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From "Neil Parker (JIRA)" <j...@apache.org>
Subject [jira] [Comment Edited] (SPARK-20937) Describe spark.sql.parquet.writeLegacyFormat property in Spark SQL, DataFrames and Datasets Guide
Date Thu, 15 Jun 2017 20:12:00 GMT

    [ https://issues.apache.org/jira/browse/SPARK-20937?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16050999#comment-16050999
] 

Neil Parker edited comment on SPARK-20937 at 6/15/17 8:11 PM:
--------------------------------------------------------------

+1
I ran into an issue recently and took me awhile to find this option


was (Author: nwparker):
+1
I ran into the issue recently and took me awhile to find this option

> 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
>            Priority: Trivial
>
> 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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