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Posted to issues@spark.apache.org by "Hyukjin Kwon (JIRA)" <ji...@apache.org> on 2019/01/30 07:18:00 UTC
[jira] [Resolved] (SPARK-26378) Queries of wide CSV/JSON data
slowed after SPARK-26151
[ https://issues.apache.org/jira/browse/SPARK-26378?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Hyukjin Kwon resolved SPARK-26378.
----------------------------------
Resolution: Fixed
Fix Version/s: 3.0.0
Issue resolved by pull request 23336
[https://github.com/apache/spark/pull/23336]
> Queries of wide CSV/JSON data slowed after SPARK-26151
> ------------------------------------------------------
>
> Key: SPARK-26378
> URL: https://issues.apache.org/jira/browse/SPARK-26378
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Affects Versions: 3.0.0
> Reporter: Bruce Robbins
> Assignee: Bruce Robbins
> Priority: Major
> Fix For: 3.0.0
>
>
> A recent change significantly slowed the queries of wide CSV tables. For example, queries against a 6000 column table slowed by 45-48% when queried with a single executor.
>
> The [PR for SPARK-26151|https://github.com/apache/spark/commit/11e5f1bcd49eec8ab4225d6e68a051b5c6a21cb2] changed FailureSafeParser#toResultRow such that the returned function recreates every row, even when the associated input record has no parsing issues and the user specified no corrupt record field in his/her schema. This extra processing is responsible for the slowdown.
> The change to FailureSafeParser also impacted queries of wide JSON tables as well.
> I propose that a row should be recreated only if there is a parsing error or columns need to be shifted due to the existence of a corrupt column field in the user-supplied schema. Otherwise, the row should be used as-is.
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