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Posted to issues@spark.apache.org by "Bruce Robbins (JIRA)" <ji...@apache.org> on 2018/12/15 22:44:00 UTC

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

Bruce Robbins created SPARK-26378:
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             Summary: Queries of wide CSV 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


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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