[SPARK-14138] [SQL] [MASTER] Fix generated SpecificColumnarIterator c…

…ode can exceed JVM size limit for cached DataFrames ## What changes were proposed in this pull request? This PR reduces Java byte code size of method in ```SpecificColumnarIterator``` by using a approach to make a group for lot of ```ColumnAccessor``` instantiations or method calls (more than 200) into a method ## How was this patch tested? Added a new unit test, which includes large instantiations and method calls, to ```InMemoryColumnarQuerySuite``` Author: Kazuaki Ishizaki <[email protected]> Closes apache#12108 from kiszk/SPARK-14138-master.
hophy · Apr 2, 2016 · 877dc71 · 877dc71
1 parent 27e71a2
commit 877dc71
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Showing 2 changed files with 51 additions and 5 deletions.
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/columnar/GenerateColumnAccessor.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/columnar/GenerateColumnAccessor.scala
@@ -88,7 +88,7 @@ object GenerateColumnAccessor extends CodeGenerator[Seq[DataType], ColumnarItera
         case array: ArrayType => classOf[ArrayColumnAccessor].getName
         case t: MapType => classOf[MapColumnAccessor].getName
       }
-      ctx.addMutableState(accessorCls, accessorName, s"$accessorName = null;")
+      ctx.addMutableState(accessorCls, accessorName, "")
 
       val createCode = dt match {
         case t if ctx.isPrimitiveType(dt) =>
@@ -114,6 +114,42 @@ object GenerateColumnAccessor extends CodeGenerator[Seq[DataType], ColumnarItera
       (createCode, extract + patch)
     }.unzip
 
+    /*
+     * 200 = 6000 bytes / 30 (up to 30 bytes per one call))
+     * the maximum byte code size to be compiled for HotSpot is 8000.
+     * We should keep less than 8000
+     */
+    val numberOfStatementsThreshold = 200
+    val (initializerAccessorCalls, extractorCalls) =
+      if (initializeAccessors.length <= numberOfStatementsThreshold) {
+        (initializeAccessors.mkString("\n"), extractors.mkString("\n"))
+      } else {
+        val groupedAccessorsItr = initializeAccessors.grouped(numberOfStatementsThreshold)
+        val groupedExtractorsItr = extractors.grouped(numberOfStatementsThreshold)
+        var groupedAccessorsLength = 0
+        groupedAccessorsItr.zipWithIndex.map { case (body, i) =>
+          groupedAccessorsLength += 1
+          val funcName = s"accessors$i"
+          val funcCode = s"""
+             |private void $funcName() {
+             |  ${body.mkString("\n")}
+             |}
+           """.stripMargin
+          ctx.addNewFunction(funcName, funcCode)
+        }
+        groupedExtractorsItr.zipWithIndex.map { case (body, i) =>
+          val funcName = s"extractors$i"
+          val funcCode = s"""
+             |private void $funcName() {
+             |  ${body.mkString("\n")}
+             |}
+           """.stripMargin
+          ctx.addNewFunction(funcName, funcCode)
+        }
+        ((0 to groupedAccessorsLength - 1).map { i => s"accessors$i();" }.mkString("\n"),
+         (0 to groupedAccessorsLength - 1).map { i => s"extractors$i();" }.mkString("\n"))
+      }
+
     val code = s"""
       import java.nio.ByteBuffer;
       import java.nio.ByteOrder;
@@ -149,8 +185,6 @@ object GenerateColumnAccessor extends CodeGenerator[Seq[DataType], ColumnarItera
           this.nativeOrder = ByteOrder.nativeOrder();
           this.buffers = new byte[${columnTypes.length}][];
           this.mutableRow = new MutableUnsafeRow(rowWriter);
-
-          ${ctx.initMutableStates()}
         }
 
         public void initialize(Iterator input, DataType[] columnTypes, int[] columnIndexes) {
@@ -159,6 +193,8 @@ object GenerateColumnAccessor extends CodeGenerator[Seq[DataType], ColumnarItera
           this.columnIndexes = columnIndexes;
         }
 
+        ${ctx.declareAddedFunctions()}
+
         public boolean hasNext() {
           if (currentRow < numRowsInBatch) {
             return true;
@@ -173,7 +209,7 @@ object GenerateColumnAccessor extends CodeGenerator[Seq[DataType], ColumnarItera
           for (int i = 0; i < columnIndexes.length; i ++) {
             buffers[i] = batch.buffers()[columnIndexes[i]];
           }
-          ${initializeAccessors.mkString("\n")}
+          ${initializerAccessorCalls}
 
           return hasNext();
         }
@@ -182,7 +218,7 @@ object GenerateColumnAccessor extends CodeGenerator[Seq[DataType], ColumnarItera
           currentRow += 1;
           bufferHolder.reset();
           rowWriter.zeroOutNullBytes();
-          ${extractors.mkString("\n")}
+          ${extractorCalls}
           unsafeRow.setTotalSize(bufferHolder.totalSize());
           return unsafeRow;
         }

diff --git a/...e/src/test/scala/org/apache/spark/sql/execution/columnar/InMemoryColumnarQuerySuite.scala b/...e/src/test/scala/org/apache/spark/sql/execution/columnar/InMemoryColumnarQuerySuite.scala
@@ -220,4 +220,14 @@ class InMemoryColumnarQuerySuite extends QueryTest with SharedSQLContext {
     assert(data.count() === 10)
     assert(data.filter($"s" === "3").count() === 1)
   }
+
+  test("SPARK-14138: Generated SpecificColumnarIterator can exceed JVM size limit for cached DF") {
+    val length1 = 3999
+    val columnTypes1 = List.fill(length1)(IntegerType)
+    val columnarIterator1 = GenerateColumnAccessor.generate(columnTypes1)
+
+    val length2 = 10000
+    val columnTypes2 = List.fill(length2)(IntegerType)
+    val columnarIterator2 = GenerateColumnAccessor.generate(columnTypes2)
+  }
 }