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Posted to issues@spark.apache.org by "jinhai (Jira)" <ji...@apache.org> on 2020/10/20 04:10:00 UTC

[jira] [Updated] (SPARK-33187) Add a check on the number of returned partitions in the HiveShim#getPartitionsByFilter method

     [ https://issues.apache.org/jira/browse/SPARK-33187?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

jinhai updated SPARK-33187:
---------------------------
    Description: 
In the method HiveShim#getPartitionsByFilter, when filter is empty or when the hive table has a large number of partitions, calling getAllPartitionsMethod or getPartitionsByFilterMethod will results in Driver OOM.

I think we need add a check on the number of returned partitions by calling Hive#getNumPartitionsByFilter, and add SQLConf spark.sql.hive.exceeded.partition.limit, default value is 100_000

  was:
In the method HiveShim#getPartitionsByFilter, will invoke getAllPartitionsMethod when filter is empty or when the hive table has a large number of partitions, calling getPartitionsByFilterMethod results in Driver OOM.

I think we need add a check on the number of returned partitions by calling Hive#getNumPartitionsByFilter, and add SQLConf spark.sql.hive.exceeded.partition.limit, default value is 100_000


> Add a check on the number of returned partitions in the HiveShim#getPartitionsByFilter method
> ---------------------------------------------------------------------------------------------
>
>                 Key: SPARK-33187
>                 URL: https://issues.apache.org/jira/browse/SPARK-33187
>             Project: Spark
>          Issue Type: Improvement
>          Components: SQL
>    Affects Versions: 3.0.1
>            Reporter: jinhai
>            Priority: Major
>
> In the method HiveShim#getPartitionsByFilter, when filter is empty or when the hive table has a large number of partitions, calling getAllPartitionsMethod or getPartitionsByFilterMethod will results in Driver OOM.
> I think we need add a check on the number of returned partitions by calling Hive#getNumPartitionsByFilter, and add SQLConf spark.sql.hive.exceeded.partition.limit, default value is 100_000



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