This is an automated email from the ASF dual-hosted git repository.
davidarthur pushed a commit to branch 4.2
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The following commit(s) were added to refs/heads/4.2 by this push:
new 280a2d2c39e MINOR: Use dynamic version linking for Javadoc and
generated static includes (#21275)
280a2d2c39e is described below
commit 280a2d2c39e925896a1bd4718352dbcbf172410c
Author: Harish Vishwanath <[email protected]>
AuthorDate: Fri Jan 9 12:44:59 2026 -0800
MINOR: Use dynamic version linking for Javadoc and generated static
includes (#21275)
Updates hard-coded version links in markdown to a variable.
Reviewers: Matthias J. Sax <[email protected]>
---
docs/apis/_index.md | 12 +--
docs/configuration/admin-configs.md | 2 +-
docs/configuration/broker-configs.md | 2 +-
docs/configuration/configuration-providers.md | 8 +-
docs/configuration/consumer-configs.md | 2 +-
docs/configuration/group-configs.md | 2 +-
docs/configuration/kafka-connect-configs.md | 6 +-
docs/configuration/kafka-streams-configs.md | 2 +-
docs/configuration/mirrormaker-configs.md | 8 +-
docs/configuration/producer-configs.md | 2 +-
docs/configuration/tiered-storage-configs.md | 4 +-
docs/configuration/topic-configs.md | 2 +-
docs/design/protocol.md | 8 +-
docs/getting-started/upgrade.md | 4 +-
docs/kafka-connect/user-guide.md | 4 +-
docs/operations/monitoring.md | 6 +-
docs/streams/developer-guide/app-reset-tool.md | 2 +-
docs/streams/developer-guide/config-streams.md | 30 ++++----
docs/streams/developer-guide/dsl-api.md | 90 +++++++++++-----------
.../streams/developer-guide/interactive-queries.md | 6 +-
docs/streams/developer-guide/processor-api.md | 26 +++----
21 files changed, 114 insertions(+), 114 deletions(-)
diff --git a/docs/apis/_index.md b/docs/apis/_index.md
index 062fce80757..cbddb641497 100644
--- a/docs/apis/_index.md
+++ b/docs/apis/_index.md
@@ -40,7 +40,7 @@ Kafka exposes all its functionality over a
language-independent protocol which h
The Producer API allows applications to send streams of data to topics in the
Kafka cluster.
-Examples of using the producer are shown in the
[javadocs](/42/javadoc/index.html?org/apache/kafka/clients/producer/KafkaProducer.html
"Kafka 4.2 Javadoc").
+Examples of using the producer are shown in the
[javadocs](/{version}/javadoc/index.html?org/apache/kafka/clients/producer/KafkaProducer.html
"Kafka 4.2 Javadoc").
To use the producer, add the following Maven dependency to your project:
@@ -55,7 +55,7 @@ To use the producer, add the following Maven dependency to
your project:
The Consumer API allows applications to read streams of data from topics in
the Kafka cluster.
-Examples of using the consumer are shown in the
[javadocs](/42/javadoc/index.html?org/apache/kafka/clients/consumer/KafkaConsumer.html
"Kafka 4.2 Javadoc").
+Examples of using the consumer are shown in the
[javadocs](/{version}/javadoc/index.html?org/apache/kafka/clients/consumer/KafkaConsumer.html
"Kafka 4.2 Javadoc").
To use the consumer, add the following Maven dependency to your project:
@@ -70,7 +70,7 @@ To use the consumer, add the following Maven dependency to
your project:
The Share Consumer API enables applications in a share group to cooperatively
consume and process data from Kafka topics.
-Examples of using the share consumer are shown in the
[javadocs](/42/javadoc/index.html?org/apache/kafka/clients/consumer/KafkaShareConsumer.html
"Kafka 4.2 Javadoc").
+Examples of using the share consumer are shown in the
[javadocs](/{version}/javadoc/index.html?org/apache/kafka/clients/consumer/KafkaShareConsumer.html
"Kafka 4.2 Javadoc").
To use the share consumer, add the following Maven dependency to your project:
@@ -85,7 +85,7 @@ To use the share consumer, add the following Maven dependency
to your project:
The [Streams](/42/documentation/streams) API allows transforming streams of
data from input topics to output topics.
-Examples of using this library are shown in the
[javadocs](/42/javadoc/index.html?org/apache/kafka/streams/KafkaStreams.html
"Kafka 4.2 Javadoc").
+Examples of using this library are shown in the
[javadocs](/{version}/javadoc/index.html?org/apache/kafka/streams/KafkaStreams.html
"Kafka 4.2 Javadoc").
Additional documentation on using the Streams API is available
[here](/42/documentation/streams).
@@ -115,7 +115,7 @@ The Connect API allows implementing connectors that
continually pull from some s
Many users of Connect won't need to use this API directly, though, they can
use pre-built connectors without needing to write any code. Additional
information on using Connect is available [here](/documentation.html#connect).
-Those who want to implement custom connectors can see the
[javadoc](/42/javadoc/index.html?org/apache/kafka/connect "Kafka 4.2 Javadoc").
+Those who want to implement custom connectors can see the
[javadoc](/{version}/javadoc/index.html?org/apache/kafka/connect "Kafka 4.2
Javadoc").
# Admin API
@@ -130,4 +130,4 @@ To use the Admin API, add the following Maven dependency to
your project:
<version>4.2.0</version>
</dependency>
-For more information about the Admin APIs, see the
[javadoc](/42/javadoc/index.html?org/apache/kafka/clients/admin/Admin.html
"Kafka 4.2 Javadoc").
+For more information about the Admin APIs, see the
[javadoc](/{version}/javadoc/index.html?org/apache/kafka/clients/admin/Admin.html
"Kafka 4.2 Javadoc").
diff --git a/docs/configuration/admin-configs.md
b/docs/configuration/admin-configs.md
index 6a377252b1a..8ab0d94de79 100644
--- a/docs/configuration/admin-configs.md
+++ b/docs/configuration/admin-configs.md
@@ -26,4 +26,4 @@ type: docs
-->
-Below is the Kafka Admin client library configuration. {{< include-html
file="/static/42/generated/admin_client_config.html" >}}
+Below is the Kafka Admin client library configuration. {{< include-html
file="/static/{version}/generated/admin_client_config.html" >}}
diff --git a/docs/configuration/broker-configs.md
b/docs/configuration/broker-configs.md
index bac5f3bbb3f..fa064d15402 100644
--- a/docs/configuration/broker-configs.md
+++ b/docs/configuration/broker-configs.md
@@ -34,7 +34,7 @@ The essential configurations are the following:
* `controller.quorum.bootstrap.servers`
* `controller.listener.names`
-Broker configurations and defaults are discussed in more detail below. {{<
include-html file="/static/42/generated/kafka_config.html" >}}
+Broker configurations and defaults are discussed in more detail below. {{<
include-html file="/static/{version}/generated/kafka_config.html" >}}
More details about broker configuration can be found in the scala class
`kafka.server.KafkaConfig`.
diff --git a/docs/configuration/configuration-providers.md
b/docs/configuration/configuration-providers.md
index 971f3945c6e..5a6eb24e6a7 100644
--- a/docs/configuration/configuration-providers.md
+++ b/docs/configuration/configuration-providers.md
@@ -30,11 +30,11 @@ Use configuration providers to load configuration data from
external sources. Th
You have the following options:
- * Use a custom provider by creating a class implementing the
[`ConfigProvider`](/42/javadoc/org/apache/kafka/common/config/provider/ConfigProvider.html)
interface and packaging it into a JAR file.
+ * Use a custom provider by creating a class implementing the
[`ConfigProvider`](/{version}/javadoc/org/apache/kafka/common/config/provider/ConfigProvider.html)
interface and packaging it into a JAR file.
* Use a built-in provider:
- *
[`DirectoryConfigProvider`](/42/javadoc/org/apache/kafka/common/config/provider/DirectoryConfigProvider.html)
- *
[`EnvVarConfigProvider`](/42/javadoc/org/apache/kafka/common/config/provider/EnvVarConfigProvider.html)
- *
[`FileConfigProvider`](/42/javadoc/org/apache/kafka/common/config/provider/FileConfigProvider.html)
+ *
[`DirectoryConfigProvider`](/{version}/javadoc/org/apache/kafka/common/config/provider/DirectoryConfigProvider.html)
+ *
[`EnvVarConfigProvider`](/{version}/javadoc/org/apache/kafka/common/config/provider/EnvVarConfigProvider.html)
+ *
[`FileConfigProvider`](/{version}/javadoc/org/apache/kafka/common/config/provider/FileConfigProvider.html)
diff --git a/docs/configuration/consumer-configs.md
b/docs/configuration/consumer-configs.md
index 46334915559..0d2db61930e 100644
--- a/docs/configuration/consumer-configs.md
+++ b/docs/configuration/consumer-configs.md
@@ -26,4 +26,4 @@ type: docs
-->
-Below is the consumer and share consumer configuration: {{< include-html
file="/static/42/generated/consumer_config.html" >}}
+Below is the consumer and share consumer configuration: {{< include-html
file="/static/{version}/generated/consumer_config.html" >}}
diff --git a/docs/configuration/group-configs.md
b/docs/configuration/group-configs.md
index bb4db28e43b..ac9cd65b28c 100644
--- a/docs/configuration/group-configs.md
+++ b/docs/configuration/group-configs.md
@@ -26,4 +26,4 @@ type: docs
-->
-Below is the group configuration: {{< include-html
file="/static/42/generated/group_config.html" >}}
+Below is the group configuration: {{< include-html
file="/static/{version}/generated/group_config.html" >}}
diff --git a/docs/configuration/kafka-connect-configs.md
b/docs/configuration/kafka-connect-configs.md
index c68a0b8ace9..8d56f70f5ce 100644
--- a/docs/configuration/kafka-connect-configs.md
+++ b/docs/configuration/kafka-connect-configs.md
@@ -26,12 +26,12 @@ type: docs
-->
-Below is the Kafka Connect framework configuration. {{< include-html
file="/static/42/generated/connect_config.html" >}}
+Below is the Kafka Connect framework configuration. {{< include-html
file="/static/{version}/generated/connect_config.html" >}}
## Source Connector Configs
-Below is the source connector configuration. {{< include-html
file="/static/42/generated/source_connector_config.html" >}}
+Below is the source connector configuration. {{< include-html
file="/static/{version}/generated/source_connector_config.html" >}}
## Sink Connector Configs
-Below is the sink connector configuration. {{< include-html
file="/static/42/generated/sink_connector_config.html" >}}
+Below is the sink connector configuration. {{< include-html
file="/static/{version}/generated/sink_connector_config.html" >}}
diff --git a/docs/configuration/kafka-streams-configs.md
b/docs/configuration/kafka-streams-configs.md
index 5522b7a0244..6c0b656bd71 100644
--- a/docs/configuration/kafka-streams-configs.md
+++ b/docs/configuration/kafka-streams-configs.md
@@ -26,4 +26,4 @@ type: docs
-->
-Below is the Kafka Streams client library configuration. {{< include-html
file="/static/42/generated/streams_config.html" >}}
+Below is the Kafka Streams client library configuration. {{< include-html
file="/static/{version}/generated/streams_config.html" >}}
diff --git a/docs/configuration/mirrormaker-configs.md
b/docs/configuration/mirrormaker-configs.md
index c2e64fa89b5..ac8c82f91bc 100644
--- a/docs/configuration/mirrormaker-configs.md
+++ b/docs/configuration/mirrormaker-configs.md
@@ -30,16 +30,16 @@ Below is the configuration of the connectors that make up
MirrorMaker 2.
