[SPARK-6231][SQL/DF] Automatically resolve join condition ambiguity for self-joins.

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/namedExpressions.scala

@@ -171,6 +171,11 @@ case class AttributeReference(
     val exprId: ExprId = NamedExpression.newExprId,
     val qualifiers: Seq[String] = Nil) extends Attribute with trees.LeafNode[Expression] {
 
+  /**
+   * Returns true iff the expression id is the same for both attributes.
+   */
+  def sameRef(other: AttributeReference): Boolean = this.exprId == other.exprId
+
   override def equals(other: Any): Boolean = other match {
     case ar: AttributeReference => name == ar.name && exprId == ar.exprId && dataType == ar.dataType
     case _ => false

sql/core/src/main/scala/org/apache/spark/sql/DataFrame.scala

@@ -416,9 +416,7 @@ class DataFrame private[sql](
    * }}}
    * @group dfops
    */
-  def join(right: DataFrame, joinExprs: Column): DataFrame = {
-    Join(logicalPlan, right.logicalPlan, joinType = Inner, Some(joinExprs.expr))
-  }
+  def join(right: DataFrame, joinExprs: Column): DataFrame = join(right, joinExprs, "inner")
 
   /**
    * Join with another [[DataFrame]], using the given join expression. The following performs
@@ -440,7 +438,39 @@ class DataFrame private[sql](
    * @group dfops
    */
   def join(right: DataFrame, joinExprs: Column, joinType: String): DataFrame = {
-    Join(logicalPlan, right.logicalPlan, JoinType(joinType), Some(joinExprs.expr))
+    // Note that in this function, we introduce a hack in the case of self-join to automatically
+    // resolve ambiguous join conditions into ones that might make sense [SPARK-6231].
+    // Consider this case: df.join(df, df("key") === df("key"))
+    // Since df("key") === df("key") is a trivially true condition, this actually becomes a
+    // cartesian join. However, most likely users expect to perform a self join using "key".
+    // With that assumption, this hack turns the trivially true condition into equality on join
+    // keys that are resolved to both sides.
+
+    // Trigger analysis so in the case of self-join, the analyzer will clone the plan.
+    // After the cloning, left and right side will have distinct expression ids.
+    val plan = Join(logicalPlan, right.logicalPlan, JoinType(joinType), Some(joinExprs.expr))
+      .queryExecution.analyzed.asInstanceOf[Join]
+
+    // If auto self join alias is disabled, return the plan.
+    if (!sqlContext.conf.dataFrameSelfJoinAutoResolveAmbiguity) {
+      return plan
+    }
+
+    // If left/right have no output set intersection, return the plan.
+    val lanalyzed = this.logicalPlan.queryExecution.analyzed
+    val ranalyzed = right.logicalPlan.queryExecution.analyzed
+    if (lanalyzed.outputSet.intersect(ranalyzed.outputSet).isEmpty) {
+      return plan
+    }
+
+    // Otherwise, find the trivially true predicates and automatically resolves them to both sides.
+    // By the time we get here, since we have already run analysis, all attributes should've been
+    // resolved and become AttributeReference.
+    val cond = plan.condition.map { _.transform {
+      case EqualTo(a: AttributeReference, b: AttributeReference) if a.sameRef(b) =>
+        EqualTo(plan.left.resolve(a.name), plan.right.resolve(b.name))
+    }}
+    plan.copy(condition = cond)
   }
 
   /**

sql/core/src/main/scala/org/apache/spark/sql/SQLConf.scala

@@ -67,6 +67,10 @@ private[spark] object SQLConf {
   // Set to false when debugging requires the ability to look at invalid query plans.
   val DATAFRAME_EAGER_ANALYSIS = "spark.sql.eagerAnalysis"
 
+  // Whether to automatically resolve ambiguity in join conditions for self-joins.
+  // See SPARK-6231.
+  val DATAFRAME_SELF_JOIN_AUTO_RESOLVE_AMBIGUITY = "spark.sql.selfJoinAutoResolveAmbiguity"
+
   val USE_SQL_SERIALIZER2 = "spark.sql.useSerializer2"
 
   object Deprecated {
@@ -219,6 +223,9 @@ private[sql] class SQLConf extends Serializable {
   private[spark] def dataFrameEagerAnalysis: Boolean =
     getConf(DATAFRAME_EAGER_ANALYSIS, "true").toBoolean
 
+  private[spark] def dataFrameSelfJoinAutoResolveAmbiguity: Boolean =
+    getConf(DATAFRAME_SELF_JOIN_AUTO_RESOLVE_AMBIGUITY, "true").toBoolean
+
   /** ********************** SQLConf functionality methods ************ */
 
