[SPARK-21720][SQL] Fix 64KB JVM bytecode limit problem with AND or OR

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala

@@ -808,6 +808,36 @@ class CodegenContext {
     }
   }
 
+  /**
+   * Wrap the generated code of expression, which was created from a row object in INPUT_ROW,
+   * by a function. ev.isNull and ev.value are passed by global variables
+   *
+   * @param ev the code to evaluate expressions.
+   * @param dataType the data type of ev.value.
+   * @param baseFuncName the split function name base.
+   */
+  def createAndAddFunction(
+      ev: ExprCode,
+      dataType: DataType,
+      baseFuncName: String): (String, String, String) = {
+    val globalIsNull = freshName("isNull")
+    addMutableState("boolean", globalIsNull, s"$globalIsNull = false;")
+    val globalValue = freshName("value")
+    addMutableState(javaType(dataType), globalValue,
+      s"$globalValue = ${defaultValue(dataType)};")
+    val funcName = freshName(baseFuncName)
+    val funcBody =
+      s"""
+         |private void $funcName(InternalRow ${INPUT_ROW}) {
+         |  ${ev.code.trim}
+         |  $globalIsNull = ${ev.isNull};
+         |  $globalValue = ${ev.value};
+         |}
+         """.stripMargin
+    val fullFuncName = addNewFunction(funcName, funcBody)
+    (fullFuncName, globalIsNull, globalValue)
+  }
+
   /**
    * Perform a function which generates a sequence of ExprCodes with a given mapping between
    * expressions and common expressions, instead of using the mapping in current context.

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

@@ -72,11 +72,11 @@ case class If(predicate: Expression, trueValue: Expression, falseValue: Expressi
       (ctx.INPUT_ROW != null && ctx.currentVars == null)) {
 
       val (condFuncName, condGlobalIsNull, condGlobalValue) =
-        createAndAddFunction(ctx, condEval, predicate.dataType, "evalIfCondExpr")
+        ctx.createAndAddFunction(condEval, predicate.dataType, "evalIfCondExpr")
       val (trueFuncName, trueGlobalIsNull, trueGlobalValue) =
-        createAndAddFunction(ctx, trueEval, trueValue.dataType, "evalIfTrueExpr")
+        ctx.createAndAddFunction(trueEval, trueValue.dataType, "evalIfTrueExpr")
       val (falseFuncName, falseGlobalIsNull, falseGlobalValue) =
-        createAndAddFunction(ctx, falseEval, falseValue.dataType, "evalIfFalseExpr")
+        ctx.createAndAddFunction(falseEval, falseValue.dataType, "evalIfFalseExpr")
       s"""
         $condFuncName(${ctx.INPUT_ROW});
         boolean ${ev.isNull} = false;
@@ -112,29 +112,6 @@ case class If(predicate: Expression, trueValue: Expression, falseValue: Expressi
     ev.copy(code = generatedCode)
   }
 
-  private def createAndAddFunction(
-      ctx: CodegenContext,
-      ev: ExprCode,
-      dataType: DataType,
-      baseFuncName: String): (String, String, String) = {
-    val globalIsNull = ctx.freshName("isNull")
-    ctx.addMutableState("boolean", globalIsNull, s"$globalIsNull = false;")
-    val globalValue = ctx.freshName("value")
-    ctx.addMutableState(ctx.javaType(dataType), globalValue,
-      s"$globalValue = ${ctx.defaultValue(dataType)};")
-    val funcName = ctx.freshName(baseFuncName)
-    val funcBody =
-      s"""
-         |private void $funcName(InternalRow ${ctx.INPUT_ROW}) {
-         |  ${ev.code.trim}
-         |  $globalIsNull = ${ev.isNull};
-         |  $globalValue = ${ev.value};
-         |}
-         """.stripMargin
-    val fullFuncName = ctx.addNewFunction(funcName, funcBody)
-    (fullFuncName, globalIsNull, globalValue)
-  }
-
   override def toString: String = s"if ($predicate) $trueValue else $falseValue"
 
   override def sql: String = s"(IF(${predicate.sql}, ${trueValue.sql}, ${falseValue.sql}))"

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

@@ -368,7 +368,46 @@ case class And(left: Expression, right: Expression) extends BinaryOperator with
     val eval2 = right.genCode(ctx)
 
