps track of
the latest
+persisted Kafka offsets in order to provide exactly-once ingestion guarantees
across
+tasks. Subsequent tasks must start reading from where the previous task
completed in
+order for the generated segments to be accepted. If the messages at the
expected
+starting offsets are no longer available in Kafka (typically because the
message retention
+period has elapsed or the topic was removed and re-created) the supervisor
will refuse
+to start and in flight tasks will fail. This operation enables you to recover
from this condition.
+
+Note that the supervisor must be running for this endpoint to be available.
+
+## Terminating Supervisors
+
+The `POST /druid/indexer/v1/supervisor/<supervisorId>/terminate` operation
terminates a supervisor and causes all
+associated indexing tasks managed by this supervisor to immediately stop and
begin
+publishing their segments. This supervisor will still exist in the metadata
store and its history may be retrieved
+with the supervisor history API, but will not be listed in the 'get
supervisors' API response nor can it's configuration
+or status report be retrieved. The only way this supervisor can start again is
by submitting a functioning supervisor
+spec to the create API.
+
+## Capacity Planning
+
+Kafka indexing tasks run on MiddleManagers and are thus limited by the
resources available in the MiddleManager
+cluster. In particular, you should make sure that you have sufficient worker
capacity (configured using the
+`druid.worker.capacity` property) to handle the configuration in the
supervisor spec. Note that worker capacity is
+shared across all types of indexing tasks, so you should plan your worker
capacity to handle your total indexing load
+(e.g. batch processing, realtime tasks, merging tasks, etc.). If your workers
run out of capacity, Kafka indexing tasks
+will queue and wait for the next available worker. This may cause queries to
return partial results but will not result
+in data loss (assuming the tasks run before Kafka purges those offsets).
+
+A running task will normally be in one of two states: *reading* or
*publishing*. A task will remain in reading state for
+`taskDuration`, at which point it will transition to publishing state. A task
will remain in publishing state for as long
+as it takes to generate segments, push segments to deep storage, and have them
be loaded and served by a Historical process
+(or until `completionTimeout` elapses).
+
+The number of reading tasks is controlled by `replicas` and `taskCount`. In
general, there will be `replicas * taskCount`
+reading tasks, the exception being if taskCount > {numKafkaPartitions} in
which case {numKafkaPartitions} tasks will
+be used instead. When `taskDuration` elapses, these tasks will transition to
publishing state and `replicas * taskCount`
+new reading tasks will be created. Therefore to allow for reading tasks and
publishing tasks to run concurrently, there
+should be a minimum capacity of:
+
+```
+workerCapacity = 2 * replicas * taskCount
+```
+
+This value is for the ideal situation in which there is at most one set of
tasks publishing while another set is reading.
+In some circumstances, it is possible to have multiple sets of tasks
publishing simultaneously. This would happen if the
+time-to-publish (generate segment, push to deep storage, loaded on Historical)
> `taskDuration`. This is a valid
+scenario (correctness-wise) but requires additional worker capacity to
support. In general, it is a good idea to have
+`taskDuration` be large enough that the previous set of tasks finishes
publishing before the current set begins.
+
+## Supervisor Persistence
+
+When a supervisor spec is submitted via the `POST
/druid/indexer/v1/supervisor` endpoint, it is persisted in the
+configured metadata database. There can only be a single supervisor per
dataSource, and submitting a second spec for
+the same dataSource will overwrite the previous one.
+
+When an Overlord gains leadership, either by being started or as a result of
another Overlord failing, it will spawn
+a supervisor for each supervisor spec in the metadata database. The supervisor
will then discover running Kafka indexing
+tasks and will attempt to adopt them if they are compatible with the
supervisor's configuration. If they are not
+compatible because they have a different ingestion spec or partition
allocation, the tasks will be killed and the
+supervisor will create a new set of tasks. In this way, the supervisors are
persistent across Overlord restarts and
+fail-overs.
+
+A supervisor is stopped via the `POST
/druid/indexer/v1/supervisor/<supervisorId>/terminate` endpoint. This places a
+tombstone marker in the database (to prevent the supervisor from being
reloaded on a restart) and then gracefully
+shuts down the currently running supervisor. When a supervisor is shut down in
this way, it will instruct its
+managed tasks to stop reading and begin publishing their segments immediately.
The call to the shutdown endpoint will
+return after all tasks have been signaled to stop but before the tasks finish
publishing their segments.
+
+### Schema/Configuration Changes
+
+Schema and configuration changes are handled by submitting the new supervisor
spec via the same
+`POST /druid/indexer/v1/supervisor` endpoint used to initially create the
supervisor. The Overlord will initiate a
+graceful shutdown of the existing supervisor which will cause the tasks being
managed by that supervisor to stop reading
+and begin publishing their segments. A new supervisor will then be started
which will create a new set of tasks that
+will start reading from the offsets where the previous now-publishing tasks
left off, but using the updated schema.
+In this way, configuration changes can be applied without requiring any pause
in ingestion.