## MirrorMaker Common Configs
-Below is the common configuration that applies to all three connectors. {{<
include-html file="/static/42/generated/mirror_connector_config.html" >}}
+Below is the common configuration that applies to all three connectors. {{<
include-html file="/static/{version}/generated/mirror_connector_config.html"
>}}
## MirrorMaker Source Configs
-Below is the configuration of MirrorMaker 2 source connector for replicating
topics. {{< include-html file="/static/42/generated/mirror_source_config.html"
>}}
+Below is the configuration of MirrorMaker 2 source connector for replicating
topics. {{< include-html
file="/static/{version}/generated/mirror_source_config.html" >}}
## MirrorMaker Checkpoint Configs
-Below is the configuration of MirrorMaker 2 checkpoint connector for emitting
consumer offset checkpoints. {{< include-html
file="/static/42/generated/mirror_checkpoint_config.html" >}}
+Below is the configuration of MirrorMaker 2 checkpoint connector for emitting
consumer offset checkpoints. {{< include-html
file="/static/{version}/generated/mirror_checkpoint_config.html" >}}
## MirrorMaker HeartBeat Configs
-Below is the configuration of MirrorMaker 2 heartbeat connector for checking
connectivity between connectors and clusters. {{< include-html
file="/static/42/generated/mirror_heartbeat_config.html" >}}
+Below is the configuration of MirrorMaker 2 heartbeat connector for checking
connectivity between connectors and clusters. {{< include-html
file="/static/{version}/generated/mirror_heartbeat_config.html" >}}
diff --git a/docs/configuration/producer-configs.md
b/docs/configuration/producer-configs.md
index eafba0c9b6d..589c54d3576 100644
--- a/docs/configuration/producer-configs.md
+++ b/docs/configuration/producer-configs.md
@@ -26,4 +26,4 @@ type: docs
-->
-Below is the producer configuration: {{< include-html
file="/static/42/generated/producer_config.html" >}}
+Below is the producer configuration: {{< include-html
file="/static/{version}/generated/producer_config.html" >}}
diff --git a/docs/configuration/tiered-storage-configs.md
b/docs/configuration/tiered-storage-configs.md
index 60c735a2e68..ad1e6f43d06 100644
--- a/docs/configuration/tiered-storage-configs.md
+++ b/docs/configuration/tiered-storage-configs.md
@@ -26,7 +26,7 @@ type: docs
-->
-Below is the Tiered Storage configuration. {{< include-html
file="/static/42/generated/remote_log_manager_config.html" >}}
+Below is the Tiered Storage configuration. {{< include-html
file="/static/{version}/generated/remote_log_manager_config.html" >}}
## RLMM Configs
@@ -34,7 +34,7 @@ Below is the configuration for
`TopicBasedRemoteLogMetadataManager`, which is th
All configurations here should start with the prefix defined by
`remote.log.metadata.manager.impl.prefix`, for example,
`rlmm.config.remote.log.metadata.consume.wait.ms`.
-{{< include-html
file="/static/42/generated/remote_log_metadata_manager_config.html" >}}
+{{< include-html
file="/static/{version}/generated/remote_log_metadata_manager_config.html" >}}
The implementation of `TopicBasedRemoteLogMetadataManager` needs to create
admin, producer, and consumer clients for the internal topic
`__remote_log_metadata`.
diff --git a/docs/configuration/topic-configs.md
b/docs/configuration/topic-configs.md
index 3e77b39ba0f..d95936c0023 100644
--- a/docs/configuration/topic-configs.md
+++ b/docs/configuration/topic-configs.md
@@ -49,4 +49,4 @@ To remove an override you can do
$ bin/kafka-configs.sh --bootstrap-server localhost:9092 --entity-type
topics --entity-name my-topic
--alter --delete-config max.message.bytes
-Below is the topic configuration. The server's default configuration for this
property is given under the Server Default Property heading. A given server
default config value only applies to a topic if it does not have an explicit
topic config override. {{< include-html
file="/static/42/generated/topic_config.html" >}}
+Below is the topic configuration. The server's default configuration for this
property is given under the Server Default Property heading. A given server
default config value only applies to a topic if it does not have an explicit
topic config override. {{< include-html
file="/static/{version}/generated/topic_config.html" >}}
diff --git a/docs/design/protocol.md b/docs/design/protocol.md
index d2953990096..31fa16b2a66 100644
--- a/docs/design/protocol.md
+++ b/docs/design/protocol.md
@@ -136,7 +136,7 @@ For interoperability with 0.9.0.x clients, the first packet
received by the serv
The protocol is built out of the following primitive types.
-{{< include-html file="/static/42/generated/protocol_types.html" >}}
+{{< include-html file="/static/{version}/generated/protocol_types.html" >}}
### Notes on reading the request format grammars
@@ -184,13 +184,13 @@ A description of the record batch format can be found
[here](/documentation/#rec
We use numeric codes to indicate what problem occurred on the server. These
can be translated by the client into exceptions or whatever the appropriate
error handling mechanism in the client language. Here is a table of the error
codes currently in use:
-{{< include-html file="/static/42/generated/protocol_errors.html" >}}
+{{< include-html file="/static/{version}/generated/protocol_errors.html" >}}
### Api Keys
The following are the numeric codes that the stable ApiKey in the request can
take for each of the below request types.
-{{< include-html file="/static/42/generated/protocol_api_keys.html" >}}
+{{< include-html file="/static/{version}/generated/protocol_api_keys.html" >}}
## The Messages
@@ -204,7 +204,7 @@ The message consists of the header and body:
`RequestOrResponseHeader` is the versioned request or response header. `Body`
is the message-specific body.
-{{< include-html file="/static/42/generated/protocol_messages.html" >}}
+{{< include-html file="/static/{version}/generated/protocol_messages.html" >}}
## Some Common Philosophical Questions
diff --git a/docs/getting-started/upgrade.md b/docs/getting-started/upgrade.md
index 34d516d462b..5b76282cc1d 100644
--- a/docs/getting-started/upgrade.md
+++ b/docs/getting-started/upgrade.md
@@ -185,14 +185,14 @@ Note: Apache Kafka 4.0 only supports KRaft mode -
ZooKeeper mode has been remove
* The `topics.blacklist` was removed from the
`org.apache.kafka.connect.mirror.MirrorSourceConfig` Please use
`topics.exclude` instead.
* The `groups.blacklist` was removed from the
`org.apache.kafka.connect.mirror.MirrorSourceConfig` Please use
`groups.exclude` instead.
* **Tools**
- * The `kafka.common.MessageReader` class was removed. Please use the
[`org.apache.kafka.tools.api.RecordReader`](/42/javadoc/org/apache/kafka/tools/api/RecordReader.html)
interface to build custom readers for the `kafka-console-producer` tool.
+ * The `kafka.common.MessageReader` class was removed. Please use the
[`org.apache.kafka.tools.api.RecordReader`](/{version}/javadoc/org/apache/kafka/tools/api/RecordReader.html)
interface to build custom readers for the `kafka-console-producer` tool.
* The `kafka.tools.DefaultMessageFormatter` class was removed. Please
use the `org.apache.kafka.tools.consumer.DefaultMessageFormatter` class
instead.
* The `kafka.tools.LoggingMessageFormatter` class was removed. Please
use the `org.apache.kafka.tools.consumer.LoggingMessageFormatter` class
instead.
* The `kafka.tools.NoOpMessageFormatter` class was removed. Please use
the `org.apache.kafka.tools.consumer.NoOpMessageFormatter` class instead.
* The `--whitelist` option was removed from the `kafka-console-consumer`
command line tool. Please use `--include` instead.
* Redirections from the old tools packages have been removed:
`kafka.admin.FeatureCommand`, `kafka.tools.ClusterTool`,
`kafka.tools.EndToEndLatency`, `kafka.tools.StateChangeLogMerger`,
`kafka.tools.StreamsResetter`, `kafka.tools.JmxTool`.
* The `--authorizer`, `--authorizer-properties`, and
`--zk-tls-config-file` options were removed from the `kafka-acls` command line
tool. Please use `--bootstrap-server` or `--bootstrap-controller` instead.
- * The `kafka.serializer.Decoder` trait was removed, please use the
[`org.apache.kafka.tools.api.Decoder`](/42/javadoc/org/apache/kafka/tools/api/Decoder.html)
interface to build custom decoders for the `kafka-dump-log` tool.
+ * The `kafka.serializer.Decoder` trait was removed, please use the
[`org.apache.kafka.tools.api.Decoder`](/{version}/javadoc/org/apache/kafka/tools/api/Decoder.html)
interface to build custom decoders for the `kafka-dump-log` tool.
* The `kafka.coordinator.group.OffsetsMessageFormatter` class was
removed. Please use the
`org.apache.kafka.tools.consumer.OffsetsMessageFormatter` class instead.
* The `kafka.coordinator.group.GroupMetadataMessageFormatter` class was
removed. Please use the
`org.apache.kafka.tools.consumer.GroupMetadataMessageFormatter` class instead.
* The `kafka.coordinator.transaction.TransactionLogMessageFormatter`
class was removed. Please use the
`org.apache.kafka.tools.consumer.TransactionLogMessageFormatter` class instead.
diff --git a/docs/kafka-connect/user-guide.md b/docs/kafka-connect/user-guide.md
index 421c8a63bb7..9a8f0e3afe4 100644
--- a/docs/kafka-connect/user-guide.md
+++ b/docs/kafka-connect/user-guide.md
@@ -186,7 +186,7 @@ Several widely-applicable data and routing transformations
are included with Kaf
Details on how to configure each transformation are listed below:
-{{< include-html file="/static/42/generated/connect_transforms.html" >}}
+{{< include-html file="/static/{version}/generated/connect_transforms.html"
>}}
### Predicates
@@ -249,7 +249,7 @@ Kafka Connect includes the following predicates:
Details on how to configure each predicate are listed below:
-{{< include-html file="/static/42/generated/connect_predicates.html" >}}
+{{< include-html file="/static/{version}/generated/connect_predicates.html"
>}}
## REST API
diff --git a/docs/operations/monitoring.md b/docs/operations/monitoring.md
index 715e50e7a5c..0b7ceab67ef 100644
--- a/docs/operations/monitoring.md
+++ b/docs/operations/monitoring.md
@@ -3286,7 +3286,7 @@ kafka.producer:type=producer-metrics,client-id=([-.\w]+)
### Producer Sender Metrics
-{{< include-html file="/static/42/generated/producer_metrics.html" >}}
+{{< include-html file="/static/{version}/generated/producer_metrics.html" >}}
## Consumer monitoring
@@ -3806,11 +3806,11 @@
kafka.consumer:type=consumer-coordinator-metrics,client-id=([-.\w]+)
### Consumer Fetch Metrics
-{{< include-html file="/static/42/generated/consumer_metrics.html" >}}
+{{< include-html file="/static/{version}/generated/consumer_metrics.html" >}}
## Connect Monitoring
-A Connect worker process contains all the producer and consumer metrics as
well as metrics specific to Connect. The worker process itself has a number of
metrics, while each connector and task have additional metrics. {{<
include-html file="/static/42/generated/connect_metrics.html" >}}
+A Connect worker process contains all the producer and consumer metrics as
well as metrics specific to Connect. The worker process itself has a number of
metrics, while each connector and task have additional metrics. {{<
include-html file="/static/{version}/generated/connect_metrics.html" >}}
## Streams Monitoring
diff --git a/docs/streams/developer-guide/app-reset-tool.md
b/docs/streams/developer-guide/app-reset-tool.md
index a16d64090ce..c2d3b26d531 100644
--- a/docs/streams/developer-guide/app-reset-tool.md
+++ b/docs/streams/developer-guide/app-reset-tool.md
@@ -132,7 +132,7 @@ All the other parameters can be combined as needed. For
example, if you want to
For a complete application reset, you must delete the application's local
state directory on any machines where the application instance was run. You
must do this before restarting an application instance on the same machine. You
can use either of these methods:
* The API method `KafkaStreams#cleanUp()` in your application code.
