[SPARK-26147][SQL] only pull out unevaluable python udf from join condition

python/pyspark/sql/tests/test_udf.py

@@ -209,6 +209,18 @@ def test_udf_in_join_condition(self):
         with self.sql_conf({"spark.sql.crossJoin.enabled": True}):
             self.assertEqual(df.collect(), [Row(a=1, b=1)])
 
+    def test_udf_in_left_outer_join_condition(self):
+        # regression test for SPARK-26147
+        from pyspark.sql.functions import udf, col
+        left = self.spark.createDataFrame([Row(a=1)])
+        right = self.spark.createDataFrame([Row(b=1)])
+        f = udf(lambda a: str(a), StringType())
+        # The join condition can't be pushed down, as it refers to attributes from both sides.
+        # The Python UDF only refer to attributes from one side, so it's evaluable.
+        df = left.join(right, f("a") == col("b").cast("string"), how="left_outer")
+        with self.sql_conf({"spark.sql.crossJoin.enabled": True}):
+            self.assertEqual(df.collect(), [Row(a=1, b=1)])
+
     def test_udf_in_left_semi_join_condition(self):
         # regression test for SPARK-25314
         from pyspark.sql.functions import udf

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/joins.scala

@@ -155,19 +155,20 @@ object EliminateOuterJoin extends Rule[LogicalPlan] with PredicateHelper {
 }
 
 /**
- * PythonUDF in join condition can not be evaluated, this rule will detect the PythonUDF
- * and pull them out from join condition. For python udf accessing attributes from only one side,
- * they are pushed down by operation push down rules. If not (e.g. user disables filter push
- * down rules), we need to pull them out in this rule too.
+ * PythonUDF in join condition can't be evaluated if it refers to attributes from both join sides.
+ * See `ExtractPythonUDFs` for details. This rule will detect un-evaluable PythonUDF and pull them
+ * out from join condition.
  */
 object PullOutPythonUDFInJoinCondition extends Rule[LogicalPlan] with PredicateHelper {
-  def hasPythonUDF(expression: Expression): Boolean = {
-    expression.collectFirst { case udf: PythonUDF => udf }.isDefined
+
+  private def hasUnevaluablePythonUDF(expr: Expression, j: Join): Boolean = {
+    expr.find { e =>
+      PythonUDF.isScalarPythonUDF(e) && !canEvaluate(e, j.left) && !canEvaluate(e, j.right)
+    }.isDefined
   }
 
   override def apply(plan: LogicalPlan): LogicalPlan = plan transformUp {
-    case j @ Join(_, _, joinType, condition)
-        if condition.isDefined && hasPythonUDF(condition.get) =>
+    case j @ Join(_, _, joinType, Some(cond)) if hasUnevaluablePythonUDF(cond, j) =>
       if (!joinType.isInstanceOf[InnerLike] && joinType != LeftSemi) {
         // The current strategy only support InnerLike and LeftSemi join because for other type,
         // it breaks SQL semantic if we run the join condition as a filter after join. If we pass
@@ -179,10 +180,9 @@ object PullOutPythonUDFInJoinCondition extends Rule[LogicalPlan] with PredicateH
       }
       // If condition expression contains python udf, it will be moved out from
       // the new join conditions.
-      val (udf, rest) =
-        splitConjunctivePredicates(condition.get).partition(hasPythonUDF)
+      val (udf, rest) = splitConjunctivePredicates(cond).partition(hasUnevaluablePythonUDF(_, j))
       val newCondition = if (rest.isEmpty) {
-        logWarning(s"The join condition:$condition of the join plan contains PythonUDF only," +
+        logWarning(s"The join condition:$cond of the join plan contains PythonUDF only," +
           s" it will be moved out and the join plan will be turned to cross join.")
         None
       } else {

sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/PullOutPythonUDFInJoinConditionSuite.scala