+
+## Deployment Notes on Kafka partitions and Druid segments
+
+Druid assigns each Kafka indexing task Kafka partitions. A task writes the
events it consumes from Kafka into a single segment for the segment granularity
interval until it reaches one of the following: `maxRowsPerSegment`,
`maxTotalRows` or `intermediateHandoffPeriod` limit. At this point, the task
creates a new partition for this segment granularity to contain subsequent
events.
+
+The Kafka Indexing Task also does incremental hand-offs. Therefore segments
become available as they are ready and you do not have to wait for all segments
until the end of the task duration. When the task reaches one of
`maxRowsPerSegment`, `maxTotalRows`, or `intermediateHandoffPeriod`, it hands
off all the segments and creates a new new set of segments will be created for
further events. This allows the task to run for longer durations without
accumulating old segments locally on Mi [...]
+
+The Kafka Indexing Service may still produce some small segments. For example,
consider the following scenario:
+- Task duration is 4 hours
+- Segment granularity is set to an HOUR
+- The supervisor was started at 9:10
+After 4 hours at 13:10, Druid starts a new set of tasks. The events for the
interval 13:00 - 14:00 may be split across existing tasks and the new set of
tasks which could result in small segments. To merge them together into new
segments of an ideal size (in the range of ~500-700 MB per segment), you can
schedule re-indexing tasks, optionally with a different segment granularity.
+
+For more detail, see [Segment size
optimization](../../operations/segment-optimization.md).
+There is also ongoing work to support automatic segment compaction of sharded
segments as well as compaction not requiring
+Hadoop (see [here](https://github.com/apache/druid/pull/5102)).
diff --git a/docs/development/extensions-core/kafka-ingestion.md
b/docs/development/extensions-core/kafka-supervisor-reference.md
similarity index 59%
copy from docs/development/extensions-core/kafka-ingestion.md
copy to docs/development/extensions-core/kafka-supervisor-reference.md
index ad3c9c0..e034585 100644
--- a/docs/development/extensions-core/kafka-ingestion.md
+++ b/docs/development/extensions-core/kafka-supervisor-reference.md
@@ -1,7 +1,8 @@
---
-id: kafka-ingestion
-title: "Apache Kafka ingestion"
-sidebar_label: "Apache Kafka"
+id: kafka-supervisor-reference
+title: "Apache Kafka supervisor reference"
+sidebar_label: "Apache Kafka supervisor"
+description: "Refrence topic for Apache Kafka supervisors"
---
<!--
@@ -22,104 +23,7 @@ sidebar_label: "Apache Kafka"
~ specific language governing permissions and limitations
~ under the License.
-->
-
-When you enable the Kafka indexing service, you can configure *supervisors* on
the Overlord to manage the creation and lifetime of Kafka indexing tasks. These
indexing tasks read events using Kafka's own partition and offset mechanism to
guarantee exactly-once ingestion. The supervisor oversees the state of the
indexing tasks to:
- - coordinate handoffs
- - manage failures
- - ensure that scalability and replication requirements are maintained.
-
-To use the Kafka indexing service, load the `druid-kafka-indexing-service`
core Apache Druid extension. See [Including
Extensions](../../development/extensions.md#loading-extensions)).
-
-This topic covers the ingestion spec for Kafka. For a general `ingestionSpec`
reference, see [Ingestion specs](../../ingestion/ingestion-spec.md). For a
walk-through, check out the [Loading from Apache
Kafka](../../tutorials/tutorial-kafka.md) tutorial.
-
-## Kafka support
-The Kafka indexing service supports transactional topics introduced in Kafka
0.11.x by default. The consumer for Kafka indexing service is incompatible with
older Kafka brokers. If you are using an older version, refer to the [Kafka
upgrade guide](https://kafka.apache.org/documentation/#upgrade).
-
-Additionally, you can set `isolation.level` to `read_uncommitted` in
`consumerProperties` if either:
-- You don't need Druid to consume transactional topics.
-- You need Druid to consume older versions of Kafka. Make sure offsets are
sequential, since there is no offset gap check in Druid anymore.
-
-If your Kafka cluster enables consumer-group based ACLs, you can set
`group.id` in `consumerProperties` to override the default auto generated group
id.