- * Manually delete the corresponding local state directory (default location:
`/${java.io.tmpdir}/kafka-streams/<application.id>`). For more information, see
[Streams](/42/javadoc/org/apache/kafka/streams/StreamsConfig.html#STATE_DIR_CONFIG)
javadocs.
+ * Manually delete the corresponding local state directory (default location:
`/${java.io.tmpdir}/kafka-streams/<application.id>`). For more information, see
[Streams](/{version}/javadoc/org/apache/kafka/streams/StreamsConfig.html#STATE_DIR_CONFIG)
javadocs.
diff --git a/docs/streams/developer-guide/config-streams.md
b/docs/streams/developer-guide/config-streams.md
index b177edcac68..8799111858a 100644
--- a/docs/streams/developer-guide/config-streams.md
+++ b/docs/streams/developer-guide/config-streams.md
@@ -47,7 +47,7 @@ Kafka and Kafka Streams configuration options must be
configured before using St
# Configuration parameter reference
-This section contains the most common Streams configuration parameters. For a
full reference, see the
[Streams](/42/javadoc/org/apache/kafka/streams/StreamsConfig.html) Javadocs.
+This section contains the most common Streams configuration parameters. For a
full reference, see the
[Streams](/{version}/javadoc/org/apache/kafka/streams/StreamsConfig.html)
Javadocs.
* Required configuration parameters
* application.id
@@ -300,7 +300,7 @@ The minimum number of in-sync replicas available for
replication if the producer
## Optional configuration parameters
-Here are the optional
[Streams](/42/javadoc/org/apache/kafka/streams/StreamsConfig.html) javadocs,
sorted by level of importance:
+Here are the optional
[Streams](/{version}/javadoc/org/apache/kafka/streams/StreamsConfig.html)
javadocs, sorted by level of importance:
> * High: These are parameters with a default value which is most likely not
> a good fit for production use. It's highly recommended to revisit these
> parameters for production usage.
> * Medium: The default values of these parameters should work for
> production for many cases, but it's not uncommon that they are changed, for
> example to tune performance.
@@ -1190,8 +1190,8 @@ Serde for the inner class of a windowed record. Must
implement the `Serde` inter
> The deserialization exception handler allows you to manage record exceptions
> that fail to deserialize. This can be caused by corrupt data, incorrect
> serialization logic, or unhandled record types. The implemented exception
> handler needs to return a `FAIL` or `CONTINUE` depending on the record and
> the exception thrown. Returning `FAIL` will signal that Streams should shut
> down and `CONTINUE` will signal that Streams should ignore the issue and
> continue processing. The following library [...]
>
-> *
[LogAndContinueExceptionHandler](/42/javadoc/org/apache/kafka/streams/errors/LogAndContinueExceptionHandler.html):
This handler logs the deserialization exception and then signals the
processing pipeline to continue processing more records. This log-and-skip
strategy allows Kafka Streams to make progress instead of failing if there are
records that fail to deserialize.
-> *
[LogAndFailExceptionHandler](/42/javadoc/org/apache/kafka/streams/errors/LogAndFailExceptionHandler.html).
This handler logs the deserialization exception and then signals the
processing pipeline to stop processing more records.
+> *
[LogAndContinueExceptionHandler](/{version}/javadoc/org/apache/kafka/streams/errors/LogAndContinueExceptionHandler.html):
This handler logs the deserialization exception and then signals the
processing pipeline to continue processing more records. This log-and-skip
strategy allows Kafka Streams to make progress instead of failing if there are
records that fail to deserialize.
+> *
[LogAndFailExceptionHandler](/{version}/javadoc/org/apache/kafka/streams/errors/LogAndFailExceptionHandler.html).
This handler logs the deserialization exception and then signals the
processing pipeline to stop processing more records.
>
>
@@ -1226,7 +1226,7 @@ Serde for the inner class of a windowed record. Must
implement the `Serde` inter
### production.exception.handler (deprecated:
default.production.exception.handler)
-> The production exception handler allows you to manage exceptions triggered
when trying to interact with a broker such as attempting to produce a record
that is too large. By default, Kafka provides and uses the
[DefaultProductionExceptionHandler](/42/javadoc/org/apache/kafka/streams/errors/DefaultProductionExceptionHandler.html)
that always fails when these exceptions occur.
+> The production exception handler allows you to manage exceptions triggered
when trying to interact with a broker such as attempting to produce a record
that is too large. By default, Kafka provides and uses the
[DefaultProductionExceptionHandler](/{version}/javadoc/org/apache/kafka/streams/errors/DefaultProductionExceptionHandler.html)
that always fails when these exceptions occur.
>
> An exception handler can return `FAIL`, `CONTINUE`, or `RETRY` depending on
> the record and the exception thrown. Returning `FAIL` will signal that
> Streams should shut down. `CONTINUE` will signal that Streams should ignore
> the issue and continue processing. For `RetriableException` the handler may
> return `RETRY` to tell the runtime to retry sending the failed record
> (**Note:** If `RETRY` is returned for a non-`RetriableException` it will be
> treated as `FAIL`.) If you want to provide an [...]
>
@@ -1260,9 +1260,9 @@ Serde for the inner class of a windowed record. Must
implement the `Serde` inter
### default.timestamp.extractor
-> A timestamp extractor pulls a timestamp from an instance of
[ConsumerRecord](/42/javadoc/org/apache/kafka/clients/consumer/ConsumerRecord.html).
Timestamps are used to control the progress of streams.
+> A timestamp extractor pulls a timestamp from an instance of
[ConsumerRecord](/{version}/javadoc/org/apache/kafka/clients/consumer/ConsumerRecord.html).
Timestamps are used to control the progress of streams.
>
-> The default extractor is
[FailOnInvalidTimestamp](/42/javadoc/org/apache/kafka/streams/processor/FailOnInvalidTimestamp.html).
This extractor retrieves built-in timestamps that are automatically embedded
into Kafka messages by the Kafka producer client since [Kafka version
0.10](https://cwiki.apache.org/confluence/x/eaSnAw). Depending on the setting
of Kafka's server-side `log.message.timestamp.type` broker and
`message.timestamp.type` topic parameters, this extractor provides you with:
+> The default extractor is
[FailOnInvalidTimestamp](/{version}/javadoc/org/apache/kafka/streams/processor/FailOnInvalidTimestamp.html).
This extractor retrieves built-in timestamps that are automatically embedded
into Kafka messages by the Kafka producer client since [Kafka version
0.10](https://cwiki.apache.org/confluence/x/eaSnAw). Depending on the setting
of Kafka's server-side `log.message.timestamp.type` broker and
`message.timestamp.type` topic parameters, this extractor provides y [...]
>
> * **event-time** processing semantics if `log.message.timestamp.type` is
> set to `CreateTime` aka "producer time" (which is the default). This
> represents the time when a Kafka producer sent the original message. If you
> use Kafka's official producer client, the timestamp represents milliseconds
> since the epoch.
> * **ingestion-time** processing semantics if `log.message.timestamp.type`
> is set to `LogAppendTime` aka "broker time". This represents the time when
> the Kafka broker received the original message, in milliseconds since the
> epoch.
@@ -1273,12 +1273,12 @@ Serde for the inner class of a windowed record. Must
implement the `Serde` inter
>
> If you have data with invalid timestamps and want to process it, then there
> are two alternative extractors available. Both work on built-in timestamps,
> but handle invalid timestamps differently.
>
-> *
[LogAndSkipOnInvalidTimestamp](/42/javadoc/org/apache/kafka/streams/processor/LogAndSkipOnInvalidTimestamp.html):
This extractor logs a warn message and returns the invalid timestamp to Kafka
Streams, which will not process but silently drop the record. This log-and-skip
strategy allows Kafka Streams to make progress instead of failing if there are
records with an invalid built-in timestamp in your input data.
-> *
[UsePartitionTimeOnInvalidTimestamp](/42/javadoc/org/apache/kafka/streams/processor/UsePartitionTimeOnInvalidTimestamp.html).
This extractor returns the record's built-in timestamp if it is valid (i.e.
not negative). If the record does not have a valid built-in timestamps, the
extractor returns the previously extracted valid timestamp from a record of the
same topic partition as the current record as a timestamp estimation. In case
that no timestamp can be estimated, it throws an e [...]
+> *
[LogAndSkipOnInvalidTimestamp](/{version}/javadoc/org/apache/kafka/streams/processor/LogAndSkipOnInvalidTimestamp.html):
This extractor logs a warn message and returns the invalid timestamp to Kafka
Streams, which will not process but silently drop the record. This log-and-skip
strategy allows Kafka Streams to make progress instead of failing if there are
records with an invalid built-in timestamp in your input data.
+> *
[UsePartitionTimeOnInvalidTimestamp](/{version}/javadoc/org/apache/kafka/streams/processor/UsePartitionTimeOnInvalidTimestamp.html).
This extractor returns the record's built-in timestamp if it is valid (i.e.
not negative). If the record does not have a valid built-in timestamps, the
extractor returns the previously extracted valid timestamp from a record of the
same topic partition as the current record as a timestamp estimation. In case
that no timestamp can be estimated, it thro [...]
>
>
-> Another built-in extractor is
[WallclockTimestampExtractor](/42/javadoc/org/apache/kafka/streams/processor/WallclockTimestampExtractor.html).
This extractor does not actually "extract" a timestamp from the consumed
record but rather returns the current time in milliseconds from the system
clock (think: `System.currentTimeMillis()`), which effectively means Streams
will operate on the basis of the so-called **processing-time** of events.
+> Another built-in extractor is
[WallclockTimestampExtractor](/{version}/javadoc/org/apache/kafka/streams/processor/WallclockTimestampExtractor.html).
This extractor does not actually "extract" a timestamp from the consumed
record but rather returns the current time in milliseconds from the system
clock (think: `System.currentTimeMillis()`), which effectively means Streams
will operate on the basis of the so-called **processing-time** of events.
>
> You can also provide your own timestamp extractors, for instance to retrieve
> timestamps embedded in the payload of messages. If you cannot extract a
> valid timestamp, you can either throw an exception, return a negative
> timestamp, or estimate a timestamp. Returning a negative timestamp will
> result in data loss - the corresponding record will not be processed but
> silently dropped. If you want to estimate a new timestamp, you can use the
> value provided via `previousTimestamp` (i.e., a Kaf [...]
