From c5419b37f2ece4842d8c2bd7463a50b61245fbcf Mon Sep 17 00:00:00 2001
From: "navis.ryu" <navis@apache.org>
Date: Tue, 30 Jun 2015 11:33:15 +0900
Subject: [PATCH] addressed comments

---
 .../spark/sql/execution/GeneratedAggregate.scala |  8 ++++++--
 .../apache/spark/sql/execution/SparkPlan.scala   |  3 ++-
 .../spark/sql/execution/AggregateSuite.scala     | 16 ++++++++--------
 3 files changed, 16 insertions(+), 11 deletions(-)

diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/GeneratedAggregate.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/GeneratedAggregate.scala
index 10cd29f6f7bc9..5f69a5e19b2be 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/GeneratedAggregate.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/GeneratedAggregate.scala
@@ -64,6 +64,11 @@ case class GeneratedAggregate(
       }
     }
 
+  // even with empty input iterator, if this group-by operator is for
+  // global(groupingExpression.isEmpty) and final(partial=false),
+  // we still need to make a row from empty buffer.
+  def needEmptyBufferForwarded: Boolean = groupingExpressions.isEmpty && !partial
+
   override def output: Seq[Attribute] = aggregateExpressions.map(_.toAttribute)
 
   protected override def doExecute(): RDD[InternalRow] = {
@@ -270,8 +275,7 @@ case class GeneratedAggregate(
 
       val joinedRow = new JoinedRow3
 
-      if (!iter.hasNext && (partial || groupingExpressions.nonEmpty)) {
-        // even with empty input, final-global groupby should forward value of empty buffer
+      if (!iter.hasNext && !needEmptyBufferForwarded) {
         Iterator[InternalRow]()
       } else if (groupingExpressions.isEmpty) {
         // TODO: Codegening anything other than the updateProjection is probably over kill.
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkPlan.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkPlan.scala
index 99f8e9433c919..d15ee93bd7aea 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkPlan.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkPlan.scala
@@ -154,7 +154,8 @@ abstract class SparkPlan extends QueryPlan[SparkPlan] with Logging with Serializ
 
   protected def newProjection(
       expressions: Seq[Expression],
-      inputSchema: Seq[Attribute], mutableRow: Boolean = false): Projection = {
+      inputSchema: Seq[Attribute],
+      mutableRow: Boolean = false): Projection = {
     log.debug(
       s"Creating Projection: $expressions, inputSchema: $inputSchema, codegen:$codegenEnabled")
     if (codegenEnabled && expressions.forall(_.isThreadSafe)) {
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/AggregateSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/AggregateSuite.scala
index b8ee523eb9c6d..7c87024ce85bb 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/AggregateSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/AggregateSuite.scala
@@ -27,16 +27,17 @@ class AggregateSuite extends SparkPlanTest {
   test("SPARK-8357 Memory leakage on unsafe aggregation path with empty input") {
 
     val input0 = Seq.empty[(String, Int, Double)]
-    val input1 = Seq(("Hello", 4, 2.0))
-
-    // hack : current default parallelism of test local backend is two
+    // in the case of needEmptyBufferForwarded=true, task makes a row from empty buffer
+    // even with empty input. And current default parallelism of SparkPlanTest is two (local[2])
     val x0 = Seq(Tuple1(0L), Tuple1(0L))
     val y0 = Seq.empty[Tuple1[Long]]
 
+    val input1 = Seq(("Hello", 4, 2.0))
     val x1 = Seq(Tuple1(0L), Tuple1(1L))
     val y1 = Seq(Tuple1(1L))
 
     val codegenDefault = TestSQLContext.getConf(SQLConf.CODEGEN_ENABLED)
+    TestSQLContext.setConf(SQLConf.CODEGEN_ENABLED, true)
     try {
       for ((input, x, y) <- Seq((input0, x0, y0), (input1, x1, y1))) {
         val df = input.toDF("a", "b", "c")
@@ -44,12 +45,11 @@ class AggregateSuite extends SparkPlanTest {
         val colC = df.col("c").expr
         val aggrExpr = Alias(Count(Cast(colC, LongType)), "Count")()
 
-        for ((codegen, unsafe) <- Seq((false, false), (true, false), (true, true));
-             partial <- Seq(false, true); groupExpr <- Seq(colB :: Nil, Seq.empty)) {
-          TestSQLContext.setConf(SQLConf.CODEGEN_ENABLED, codegen)
+        for (partial <- Seq(false, true); groupExpr <- Seq(Seq(colB), Seq.empty)) {
+          val aggregate = GeneratedAggregate(partial, groupExpr, Seq(aggrExpr), true, _: SparkPlan)
           checkAnswer(df,
-            GeneratedAggregate(partial, groupExpr, aggrExpr :: Nil, unsafe, _: SparkPlan),
-            if (groupExpr.isEmpty && !partial) x else y)
+            aggregate,
+            if (aggregate(null).needEmptyBufferForwarded) x else y)
         }
       }
     } finally {