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https://issues.apache.org/jira/browse/CASSANDRA-10707?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15179895#comment-15179895
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Benjamin Lerer commented on CASSANDRA-10707:
--------------------------------------------
||patch||utests||dtests||
|[trunk|https://github.com/apache/cassandra/compare/trunk...blerer:10707-trunk]|[trunk|http://cassci.datastax.com/view/Dev/view/blerer/job/blerer-10707-trunk-testall/]|[trunk|http://cassci.datastax.com/view/Dev/view/blerer/job/blerer-10707-trunk-dtest/]|
I have pushed new commits to handle the last review comments.
The patch does not fix yet the problem of shortRead but the current
implementation is definitely broken. As {{countedInCurrentPartition()}} is not
overridden the row count is used to compute the number of rows to fetch but the
limit is then set in term of groups.
I have to take something to properly investigate this problem.
{quote}In the news file, you have IN restrictions with only one element are now
considered as equality restrictions. What does that mean for the user?{quote}
Some queries which use to be rejected will suddenly get accepted like
multipartitions-queries with {{ORDER BY}} and paging.
Some error messages will also be slightly different.
I removed the entry for now as I agree that it might not be fully relevant for
the users.
> Add support for Group By to Select statement
> --------------------------------------------
>
> Key: CASSANDRA-10707
> URL: https://issues.apache.org/jira/browse/CASSANDRA-10707
> Project: Cassandra
> Issue Type: Improvement
> Components: CQL
> Reporter: Benjamin Lerer
> Assignee: Benjamin Lerer
>
> Now that Cassandra support aggregate functions, it makes sense to support
> {{GROUP BY}} on the {{SELECT}} statements.
> It should be possible to group either at the partition level or at the
> clustering column level.
> {code}
> SELECT partitionKey, max(value) FROM myTable GROUP BY partitionKey;
> SELECT partitionKey, clustering0, clustering1, max(value) FROM myTable GROUP
> BY partitionKey, clustering0, clustering1;
> {code}
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