>
@@ -1450,8 +1450,8 @@ Serde for the inner class of a windowed record. Must
implement the `Serde` inter
>
> The following library built-in exception handlers are available:
>
-> *
[LogAndContinueProcessingExceptionHandler](/42/javadoc/org/apache/kafka/streams/errors/LogAndContinueProcessingExceptionHandler.html):
This handler logs the processing exception and then signals the processing
pipeline to continue processing more records. This log-and-skip strategy allows
Kafka Streams to make progress instead of failing if there are records that
fail to be processed.
-> *
[LogAndFailProcessingExceptionHandler](/42/javadoc/org/apache/kafka/streams/errors/LogAndFailProcessingExceptionHandler.html).
This handler logs the processing exception and then signals the processing
pipeline to stop processing more records.
+> *
[LogAndContinueProcessingExceptionHandler](/{version}/javadoc/org/apache/kafka/streams/errors/LogAndContinueProcessingExceptionHandler.html):
This handler logs the processing exception and then signals the processing
pipeline to continue processing more records. This log-and-skip strategy allows
Kafka Streams to make progress instead of failing if there are records that
fail to be processed.
+> *
[LogAndFailProcessingExceptionHandler](/{version}/javadoc/org/apache/kafka/streams/errors/LogAndFailProcessingExceptionHandler.html).
This handler logs the processing exception and then signals the processing
pipeline to stop processing more records.
>
>
@@ -1506,7 +1506,7 @@ Serde for the inner class of a windowed record. Must
implement the `Serde` inter
### rocksdb.config.setter
-> The RocksDB configuration. Kafka Streams uses RocksDB as the default storage
engine for persistent stores. To change the default configuration for RocksDB,
you can implement `RocksDBConfigSetter` and provide your custom class via
[rocksdb.config.setter](/42/javadoc/org/apache/kafka/streams/state/RocksDBConfigSetter.html).
+> The RocksDB configuration. Kafka Streams uses RocksDB as the default storage
engine for persistent stores. To change the default configuration for RocksDB,
you can implement `RocksDBConfigSetter` and provide your custom class via
[rocksdb.config.setter](/{version}/javadoc/org/apache/kafka/streams/state/RocksDBConfigSetter.html).
>
> Here is an example that adjusts the memory size consumed by RocksDB.
>
@@ -1574,9 +1574,9 @@ Note that you need to do two things to enable
optimizations. In addition to sett
### Kafka consumers, producer and admin client configuration parameters
- You can specify parameters for the Kafka
[consumers](/42/javadoc/org/apache/kafka/clients/consumer/package-summary.html),
[producers](/42/javadoc/org/apache/kafka/clients/producer/package-summary.html),
and [admin
client](/42/javadoc/org/apache/kafka/kafka/clients/admin/package-summary.html)
that are used internally. The consumer, producer and admin client settings are
defined by specifying parameters in a `StreamsConfig` instance.
+ You can specify parameters for the Kafka
[consumers](/{version}/javadoc/org/apache/kafka/clients/consumer/package-summary.html),
[producers](/{version}/javadoc/org/apache/kafka/clients/producer/package-summary.html),
and [admin
client](/{version}/javadoc/org/apache/kafka/kafka/clients/admin/package-summary.html)
that are used internally. The consumer, producer and admin client settings are
defined by specifying parameters in a `StreamsConfig` instance.
- In this example, the Kafka [consumer session
timeout](/42/javadoc/org/apache/kafka/clients/consumer/ConsumerConfig.html#SESSION_TIMEOUT_MS_CONFIG)
is configured to be 60000 milliseconds in the Streams settings:
+ In this example, the Kafka [consumer session
timeout](/{version}/javadoc/org/apache/kafka/clients/consumer/ConsumerConfig.html#SESSION_TIMEOUT_MS_CONFIG)
is configured to be 60000 milliseconds in the Streams settings:
Properties streamsSettings = new Properties();
diff --git a/docs/streams/developer-guide/dsl-api.md
b/docs/streams/developer-guide/dsl-api.md
index 981614db1ed..83ba64256fd 100644
--- a/docs/streams/developer-guide/dsl-api.md
+++ b/docs/streams/developer-guide/dsl-api.md
@@ -75,7 +75,7 @@ With the DSL, you can define [processor
topologies](../core-concepts.html#stream
After the application is run, the defined processor topologies are
continuously executed (i.e., the processing plan is put into action). A
step-by-step guide for writing a stream processing application using the DSL is
provided below.
-For a complete list of available API functionality, see also the
[Streams](/42/javadoc/org/apache/kafka/streams/package-summary.html) API docs.
+For a complete list of available API functionality, see also the
[Streams](/{version}/javadoc/org/apache/kafka/streams/package-summary.html) API
docs.
### KStream
@@ -167,7 +167,7 @@ Description
-Creates a KStream from the specified Kafka input topics and interprets the
data as a record stream. A `KStream` represents a _partitioned_ record stream.
[(details)](/42/javadoc/org/apache/kafka/streams/StreamsBuilder.html#stream\(java.lang.String\))
+Creates a KStream from the specified Kafka input topics and interprets the
data as a record stream. A `KStream` represents a _partitioned_ record stream.
[(details)](/{version}/javadoc/org/apache/kafka/streams/StreamsBuilder.html#stream\(java.lang.String\))
In the case of a KStream, the local KStream instance of every application
instance will be populated with data from only **a subset** of the partitions
of the input topic. Collectively, across all application instances, all input
topic partitions are read and processed.
@@ -208,7 +208,7 @@ Several variants of `stream` exist. For example, you can
specify a regex pattern
-Reads the specified Kafka input topic into a KTable. The topic is interpreted
as a changelog stream, where records with the same key are interpreted as
UPSERT aka INSERT/UPDATE (when the record value is not `null`) or as DELETE
(when the value is `null`) for that key.
[(details)](/42/javadoc/org/apache/kafka/streams/StreamsBuilder.html#table-java.lang.String\(java.lang.String\))
+Reads the specified Kafka input topic into a KTable. The topic is interpreted
as a changelog stream, where records with the same key are interpreted as
UPSERT aka INSERT/UPDATE (when the record value is not `null`) or as DELETE
(when the value is `null`) for that key.
[(details)](/{version}/javadoc/org/apache/kafka/streams/StreamsBuilder.html#table-java.lang.String\(java.lang.String\))
In the case of a KTable, the local KTable instance of every application
instance will be populated with data from only **a subset** of the partitions
of the input topic. Collectively, across all application instances, all input
topic partitions are read and processed.
@@ -237,7 +237,7 @@ Several variants of `table` exist, for example to specify
the `auto.offset.reset
-Reads the specified Kafka input topic into a GlobalKTable. The topic is
interpreted as a changelog stream, where records with the same key are
interpreted as UPSERT aka INSERT/UPDATE (when the record value is not `null`)
or as DELETE (when the value is `null`) for that key.
[(details)](/42/javadoc/org/apache/kafka/streams/StreamsBuilder.html#globalTable-java.lang.String\(java.lang.String\))
+Reads the specified Kafka input topic into a GlobalKTable. The topic is
interpreted as a changelog stream, where records with the same key are
interpreted as UPSERT aka INSERT/UPDATE (when the record value is not `null`)
or as DELETE (when the value is `null`) for that key.
[(details)](/{version}/javadoc/org/apache/kafka/streams/StreamsBuilder.html#globalTable-java.lang.String\(java.lang.String\))
In the case of a GlobalKTable, the local GlobalKTable instance of every
application instance will be populated with data from **all** the partitions of
the input topic.
@@ -311,7 +311,7 @@ Description
-Branch (or split) a `KStream` based on the supplied predicates into one or
more `KStream` instances.
([details](/42/javadoc/org/apache/kafka/streams/kstream/KStream.html#split\(\)))
+Branch (or split) a `KStream` based on the supplied predicates into one or
more `KStream` instances.
([details](/{version}/javadoc/org/apache/kafka/streams/kstream/KStream.html#split\(\)))
Predicates are evaluated in order. A record is placed to one and only one
output stream on the first match: if the n-th predicate evaluates to true, the
record is placed to n-th stream. If a record does not match any predicates, it
will be routed to the default branch, or dropped if no default branch is
created.
@@ -392,7 +392,7 @@ A multicast is implemented as a broadcast plus filters.
-Evaluates a boolean function for each element and retains those for which the
function returns true. ([KStream
details](/42/javadoc/org/apache/kafka/streams/kstream/KStream.html#filter-org.apache.kafka.streams.kstream.Predicate-),
[KTable
details](/42/javadoc/org/apache/kafka/streams/kstream/KTable.html#filter-org.apache.kafka.streams.kstream.Predicate-))
+Evaluates a boolean function for each element and retains those for which the
function returns true. ([KStream
details](/{version}/javadoc/org/apache/kafka/streams/kstream/KStream.html#filter-org.apache.kafka.streams.kstream.Predicate-),
[KTable
details](/{version}/javadoc/org/apache/kafka/streams/kstream/KTable.html#filter-org.apache.kafka.streams.kstream.Predicate-))
KStream<String, Long> stream = ...;
@@ -419,7 +419,7 @@ Evaluates a boolean function for each element and retains
those for which the fu
-Evaluates a boolean function for each element and drops those for which the
function returns true. ([KStream
details](/42/javadoc/org/apache/kafka/streams/kstream/KStream.html#filterNot-org.apache.kafka.streams.kstream.Predicate-),
[KTable
details](/42/javadoc/org/apache/kafka/streams/kstream/KTable.html#filterNot-org.apache.kafka.streams.kstream.Predicate-))
+Evaluates a boolean function for each element and drops those for which the
function returns true. ([KStream
details](/{version}/javadoc/org/apache/kafka/streams/kstream/KStream.html#filterNot-org.apache.kafka.streams.kstream.Predicate-),
[KTable
details](/{version}/javadoc/org/apache/kafka/streams/kstream/KTable.html#filterNot-org.apache.kafka.streams.kstream.Predicate-))
KStream<String, Long> stream = ...;
@@ -446,7 +446,7 @@ Evaluates a boolean function for each element and drops
those for which the func
-Takes one record and produces zero, one, or more records. You can modify the
record keys and values, including their types.
([details](/42/javadoc/org/apache/kafka/streams/kstream/KStream.html#flatMap-org.apache.kafka.streams.kstream.KeyValueMapper-))
+Takes one record and produces zero, one, or more records. You can modify the
record keys and values, including their types.
([details](/{version}/javadoc/org/apache/kafka/streams/kstream/KStream.html#flatMap-org.apache.kafka.streams.kstream.KeyValueMapper-))
**Marks the stream for data re-partitioning:** Applying a grouping or a join
after `flatMap` will result in re-partitioning of the records. If possible use
`flatMapValues` instead, which will not cause data re-partitioning.
@@ -482,7 +482,7 @@ Takes one record and produces zero, one, or more records.
You can modify the rec
-Takes one record and produces zero, one, or more records, while retaining the
key of the original record. You can modify the record values and the value
type.
([details](/42/javadoc/org/apache/kafka/streams/kstream/KStream.html#flatMapValues-org.apache.kafka.streams.kstream.ValueMapper-))
+Takes one record and produces zero, one, or more records, while retaining the
key of the original record. You can modify the record values and the value
type.
