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https://issues.apache.org/jira/browse/SPARK-19428?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15852882#comment-15852882
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koert kuipers edited comment on SPARK-19428 at 2/4/17 6:10 PM:
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getting a first element for each group (which is somewhat ill defined if the
group is not sorted), or a single row from each group based on the maximum or
minimum of some column, can be easily done with an aggregator.
what is wrong with:
{noformat}
df.groupBy("group").agg(first("somecolumn"))
{noformat}
it wouldn't be hard to write an aggregator that takes some sorting into account
as well to select first element sorted.
was (Author: koert):
getting a first element for each group (which is somewhat ill defined if the
group is not sorted), or a single row from each group based on the maximum or
minimum of some column, can be easily done with an aggregator.
what is wrong with:
df.groupBy("group").agg(first("somecolumn"))
it wouldn't be hard to write an aggregator that takes some sorting into account
as well to select first element sorted.
> Ability to select first row of groupby
> --------------------------------------
>
> Key: SPARK-19428
> URL: https://issues.apache.org/jira/browse/SPARK-19428
> Project: Spark
> Issue Type: Brainstorming
> Components: SQL
> Affects Versions: 2.1.0
> Reporter: Luke Miner
> Priority: Minor
>
> It would be nice to be able to select the first row from {{GroupedData}}.
> Pandas has something like this:
> {{df.groupby('group').first()}}
> It's especially handy if you can order the group as well.
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