You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Andrew Grigorev (Jira)" <ji...@apache.org> on 2021/08/23 18:55:00 UTC

[jira] [Commented] (SPARK-29223) Kafka source: offset by timestamp - allow specifying timestamp for "all partitions"

    [ https://issues.apache.org/jira/browse/SPARK-29223?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17403341#comment-17403341 ] 

Andrew Grigorev commented on SPARK-29223:
-----------------------------------------

Just an idea - couldn't this be implemented in "timestamp field filter pushdown"-like way?

> Kafka source: offset by timestamp - allow specifying timestamp for "all partitions"
> -----------------------------------------------------------------------------------
>
>                 Key: SPARK-29223
>                 URL: https://issues.apache.org/jira/browse/SPARK-29223
>             Project: Spark
>          Issue Type: Improvement
>          Components: SQL, Structured Streaming
>    Affects Versions: 3.1.0
>            Reporter: Jungtaek Lim
>            Assignee: Jungtaek Lim
>            Priority: Minor
>             Fix For: 3.2.0
>
>
> This issue is a follow-up of SPARK-26848.
> In SPARK-26848, we decided to open possibility to let end users set individual timestamp per partition. But in many cases, specifying timestamp represents the intention that we would want to go back to specific timestamp and reprocess records, which should be applied to all topics and partitions.
> According to the format of `startingOffsetsByTimestamp`/`endingOffsetsByTimestamp`, while it's not intuitive to provide an option to set a global timestamp across topic, it's still intuitive to provide an option to set a global timestamp across partitions in a topic.
> This issue tracks the efforts to deal with this.



--
This message was sent by Atlassian Jira
(v8.3.4#803005)

---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org