([details](/{version}/javadoc/org/apache/kafka/streams/kstream/KStream.html#flatMapValues-org.apache.kafka.streams.kstream.ValueMapper-))
`flatMapValues` is preferable to `flatMap` because it will not cause data
re-partitioning. However, you cannot modify the key or key type like `flatMap`
does.
@@ -511,7 +511,7 @@ Takes one record and produces zero, one, or more records,
while retaining the ke
-**Terminal operation.** Performs a stateless action on each record.
([details](/42/javadoc/org/apache/kafka/streams/kstream/KStream.html#foreach-org.apache.kafka.streams.kstream.ForeachAction-))
+**Terminal operation.** Performs a stateless action on each record.
([details](/{version}/javadoc/org/apache/kafka/streams/kstream/KStream.html#foreach-org.apache.kafka.streams.kstream.ForeachAction-))
You would use `foreach` to cause _side effects_ based on the input data
(similar to `peek`) and then _stop_ _further processing_ of the input data
(unlike `peek`, which is not a terminal operation).
@@ -541,7 +541,7 @@ You would use `foreach` to cause _side effects_ based on
the input data (similar
-Groups the records by the existing key.
([details](/42/javadoc/org/apache/kafka/streams/kstream/KStream.html#groupByKey--))
+Groups the records by the existing key.
([details](/{version}/javadoc/org/apache/kafka/streams/kstream/KStream.html#groupByKey--))
Grouping is a prerequisite for aggregating a stream or a table and ensures
that data is properly partitioned ("keyed") for subsequent operations.
@@ -586,7 +586,7 @@ Grouping is a prerequisite for aggregating a stream or a
table and ensures that
-Groups the records by a _new_ key, which may be of a different key type. When
grouping a table, you may also specify a new value and value type. `groupBy` is
a shorthand for `selectKey(...).groupByKey()`. ([KStream
details](/42/javadoc/org/apache/kafka/streams/kstream/KStream.html#groupBy-org.apache.kafka.streams.kstream.KeyValueMapper-),
[KTable
details](/42/javadoc/org/apache/kafka/streams/kstream/KTable.html#groupBy-org.apache.kafka.streams.kstream.KeyValueMapper-))
+Groups the records by a _new_ key, which may be of a different key type. When
grouping a table, you may also specify a new value and value type. `groupBy` is
a shorthand for `selectKey(...).groupByKey()`. ([KStream
details](/{version}/javadoc/org/apache/kafka/streams/kstream/KStream.html#groupBy-org.apache.kafka.streams.kstream.KeyValueMapper-),
[KTable
details](/{version}/javadoc/org/apache/kafka/streams/kstream/KTable.html#groupBy-org.apache.kafka.streams.kstream.KeyValueMapper-))
Grouping is a prerequisite for aggregating a stream or a table and ensures
that data is properly partitioned ("keyed") for subsequent operations.
@@ -638,7 +638,7 @@ Grouping is a prerequisite for aggregating a stream or a
table and ensures that
-Cogrouping allows to aggregate multiple input streams in a single operation.
The different (already grouped) input streams must have the same key type and
may have different values types.
[KGroupedStream#cogroup()](/42/javadoc/org/apache/kafka/streams/kstream/KGroupedStream.html#cogroup)
creates a new cogrouped stream with a single input stream, while
[CogroupedKStream#cogroup()](/42/javadoc/org/apache/kafka/streams/kstream/CogroupedKStream.html#cogroup)
adds a grouped stream to an exist [...]
+Cogrouping allows to aggregate multiple input streams in a single operation.
The different (already grouped) input streams must have the same key type and
may have different values types.
[KGroupedStream#cogroup()](/{version}/javadoc/org/apache/kafka/streams/kstream/KGroupedStream.html#cogroup)
creates a new cogrouped stream with a single input stream, while
[CogroupedKStream#cogroup()](/{version}/javadoc/org/apache/kafka/streams/kstream/CogroupedKStream.html#cogroup)
adds a grouped stre [...]
Cogroup does not cause a repartition as it has the prerequisite that the input
streams are grouped. In the process of creating these groups they will have
already been repartitioned if the stream was already marked for repartitioning.
@@ -673,7 +673,7 @@ Cogroup does not cause a repartition as it has the
prerequisite that the input s
-Takes one record and produces one record. You can modify the record key and
value, including their types.
([details](/42/javadoc/org/apache/kafka/streams/kstream/KStream.html#map-org.apache.kafka.streams.kstream.KeyValueMapper-))
+Takes one record and produces one record. You can modify the record key and
value, including their types.
([details](/{version}/javadoc/org/apache/kafka/streams/kstream/KStream.html#map-org.apache.kafka.streams.kstream.KeyValueMapper-))
**Marks the stream for data re-partitioning:** Applying a grouping or a join
after `map` will result in re-partitioning of the records. If possible use
`mapValues` instead, which will not cause data re-partitioning.
@@ -704,7 +704,7 @@ Takes one record and produces one record. You can modify
the record key and valu
-Takes one record and produces one record, while retaining the key of the
original record. You can modify the record value and the value type. ([KStream
details](/42/javadoc/org/apache/kafka/streams/kstream/KStream.html#mapValues-org.apache.kafka.streams.kstream.ValueMapper-),
[KTable
details](/42/javadoc/org/apache/kafka/streams/kstream/KTable.html#mapValues-org.apache.kafka.streams.kstream.ValueMapper-))
+Takes one record and produces one record, while retaining the key of the
original record. You can modify the record value and the value type. ([KStream
details](/{version}/javadoc/org/apache/kafka/streams/kstream/KStream.html#mapValues-org.apache.kafka.streams.kstream.ValueMapper-),
[KTable
details](/{version}/javadoc/org/apache/kafka/streams/kstream/KTable.html#mapValues-org.apache.kafka.streams.kstream.ValueMapper-))
`mapValues` is preferable to `map` because it will not cause data
re-partitioning. However, it does not allow you to modify the key or key type
like `map` does.
@@ -731,7 +731,7 @@ Takes one record and produces one record, while retaining
the key of the origina
-Merges records of two streams into one larger stream.
([details](/42/javadoc/org/apache/kafka/streams/kstream/KStream.html#merge-org.apache.kafka.streams.kstream.KStream-))
+Merges records of two streams into one larger stream.
([details](/{version}/javadoc/org/apache/kafka/streams/kstream/KStream.html#merge-org.apache.kafka.streams.kstream.KStream-))
There is no ordering guarantee between records from different streams in the
merged stream. Relative order is preserved within each input stream though (ie,
records within the same input stream are processed in order)
@@ -759,7 +759,7 @@ There is no ordering guarantee between records from
different streams in the mer
-Performs a stateless action on each record, and returns an unchanged stream.
([details](/42/javadoc/org/apache/kafka/streams/kstream/KStream.html#peek-org.apache.kafka.streams.kstream.ForeachAction-))
+Performs a stateless action on each record, and returns an unchanged stream.
([details](/{version}/javadoc/org/apache/kafka/streams/kstream/KStream.html#peek-org.apache.kafka.streams.kstream.ForeachAction-))
You would use `peek` to cause _side effects_ based on the input data (similar
to `foreach`) and _continue_ _processing_ the input data (unlike `foreach`,
which is a terminal operation). `peek` returns the input stream as-is; if you
need to modify the input stream, use `map` or `mapValues` instead.
@@ -791,7 +791,7 @@ You would use `peek` to cause _side effects_ based on the
input data (similar to
-**Terminal operation.** Prints the records to `System.out`. See Javadocs for
serde and `toString()` caveats.
([details](/42/javadoc/org/apache/kafka/streams/kstream/KStream.html#print--))
+**Terminal operation.** Prints the records to `System.out`. See Javadocs for
serde and `toString()` caveats.
([details](/{version}/javadoc/org/apache/kafka/streams/kstream/KStream.html#print--))
Calling `print()` is the same as calling `foreach((key, value) ->
System.out.println(key + ", " + value))`
@@ -822,7 +822,7 @@ Calling `print()` is the same as calling `foreach((key,
value) -> System.out.pri
-Assigns a new key - possibly of a new key type - to each record.
([details](/42/javadoc/org/apache/kafka/streams/kstream/KStream.html#selectKey-org.apache.kafka.streams.kstream.KeyValueMapper-))
+Assigns a new key - possibly of a new key type - to each record.
([details](/{version}/javadoc/org/apache/kafka/streams/kstream/KStream.html#selectKey-org.apache.kafka.streams.kstream.KeyValueMapper-))
Calling `selectKey(mapper)` is the same as calling `map((key, value) ->
mapper(key, value), value)`.
@@ -852,7 +852,7 @@ Calling `selectKey(mapper)` is the same as calling
`map((key, value) -> mapper(k
-Get the changelog stream of this table.
([details](/42/javadoc/org/apache/kafka/streams/kstream/KTable.html#toStream--))
+Get the changelog stream of this table.
([details](/{version}/javadoc/org/apache/kafka/streams/kstream/KTable.html#toStream--))
KTable<byte[], String> table = ...;
@@ -878,7 +878,7 @@ Get the changelog stream of this table.
([details](/42/javadoc/org/apache/kafka/
-Convert an event stream into a table, or say a changelog stream.
([details](/42/javadoc/org/apache/kafka/streams/kstream/KStream.html#toTable--))
+Convert an event stream into a table, or say a changelog stream.
([details](/{version}/javadoc/org/apache/kafka/streams/kstream/KStream.html#toTable--))
KStream<byte[], String> stream = ...;
@@ -902,7 +902,7 @@ Convert an event stream into a table, or say a changelog
stream. ([details](/42/
-Manually trigger repartitioning of the stream with desired number of
partitions.
([details](/42/javadoc/org/apache/kafka/streams/kstream/KStream.html#repartition--))
+Manually trigger repartitioning of the stream with desired number of
partitions.
([details](/{version}/javadoc/org/apache/kafka/streams/kstream/KStream.html#repartition--))
Kafka Streams will manage the topic for `repartition()`. Generated topic is
treated as internal topic, as a result data will be purged automatically as any
other internal repartition topic. In addition, you can specify the desired
number of partitions, which allows to easily scale in/out downstream
sub-topologies. `repartition()` operation always triggers repartitioning of the
stream, as a result it can be used with embedded Processor API methods (like
`process()` et al.) that do not tri [...]
