[jira] [Updated] (SPARK-26378) Queries of wide CSV/JSON data slowed after SPARK-26151

["Bruce Robbins (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-26378?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Bruce Robbins updated SPARK-26378:
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    Summary: Queries of wide CSV/JSON data slowed after SPARK-26151  (was: Queries of wide CSV data slowed after SPARK-26151)

> 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
>            Priority: Major
>
> 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.
>   
>  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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