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Posted to issues@spark.apache.org by "Sergei (JIRA)" <ji...@apache.org> on 2018/09/18 06:40:00 UTC
[jira] [Issue Comment Deleted] (SPARK-20937) Describe
spark.sql.parquet.writeLegacyFormat property in Spark SQL, DataFrames and
Datasets Guide
[ https://issues.apache.org/jira/browse/SPARK-20937?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Sergei updated SPARK-20937:
---------------------------
Comment: was deleted
(was: do you remember what did you do with it finally? )
> 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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