@@ -919,9 +919,9 @@ Stateful transformations depend on state for processing
inputs and producing out
**Note:** Following store types are used regardless of the possibly specified
type (via the parameter `materialized`):
- * non-windowed aggregations and non-windowed KTables use
[TimestampedKeyValueStore](/42/javadoc/org/apache/kafka/streams/state/TimestampedKeyValueStore.html)s
or
[VersionedKeyValueStore](/42/javadoc/org/apache/kafka/streams/state/VersionedKeyValueStore.html)s,
depending on whether the parameter `materialized` is versioned
- * time-windowed aggregations and KStream-KStream joins use
[TimestampedWindowStore](/42/javadoc/org/apache/kafka/streams/state/TimestampedWindowStore.html)s
- * session windowed aggregations use
[SessionStore](/42/javadoc/org/apache/kafka/streams/state/SessionStore.html)s
(there is no timestamped session store as of now)
+ * non-windowed aggregations and non-windowed KTables use
[TimestampedKeyValueStore](/{version}/javadoc/org/apache/kafka/streams/state/TimestampedKeyValueStore.html)s
or
[VersionedKeyValueStore](/{version}/javadoc/org/apache/kafka/streams/state/VersionedKeyValueStore.html)s,
depending on whether the parameter `materialized` is versioned
+ * time-windowed aggregations and KStream-KStream joins use
[TimestampedWindowStore](/{version}/javadoc/org/apache/kafka/streams/state/TimestampedWindowStore.html)s
+ * session windowed aggregations use
[SessionStore](/{version}/javadoc/org/apache/kafka/streams/state/SessionStore.html)s
(there is no timestamped session store as of now)
@@ -996,7 +996,7 @@ Description
-**Rolling aggregation.** Aggregates the values of (non-windowed) records by
the grouped key or cogrouped. Aggregating is a generalization of `reduce` and
allows, for example, the aggregate value to have a different type than the
input values. ([KGroupedStream
details](/42/javadoc/org/apache/kafka/streams/kstream/KGroupedStream.html),
[KGroupedTable
details](/42/javadoc/org/apache/kafka/streams/kstream/KGroupedTable.html)
[KGroupedTable details](/42/javadoc/org/apache/kafka/streams/kstrea [...]
+**Rolling aggregation.** Aggregates the values of (non-windowed) records by
the grouped key or cogrouped. Aggregating is a generalization of `reduce` and
allows, for example, the aggregate value to have a different type than the
input values. ([KGroupedStream
details](/{version}/javadoc/org/apache/kafka/streams/kstream/KGroupedStream.html),
[KGroupedTable
details](/{version}/javadoc/org/apache/kafka/streams/kstream/KGroupedTable.html)
[KGroupedTable details](/{version}/javadoc/org/apache [...]
When aggregating a _grouped stream_ , you must provide an initializer (e.g.,
`aggValue = 0`) and an "adder" aggregator (e.g., `aggValue + curValue`). When
aggregating a _grouped table_ , you must additionally provide a "subtractor"
aggregator (think: `aggValue - oldValue`).
@@ -1061,7 +1061,7 @@ See the example at the bottom of this section for a
visualization of the aggrega
-**Windowed aggregation.** Aggregates the values of records, per window, by the
grouped key. Aggregating is a generalization of `reduce` and allows, for
example, the aggregate value to have a different type than the input values.
([TimeWindowedKStream
details](/42/javadoc/org/apache/kafka/streams/kstream/TimeWindowedKStream.html),
[SessionWindowedKStream
details](/42/javadoc/org/apache/kafka/streams/kstream/SessionWindowedKStream.html))
+**Windowed aggregation.** Aggregates the values of records, per window, by the
grouped key. Aggregating is a generalization of `reduce` and allows, for
example, the aggregate value to have a different type than the input values.
([TimeWindowedKStream
details](/{version}/javadoc/org/apache/kafka/streams/kstream/TimeWindowedKStream.html),
[SessionWindowedKStream
details](/{version}/javadoc/org/apache/kafka/streams/kstream/SessionWindowedKStream.html))
You must provide an initializer (e.g., `aggValue = 0`), "adder" aggregator
(e.g., `aggValue + curValue`), and a window. When windowing based on sessions,
you must additionally provide a "session merger" aggregator (e.g.,
`mergedAggValue = leftAggValue + rightAggValue`).
@@ -1129,7 +1129,7 @@ See the example at the bottom of this section for a
visualization of the aggrega
-**Rolling aggregation.** Counts the number of records by the grouped key.
([KGroupedStream
details](/42/javadoc/org/apache/kafka/streams/kstream/KGroupedStream.html),
[KGroupedTable
details](/42/javadoc/org/apache/kafka/streams/kstream/KGroupedTable.html))
+**Rolling aggregation.** Counts the number of records by the grouped key.
([KGroupedStream
details](/{version}/javadoc/org/apache/kafka/streams/kstream/KGroupedStream.html),
[KGroupedTable
details](/{version}/javadoc/org/apache/kafka/streams/kstream/KGroupedTable.html))
Several variants of `count` exist, see Javadocs for details.
@@ -1170,7 +1170,7 @@ Detailed behavior for `KGroupedTable`:
-**Windowed aggregation.** Counts the number of records, per window, by the
grouped key. ([TimeWindowedKStream
details](/42/javadoc/org/apache/kafka/streams/kstream/TimeWindowedKStream.html),
[SessionWindowedKStream
details](/42/javadoc/org/apache/kafka/streams/kstream/SessionWindowedKStream.html))
+**Windowed aggregation.** Counts the number of records, per window, by the
grouped key. ([TimeWindowedKStream
details](/{version}/javadoc/org/apache/kafka/streams/kstream/TimeWindowedKStream.html),
[SessionWindowedKStream
details](/{version}/javadoc/org/apache/kafka/streams/kstream/SessionWindowedKStream.html))
The windowed `count` turns a `TimeWindowedKStream<K, V>` or
`SessionWindowedKStream<K, V>` into a windowed `KTable<Windowed<K>, V>`.
@@ -1217,7 +1217,7 @@ Detailed behavior:
-**Rolling aggregation.** Combines the values of (non-windowed) records by the
grouped key. The current record value is combined with the last reduced value,
and a new reduced value is returned. The result value type cannot be changed,
unlike `aggregate`. ([KGroupedStream
details](/42/javadoc/org/apache/kafka/streams/kstream/KGroupedStream.html),
[KGroupedTable
details](/42/javadoc/org/apache/kafka/streams/kstream/KGroupedTable.html))
+**Rolling aggregation.** Combines the values of (non-windowed) records by the
grouped key. The current record value is combined with the last reduced value,
and a new reduced value is returned. The result value type cannot be changed,
unlike `aggregate`. ([KGroupedStream
details](/{version}/javadoc/org/apache/kafka/streams/kstream/KGroupedStream.html),
[KGroupedTable
details](/{version}/javadoc/org/apache/kafka/streams/kstream/KGroupedTable.html))
When reducing a _grouped stream_ , you must provide an "adder" reducer (e.g.,
`aggValue + curValue`). When reducing a _grouped table_ , you must additionally
provide a "subtractor" reducer (e.g., `aggValue - oldValue`).
@@ -1274,7 +1274,7 @@ See the example at the bottom of this section for a
visualization of the aggrega
-**Windowed aggregation.** Combines the values of records, per window, by the
grouped key. The current record value is combined with the last reduced value,
and a new reduced value is returned. Records with `null` key or value are
ignored. The result value type cannot be changed, unlike `aggregate`.
([TimeWindowedKStream
details](/42/javadoc/org/apache/kafka/streams/kstream/TimeWindowedKStream.html),
[SessionWindowedKStream
details](/42/javadoc/org/apache/kafka/streams/kstream/SessionWind [...]
+**Windowed aggregation.** Combines the values of records, per window, by the
grouped key. The current record value is combined with the last reduced value,
and a new reduced value is returned. Records with `null` key or value are
ignored. The result value type cannot be changed, unlike `aggregate`.
([TimeWindowedKStream
details](/{version}/javadoc/org/apache/kafka/streams/kstream/TimeWindowedKStream.html),
[SessionWindowedKStream
details](/{version}/javadoc/org/apache/kafka/streams/kstre [...]
The windowed `reduce` turns a `TimeWindowedKStream<K, V>` or a
`SessionWindowedKStream<K, V>` into a windowed `KTable<Windowed<K>, V>`.
@@ -2154,7 +2154,7 @@ Description
-Performs an INNER JOIN of this stream with another stream. Even though this
operation is windowed, the joined stream will be of type `KStream<K, ...>`
rather than `KStream<Windowed<K>, ...>`.
[(details)](/42/javadoc/org/apache/kafka/streams/kstream/KStream.html#join-org.apache.kafka.streams.kstream.KStream-org.apache.kafka.streams.kstream.ValueJoiner-org.apache.kafka.streams.kstream.JoinWindows-)
+Performs an INNER JOIN of this stream with another stream. Even though this
operation is windowed, the joined stream will be of type `KStream<K, ...>`
rather than `KStream<Windowed<K>, ...>`.
[(details)](/{version}/javadoc/org/apache/kafka/streams/kstream/KStream.html#join-org.apache.kafka.streams.kstream.KStream-org.apache.kafka.streams.kstream.ValueJoiner-org.apache.kafka.streams.kstream.JoinWindows-)
**Data must be co-partitioned** : The input data for both sides must be
co-partitioned.
@@ -2207,7 +2207,7 @@ See the semantics overview at the bottom of this section
for a detailed descript
-Performs a LEFT JOIN of this stream with another stream. Even though this
operation is windowed, the joined stream will be of type `KStream<K, ...>`
rather than `KStream<Windowed<K>, ...>`.
[(details)](/42/javadoc/org/apache/kafka/streams/kstream/KStream.html#leftJoin-org.apache.kafka.streams.kstream.KStream-org.apache.kafka.streams.kstream.ValueJoiner-org.apache.kafka.streams.kstream.JoinWindows-)
+Performs a LEFT JOIN of this stream with another stream. Even though this
operation is windowed, the joined stream will be of type `KStream<K, ...>`
rather than `KStream<Windowed<K>, ...>`.
[(details)](/{version}/javadoc/org/apache/kafka/streams/kstream/KStream.html#leftJoin-org.apache.kafka.streams.kstream.KStream-org.apache.kafka.streams.kstream.ValueJoiner-org.apache.kafka.streams.kstream.JoinWindows-)
**Data must be co-partitioned** : The input data for both sides must be
co-partitioned.
@@ -2262,7 +2262,7 @@ See the semantics overview at the bottom of this section
for a detailed descript
-Performs an OUTER JOIN of this stream with another stream. Even though this
operation is windowed, the joined stream will be of type `KStream<K, ...>`
rather than `KStream<Windowed<K>, ...>`.
[(details)](/42/javadoc/org/apache/kafka/streams/kstream/KStream.html#outerJoin-org.apache.kafka.streams.kstream.KStream-org.apache.kafka.streams.kstream.ValueJoiner-org.apache.kafka.streams.kstream.JoinWindows-)
+Performs an OUTER JOIN of this stream with another stream. Even though this
operation is windowed, the joined stream will be of type `KStream<K, ...>`
rather than `KStream<Windowed<K>, ...>`.
[(details)](/{version}/javadoc/org/apache/kafka/streams/kstream/KStream.html#outerJoin-org.apache.kafka.streams.kstream.KStream-org.apache.kafka.streams.kstream.ValueJoiner-org.apache.kafka.streams.kstream.JoinWindows-)
**Data must be co-partitioned** : The input data for both sides must be
co-partitioned.
@@ -2307,7 +2307,7 @@ See the semantics overview at the bottom of this section
for a detailed descript
**Note:** If you use the old and now deprecated API to specify the grace
period, i.e., `JoinWindows.of(...).grace(...)`, left/outer join results are
emitted eagerly, and the observed result might differ from the result shown
below.
-The columns INNER JOIN, LEFT JOIN, and OUTER JOIN denote what is passed as
arguments to the user-supplied
[ValueJoiner](/42/javadoc/org/apache/kafka/streams/kstream/ValueJoiner.html)
for the `join`, `leftJoin`, and `outerJoin` methods, respectively, whenever a
new input record is received on either side of the join. An empty table cell
denotes that the `ValueJoiner` is not called at all.
