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apache · Jul 12, 2020 · 99493e4 · 99493e4
1 parent a0366f2
commit 99493e4
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Showing 2 changed files with 2 additions and 33 deletions.
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/exchange/EnsureRequirements.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/exchange/EnsureRequirements.scala
@@ -184,8 +184,8 @@ case class EnsureRequirements(conf: SQLConf) extends Rule[SparkPlan] {
   }
 
   /**
-   * Recursively reorders the join keys based on the partitioning. It starts reordering
-   * keys to match HashPartitioning on either side, followed by PartitioningCollection.
+   * Recursively reorders the join keys based on partitioning. It starts reordering the
+   * join keys to match HashPartitioning on either side, followed by PartitioningCollection.
    */
   private def reorderJoinKeysRecursively(
       leftKeys: Seq[Expression],

diff --git a/sql/core/src/test/scala/org/apache/spark/sql/sources/BucketedReadSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/sources/BucketedReadSuite.scala
@@ -943,37 +943,6 @@ abstract class BucketedReadSuite extends QueryTest with SQLTestUtils {
     }
   }
 
-  test("terry - hashpartitioning") {
-    withTable("t1", "t2") {
-      withSQLConf(
-        SQLConf.AUTO_BROADCASTJOIN_THRESHOLD.key -> "0",
-        SQLConf.SHUFFLE_PARTITIONS.key -> "4") {
-        val df1 = (0 until 10).map(i => (i % 5, i % 13)).toDF("i1", "j1")
-        val df2 = (0 until 10).map(i => (i % 7, i % 11)).toDF("i2", "j2")
-
-        df1.write.format("parquet").bucketBy(4, "i1", "j1").saveAsTable("t1")
-        df2.write.format("parquet").bucketBy(4, "i2", "j2").saveAsTable("t2")
-
-        val t1 = spark.table("t1")
-        val t2 = spark.table("t2")
-        val join = t1.join(t2, t1("i1") === t2("j2") && t1("i1") === t2("i2"))
-        join.explain
-      }
-    }
-  }
-
-
-  test("terry - collectionpartition") {
-    withSQLConf(SQLConf.AUTO_BROADCASTJOIN_THRESHOLD.key -> "0") {
-      val df1 = (0 until 100).map(i => (i % 5, i % 13, i.toString)).toDF("i1", "j1", "k1")
-      val df2 = (0 until 100).map(i => (i % 7, i % 11, i.toString)).toDF("i2", "j2", "k2")
-      val df3 = (0 until 100).map(i => (i % 5, i % 13, i.toString)).toDF("i3", "j3", "k3")
-      val join = df1.join(df2, df1("i1") === df2("i2") && df1("j1") === df2("j2"))
-      val join2 = join.join(df3, join("j1") === df3("j3") && join("i1") === df3("i3"))
-      join2.explain
-    }
-  }
-
   test("bucket coalescing is applied when join expressions match with partitioning expressions") {
     withTable("t1", "t2") {
       df1.write.format("parquet").bucketBy(8, "i", "j").saveAsTable("t1")