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Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2015/12/10 04:47:10 UTC
[jira] [Commented] (SPARK-8887) Explicitly define which data types
can be used as dynamic partition columns
[ https://issues.apache.org/jira/browse/SPARK-8887?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15049984#comment-15049984 ]
Apache Spark commented on SPARK-8887:
-------------------------------------
User 'yjshen' has created a pull request for this issue:
https://github.com/apache/spark/pull/8201
> Explicitly define which data types can be used as dynamic partition columns
> ---------------------------------------------------------------------------
>
> Key: SPARK-8887
> URL: https://issues.apache.org/jira/browse/SPARK-8887
> Project: Spark
> Issue Type: Sub-task
> Components: SQL
> Affects Versions: 1.4.0, 1.5.0
> Reporter: Cheng Lian
> Assignee: Yijie Shen
> Fix For: 1.6.0
>
>
> {{InsertIntoHadoopFsRelation}} implements Hive compatible dynamic partitioning insertion, which uses {{String.valueOf}} to write encode partition column values into dynamic partition directories. This actually limits the data types that can be used in partition column. For example, string representation of {{StructType}} values is not well defined. However, this limitation is not explicitly enforced.
> There are several things we can improve:
> # Enforce dynamic column data type requirements by adding analysis rules and throws {{AnalysisException}} when violation occurs.
> # Abstract away string representation of various data types, so that we don't need to convert internal representation types (e.g. {{UTF8String}}) to external types (e.g. {{String}}). A set of Hive compatible implementations should be provided to ensure compatibility with Hive.
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