+The columns INNER JOIN, LEFT JOIN, and OUTER JOIN denote what is passed as
arguments to the user-supplied
[ValueJoiner](/{version}/javadoc/org/apache/kafka/streams/kstream/ValueJoiner.html)
for the `join`, `leftJoin`, and `outerJoin` methods, respectively, whenever a
new input record is received on either side of the join. An empty table cell
denotes that the `ValueJoiner` is not called at all.
<table>
<tr>
@@ -2952,7 +2952,7 @@ Description
-Performs an INNER JOIN of this table with another table. The result is an
ever-updating KTable that represents the "current" result of the join.
[(details)](/42/javadoc/org/apache/kafka/streams/kstream/KTable.html#join-org.apache.kafka.streams.kstream.KTable-org.apache.kafka.streams.kstream.ValueJoiner-)
+Performs an INNER JOIN of this table with another table. The result is an
ever-updating KTable that represents the "current" result of the join.
[(details)](/{version}/javadoc/org/apache/kafka/streams/kstream/KTable.html#join-org.apache.kafka.streams.kstream.KTable-org.apache.kafka.streams.kstream.ValueJoiner-)
**Data must be co-partitioned** : The input data for both sides must be
co-partitioned.
@@ -2997,7 +2997,7 @@ See the semantics overview at the bottom of this section
for a detailed descript
-Performs a LEFT JOIN of this table with another table.
[(details)](/42/javadoc/org/apache/kafka/streams/kstream/KTable.html#leftJoin-org.apache.kafka.streams.kstream.KTable-org.apache.kafka.streams.kstream.ValueJoiner-)
+Performs a LEFT JOIN of this table with another table.
[(details)](/{version}/javadoc/org/apache/kafka/streams/kstream/KTable.html#leftJoin-org.apache.kafka.streams.kstream.KTable-org.apache.kafka.streams.kstream.ValueJoiner-)
**Data must be co-partitioned** : The input data for both sides must be
co-partitioned.
@@ -3044,7 +3044,7 @@ See the semantics overview at the bottom of this section
for a detailed descript
-Performs an OUTER JOIN of this table with another table.
[(details)](/42/javadoc/org/apache/kafka/streams/kstream/KTable.html#outerJoin-org.apache.kafka.streams.kstream.KTable-org.apache.kafka.streams.kstream.ValueJoiner-)
+Performs an OUTER JOIN of this table with another table.
[(details)](/{version}/javadoc/org/apache/kafka/streams/kstream/KTable.html#outerJoin-org.apache.kafka.streams.kstream.KTable-org.apache.kafka.streams.kstream.ValueJoiner-)
**Data must be co-partitioned** : The input data for both sides must be
co-partitioned.
@@ -3077,7 +3077,7 @@ See the semantics overview at the bottom of this section
for a detailed descript
</td> </tr> </table>
-**Semantics of table-table equi-joins:** The semantics of the various
table-table equi-join variants are explained below. To improve the readability
of the table, you can assume that (1) all records have the same key (and thus
the key in the table is omitted) and that (2) all records are processed in
timestamp order. The columns INNER JOIN, LEFT JOIN, and OUTER JOIN denote what
is passed as arguments to the user-supplied
[ValueJoiner](/42/javadoc/org/apache/kafka/streams/kstream/ValueJoi [...]
+**Semantics of table-table equi-joins:** The semantics of the various
table-table equi-join variants are explained below. To improve the readability
of the table, you can assume that (1) all records have the same key (and thus
the key in the table is omitted) and that (2) all records are processed in
timestamp order. The columns INNER JOIN, LEFT JOIN, and OUTER JOIN denote what
is passed as arguments to the user-supplied
[ValueJoiner](/{version}/javadoc/org/apache/kafka/streams/kstream/V [...]
<table>
<tr>
@@ -3875,7 +3875,7 @@ Description
-Performs an INNER JOIN of this stream with the table, effectively doing a
table lookup.
[(details)](/42/javadoc/org/apache/kafka/streams/kstream/KStream.html#join-org.apache.kafka.streams.kstream.KTable-org.apache.kafka.streams.kstream.ValueJoiner-)
+Performs an INNER JOIN of this stream with the table, effectively doing a
table lookup.
[(details)](/{version}/javadoc/org/apache/kafka/streams/kstream/KStream.html#join-org.apache.kafka.streams.kstream.KTable-org.apache.kafka.streams.kstream.ValueJoiner-)
**Data must be co-partitioned** : The input data for both sides must be
co-partitioned.
@@ -3929,7 +3929,7 @@ See the semantics overview at the bottom of this section
for a detailed descript
-Performs a LEFT JOIN of this stream with the table, effectively doing a table
lookup.
[(details)](/42/javadoc/org/apache/kafka/streams/kstream/KStream.html#leftJoin-org.apache.kafka.streams.kstream.KTable-org.apache.kafka.streams.kstream.ValueJoiner-)
+Performs a LEFT JOIN of this stream with the table, effectively doing a table
lookup.
[(details)](/{version}/javadoc/org/apache/kafka/streams/kstream/KStream.html#leftJoin-org.apache.kafka.streams.kstream.KTable-org.apache.kafka.streams.kstream.ValueJoiner-)
**Data must be co-partitioned** : The input data for both sides must be
co-partitioned.
@@ -3971,7 +3971,7 @@ See the semantics overview at the bottom of this section
for a detailed descript
</td> </tr> </table>
-**Semantics of stream-table joins:** The semantics of the various stream-table
join variants are explained below. To improve the readability of the table we
assume that (1) all records have the same key (and thus we omit the key in the
table) and that (2) all records are processed in timestamp order. The columns
INNER JOIN and LEFT JOIN denote what is passed as arguments to the
user-supplied
[ValueJoiner](/42/javadoc/org/apache/kafka/streams/kstream/ValueJoiner.html)
for the `join` and ` [...]
+**Semantics of stream-table joins:** The semantics of the various stream-table
join variants are explained below. To improve the readability of the table we
assume that (1) all records have the same key (and thus we omit the key in the
table) and that (2) all records are processed in timestamp order. The columns
INNER JOIN and LEFT JOIN denote what is passed as arguments to the
user-supplied
[ValueJoiner](/{version}/javadoc/org/apache/kafka/streams/kstream/ValueJoiner.html)
for the `join [...]
<table>
<tr>
@@ -4362,7 +4362,7 @@ Description
-Performs an INNER JOIN of this stream with the global table, effectively doing
a table lookup.
[(details)](/42/javadoc/org/apache/kafka/streams/kstream/KStream.html#join-org.apache.kafka.streams.kstream.GlobalKTable-org.apache.kafka.streams.kstream.KeyValueMapper-org.apache.kafka.streams.kstream.ValueJoiner-)
+Performs an INNER JOIN of this stream with the global table, effectively doing
a table lookup.
[(details)](/{version}/javadoc/org/apache/kafka/streams/kstream/KStream.html#join-org.apache.kafka.streams.kstream.GlobalKTable-org.apache.kafka.streams.kstream.KeyValueMapper-org.apache.kafka.streams.kstream.ValueJoiner-)
The `GlobalKTable` is fully bootstrapped upon (re)start of a `KafkaStreams`
instance, which means the table is fully populated with all the data in the
underlying topic that is available at the time of the startup. The actual data
processing begins only once the bootstrapping has completed.
@@ -4406,7 +4406,7 @@ Detailed behavior:
-Performs a LEFT JOIN of this stream with the global table, effectively doing a
table lookup.
[(details)](/42/javadoc/org/apache/kafka/streams/kstream/KStream.html#leftJoin-org.apache.kafka.streams.kstream.GlobalKTable-org.apache.kafka.streams.kstream.KeyValueMapper-org.apache.kafka.streams.kstream.ValueJoiner-)
+Performs a LEFT JOIN of this stream with the global table, effectively doing a
table lookup.
[(details)](/{version}/javadoc/org/apache/kafka/streams/kstream/KStream.html#leftJoin-org.apache.kafka.streams.kstream.GlobalKTable-org.apache.kafka.streams.kstream.KeyValueMapper-org.apache.kafka.streams.kstream.ValueJoiner-)
The `GlobalKTable` is fully bootstrapped upon (re)start of a `KafkaStreams`
instance, which means the table is fully populated with all the data in the
underlying topic that is available at the time of the startup. The actual data
processing begins only once the bootstrapping has completed.
@@ -5693,7 +5693,7 @@ Description
-**Terminal operation.** Write the records to Kafka topic(s). ([KStream
details](/42/javadoc/org/apache/kafka/streams/kstream/KStream.html#to\(java.lang.String\)))
+**Terminal operation.** Write the records to Kafka topic(s). ([KStream
details](/{version}/javadoc/org/apache/kafka/streams/kstream/KStream.html#to\(java.lang.String\)))
When to provide serdes explicitly:
diff --git a/docs/streams/developer-guide/interactive-queries.md
b/docs/streams/developer-guide/interactive-queries.md
index 2f168d3cea2..eb9063fc560 100644
--- a/docs/streams/developer-guide/interactive-queries.md
+++ b/docs/streams/developer-guide/interactive-queries.md
@@ -384,7 +384,7 @@ There are many ways to add an RPC layer. The only
requirements are that the RPC
## Exposing the RPC endpoints of your application
-To enable remote state store discovery in a distributed Kafka Streams
application, you must set the [configuration
property](config-streams.html#streams-developer-guide-required-configs) in the
config properties. The `application.server` property defines a unique
`host:port` pair that points to the RPC endpoint of the respective instance of
a Kafka Streams application. The value of this configuration property will vary
across the instances of your application. When this property is set, [...]
+To enable remote state store discovery in a distributed Kafka Streams
application, you must set the [configuration
property](config-streams.html#streams-developer-guide-required-configs) in the
config properties. The `application.server` property defines a unique
`host:port` pair that points to the RPC endpoint of the respective instance of
a Kafka Streams application. The value of this configuration property will vary
across the instances of your application. When this property is set, [...]
**Tip**
@@ -429,7 +429,7 @@ This example shows how to configure and run a Kafka Streams
application that sup
## Discovering and accessing application instances and their local state stores
-The following methods return
[StreamsMetadata](/42/javadoc/org/apache/kafka/streams/state/StreamsMetadata.html)
objects, which provide meta-information about application instances such as
their RPC endpoint and locally available state stores.
+The following methods return
[StreamsMetadata](/{version}/javadoc/org/apache/kafka/streams/state/StreamsMetadata.html)
objects, which provide meta-information about application instances such as
their RPC endpoint and locally available state stores.
* `KafkaStreams#allMetadata()`: find all instances of this application
* `KafkaStreams#allMetadataForStore(String storeName)`: find those
applications instances that manage local instances of the state store
"storeName"
@@ -440,7 +440,7 @@ The following methods return
[StreamsMetadata](/42/javadoc/org/apache/kafka/stre
Attention
-If `application.server` is not configured for an application instance, then
the above methods will not find any
[StreamsMetadata](/42/javadoc/org/apache/kafka/streams/state/StreamsMetadata.html)
for it.
+If `application.server` is not configured for an application instance, then
the above methods will not find any
[StreamsMetadata](/{version}/javadoc/org/apache/kafka/streams/state/StreamsMetadata.html)
for it.