-
-## Submitting a Supervisor Spec
-
-To use the Kafka indexing service, load the `druid-kafka-indexing-service`
extension on both the Overlord and the MiddleManagers. Druid starts a
supervisor for a dataSource when you submit a supervisor spec. You can use the
following endpoint:
-
-`http://<OVERLORD_IP>:<OVERLORD_PORT>/druid/indexer/v1/supervisor`
-
-For example:
-
-```
-curl -X POST -H 'Content-Type: application/json' -d @supervisor-spec.json
http://localhost:8090/druid/indexer/v1/supervisor
-```
-
-Where the file `supervisor-spec.json` contains a Kafka supervisor spec:
-
-```json
-{
- "type": "kafka",
- "spec": {
- "dataSchema": {
- "dataSource": "metrics-kafka",
- "timestampSpec": {
- "column": "timestamp",
- "format": "auto"
- },
- "dimensionsSpec": {
- "dimensions": [],
- "dimensionExclusions": [
- "timestamp",
- "value"
- ]
- },
- "metricsSpec": [
- {
- "name": "count",
- "type": "count"
- },
- {
- "name": "value_sum",
- "fieldName": "value",
- "type": "doubleSum"
- },
- {
- "name": "value_min",
- "fieldName": "value",
- "type": "doubleMin"
- },
- {
- "name": "value_max",
- "fieldName": "value",
- "type": "doubleMax"
- }
- ],
- "granularitySpec": {
- "type": "uniform",
- "segmentGranularity": "HOUR",
- "queryGranularity": "NONE"
- }
- },
- "ioConfig": {
- "topic": "metrics",
- "inputFormat": {
- "type": "json"
- },
- "consumerProperties": {
- "bootstrap.servers": "localhost:9092"
- },
- "taskCount": 1,
- "replicas": 1,
- "taskDuration": "PT1H"
- },
- "tuningConfig": {
- "type": "kafka",
- "maxRowsPerSegment": 5000000
- }
- }
-}
-```
-
-## Supervisor Configuration
+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|
|--------|-----------|---------|
@@ -129,7 +33,7 @@ Where the file `supervisor-spec.json` contains a Kafka
supervisor spec:
|`ioConfig`|A `KafkaSupervisorIOConfig` object to define the Kafka connection
and I/O-related settings for the supervisor and indexing task. See
[KafkaSupervisorIOConfig](#kafkasupervisorioconfig).|yes|
|`tuningConfig`|A KafkaSupervisorTuningConfig object to define
performance-related settings for the supervisor and indexing tasks. See
[KafkaSupervisorTuningConfig](#kafkasupervisortuningconfig).|no|
-### KafkaSupervisorIOConfig
+## KafkaSupervisorIOConfig
|Field|Type|Description|Required|
|-----|----|-----------|--------|
@@ -138,18 +42,18 @@ Where the file `supervisor-spec.json` contains a Kafka
supervisor spec:
|`consumerProperties`|Map<String, Object>|A map of properties to pass to the
Kafka consumer. See [More on consumer
properties](#more-on-consumerproperties).|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](#capacity-planning) for more details. When
`taskCount > {numKafkaPartitions}`, the actual number of reading tasks is less
than the `taskCount` value.|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](./kafka-supervisor-operations.md#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)|
+|`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 [...]
|`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 an [...]
|`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 earlyMessageReject [...]
|`autoScalerConfig`|Object|Defines auto scaling behavior for Kafka ingest
tasks. See [Tasks Autoscaler Properties](#task-autoscaler-properties).|no
(default == null)|
-#### Task Autoscaler Properties
+## Task Autoscaler Properties
> Note that Task AutoScaler is currently designated as experimental.
@@ -161,7 +65,7 @@ Where the file `supervisor-spec.json` contains a Kafka
supervisor spec:
| `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](#lag-based-autoscaler-strategy-related-properties) for details.| no
(default == `lagBased`) |
-##### Lag Based AutoScaler Strategy Related Properties
+## Lag Based AutoScaler Strategy Related Properties
| Property | Description | Required |
| ------------- | ------------- | ------------- |
| `lagCollectionIntervalMillis` | Period of lag points collection. | no
(default == 30000) |
@@ -219,7 +123,7 @@ The following example demonstrates supervisor spec with
`lagBased` autoScaler en
}
```
-#### More on consumerProperties
+## 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`.
@@ -239,7 +143,7 @@ export SSL_TRUSTSTORE_PASSWORD=mysecrettruststorepassword
"druid.dynamic.config.provider": {
"type": "environment",
"variables": {
- "sasl.jaas.config": "KAFKA_JAAS_CONFIG"
+ "sasl.jaas.config": "KAFKA_JAAS_CONFIG",
"ssl.key.password": "SSL_KEY_PASSWORD",
"ssl.keystore.password": "SSL_KEYSTORE_PASSWORD",
"ssl.truststore.password": "SSL_TRUSTSTORE_PASSWORD"
@@ -251,7 +155,7 @@ Verify that you've changed the values for all
configurations to match your own e
Note: You can provide SSL connections with [Password
Provider](../../operations/password-provider.md) interface to define the
`keystore`, `truststore`, and `key`, but this feature is deprecated.
-#### Specifying data format
+## Specifying data format
Kafka indexing service supports both
[`inputFormat`](../../ingestion/data-formats.md#input-format) and
[`parser`](../../ingestion/data-formats.md#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`.
@@ -268,24 +172,24 @@ For more information, see [Data
formats](../../ingestion/data-formats.md). You c
<a name="tuningconfig"></a>
-### KafkaSupervisorTuningConfig
+## KafkaSupervisorTuningConfig
-The tuningConfig is optional and default parameters will be used if no
tuningConfig is specified.
+The `tuningConfig` is optional and default parameters will be used if no
`tuningConfig` is specified.
| Field | Type | Description
[...]
|-----------------------------------|----------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
[...]
| `type` | String | The indexing task type,
this should always be `kafka`.
[...]
-| `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 [...]
-| `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).
[...]
+| `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 [...]
+| `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`).
[...]
| `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.
[...]
| `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.
[...]
| `intermediatePersistPeriod` | ISO8601 Period | The period that
determines the rate at which intermediate persists occur.