   /** Set Spark SQL configuration properties. */

sql/core/src/test/scala/org/apache/spark/sql/DataFrameJoinSuite.scala

@@ -0,0 +1,86 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql
+
+import org.apache.spark.sql.TestData._
+import org.apache.spark.sql.functions._
+import org.apache.spark.sql.test.TestSQLContext._
+import org.apache.spark.sql.test.TestSQLContext.implicits._
+
+
+class DataFrameJoinSuite extends QueryTest {
+
+  test("join - join using") {
+    val df = Seq(1, 2, 3).map(i => (i, i.toString)).toDF("int", "str")
+    val df2 = Seq(1, 2, 3).map(i => (i, (i + 1).toString)).toDF("int", "str")
+
+    checkAnswer(
+      df.join(df2, "int"),
+      Row(1, "1", "2") :: Row(2, "2", "3") :: Row(3, "3", "4") :: Nil)
+  }
+
+  test("join - join using self join") {
+    val df = Seq(1, 2, 3).map(i => (i, i.toString)).toDF("int", "str")
+
+    // self join
+    checkAnswer(
+      df.join(df, "int"),
+      Row(1, "1", "1") :: Row(2, "2", "2") :: Row(3, "3", "3") :: Nil)
+  }
+
+  test("join - self join") {
+    val df1 = testData.select(testData("key")).as('df1)
+    val df2 = testData.select(testData("key")).as('df2)
+
+    checkAnswer(
+      df1.join(df2, $"df1.key" === $"df2.key"),
+      sql("SELECT a.key, b.key FROM testData a JOIN testData b ON a.key = b.key").collect().toSeq)
+  }
+
+  test("join - using aliases after self join") {
+    val df = Seq(1, 2, 3).map(i => (i, i.toString)).toDF("int", "str")
+    checkAnswer(
+      df.as('x).join(df.as('y), $"x.str" === $"y.str").groupBy("x.str").count(),
+      Row("1", 1) :: Row("2", 1) :: Row("3", 1) :: Nil)
+
+    checkAnswer(
+      df.as('x).join(df.as('y), $"x.str" === $"y.str").groupBy("y.str").count(),
+      Row("1", 1) :: Row("2", 1) :: Row("3", 1) :: Nil)
+  }
+
+  test("[SPARK-6231] join - self join auto resolve ambiguity") {
+    val df = Seq((1, "1"), (2, "2")).toDF("key", "value")
+    checkAnswer(
+      df.join(df, df("key") === df("key")),
+      Row(1, "1", 1, "1") :: Row(2, "2", 2, "2") :: Nil)
+
+    checkAnswer(
+      df.join(df.filter($"value" === "2"), df("key") === df("key")),
+      Row(2, "2", 2, "2") :: Nil)
+
+    checkAnswer(
+      df.join(df, df("key") === df("key") && df("value") === 1),
+      Row(1, "1", 1, "1") :: Nil)
+
+    val left = df.groupBy("key").agg($"key", count("*"))
+    val right = df.groupBy("key").agg($"key", sum("key"))
+    checkAnswer(
+      left.join(right, left("key") === right("key")),
+      Row(1, 1, 1, 1) :: Row(2, 1, 2, 2) :: Nil)
+  }
+}

sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala

@@ -24,7 +24,6 @@ import org.apache.spark.sql.types._
 import org.apache.spark.sql.test.{ExamplePointUDT, ExamplePoint, TestSQLContext}
 import org.apache.spark.sql.test.TestSQLContext.logicalPlanToSparkQuery
 import org.apache.spark.sql.test.TestSQLContext.implicits._
-import org.apache.spark.sql.test.TestSQLContext.sql
 
 
 class DataFrameSuite extends QueryTest {
@@ -118,44 +117,6 @@ class DataFrameSuite extends QueryTest {
     )
   }
 
-  test("join - join using") {
-    val df = Seq(1, 2, 3).map(i => (i, i.toString)).toDF("int", "str")
-    val df2 = Seq(1, 2, 3).map(i => (i, (i + 1).toString)).toDF("int", "str")
-
-    checkAnswer(
-      df.join(df2, "int"),
-      Row(1, "1", "2") :: Row(2, "2", "3") :: Row(3, "3", "4") :: Nil)
-  }
-
-  test("join - join using self join") {
-    val df = Seq(1, 2, 3).map(i => (i, i.toString)).toDF("int", "str")
-
-    // self join
-    checkAnswer(
-      df.join(df, "int"),
-      Row(1, "1", "1") :: Row(2, "2", "2") :: Row(3, "3", "3") :: Nil)
-  }
-
-  test("join - self join") {
-    val df1 = testData.select(testData("key")).as('df1)
-    val df2 = testData.select(testData("key")).as('df2)
-
-    checkAnswer(
-      df1.join(df2, $"df1.key" === $"df2.key"),
-      sql("SELECT a.key, b.key FROM testData a JOIN testData b ON a.key = b.key").collect().toSeq)
-  }
-
-  test("join - using aliases after self join") {
-    val df = Seq(1, 2, 3).map(i => (i, i.toString)).toDF("int", "str")
-    checkAnswer(
-      df.as('x).join(df.as('y), $"x.str" === $"y.str").groupBy("x.str").count(),
-      Row("1", 1) :: Row("2", 1) :: Row("3", 1) :: Nil)
-
-    checkAnswer(
-      df.as('x).join(df.as('y), $"x.str" === $"y.str").groupBy("y.str").count(),
-      Row("1", 1) :: Row("2", 1) :: Row("3", 1) :: Nil)
-  }
-
   test("explode") {
     val df = Seq((1, "a b c"), (2, "a b"), (3, "a")).toDF("number", "letters")
     val df2 =

sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveDataFrameJoinSuite.scala

@@ -0,0 +1,38 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.hive
+
+import org.apache.spark.sql.{Row, QueryTest}
+import org.apache.spark.sql.hive.test.TestHive.implicits._
+
+
+class HiveDataFrameJoinSuite extends QueryTest {
+
+  // We should move this into SQL package if we make case sensitivity configurable in SQL.
+  test("join - self join auto resolve ambiguity with case insensitivity") {
+    val df = Seq((1, "1"), (2, "2")).toDF("key", "value")
+    checkAnswer(
+      df.join(df, df("key") === df("Key")),
+      Row(1, "1", 1, "1") :: Row(2, "2", 2, "2") :: Nil)
+
+    checkAnswer(
+      df.join(df.filter($"value" === "2"), df("key") === df("Key")),
+      Row(2, "2", 2, "2") :: Nil)
+  }
+
+}