agrawaldevesh commented on a change in pull request #29342:
URL: https://github.com/apache/spark/pull/29342#discussion_r470211909
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File path: sql/core/src/test/scala/org/apache/spark/sql/JoinSuite.scala
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@@ -1188,4 +1188,53 @@ class JoinSuite extends QueryTest with
SharedSparkSession with AdaptiveSparkPlan
classOf[BroadcastNestedLoopJoinExec]))
}
}
+
+ test("SPARK-32399: Full outer shuffled hash join") {
+ val inputDFs = Seq(
+ // Test unique join key
+ (spark.range(10).selectExpr("id as k1"),
+ spark.range(30).selectExpr("id as k2"),
+ $"k1" === $"k2"),
+ // Test non-unique join key
+ (spark.range(10).selectExpr("id % 5 as k1"),
+ spark.range(30).selectExpr("id % 5 as k2"),
+ $"k1" === $"k2"),
+ // Test string join key
+ (spark.range(10).selectExpr("cast(id * 3 as string) as k1"),
+ spark.range(30).selectExpr("cast(id as string) as k2"),
+ $"k1" === $"k2"),
+ // Test build side at right
+ (spark.range(30).selectExpr("cast(id / 3 as string) as k1"),
+ spark.range(10).selectExpr("cast(id as string) as k2"),
+ $"k1" === $"k2"),
+ // Test NULL join key
+ (spark.range(10).map(i => if (i % 2 == 0) i else null).selectExpr("value
as k1"),
+ spark.range(30).map(i => if (i % 4 == 0) i else
null).selectExpr("value as k2"),
+ $"k1" === $"k2"),
+ // Test multiple join keys
+ (spark.range(10).map(i => if (i % 2 == 0) i else null).selectExpr(
+ "value as k1", "cast(value % 5 as short) as k2", "cast(value * 3 as
long) as k3"),
+ spark.range(30).map(i => if (i % 4 == 0) i else null).selectExpr(
+ "value as k4", "cast(value % 5 as short) as k5", "cast(value * 3 as
long) as k6"),
+ $"k1" === $"k4" && $"k2" === $"k5" && $"k3" === $"k6")
+ )
+ inputDFs.foreach { case (df1, df2, joinExprs) =>
+ withSQLConf(
+ SQLConf.AUTO_BROADCASTJOIN_THRESHOLD.key -> "80",
Review comment:
Okay fine :-P the assert on line 1234 convinces me that the magic number
"works". Tricking this thing to use SHJ is hard !.
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