[...]
-| `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).
[...]
+| `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`).
[...]
| `indexSpec` | Object | Tune how data is
indexed. See [IndexSpec](#indexspec) for more information.
[...]
-| `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](#indexspec) for possib [...]
+| `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](#indexspec) for possib [...]
| `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. [...]
| `handoffConditionTimeout` | Long | Milliseconds to wait
for segment handoff. It must be >= 0, where 0 means to wait forever.
[...]
-| `resetOffsetAutomatically` | Boolean | Controls behavior when
Druid needs to read Kafka messages that are no longer available (i.e. when
OffsetOutOfRangeException is encountered).<br/><br/>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](../../operations/api-reference.md#supervisors). This mode is useful f [...]
+| `resetOffsetAutomatically` | Boolean | Controls behavior when
Druid needs to read Kafka messages that are no longer available (i.e. when
`OffsetOutOfRangeException` is encountered).<br/><br/>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](../../operations/api-reference.md#supervisors). This mode is useful [...]
| `workerThreads` | Integer | The number of threads
that the supervisor uses to handle requests/responses for worker tasks, along
with any other internal asynchronous operation.
[...]
| `chatThreads` | Integer | The number of threads
that will be used for communicating with indexing tasks.
[...]
| `chatRetries` | Integer | The number of times
HTTP requests to indexing tasks will be retried before considering tasks
unresponsive.
[...]
@@ -296,7 +200,7 @@ The tuningConfig is optional and default parameters will be
used if no tuningCon
| `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.
[...]
| `logParseExceptions` | Boolean | If true, log an error
message when a parsing exception occurs, containing information about the row
where the error occurred.
[...]
| `maxParseExceptions` | Integer | The maximum number of
parse exceptions that can occur before the task halts ingestion and fails.
Overridden if `reportParseExceptions` is set.
[...]
-| `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](../../ingestion/tasks.md#reports). Overridden if
`reportParseExceptions` is set.
[...]
+| `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](../../ingestion/tasks.md#reports). Overridden if
`reportParseExceptions` is set.
[...]
#### IndexSpec
@@ -327,195 +231,3 @@ For Concise bitmaps:
|Field|Type|Description|Required|
|-----|----|-----------|--------|
|`type`|String|See [Additional Peon Configuration:
SegmentWriteOutMediumFactory](../../configuration/index.md#segmentwriteoutmediumfactory)
for explanation and available options.|yes|
-
-## Operations
-
-This section gives descriptions of how some supervisor APIs work specifically
in Kafka Indexing Service.
-For all supervisor APIs, please check [Supervisor
APIs](../../operations/api-reference.md#supervisors).
-
-### Getting Supervisor Status Report
-
-`GET /druid/indexer/v1/supervisor/<supervisorId>/status` returns a snapshot
report of the current state of the tasks managed by the given supervisor. This
includes the latest
-offsets as reported by Kafka, the consumer lag per partition, as well as the
aggregate lag of all partitions. The
-consumer lag per partition may be reported as negative values if the
supervisor has not received a recent latest offset
-response from Kafka. The aggregate lag value will always be >= 0.
-
-The status report also contains the supervisor's state and a list of recently
thrown exceptions (reported as
-`recentErrors`, whose max size can be controlled using the
`druid.supervisor.maxStoredExceptionEvents` configuration).
-There are two fields related to the supervisor's state - `state` and
`detailedState`. The `state` field will always be
-one of a small number of generic states that are applicable to any type of
supervisor, while the `detailedState` field
-will contain a more descriptive, implementation-specific state that may
provide more insight into the supervisor's
-activities than the generic `state` field.
-
-The list of possible `state` values are: [`PENDING`, `RUNNING`, `SUSPENDED`,
`STOPPING`, `UNHEALTHY_SUPERVISOR`, `UNHEALTHY_TASKS`]
-
-The list of `detailedState` values and their corresponding `state` mapping is
as follows:
-
-|Detailed State|Corresponding State|Description|
-|--------------|-------------------|-----------|
-|UNHEALTHY_SUPERVISOR|UNHEALTHY_SUPERVISOR|The supervisor has encountered
errors on the past `druid.supervisor.unhealthinessThreshold` iterations|
-|UNHEALTHY_TASKS|UNHEALTHY_TASKS|The last
`druid.supervisor.taskUnhealthinessThreshold` tasks have all failed|
-|UNABLE_TO_CONNECT_TO_STREAM|UNHEALTHY_SUPERVISOR|The supervisor is
encountering connectivity issues with Kafka and has not successfully connected
in the past|
-|LOST_CONTACT_WITH_STREAM|UNHEALTHY_SUPERVISOR|The supervisor is encountering
connectivity issues with Kafka but has successfully connected in the past|
-|PENDING (first iteration only)|PENDING|The supervisor has been initialized
and hasn't started connecting to the stream|
-|CONNECTING_TO_STREAM (first iteration only)|RUNNING|The supervisor is trying
to connect to the stream and update partition data|
-|DISCOVERING_INITIAL_TASKS (first iteration only)|RUNNING|The supervisor is
discovering already-running tasks|
-|CREATING_TASKS (first iteration only)|RUNNING|The supervisor is creating
tasks and discovering state|
-|RUNNING|RUNNING|The supervisor has started tasks and is waiting for
taskDuration to elapse|
-|SUSPENDED|SUSPENDED|The supervisor has been suspended|
-|STOPPING|STOPPING|The supervisor is stopping|
-
-On each iteration of the supervisor's run loop, the supervisor completes the
following tasks in sequence:
- 1) Fetch the list of partitions from Kafka and determine the starting offset
for each partition (either based on the
- last processed offset if continuing, or starting from the beginning or
ending of the stream if this is a new topic).
