[jira] [Created] (SPARK-25368) Incorrect predicate pushdown returns in incorrect result

["Lev Katzav (JIRA)" <ji...@apache.org>]

Lev Katzav created SPARK-25368:
----------------------------------

             Summary: Incorrect predicate pushdown returns in incorrect result
                 Key: SPARK-25368
                 URL: https://issues.apache.org/jira/browse/SPARK-25368
             Project: Spark
          Issue Type: Bug
          Components: Optimizer, SQL
    Affects Versions: 2.3.1, 2.3.2
            Reporter: Lev Katzav


there is a breaking change in spark 2.3 (I checked on 2.3.1 and 2.3.2-rc5)

the following code recreates the problem
(it's a bit convoluted examples, I tried to simplify it as much as possible from my code)
{code:java}
import org.apache.spark.sql.{DataFrame, SQLContext}
import org.apache.spark.sql.expressions.Window
import org.apache.spark.sql.functions._

import spark.implicits._

case class Data(a: Option[Int],b: String,c: Option[String],d: String)

val df1 = spark.createDataFrame(Seq(
   Data(Some(1), "1", None, "1"),
   Data(None, "2", Some("2"), "2")
))

val df2 = df1
.where( $"a".isNotNull)
.withColumn("e", lit(null).cast("string"))

val columns = df2.columns.map(c => col(c))

val df3 = df1
.select(
  $"c",
  $"b" as "e"
  )
  .withColumn("a", lit(null).cast("int"))
  .withColumn("b", lit(null).cast("string"))
  .withColumn("d", lit(null).cast("string"))
  .select(columns :_*)

val df4 =
  df2.union(df3)
  .withColumn("e", last(col("e"), ignoreNulls = true).over(Window.partitionBy($"c").orderBy($"d")))
  .filter($"a".isNotNull)

df4.show

{code}
 

notice that the last statement in for df4 is to filter rows where a is null

in spark 2.2.1, the above code prints:
{code:java}
+---+---+----+---+---+ 
| a| b| c| d| e|
 +---+---+----+---+---+ 
| 1| 1|null| 1| 1| 
+---+---+----+---+---+
{code}
in spark 2.3.x, it prints: 
{code:java}
+----+----+----+----+---+ 
| a| b| c| d| e| 
+----+----+----+----+---+ 
|null|null|null|null| 1| 
| 1| 1|null| 1| 1| 
|null|null| 2|null| 2|
 +----+----+----+----+---+
{code}
 the column a still contains null values

 



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