[jira] [Created] (SPARK-26057) Table joining is broken in Spark 2.4

["Pavel Parkhomanko (JIRA)" <ji...@apache.org>]

Pavel Parkhomanko created SPARK-26057:
-----------------------------------------

             Summary: Table joining is broken in Spark 2.4
                 Key: SPARK-26057
                 URL: https://issues.apache.org/jira/browse/SPARK-26057
             Project: Spark
          Issue Type: Bug
          Components: SQL
    Affects Versions: 2.4.0
            Reporter: Pavel Parkhomanko


This sample works in spark-shell 2.3.1 and throws an exception in 2.4.0
{code:java}
import java.util.Arrays.asList
import org.apache.spark.sql.Row
import org.apache.spark.sql.types._

spark.createDataFrame(
  asList(
    Row("1-1", "sp", 6),
    Row("1-1", "pc", 5),
    Row("1-2", "pc", 4),
    Row("2-1", "sp", 3),
    Row("2-2", "pc", 2),
    Row("2-2", "sp", 1)
  ),
  StructType(List(StructField("id", StringType), StructField("layout", StringType), StructField("n", IntegerType)))
).createOrReplaceTempView("cc")

spark.createDataFrame(
  asList(
    Row("sp", 1),
    Row("sp", 1),
    Row("sp", 2),
    Row("sp", 3),
    Row("sp", 3),
    Row("sp", 4),
    Row("sp", 5),
    Row("sp", 5),
    Row("pc", 1),
    Row("pc", 2),
    Row("pc", 2),
    Row("pc", 3),
    Row("pc", 4),
    Row("pc", 4),
    Row("pc", 5)
  ),
  StructType(List(StructField("layout", StringType), StructField("ts", IntegerType)))
).createOrReplaceTempView("p")

spark.createDataFrame(
 asList(
    Row("1-1", "sp", 1),
    Row("1-1", "sp", 2),
    Row("1-1", "pc", 3),
    Row("1-2", "pc", 3),
    Row("1-2", "pc", 4),
    Row("2-1", "sp", 4),
    Row("2-1", "sp", 5),
    Row("2-2", "pc", 6),
    Row("2-2", "sp", 6)
  ),
  StructType(List(StructField("id", StringType), StructField("layout", StringType), StructField("ts", IntegerType)))
).createOrReplaceTempView("c")

spark.sql("""
SELECT cc.id, cc.layout, count(*) as m
  FROM cc
  JOIN p USING(layout)
  WHERE EXISTS(SELECT 1 FROM c WHERE c.id = cc.id AND c.layout = cc.layout AND c.ts > p.ts)
  GROUP BY cc.id, cc.layout
""").createOrReplaceTempView("pcc")

spark.sql("SELECT * FROM pcc ORDER BY id, layout").show

spark.sql("""
SELECT cc.id, cc.layout, n, m
  FROM cc
  LEFT OUTER JOIN pcc ON pcc.id = cc.id AND pcc.layout = cc.layout
""").createOrReplaceTempView("k")

spark.sql("SELECT * FROM k ORDER BY id, layout").show

{code}
Actually I tried to catch another bug: similar calculations with joins and nested queries have different results in Spark 2.3.1 and 2.4.0, but when I tried to create a minimal example I received exception
{code:java}
java.lang.RuntimeException: Couldn't find id#0 in [id#38,layout#39,ts#7,id#10,layout#11,ts#12]
{code}



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