- 2) Discover any running indexing tasks that are writing to the supervisor's
datasource and adopt them if they match
- the supervisor's configuration, else signal them to stop.
- 3) Send a status request to each supervised task to update our view of the
state of the tasks under our supervision.
- 4) Handle tasks that have exceeded `taskDuration` and should transition from
the reading to publishing state.
- 5) Handle tasks that have finished publishing and signal redundant replica
tasks to stop.
- 6) Handle tasks that have failed and clean up the supervisor's internal
state.
- 7) Compare the list of healthy tasks to the requested `taskCount` and
`replicas` configurations and create additional tasks if required.
-
-The `detailedState` field will show additional values (those marked with
"first iteration only") the first time the
-supervisor executes this run loop after startup or after resuming from a
suspension. This is intended to surface
-initialization-type issues, where the supervisor is unable to reach a stable
state (perhaps because it can't connect to
-Kafka, it can't read from the Kafka topic, or it can't communicate with
existing tasks). Once the supervisor is stable -
-that is, once it has completed a full execution without encountering any
issues - `detailedState` will show a `RUNNING`
-state until it is stopped, suspended, or hits a task failure threshold and
transitions to an unhealthy state.
-
-### Getting Supervisor Ingestion Stats Report
-
-`GET /druid/indexer/v1/supervisor/<supervisorId>/stats` returns a snapshot of
the current ingestion row counters for each task being managed by the
supervisor, along with moving averages for the row counters.
-
-See [Task Reports: Row Stats](../../ingestion/tasks.md#row-stats) for more
information.
-
-### Supervisor Health Check
-
-`GET /druid/indexer/v1/supervisor/<supervisorId>/health` returns `200 OK` if
the supervisor is healthy and
-`503 Service Unavailable` if it is unhealthy. Healthiness is determined by the
supervisor's `state` (as returned by the
-`/status` endpoint) and the `druid.supervisor.*` Overlord configuration
thresholds.
-
-### Updating Existing Supervisors
-
-`POST /druid/indexer/v1/supervisor` can be used to update existing supervisor
spec.
-Calling this endpoint when there is already an existing supervisor for the
same dataSource will cause:
-
-- The running supervisor to signal its managed tasks to stop reading and begin
publishing.
-- The running supervisor to exit.
-- A new supervisor to be created using the configuration provided in the
request body. This supervisor will retain the
-existing publishing tasks and will create new tasks starting at the offsets
the publishing tasks ended on.
-
-Seamless schema migrations can thus be achieved by simply submitting the new
schema using this endpoint.
-
-### Suspending and Resuming Supervisors
-
-You can suspend and resume a supervisor using `POST
/druid/indexer/v1/supervisor/<supervisorId>/suspend` and `POST
/druid/indexer/v1/supervisor/<supervisorId>/resume`, respectively.
-
-Note that the supervisor itself will still be operating and emitting logs and
metrics,
-it will just ensure that no indexing tasks are running until the supervisor is
resumed.
-
-### Resetting Supervisors
-
-The `POST /druid/indexer/v1/supervisor/<supervisorId>/reset` operation clears
stored
-offsets, causing the supervisor to start reading offsets from either the
earliest or latest
-offsets in Kafka (depending on the value of `useEarliestOffset`). After
clearing stored
-offsets, the supervisor kills and recreates any active tasks, so that tasks
begin reading
-from valid offsets.
-
-Use care when using this operation! Resetting the supervisor may cause Kafka
messages
-to be skipped or read twice, resulting in missing or duplicate data.
-
-The reason for using this operation is to recover from a state in which the
supervisor
-ceases operating due to missing offsets. The indexing service keeps track of
the latest
-persisted Kafka offsets in order to provide exactly-once ingestion guarantees
across
-tasks. Subsequent tasks must start reading from where the previous task
completed in
-order for the generated segments to be accepted. If the messages at the
expected
-starting offsets are no longer available in Kafka (typically because the
message retention
-period has elapsed or the topic was removed and re-created) the supervisor
will refuse
-to start and in flight tasks will fail. This operation enables you to recover
from this condition.
-
-Note that the supervisor must be running for this endpoint to be available.
-
-### Terminating Supervisors
-
-The `POST /druid/indexer/v1/supervisor/<supervisorId>/terminate` operation
terminates a supervisor and causes all
-associated indexing tasks managed by this supervisor to immediately stop and
begin
-publishing their segments. This supervisor will still exist in the metadata
store and it's history may be retrieved
-with the supervisor history API, but will not be listed in the 'get
supervisors' API response nor can it's configuration
-or status report be retrieved. The only way this supervisor can start again is
by submitting a functioning supervisor
-spec to the create API.
