[jira] [Commented] (SPARK-25206) Wrong data may be returned when enable pushdown

["Wenchen Fan (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-25206?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16589914#comment-16589914 ] 

Wenchen Fan commented on SPARK-25206:
-------------------------------------

SGTM. We should backport it with a regression test, and also add the test to the master branch.

> Wrong data may be returned when enable pushdown
> -----------------------------------------------
>
>                 Key: SPARK-25206
>                 URL: https://issues.apache.org/jira/browse/SPARK-25206
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 2.3.1
>            Reporter: yucai
>            Priority: Major
>
> In current Spark 2.3.1, below query returns wrong data silently.
> {code:java}
> spark.range(10).write.parquet("/tmp/data")
> sql("DROP TABLE t")
> sql("CREATE TABLE t (ID LONG) USING parquet LOCATION '/tmp/data'")
> scala> sql("select * from t where id > 0").show
> +---+
> | ID|
> +---+
> +---+{code}
>  
> *Root Cause*
> Spark pushdowns FilterApi.gt(intColumn("{color:#ff0000}ID{color}"), 0: Integer) into parquet, but {color:#ff0000}ID{color} does not exist in /tmp/data (parquet is case sensitive, it has {color:#ff0000}id{color} actually).
> So no records are returned.
> In Spark 2.1, the user will get Exception:
> {code:java}
> Caused by: java.lang.IllegalArgumentException: Column [ID] was not found in schema!{code}
> But in Spark 2.3, they will get the wrong results sliently.
>  
> Since SPARK-24716, Spark uses Parquet schema instead of Hive metastore schema to do the pushdown, perfect for this issue.
> [~yumwang], [~cloud_fan], [~smilegator], any thoughts? Should we backport it?



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