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https://issues.apache.org/jira/browse/SPARK-43106?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17717882#comment-17717882
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kalyan s commented on SPARK-43106:
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Thank you for the response [~dongjoon] .
Most of the workloads have been running on 2.4, while we have made good
progress moving workloads to 3.X this year.
We notice this in a few long-running workloads on static
partitions/unpartitioned datasets.
While HDFS has been our primary storage backend, moving to object stores on GCP
has been making this problem more pronounced, due to inherent slowness in
writing to these.
[~vaibhavb] can you share some test code to help here?
> Data lost from the table if the INSERT OVERWRITE query fails
> ------------------------------------------------------------
>
> Key: SPARK-43106
> URL: https://issues.apache.org/jira/browse/SPARK-43106
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 3.3.2
> Reporter: Vaibhav Beriwala
> Priority: Major
>
> When we run an INSERT OVERWRITE query for an unpartitioned table on Spark-3,
> Spark has the following behavior:
> 1) It will first clean up all the data from the actual table path.
> 2) It will then launch a job that performs the actual insert.
>
> There are 2 major issues with this approach:
> 1) If the insert job launched in step 2 above fails for any reason, the data
> from the original table is lost.
> 2) If the insert job in step 2 above takes a huge time to complete, then
> table data is unavailable to other readers for the entire duration the job
> takes.
> This behavior is the same even for the partitioned tables when using static
> partitioning. For dynamic partitioning, we do not delete the table data
> before the job launch.
>
> Is there a reason as to why we perform this delete before the job launch and
> not as part of the Job commit operation? This issue is not there with Hive -
> where the data is cleaned up as part of the Job commit operation probably. As
> part of SPARK-19183, we did add a new hook in the commit protocol for this
> exact same purpose, but seems like its default behavior is still to delete
> the table data before the job launch.
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