-
-### Capacity Planning
-
-Kafka indexing tasks run on MiddleManagers and are thus limited by the
resources available in the MiddleManager
-cluster. In particular, you should make sure that you have sufficient worker
capacity (configured using the
-`druid.worker.capacity` property) to handle the configuration in the
supervisor spec. Note that worker capacity is
-shared across all types of indexing tasks, so you should plan your worker
capacity to handle your total indexing load
-(e.g. batch processing, realtime tasks, merging tasks, etc.). If your workers
run out of capacity, Kafka indexing tasks
-will queue and wait for the next available worker. This may cause queries to
return partial results but will not result
-in data loss (assuming the tasks run before Kafka purges those offsets).
-
-A running task will normally be in one of two states: *reading* or
*publishing*. A task will remain in reading state for
-`taskDuration`, at which point it will transition to publishing state. A task
will remain in publishing state for as long
-as it takes to generate segments, push segments to deep storage, and have them
be loaded and served by a Historical process
-(or until `completionTimeout` elapses).
-
-The number of reading tasks is controlled by `replicas` and `taskCount`. In
general, there will be `replicas * taskCount`
-reading tasks, the exception being if taskCount > {numKafkaPartitions} in
which case {numKafkaPartitions} tasks will
-be used instead. When `taskDuration` elapses, these tasks will transition to
publishing state and `replicas * taskCount`
-new reading tasks will be created. Therefore to allow for reading tasks and
publishing tasks to run concurrently, there
-should be a minimum capacity of:
-
-```
-workerCapacity = 2 * replicas * taskCount
-```
-
-This value is for the ideal situation in which there is at most one set of
tasks publishing while another set is reading.
-In some circumstances, it is possible to have multiple sets of tasks
publishing simultaneously. This would happen if the
-time-to-publish (generate segment, push to deep storage, loaded on Historical)
> `taskDuration`. This is a valid
-scenario (correctness-wise) but requires additional worker capacity to
support. In general, it is a good idea to have
-`taskDuration` be large enough that the previous set of tasks finishes
publishing before the current set begins.
-
-### Supervisor Persistence
-
-When a supervisor spec is submitted via the `POST
/druid/indexer/v1/supervisor` endpoint, it is persisted in the
-configured metadata database. There can only be a single supervisor per
dataSource, and submitting a second spec for
-the same dataSource will overwrite the previous one.
-
-When an Overlord gains leadership, either by being started or as a result of
another Overlord failing, it will spawn
-a supervisor for each supervisor spec in the metadata database. The supervisor
will then discover running Kafka indexing
-tasks and will attempt to adopt them if they are compatible with the
supervisor's configuration. If they are not
-compatible because they have a different ingestion spec or partition
allocation, the tasks will be killed and the
-supervisor will create a new set of tasks. In this way, the supervisors are
persistent across Overlord restarts and
-fail-overs.
-
-A supervisor is stopped via the `POST
/druid/indexer/v1/supervisor/<supervisorId>/terminate` endpoint. This places a
-tombstone marker in the database (to prevent the supervisor from being
reloaded on a restart) and then gracefully
-shuts down the currently running supervisor. When a supervisor is shut down in
this way, it will instruct its
-managed tasks to stop reading and begin publishing their segments immediately.
The call to the shutdown endpoint will
-return after all tasks have been signaled to stop but before the tasks finish
publishing their segments.
-
-### Schema/Configuration Changes
-
-Schema and configuration changes are handled by submitting the new supervisor
spec via the same
-`POST /druid/indexer/v1/supervisor` endpoint used to initially create the
supervisor. The Overlord will initiate a
-graceful shutdown of the existing supervisor which will cause the tasks being
managed by that supervisor to stop reading
-and begin publishing their segments. A new supervisor will then be started
which will create a new set of tasks that
-will start reading from the offsets where the previous now-publishing tasks
left off, but using the updated schema.
-In this way, configuration changes can be applied without requiring any pause
in ingestion.
-
-### Deployment Notes on Kafka partitions and Druid segments
-
-Druid assigns each Kafka indexing task Kafka partitions. A task writes the
events it consumes from Kafka into a single segment for the segment granularity
interval until it reaches one of the following: `maxRowsPerSegment`,
`maxTotalRows` or `intermediateHandoffPeriod` limit. At this point, the task
creates a new partition for this segment granularity to contain subsequent
events.
-
-The Kafka Indexing Task also does incremental hand-offs. Therefore segments
become available as they are ready and you do not have to wait for all segments
until the end of the task duration. When the task reaches one of
`maxRowsPerSegment`, `maxTotalRows`, or `intermediateHandoffPeriod`, it hands
off all the segments and creates a new new set of segments will be created for
further events. This allows the task to run for longer durations without
accumulating old segments locally on Mi [...]