@@ -17,8 +17,6 @@
 
 package org.apache.spark.sql.catalyst.optimizer
 
-import org.scalatest.Matchers._
-
 import org.apache.spark.api.python.PythonEvalType
 import org.apache.spark.sql.AnalysisException
 import org.apache.spark.sql.catalyst.dsl.expressions._
@@ -28,7 +26,7 @@ import org.apache.spark.sql.catalyst.plans._
 import org.apache.spark.sql.catalyst.plans.logical.{LocalRelation, LogicalPlan}
 import org.apache.spark.sql.catalyst.rules.RuleExecutor
 import org.apache.spark.sql.internal.SQLConf._
-import org.apache.spark.sql.types.BooleanType
+import org.apache.spark.sql.types.{BooleanType, IntegerType}
 
 class PullOutPythonUDFInJoinConditionSuite extends PlanTest {
 
@@ -40,13 +38,29 @@ class PullOutPythonUDFInJoinConditionSuite extends PlanTest {
         CheckCartesianProducts) :: Nil
   }
 
-  val testRelationLeft = LocalRelation('a.int, 'b.int)
-  val testRelationRight = LocalRelation('c.int, 'd.int)
+  val attrA = 'a.int
+  val attrB = 'b.int
+  val attrC = 'c.int
+  val attrD = 'd.int
+
+  val testRelationLeft = LocalRelation(attrA, attrB)
+  val testRelationRight = LocalRelation(attrC, attrD)
+
+  // This join condition refers to attributes from 2 tables, but the PythonUDF inside it only
+  // refer to attributes from one side.
+  val evaluableJoinCond = {
+    val pythonUDF = PythonUDF("evaluable", null,
+      IntegerType,
+      Seq(attrA),
+      PythonEvalType.SQL_BATCHED_UDF,
+      udfDeterministic = true)
+    pythonUDF === attrC
+  }
 
-  // Dummy python UDF for testing. Unable to execute.
-  val pythonUDF = PythonUDF("pythonUDF", null,
+  // This join condition is a PythonUDF which refers to attributes from 2 tables.
+  val unevaluableJoinCond = PythonUDF("unevaluable", null,
     BooleanType,
-    Seq.empty,
+    Seq(attrA, attrC),
     PythonEvalType.SQL_BATCHED_UDF,
     udfDeterministic = true)
 
@@ -66,62 +80,76 @@ class PullOutPythonUDFInJoinConditionSuite extends PlanTest {
     }
   }
 
-  test("inner join condition with python udf only") {
-    val query = testRelationLeft.join(
+  test("inner join condition with python udf") {
+    val query1 = testRelationLeft.join(
       testRelationRight,
       joinType = Inner,
-      condition = Some(pythonUDF))
-    val expected = testRelationLeft.join(
+      condition = Some(unevaluableJoinCond))
+    val expected1 = testRelationLeft.join(
       testRelationRight,
       joinType = Inner,
-      condition = None).where(pythonUDF).analyze
-    comparePlanWithCrossJoinEnable(query, expected)
+      condition = None).where(unevaluableJoinCond).analyze
+    comparePlanWithCrossJoinEnable(query1, expected1)
+
+    // evaluable PythonUDF will not be touched
+    val query2 = testRelationLeft.join(
+      testRelationRight,
+      joinType = Inner,
+      condition = Some(evaluableJoinCond))
+    comparePlans(Optimize.execute(query2), query2)
   }
 
-  test("left semi join condition with python udf only") {
-    val query = testRelationLeft.join(
+  test("left semi join condition with python udf") {
+    val query1 = testRelationLeft.join(
       testRelationRight,
       joinType = LeftSemi,
-      condition = Some(pythonUDF))
-    val expected = testRelationLeft.join(
+      condition = Some(unevaluableJoinCond))
+    val expected1 = testRelationLeft.join(
       testRelationRight,
       joinType = Inner,
-      condition = None).where(pythonUDF).select('a, 'b).analyze
-    comparePlanWithCrossJoinEnable(query, expected)
+      condition = None).where(unevaluableJoinCond).select('a, 'b).analyze
+    comparePlanWithCrossJoinEnable(query1, expected1)
+
+    // evaluable PythonUDF will not be touched
+    val query2 = testRelationLeft.join(
+      testRelationRight,
+      joinType = LeftSemi,
+      condition = Some(evaluableJoinCond))
+    comparePlans(Optimize.execute(query2), query2)
   }
 
-  test("python udf and common condition") {
+  test("unevaluable python udf and common condition") {
     val query = testRelationLeft.join(
       testRelationRight,
       joinType = Inner,
-      condition = Some(pythonUDF && 'a.attr === 'c.attr))
+      condition = Some(unevaluableJoinCond && 'a.attr === 'c.attr))
     val expected = testRelationLeft.join(
       testRelationRight,
       joinType = Inner,
-      condition = Some('a.attr === 'c.attr)).where(pythonUDF).analyze
+      condition = Some('a.attr === 'c.attr)).where(unevaluableJoinCond).analyze
     val optimized = Optimize.execute(query.analyze)
     comparePlans(optimized, expected)
   }
 
