[jira] [Resolved] (SPARK-20937) Describe spark.sql.parquet.writeLegacyFormat property in Spark SQL, DataFrames and Datasets Guide

["Hyukjin Kwon (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-20937?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Hyukjin Kwon resolved SPARK-20937.
----------------------------------
       Resolution: Fixed
    Fix Version/s: 2.4.1
                   2.5.0

Issue resolved by pull request 22453
[https://github.com/apache/spark/pull/22453]

> Describe spark.sql.parquet.writeLegacyFormat property in Spark SQL, DataFrames and Datasets Guide
> -------------------------------------------------------------------------------------------------
>
>                 Key: SPARK-20937
>                 URL: https://issues.apache.org/jira/browse/SPARK-20937
>             Project: Spark
>          Issue Type: Improvement
>          Components: Documentation, SQL
>    Affects Versions: 2.3.0
>            Reporter: Jacek Laskowski
>            Assignee: Chenxiao Mao
>            Priority: Trivial
>             Fix For: 2.5.0, 2.4.1
>
>
> As a follow-up to SPARK-20297 (and SPARK-10400) in which {{spark.sql.parquet.writeLegacyFormat}} property was recommended for Impala and Hive, Spark SQL docs for [Parquet Files|https://spark.apache.org/docs/latest/sql-programming-guide.html#configuration] should have it documented.
> p.s. It was asked about in [Why can't Impala read parquet files after Spark SQL's write?|https://stackoverflow.com/q/44279870/1305344] on StackOverflow today.
> p.s. It's also covered in [~holden.karau@gmail.com]'s "High Performance Spark: Best Practices for Scaling and Optimizing Apache Spark" book (in Table 3-10. Parquet data source options) that gives the option some wider publicity.



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