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https://issues.apache.org/jira/browse/SPARK-20937?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16050999#comment-16050999
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Neil Parker commented on SPARK-20937:
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+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.ka...@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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