-  test("python udf or common condition") {
+  test("unevaluable python udf or common condition") {
     val query = testRelationLeft.join(
       testRelationRight,
       joinType = Inner,
-      condition = Some(pythonUDF || 'a.attr === 'c.attr))
+      condition = Some(unevaluableJoinCond || 'a.attr === 'c.attr))
     val expected = testRelationLeft.join(
       testRelationRight,
       joinType = Inner,
-      condition = None).where(pythonUDF || 'a.attr === 'c.attr).analyze
+      condition = None).where(unevaluableJoinCond || 'a.attr === 'c.attr).analyze
     comparePlanWithCrossJoinEnable(query, expected)
   }
 
-  test("pull out whole complex condition with multiple python udf") {
+  test("pull out whole complex condition with multiple unevaluable python udf") {
     val pythonUDF1 = PythonUDF("pythonUDF1", null,
       BooleanType,
-      Seq.empty,
+      Seq(attrA, attrC),
       PythonEvalType.SQL_BATCHED_UDF,
       udfDeterministic = true)
-    val condition = (pythonUDF || 'a.attr === 'c.attr) && pythonUDF1
+    val condition = (unevaluableJoinCond || 'a.attr === 'c.attr) && pythonUDF1
 
     val query = testRelationLeft.join(
       testRelationRight,
@@ -134,13 +162,13 @@ class PullOutPythonUDFInJoinConditionSuite extends PlanTest {
     comparePlanWithCrossJoinEnable(query, expected)
   }
 
-  test("partial pull out complex condition with multiple python udf") {
+  test("partial pull out complex condition with multiple unevaluable python udf") {
     val pythonUDF1 = PythonUDF("pythonUDF1", null,
       BooleanType,
-      Seq.empty,
+      Seq(attrA, attrC),
       PythonEvalType.SQL_BATCHED_UDF,
       udfDeterministic = true)
-    val condition = (pythonUDF || pythonUDF1) && 'a.attr === 'c.attr
+    val condition = (unevaluableJoinCond || pythonUDF1) && 'a.attr === 'c.attr
 
     val query = testRelationLeft.join(
       testRelationRight,
@@ -149,23 +177,41 @@ class PullOutPythonUDFInJoinConditionSuite extends PlanTest {
     val expected = testRelationLeft.join(
       testRelationRight,
       joinType = Inner,
-      condition = Some('a.attr === 'c.attr)).where(pythonUDF || pythonUDF1).analyze
+      condition = Some('a.attr === 'c.attr)).where(unevaluableJoinCond || pythonUDF1).analyze
+    val optimized = Optimize.execute(query.analyze)
+    comparePlans(optimized, expected)
+  }
+
+  test("pull out unevaluable python udf when it's mixed with evaluable one") {
+    val query = testRelationLeft.join(
+      testRelationRight,
+      joinType = Inner,
+      condition = Some(evaluableJoinCond && unevaluableJoinCond))
+    val expected = testRelationLeft.join(
+      testRelationRight,
+      joinType = Inner,
+      condition = Some(evaluableJoinCond)).where(unevaluableJoinCond).analyze
     val optimized = Optimize.execute(query.analyze)
     comparePlans(optimized, expected)
   }
 
   test("throw an exception for not support join type") {
     for (joinType <- unsupportedJoinTypes) {
-      val thrownException = the [AnalysisException] thrownBy {
+      val e = intercept[AnalysisException] {
         val query = testRelationLeft.join(
           testRelationRight,
           joinType,
-          condition = Some(pythonUDF))
+          condition = Some(unevaluableJoinCond))
         Optimize.execute(query.analyze)
       }
-      assert(thrownException.message.contentEquals(
+      assert(e.message.contentEquals(
         s"Using PythonUDF in join condition of join type $joinType is not supported."))
+
+      val query2 = testRelationLeft.join(
+        testRelationRight,
+        joinType,
+        condition = Some(evaluableJoinCond))
+      comparePlans(Optimize.execute(query2), query2)
     }
   }
 }
-