[
https://issues.apache.org/jira/browse/SPARK-17436?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15836847#comment-15836847
]
Jason Moore commented on SPARK-17436:
-------------------------------------
Ahh, I think you are correct. The issue on the write seems to be resolved as
of 2.1+ (checked using parquet-tools).
On a read, some optimizations were made in
https://github.com/apache/spark/pull/12095 that would mean that some files may
get merged into a single partition (which will almost certainly be not sorted).
I mentioned the issue mailing list, but had missed the (useful) responses:
http://apache-spark-developers-list.1001551.n3.nabble.com/Sorting-within-partitions-is-not-maintained-in-parquet-td18618.html
If I set spark.sql.files.openCostInBytes very high, the re-read test now seems
fine.
Thanks!
> dataframe.write sometimes does not keep sorting
> -----------------------------------------------
>
> Key: SPARK-17436
> URL: https://issues.apache.org/jira/browse/SPARK-17436
> Project: Spark
> Issue Type: Bug
> Affects Versions: 1.6.1, 1.6.2, 2.0.0
> Reporter: Ran Haim
> Priority: Minor
>
> update
> ***************
> It seems that in spark 2.1 code, the sorting issue is resolved.
> The sorter does consider inner sorting in the sorting key - but I think it
> will be faster to just insert the rows to a list in a hash map.
> ***************
> When using partition by, datawriter can sometimes mess up an ordered
> dataframe.
> The problem originates in
> org.apache.spark.sql.execution.datasources.DynamicPartitionWriterContainer.
> In the writeRows method when too many files are opened (configurable), it
> starts inserting rows to UnsafeKVExternalSorter, then it reads all the rows
> again from the sorter and writes them to the corresponding files.
> The problem is that the sorter actually sorts the rows using the partition
> key, and that can sometimes mess up the original sort (or secondary sort if
> you will).
> I think the best way to fix it is to stop using a sorter, and just put the
> rows in a map using key as partition key and value as an arraylist, and then
> just walk through all the keys and write it in the original order - this will
> probably be faster as there no need for ordering.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
