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https://issues.apache.org/jira/browse/SPARK-20144?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15950988#comment-15950988
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Sean Owen commented on SPARK-20144:
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If the data were sorted, sorting would be pretty cheap, in general. Correctness
has to take precedence in any event, if you're describing this as a blocker for
you.
I don't believe projection can change ordering, no. I am saying that I would
not necessarily expect that to extend to external serialization. I don't see
that being tabular or on HDFS matters. I think some serializations would
naturally preserve order and others would not. I am still not 100% sure what
the expected semantics of Parquet are here, but you have de facto evidence it
is not guaranteed.
> spark.read.parquet no long maintains ordering of the data
> ---------------------------------------------------------
>
> Key: SPARK-20144
> URL: https://issues.apache.org/jira/browse/SPARK-20144
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 2.0.2
> Reporter: Li Jin
>
> Hi, We are trying to upgrade Spark from 1.6.3 to 2.0.2. One issue we found is
> when we read parquet files in 2.0.2, the ordering of rows in the resulting
> dataframe is not the same as the ordering of rows in the dataframe that the
> parquet file was reproduced with.
> This is because FileSourceStrategy.scala combines the parquet files into
> fewer partitions and also reordered them. This breaks our workflows because
> they assume the ordering of the data.
> Is this considered a bug? Also FileSourceStrategy and FileSourceScanExec
> changed quite a bit from 2.0.2 to 2.1, so not sure if this is an issue with
> 2.1.
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