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https://issues.apache.org/jira/browse/SPARK-17436?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Ran Haim updated SPARK-17436:
-----------------------------
    Description: 
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.



  was:
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.


> 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
>
> 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.



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