You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "kant kodali (JIRA)" <ji...@apache.org> on 2017/10/11 04:58:00 UTC
[jira] [Commented] (SPARK-21641) Combining windowing (groupBy) and
mapGroupsWithState (groupByKey) in Spark Structured Streaming
[ https://issues.apache.org/jira/browse/SPARK-21641?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16199811#comment-16199811 ]
kant kodali commented on SPARK-21641:
-------------------------------------
[~marmbrus]
> Combining windowing (groupBy) and mapGroupsWithState (groupByKey) in Spark Structured Streaming
> -----------------------------------------------------------------------------------------------
>
> Key: SPARK-21641
> URL: https://issues.apache.org/jira/browse/SPARK-21641
> Project: Spark
> Issue Type: Improvement
> Components: Structured Streaming
> Affects Versions: 2.2.0
> Reporter: Tudor Miu
>
> Given a stream of timestamped data with watermarking, there seems to be no way to combine (1) the {{groupBy}} operation to achieve windowing by the timestamp field and other grouping criteria with (2) the {{groupByKey}} operation in order to apply {{mapGroupsWithState }}to the groups for custom sessionization.
> For context:
> - calling {{groupBy}}, which supports windowing, on a Dataset returns a {{RelationalGroupedDataset}} which does not have {{mapGroupsWithState}}.
> - calling {{groupByKey}}, which supports {{mapGroupsWithState}}, returns a {{KeyValueGroupedDataset}}, but that has no support for windowing.
> The suggestion is to _somehow_ unify the two APIs.
--
This message was sent by Atlassian JIRA
(v6.4.14#64029)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org