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https://issues.apache.org/jira/browse/SPARK-17091?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16065413#comment-16065413
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Michael Styles commented on SPARK-17091:
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By not pushing the filter to Parquet, are we not preventing Parquet from
skipping blocks during read operations? I have tests that show big improvements
when applying this transformation.
For instance, I have a Parquet file with 162,456,394 rows which is sorted on
column C1.
*IN Predicate*
{noformat}
df.filter[df['C1'].isin([42, 139])).collect()
{noformat}
*OR Predicate*
{noformat}
df.filter((df['C1'] == 42) | (df['C1'] == 139)).collect()
{noformat}
I'm seeing about a 50 -75 % improvement.
> ParquetFilters rewrite IN to OR of Eq
> -------------------------------------
>
> Key: SPARK-17091
> URL: https://issues.apache.org/jira/browse/SPARK-17091
> Project: Spark
> Issue Type: Bug
> Reporter: Andrew Duffy
>
> Past attempts at pushing down the InSet operation for Parquet relied on
> user-defined predicates. It would be simpler to rewrite an IN clause into the
> corresponding OR union of a set of equality conditions.
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