For example, we can now find the `StreamsMetadata` for the state store named
"word-count" that we defined in the code example shown in the previous section:
diff --git a/docs/streams/developer-guide/processor-api.md
b/docs/streams/developer-guide/processor-api.md
index ae7f810d09e..c67c42fcb3a 100644
--- a/docs/streams/developer-guide/processor-api.md
+++ b/docs/streams/developer-guide/processor-api.md
@@ -39,7 +39,7 @@ The Processor API can be used to implement both **stateless**
as well as **state
**Combining the DSL and the Processor API:** You can combine the convenience
of the DSL with the power and flexibility of the Processor API as described in
the section [Applying processors (Processor API
integration)](dsl-api.html#streams-developer-guide-dsl-process).
-For a complete list of available API functionality, see the
[Streams](/42/javadoc/org/apache/kafka/streams/package-summary.html) API docs.
+For a complete list of available API functionality, see the
[Streams](/{version}/javadoc/org/apache/kafka/streams/package-summary.html) API
docs.
# Defining a Stream Processor
@@ -173,11 +173,11 @@ Yes (enabled by default)
* Stores its data on local disk.
* Storage capacity: managed local state can be larger than the memory (heap
space) of an application instance, but must fit into the available local disk
space.
* RocksDB settings can be fine-tuned, see [RocksDB
configuration](config-streams.html#streams-developer-guide-rocksdb-config).
- * Available [store
variants](/42/javadoc/org/apache/kafka/streams/state/Stores.html#persistentKeyValueStore\(java.lang.String\)):
timestamped key-value store, versioned key-value store, time window key-value
store, session window key-value store.
- * Use
[persistentTimestampedKeyValueStore](/42/javadoc/org/apache/kafka/streams/state/Stores.html#persistentTimestampedKeyValueStore\(java.lang.String\))
when you need a persistent key-(value/timestamp) store that supports
put/get/delete and range queries.
- * Use
[persistentVersionedKeyValueStore](/42/javadoc/org/apache/kafka/streams/state/Stores.html#persistentVersionedKeyValueStore\(java.lang.String,java.time.Duration\))
when you need a persistent, versioned key-(value/timestamp) store that
supports put/get/delete and timestamped get operations.
- * Use
[persistentWindowStore](/42/javadoc/org/apache/kafka/streams/state/Stores.html#persistentWindowStore\(java.lang.String,java.time.Duration,java.time.Duration,boolean\))
or
[persistentTimestampedWindowStore](/42/javadoc/org/apache/kafka/streams/state/Stores.html#persistentTimestampedWindowStore\(java.lang.String,java.time.Duration,java.time.Duration,boolean\))
when you need a persistent timeWindowedKey-value or
timeWindowedKey-(value/timestamp) store, respectively.
- * Use
[persistentSessionStore](/42/javadoc/org/apache/kafka/streams/state/Stores.html#persistentSessionStore\(java.lang.String,java.time.Duration\))
when you need a persistent sessionWindowedKey-value store.
+ * Available [store
variants](/{version}/javadoc/org/apache/kafka/streams/state/Stores.html#persistentKeyValueStore\(java.lang.String\)):
timestamped key-value store, versioned key-value store, time window key-value
store, session window key-value store.
+ * Use
[persistentTimestampedKeyValueStore](/{version}/javadoc/org/apache/kafka/streams/state/Stores.html#persistentTimestampedKeyValueStore\(java.lang.String\))
when you need a persistent key-(value/timestamp) store that supports
put/get/delete and range queries.
+ * Use
[persistentVersionedKeyValueStore](/{version}/javadoc/org/apache/kafka/streams/state/Stores.html#persistentVersionedKeyValueStore\(java.lang.String,java.time.Duration\))
when you need a persistent, versioned key-(value/timestamp) store that
supports put/get/delete and timestamped get operations.
+ * Use
[persistentWindowStore](/{version}/javadoc/org/apache/kafka/streams/state/Stores.html#persistentWindowStore\(java.lang.String,java.time.Duration,java.time.Duration,boolean\))
or
[persistentTimestampedWindowStore](/{version}/javadoc/org/apache/kafka/streams/state/Stores.html#persistentTimestampedWindowStore\(java.lang.String,java.time.Duration,java.time.Duration,boolean\))
when you need a persistent timeWindowedKey-value or
timeWindowedKey-(value/timestamp) store, respectively.
+ * Use
[persistentSessionStore](/{version}/javadoc/org/apache/kafka/streams/state/Stores.html#persistentSessionStore\(java.lang.String,java.time.Duration\))
when you need a persistent sessionWindowedKey-value store.
@@ -217,9 +217,9 @@ Yes (enabled by default)
* Stores its data in memory.
* Storage capacity: managed local state must fit into memory (heap space) of
an application instance.
* Useful when application instances run in an environment where local disk
space is either not available or local disk space is wiped in-between app
instance restarts.
- * Available [store
variants](/42/javadoc/org/apache/kafka/streams/state/Stores.html#inMemoryKeyValueStore-java.lang.String-):
time window key-value store, session window key-value store.
- * Use
[TimestampedKeyValueStore](/42/javadoc/org/apache/kafka/streams/state/TimestampedKeyValueStore.html)
when you need a key-(value/timestamp) store that supports put/get/delete and
range queries.
- * Use
[TimestampedWindowStore](/42/javadoc/org/apache/kafka/streams/state/TimestampedWindowStore.html)
when you need to store windowedKey-(value/timestamp) pairs.
+ * Available [store
variants](/{version}/javadoc/org/apache/kafka/streams/state/Stores.html#inMemoryKeyValueStore-java.lang.String-):
time window key-value store, session window key-value store.
+ * Use
[TimestampedKeyValueStore](/{version}/javadoc/org/apache/kafka/streams/state/TimestampedKeyValueStore.html)
when you need a key-(value/timestamp) store that supports put/get/delete and
range queries.
+ * Use
[TimestampedWindowStore](/{version}/javadoc/org/apache/kafka/streams/state/TimestampedWindowStore.html)
when you need to store windowedKey-(value/timestamp) pairs.
* There is no built-in in-memory, versioned key-value store at this time.
@@ -297,7 +297,7 @@ You can query timestamped state stores both with and
without a timestamp.
* For Processor API users, nothing changes in existing applications, and you
have the option of using the timestamped stores.
* For DSL operators, store data is upgraded lazily in the background.
- * No upgrade happens if you provide a custom XxxBytesStoreSupplier, but you
can opt-in by implementing the
[TimestampedBytesStore](/42/javadoc/org/apache/kafka/streams/state/TimestampedBytesStore.html)
interface. In this case, the old format is retained, and Streams uses a proxy
store that removes/adds timestamps on read/write.
+ * No upgrade happens if you provide a custom XxxBytesStoreSupplier, but you
can opt-in by implementing the
[TimestampedBytesStore](/{version}/javadoc/org/apache/kafka/streams/state/TimestampedBytesStore.html)
interface. In this case, the old format is retained, and Streams uses a proxy
store that removes/adds timestamps on read/write.
@@ -305,7 +305,7 @@ You can query timestamped state stores both with and
without a timestamp.
Versioned key-value state stores are available since Kafka Streams 3.5. Rather
than storing a single record version (value and timestamp) per key, versioned
state stores may store multiple record versions per key. This allows versioned
state stores to support timestamped retrieval operations to return the latest
record (per key) as of a specified timestamp.
-You can create a persistent, versioned state store by passing a
[VersionedBytesStoreSupplier](/42/javadoc/org/apache/kafka/streams/state/Stores.html#persistentVersionedKeyValueStore\(java.lang.String,java.time.Duration\))
to the
[versionedKeyValueStoreBuilder](/42/javadoc/org/apache/kafka/streams/state/Stores.html#versionedKeyValueStoreBuilder\(java.lang.String,java.time.Duration\)),
or by implementing your own
[VersionedKeyValueStore](/42/javadoc/org/apache/kafka/streams/state/Versioned
[...]
+You can create a persistent, versioned state store by passing a
[VersionedBytesStoreSupplier](/{version}/javadoc/org/apache/kafka/streams/state/Stores.html#persistentVersionedKeyValueStore\(java.lang.String,java.time.Duration\))
to the
[versionedKeyValueStoreBuilder](/{version}/javadoc/org/apache/kafka/streams/state/Stores.html#versionedKeyValueStoreBuilder\(java.lang.String,java.time.Duration\)),
or by implementing your own
[VersionedKeyValueStore](/{version}/javadoc/org/apache/kafka/st [...]
Each versioned store has an associated, fixed-duration _history retention_
parameter which specifies long old record versions should be kept for. In
particular, a versioned store guarantees to return accurate results for
timestamped retrieval operations where the timestamp being queried is within
history retention of the current observed stream time.
@@ -317,7 +317,7 @@ Versioned stores do not support caching or interactive
queries at this time. Als
**Upgrade note:** Versioned state stores are opt-in only; no automatic
upgrades from non-versioned to versioned stores will take place.
-Upgrades are supported from persistent, non-versioned key-value stores to
persistent, versioned key-value stores as long as the original store has the
same changelog topic format as the versioned store being upgraded to. Both
persistent [key-value
stores](/42/javadoc/org/apache/kafka/streams/state/Stores.html#persistentKeyValueStore\(java.lang.String\))
and [timestamped key-value
stores](/42/javadoc/org/apache/kafka/streams/state/Stores.html#persistentTimestampedKeyValueStore\(java.lang.
[...]
+Upgrades are supported from persistent, non-versioned key-value stores to
persistent, versioned key-value stores as long as the original store has the
same changelog topic format as the versioned store being upgraded to. Both
persistent [key-value
stores](/{version}/javadoc/org/apache/kafka/streams/state/Stores.html#persistentKeyValueStore\(java.lang.String\))
and [timestamped key-value
stores](/{version}/javadoc/org/apache/kafka/streams/state/Stores.html#persistentTimestampedKeyValueSto
[...]
If you wish to upgrade an application using persistent, non-versioned
key-value stores to use persistent, versioned key-value stores instead, you can
perform the following procedure:
@@ -338,7 +338,7 @@ A read-only state store materialized the data from its
input topic. It also uses
You can use the built-in state store types or implement your own. The primary
interface to implement for the store is
`org.apache.kafka.streams.processor.StateStore`. Kafka Streams also has a few
extended interfaces such as `KeyValueStore` and `VersionedKeyValueStore`.
-Note that your customized `org.apache.kafka.streams.processor.StateStore`
implementation also needs to provide the logic on how to restore the state via
the `org.apache.kafka.streams.processor.StateRestoreCallback` or
`org.apache.kafka.streams.processor.BatchingStateRestoreCallback` interface.
Details on how to instantiate these interfaces can be found in the
[javadocs](/42/javadoc/org/apache/kafka/streams/processor/StateStore.html).
+Note that your customized `org.apache.kafka.streams.processor.StateStore`
implementation also needs to provide the logic on how to restore the state via
the `org.apache.kafka.streams.processor.StateRestoreCallback` or
`org.apache.kafka.streams.processor.BatchingStateRestoreCallback` interface.
Details on how to instantiate these interfaces can be found in the
[javadocs](/{version}/javadoc/org/apache/kafka/streams/processor/StateStore.html).
You also need to provide a "builder" for the store by implementing the
`org.apache.kafka.streams.state.StoreBuilder` interface, which Kafka Streams
uses to create instances of your store.
