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https://issues.apache.org/jira/browse/SPARK-20240?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Apache Spark reassigned SPARK-20240:
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Assignee: (was: Apache Spark)
> SparkSQL support limitations of max dynamic partitions when inserting hive
> table
> --------------------------------------------------------------------------------
>
> Key: SPARK-20240
> URL: https://issues.apache.org/jira/browse/SPARK-20240
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Affects Versions: 1.6.2, 1.6.3, 2.1.0
> Reporter: zenglinxi
>
> We found that HDFS problem occurs sometimes when user have a typo in their
> code while using SparkSQL inserting data into a partition table.
> For Example:
> create table:
> {quote}
> create table test_tb (
> price double,
> ) PARTITIONED BY (day_partition string ,hour_partition string)
> {quote}
> normal sql for inserting table:
> {quote}
> insert overwrite table test_tb partition(day_partition, hour_partition)
> select price, day_partition, hour_partition from other_table;
> {quote}
> sql with typo:
> {quote}
> insert overwrite table test_tb partition(day_partition, hour_partition)
> select hour_partition, day_partition, price from other_table;
> {quote}
> This typo makes SparkSQL take column "price" as "hour_partition", which may
> create million HDFS files in short time if the "other_table" has large data
> with a wide range of "price" and give rise to awful performance of NameNode
> RPC.
> We think it's a good idea to limit the maximum number of files allowed to be
> create by each task for protecting HDFS NameNode from unconscious error.
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