-
-The Kafka Indexing Service may still produce some small segments. For example,
consider the following scenario:
-- Task duration is 4 hours
-- Segment granularity is set to an HOUR
-- The supervisor was started at 9:10
-After 4 hours at 13:10, Druid starts a new set of tasks. The events for the
interval 13:00 - 14:00 may be split across existing tasks and the new set of
tasks which could result in small segments. To merge them together into new
segments of an ideal size (in the range of ~500-700 MB per segment), you can
schedule re-indexing tasks, optionally with a different segment granularity.
-
-For more detail, see [Segment size
optimization](../../operations/segment-optimization.md).
-There is also ongoing work to support automatic segment compaction of sharded
segments as well as compaction not requiring
-Hadoop (see [here](https://github.com/apache/druid/pull/5102)).
diff --git a/docs/ingestion/data-formats.md b/docs/ingestion/data-formats.md
index 19707b4..8f4b235 100644
--- a/docs/ingestion/data-formats.md
+++ b/docs/ingestion/data-formats.md
@@ -164,8 +164,8 @@ Configure the Kafka `inputFormat` to load complete kafka
records including heade
| timestampColumnName | String | Name of the column for the kafka record's
timestamp.| no (default = "kafka.timestamp") |
| keyColumnName | String | Name of the column for the kafka record's key.| no
(default = "kafka.key") |
| headerFormat | Object | `headerFormat` specifies how to parse the Kafka
headers. Supports String types. Because Kafka header values are bytes, the
parser decodes them as UTF-8 encoded strings. To change this behavior,
implement your own parser based on the encoding style. Change the 'encoding'
type in `KafkaStringHeaderFormat` to match your custom implementation. | no |
-| keyFormat | [InputFormat](#input-format) | Any existing `inputFormat` used
to parse the Kafka key. It only processes the first entry of the input format.
For details, see [Specifying data
format](../development/extensions-core/kafka-ingestion.md#specifying-data-format).
| no |
-| valueFormat | [InputFormat](#input-format) | `valueFormat` can be any
existing `inputFormat` to parse the Kafka value payload. For details about
specifying the input format, see [Specifying data
format](../development/extensions-core/kafka-ingestion.md#specifying-data-format).
| yes |
+| keyFormat | [InputFormat](#input-format) | Any existing `inputFormat` used
to parse the Kafka key. It only processes the first entry of the input format.
For details, see [Specifying data
format](../development/extensions-core/kafka-supervisor-reference.md#specifying-data-format).
| no |
+| valueFormat | [InputFormat](#input-format) | `valueFormat` can be any
existing `inputFormat` to parse the Kafka value payload. For details about
specifying the input format, see [Specifying data
format](../development/extensions-core/kafka-supervisor-reference.md#specifying-data-format).
| yes |
For example:
```
diff --git a/docs/ingestion/ingestion-spec.md b/docs/ingestion/ingestion-spec.md
index d2b4a5b..9c7315b 100644
--- a/docs/ingestion/ingestion-spec.md
+++ b/docs/ingestion/ingestion-spec.md
@@ -466,7 +466,7 @@ is:
|maxBytesInMemory|The maximum aggregate size of records, in bytes, to store in
the JVM heap before persisting. This is based on a rough estimate of memory
usage. Ingested records will be persisted to disk when either `maxRowsInMemory`
or `maxBytesInMemory` are reached (whichever happens first). `maxBytesInMemory`
also includes heap usage of artifacts created from intermediary persists. This
means that after every persist, the amount of `maxBytesInMemory` until next
persist will decreases [...]
|skipBytesInMemoryOverheadCheck|The calculation of maxBytesInMemory takes into
account overhead objects created during ingestion and each intermediate
persist. Setting this to true can exclude the bytes of these overhead objects
from maxBytesInMemory check.|false|
|indexSpec|Tune how data is indexed. See below for more information.|See table
below|
-|Other properties|Each ingestion method has its own list of additional tuning
properties. See the documentation for each method for a full list: [Kafka
indexing
service](../development/extensions-core/kafka-ingestion.md#tuningconfig),
[Kinesis indexing
service](../development/extensions-core/kinesis-ingestion.md#tuningconfig),
[Native batch](native-batch.md#tuningconfig), and
[Hadoop-based](hadoop.md#tuningconfig).||
+|Other properties|Each ingestion method has its own list of additional tuning
properties. See the documentation for each method for a full list: [Kafka
indexing
service](../development/extensions-core/kafka-supervisor-reference.md#tuningconfig),
[Kinesis indexing
service](../development/extensions-core/kinesis-ingestion.md#tuningconfig),
[Native batch](native-batch.md#tuningconfig), and
[Hadoop-based](hadoop.md#tuningconfig).||
#### `indexSpec`
diff --git a/docs/operations/api-reference.md b/docs/operations/api-reference.md
index 7fcf988..e86a96a 100644
--- a/docs/operations/api-reference.md
+++ b/docs/operations/api-reference.md
@@ -659,7 +659,7 @@ Returns a list of objects of the currently active
supervisors.
|Field|Type|Description|
|---|---|---|
|`id`|String|supervisor unique identifier|
-|`state`|String|basic state of the supervisor. Available
states:`UNHEALTHY_SUPERVISOR`, `UNHEALTHY_TASKS`, `PENDING`, `RUNNING`,
`SUSPENDED`, `STOPPING`. Check [Kafka
Docs](../development/extensions-core/kafka-ingestion.md#operations) for
details.|
+|`state`|String|basic state of the supervisor. Available
states:`UNHEALTHY_SUPERVISOR`, `UNHEALTHY_TASKS`, `PENDING`, `RUNNING`,
`SUSPENDED`, `STOPPING`. Check [Kafka
Docs](../development/extensions-core/kafka-supervisor-operations.md) for
details.|
|`detailedState`|String|supervisor specific state. (See documentation of
specific supervisor for details), e.g.
