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https://issues.apache.org/jira/browse/SPARK-19428?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15852893#comment-15852893
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Hyukjin Kwon commented on SPARK-19428:
--------------------------------------
[~lminer], another workaround might be (with {{from pyspark.sql import
functions as F}}) ..
{code}
cols = [F.first(f.name) for f in df.schema.fields]
df.groupBy('A').agg(*cols).show()
{code}
prints
{code}
+---+---------------+---------------+
| A|first(A, false)|first(B, false)|
+---+---------------+---------------+
| 1| 1| 4|
| 3| 3| 7|
| 2| 2| 5|
+---+---------------+---------------+
{code}
It seems a pretty simple workaround.
> 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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