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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