[jira] [Comment Edited] (SPARK-21641) Combining windowing (groupBy) and mapGroupsWithState (groupByKey) in Spark Structured Streaming
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https://issues.apache.org/jira/browse/SPARK-21641?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16199811#comment-16199811
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kant kodali edited comment on SPARK-21641 at 10/11/17 4:58 AM:
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@[~marmbrus] When can we possibly expect this?
was (Author: kant):
@[~marmbrus] When can we possible expect this?
> 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.
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[jira] [Comment Edited] (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=16199811#comment-16199811
]
kant kodali edited comment on SPARK-21641 at 10/11/17 4:58 AM:
---
@[~marmbrus] When can we possible expect this?
was (Author: kant):
[~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.
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