[jira] [Created] (SPARK-24934) Should handle missing upper/lower bounds cases in in-memory partition pruning

["Hyukjin Kwon (JIRA)" <ji...@apache.org>]

Hyukjin Kwon created SPARK-24934:
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             Summary: Should handle missing upper/lower bounds cases in in-memory partition pruning
                 Key: SPARK-24934
                 URL: https://issues.apache.org/jira/browse/SPARK-24934
             Project: Spark
          Issue Type: Bug
          Components: SQL
    Affects Versions: 2.4.0
            Reporter: Hyukjin Kwon


For example, if array is used (where the lower and upper bounds for its column batch are {{null}})), it looks wrongly filtering all data out:

{code}
scala> import org.apache.spark.sql.functions
import org.apache.spark.sql.functions

scala> val df = Seq(Array("a", "b"), Array("c", "d")).toDF("arrayCol")
df: org.apache.spark.sql.DataFrame = [arrayCol: array<string>]

scala> df.filter(df.col("arrayCol").eqNullSafe(functions.array(functions.lit("a"), functions.lit("b")))).show()
+--------+
|arrayCol|
+--------+
|  [a, b]|
+--------+


scala> df.cache().filter(df.col("arrayCol").eqNullSafe(functions.array(functions.lit("a"), functions.lit("b")))).show()
+--------+
|arrayCol|
+--------+
+--------+
{code}



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