[Kafka](../development/extensions-core/kafka-ingestion.md) or
[Kinesis](../development/extensions-core/kinesis-ingestion.md))|
|`healthy`|Boolean|true or false indicator of overall supervisor health|
|`spec`|SupervisorSpec|json specification of supervisor (See Supervisor
Configuration for details)|
@@ -671,7 +671,7 @@ Returns a list of objects of the currently active
supervisors and their current
|Field|Type|Description|
|---|---|---|
|`id`|String|supervisor unique identifier|
-|`state`|String|basic state of the supervisor. Available states:
`UNHEALTHY_SUPERVISOR`, `UNHEALTHY_TASKS`, `PENDING`, `RUNNING`, `SUSPENDED`,
`STOPPING`. Check [Kafka
Docs](../development/extensions-core/kafka-ingestion.md#operations) for
details.|
+|`state`|String|basic state of the supervisor. Available states:
`UNHEALTHY_SUPERVISOR`, `UNHEALTHY_TASKS`, `PENDING`, `RUNNING`, `SUSPENDED`,
`STOPPING`. Check [Kafka
Docs](../development/extensions-core/kafka-supervisor-operations.md) for
details.|
|`detailedState`|String|supervisor specific state. (See documentation of the
specific supervisor for details, e.g.
[Kafka](../development/extensions-core/kafka-ingestion.md) or
[Kinesis](../development/extensions-core/kinesis-ingestion.md))|
|`healthy`|Boolean|true or false indicator of overall supervisor health|
|`suspended`|Boolean|true or false indicator of whether the supervisor is in
suspended state|
diff --git a/docs/operations/dynamic-config-provider.md
b/docs/operations/dynamic-config-provider.md
index ead0323..a0413d8 100644
--- a/docs/operations/dynamic-config-provider.md
+++ b/docs/operations/dynamic-config-provider.md
@@ -62,8 +62,8 @@ When you define the consumer properties in the supervisor
spec, use the dynamic
...
"consumerProperties": {
"bootstrap.servers": "localhost:9092",
- "ssl.keystore.location": "/opt/kafka/config/kafka01.keystore.jks"
- "ssl.truststore.location": "/opt/kafka/config/kafka.truststore.jks"
+ "ssl.keystore.location": "/opt/kafka/config/kafka01.keystore.jks",
+ "ssl.truststore.location": "/opt/kafka/config/kafka.truststore.jks",
"druid.dynamic.config.provider": {
"type": "environment",
"variables": {
diff --git a/docs/querying/sql.md b/docs/querying/sql.md
index 8d658e4..35dfc35 100644
--- a/docs/querying/sql.md
+++ b/docs/querying/sql.md
@@ -1337,7 +1337,7 @@ The supervisors table provides information about
supervisors.
|Column|Type|Notes|
|------|-----|-----|
|supervisor_id|STRING|Supervisor task identifier|
-|state|STRING|Basic state of the supervisor. Available states:
`UNHEALTHY_SUPERVISOR`, `UNHEALTHY_TASKS`, `PENDING`, `RUNNING`, `SUSPENDED`,
`STOPPING`. Check [Kafka
Docs](../development/extensions-core/kafka-ingestion.md#operations) for
details.|
+|state|STRING|Basic state of the supervisor. Available states:
`UNHEALTHY_SUPERVISOR`, `UNHEALTHY_TASKS`, `PENDING`, `RUNNING`, `SUSPENDED`,
`STOPPING`. Check [Kafka
Docs](../development/extensions-core/kafka-supervisor-operations.md) for
details.|
|detailed_state|STRING|Supervisor specific state. (See documentation of the
specific supervisor for details, e.g.
[Kafka](../development/extensions-core/kafka-ingestion.md) or
[Kinesis](../development/extensions-core/kinesis-ingestion.md))|
|healthy|LONG|Boolean represented as long type where 1 = true, 0 = false. 1
indicates a healthy supervisor|
|type|STRING|Type of supervisor, e.g. `kafka`, `kinesis` or
`materialized_view`|
diff --git a/website/sidebars.json b/website/sidebars.json
index cc9f393..69d8ebf 100644
--- a/website/sidebars.json
+++ b/website/sidebars.json
@@ -44,6 +44,8 @@
"label": "Stream ingestion",
"ids": [
"development/extensions-core/kafka-ingestion",
+ "development/extensions-core/kafka-supervisor-reference",
+ "development/extensions-core/kafka-supervisor-operations",
"development/extensions-core/kinesis-ingestion",
"ingestion/standalone-realtime"
]
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