[jira] [Updated] (IGNITE-19369) Metadata topic offset must be stored only after commit

["Nikolay Izhikov (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/IGNITE-19369?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Nikolay Izhikov updated IGNITE-19369:
-------------------------------------
    Priority: Blocker  (was: Minor)

> Metadata topic offset must be stored only after commit
> ------------------------------------------------------
>
>                 Key: IGNITE-19369
>                 URL: https://issues.apache.org/jira/browse/IGNITE-19369
>             Project: Ignite
>          Issue Type: Improvement
>          Components: extensions
>            Reporter: Nikolay Izhikov
>            Assignee: Nikolay Izhikov
>            Priority: Blocker
>              Labels: IEP-59, ise
>
> Currently, when CDC through Kafka is used there are possible delays in replication between clusters when {{KafkaToIgniteCdcStreamerApplier}} tries to update binary metadata and marshaller mappings.
> Delays caused by calls of {{KafkaConsumer#poll}} in {{KafkaToIgniteMetadataUpdater#updateMetadata}} , when meta topic is empty:
> # When first {{KafkaToIgniteCdcStreamerApplier}} meets {{META_UPDATE_MARKER}} it calls {{KafkaToIgniteMetadataUpdater#updateMetadata}} which in turn calls {{KafkaConsumer#poll}}, which returns immediately [1] when data is present in metadata topic. If there are few binary types and mappings to update, first {{KafkaToIgniteCdcStreamerApplier}} will consume all entries from metadata topic. 
> # {{KafkaToIgniteCdcStreamerApplier}} consequently call {{KafkaToIgniteMetadataUpdater#updateMetadata}} for each partition with meta update marker.  All further consequent calls will wait for {{kafkaReqTimeout}}.
> # Also there is a bottleneck, when multiple applier threads tries to update metadata and call synchronized method {{KafkaToIgniteMetadataUpdater#updateMetadata}}, because {{KafkaToIgniteMetadataUpdater}} is shared between applier threads.
> # Because {{META_UPDATE_MARKER}} is sent twice to each Kafka partition of event topic from every node: firstly, in case of type mappings updates, secondly, in case of binary types update there are possible delays up to {{clusterSize x (topicPartitions x 2 - 1) x kafkaReqTimeout}}. 
> # Data updates are blocked for Kafka partitions with unprocessed update markers.
> # For example for default timeout and 16 Kafka partitions _last partition will be consumed after 1.5 minutes_ in case of two one-node clusters.
> Links:
>  # [https://kafka.apache.org/27/javadoc/org/apache/kafka/clients/consumer/KafkaConsumer.html#poll-java.time.Duration-]



--
This message was sent by Atlassian Jira
(v8.20.10#820010)