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Apache Kafka 3.4 - New Features & Improvements

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Manage episode 354728138 series 2355972
Contenu fourni par Confluent, founded by the original creators of Apache Kafka® and Founded by the original creators of Apache Kafka®. Tout le contenu du podcast, y compris les épisodes, les graphiques et les descriptions de podcast, est téléchargé et fourni directement par Confluent, founded by the original creators of Apache Kafka® and Founded by the original creators of Apache Kafka® ou son partenaire de plateforme de podcast. Si vous pensez que quelqu'un utilise votre œuvre protégée sans votre autorisation, vous pouvez suivre le processus décrit ici https://fr.player.fm/legal.

Apache Kafka® 3.4 is released! In this special episode, Danica Fine (Senior Developer Advocate, Confluent), shares highlights of the Apache Kafka 3.4 release. This release introduces new KIPs in Kafka Core, Kafka Streams, and Kafka Connect.
In Kafka Core:

  • KIP-792 expands the metadata each group member passes to the group leader in its JoinGroup subscription to include the highest stable generation that consumer was a part of.
  • KIP-830 includes a new configuration setting that allows you to disable the JMX reporter for environments where it’s not being used.
  • KIP-854 introduces changes to clean up producer IDs more efficiently, to avoid excess memory usage. It introduces a new timeout parameter that affects the expiry of producer IDs and updates the old parameter to only affect the expiry of transaction IDs.
  • KIP-866 (early access) provides a bridge to migrate between existing Zookeeper clusters to new KRaft mode clusters, enabling the migration of existing metadata from Zookeeper to KRaft.
  • KIP-876 adds a new property that defines the maximum amount of time that the server will wait to generate a snapshot; the default is 1 hour.
  • KIP-881, an extension of KIP-392, makes it so that consumers can now be rack-aware when it comes to partition assignments and consumer rebalancing.

In Kafka Streams:

  • KIP-770 updates some Kafka Streams configs and metrics related to the record cache size.
  • KIP-837 allows users to multicast result records to every partition of downstream sink topics and adds functionality for users to choose to drop result records without sending.

And finally, for Kafka Connect:

  • KIP-787 allows users to run MirrorMaker2 with custom implementations for the Kafka resource manager and makes it easier to integrate with your ecosystem.

Tune in to learn more about the Apache Kafka 3.4 release!
EPISODE LINKS

  continue reading

Chapitres

1. Intro (00:00:00)

2. KIP-866: ZooKeeper to KRaft cluster upgrade (00:00:23)

3. KIP-830: Allow disabling JMX Reporter (00:00:57)

4. KIP-881: Rack-aware Partition Assignment for Kafka Consumers (00:01:31)

5. KIP-876: Time based Cluster Metadata Snapshots (00:02:08)

6. KIP-854: Separate configuration for producer ID expiry (00:02:38)

7. KIP-837: Allow MultiCasting a Result Record (00:03:31)

8. KIP-787: MM2 manage Kafka resources with custom Admin implementations (00:04:12)

9. It's a wrap! (00:04:47)

265 episodes

Artwork
iconPartager
 
Manage episode 354728138 series 2355972
Contenu fourni par Confluent, founded by the original creators of Apache Kafka® and Founded by the original creators of Apache Kafka®. Tout le contenu du podcast, y compris les épisodes, les graphiques et les descriptions de podcast, est téléchargé et fourni directement par Confluent, founded by the original creators of Apache Kafka® and Founded by the original creators of Apache Kafka® ou son partenaire de plateforme de podcast. Si vous pensez que quelqu'un utilise votre œuvre protégée sans votre autorisation, vous pouvez suivre le processus décrit ici https://fr.player.fm/legal.

Apache Kafka® 3.4 is released! In this special episode, Danica Fine (Senior Developer Advocate, Confluent), shares highlights of the Apache Kafka 3.4 release. This release introduces new KIPs in Kafka Core, Kafka Streams, and Kafka Connect.
In Kafka Core:

  • KIP-792 expands the metadata each group member passes to the group leader in its JoinGroup subscription to include the highest stable generation that consumer was a part of.
  • KIP-830 includes a new configuration setting that allows you to disable the JMX reporter for environments where it’s not being used.
  • KIP-854 introduces changes to clean up producer IDs more efficiently, to avoid excess memory usage. It introduces a new timeout parameter that affects the expiry of producer IDs and updates the old parameter to only affect the expiry of transaction IDs.
  • KIP-866 (early access) provides a bridge to migrate between existing Zookeeper clusters to new KRaft mode clusters, enabling the migration of existing metadata from Zookeeper to KRaft.
  • KIP-876 adds a new property that defines the maximum amount of time that the server will wait to generate a snapshot; the default is 1 hour.
  • KIP-881, an extension of KIP-392, makes it so that consumers can now be rack-aware when it comes to partition assignments and consumer rebalancing.

In Kafka Streams:

  • KIP-770 updates some Kafka Streams configs and metrics related to the record cache size.
  • KIP-837 allows users to multicast result records to every partition of downstream sink topics and adds functionality for users to choose to drop result records without sending.

And finally, for Kafka Connect:

  • KIP-787 allows users to run MirrorMaker2 with custom implementations for the Kafka resource manager and makes it easier to integrate with your ecosystem.

Tune in to learn more about the Apache Kafka 3.4 release!
EPISODE LINKS

  continue reading

Chapitres

1. Intro (00:00:00)

2. KIP-866: ZooKeeper to KRaft cluster upgrade (00:00:23)

3. KIP-830: Allow disabling JMX Reporter (00:00:57)

4. KIP-881: Rack-aware Partition Assignment for Kafka Consumers (00:01:31)

5. KIP-876: Time based Cluster Metadata Snapshots (00:02:08)

6. KIP-854: Separate configuration for producer ID expiry (00:02:38)

7. KIP-837: Allow MultiCasting a Result Record (00:03:31)

8. KIP-787: MM2 manage Kafka resources with custom Admin implementations (00:04:12)

9. It's a wrap! (00:04:47)

265 episodes

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