     // The result should be `false`, if any of them is `false` whenever the other is null or not.
-    if (!left.nullable && !right.nullable) {
+
+    // place generated code of eval1 and eval2 in separate methods if their code combined is large
+    val combinedLength = eval1.code.length + eval2.code.length
+    if (combinedLength > 1024 &&
+      // Split these expressions only if they are created from a row object
+      (ctx.INPUT_ROW != null && ctx.currentVars == null)) {
+
+      val (eval1FuncName, eval1GlobalIsNull, eval1GlobalValue) =
+        ctx.createAndAddFunction(eval1, BooleanType, "eval1Expr")
+      val (eval2FuncName, eval2GlobalIsNull, eval2GlobalValue) =
+        ctx.createAndAddFunction(eval2, BooleanType, "eval2Expr")
+      if (!left.nullable && !right.nullable) {
+        val generatedCode = s"""
+         $eval1FuncName(${ctx.INPUT_ROW});
+         boolean ${ev.value} = false;
+         if (${eval1GlobalValue}) {
+           $eval2FuncName(${ctx.INPUT_ROW});
+           ${ev.value} = ${eval2GlobalValue};
+         }
+       """
+        ev.copy(code = generatedCode, isNull = "false")
+      } else {
+        val generatedCode = s"""
+         $eval1FuncName(${ctx.INPUT_ROW});
+         boolean ${ev.isNull} = false;
+         boolean ${ev.value} = false;
+         if (!${eval1GlobalIsNull} && !${eval1GlobalValue}) {
+         } else {
+           $eval2FuncName(${ctx.INPUT_ROW});
+           if (!${eval2GlobalIsNull} && !${eval2GlobalValue}) {
+           } else if (!${eval1GlobalIsNull} && !${eval2GlobalIsNull}) {
+             ${ev.value} = true;
+           } else {
+             ${ev.isNull} = true;
+           }
+         }
+       """
+        ev.copy(code = generatedCode)
+      }
+    } else if (!left.nullable && !right.nullable) {
       ev.copy(code = s"""
         ${eval1.code}
         boolean ${ev.value} = false;
@@ -431,7 +470,46 @@ case class Or(left: Expression, right: Expression) extends BinaryOperator with P
     val eval2 = right.genCode(ctx)
 
     // The result should be `true`, if any of them is `true` whenever the other is null or not.
-    if (!left.nullable && !right.nullable) {
+
+    // place generated code of eval1 and eval2 in separate methods if their code combined is large
+    val combinedLength = eval1.code.length + eval2.code.length
+    if (combinedLength > 1024 &&
+      // Split these expressions only if they are created from a row object
+      (ctx.INPUT_ROW != null && ctx.currentVars == null)) {
+
+      val (eval1FuncName, eval1GlobalIsNull, eval1GlobalValue) =
+        ctx.createAndAddFunction(eval1, BooleanType, "eval1Expr")
+      val (eval2FuncName, eval2GlobalIsNull, eval2GlobalValue) =
+        ctx.createAndAddFunction(eval2, BooleanType, "eval2Expr")
+      if (!left.nullable && !right.nullable) {
+        val generatedCode = s"""
+         $eval1FuncName(${ctx.INPUT_ROW});
+         boolean ${ev.value} = true;
+         if (!${eval1GlobalValue}) {
+           $eval2FuncName(${ctx.INPUT_ROW});
+           ${ev.value} = ${eval2GlobalValue};
+         }
+       """
+        ev.copy(code = generatedCode, isNull = "false")
+      } else {
+        val generatedCode = s"""
+         $eval1FuncName(${ctx.INPUT_ROW});
+         boolean ${ev.isNull} = false;
+         boolean ${ev.value} = true;
+         if (!${eval1GlobalIsNull} && ${eval1GlobalValue}) {
+         } else {
+           $eval2FuncName(${ctx.INPUT_ROW});
+           if (!${eval2GlobalIsNull} && ${eval2GlobalValue}) {
+           } else if (!${eval1GlobalIsNull} && !${eval2GlobalIsNull}) {
+             ${ev.value} = false;
+           } else {
+             ${ev.isNull} = true;
+           }
+         }
+       """
+        ev.copy(code = generatedCode)
+      }
+    } else if (!left.nullable && !right.nullable) {
       ev.isNull = "false"
       ev.copy(code = s"""
         ${eval1.code}

sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/CodeGenerationSuite.scala

@@ -324,4 +324,43 @@ class CodeGenerationSuite extends SparkFunSuite with ExpressionEvalHelper {
     // should not throw exception
     projection(row)
   }
+
+  test("SPARK-21720: split large predications into blocks due to JVM code size limit") {
+    val length = 600
+
+    val input = new GenericInternalRow(length)
+    val utf8Str = UTF8String.fromString(s"abc")
+    for (i <- 0 until length) {
+      input.update(i, utf8Str)
+    }
+
+    var exprOr: Expression = Literal(false)
+    for (i <- 0 until length) {
+      exprOr = Or(EqualTo(BoundReference(i, StringType, true), Literal(s"c$i")), exprOr)
+    }
+
+    val planOr = GenerateMutableProjection.generate(Seq(exprOr))
+    val actualOr = planOr(input).toSeq(Seq(exprOr.dataType))
+    assert(actualOr.length == 1)
+    val expectedOr = false
+
+    if (!checkResult(actualOr.head, expectedOr, exprOr.dataType)) {
+      fail(s"Incorrect Evaluation: expressions: $exprOr, actual: $actualOr, expected: $expectedOr")
+    }
+
+    var exprAnd: Expression = Literal(true)
+    for (i <- 0 until length) {
+      exprAnd = And(EqualTo(BoundReference(i, StringType, true), Literal(s"c$i")), exprAnd)
+    }
+
+    val planAnd = GenerateMutableProjection.generate(Seq(exprAnd))
+    val actualAnd = planAnd(input).toSeq(Seq(exprAnd.dataType))
+    assert(actualAnd.length == 1)
+    val expectedAnd = false
+
+    if (!checkResult(actualAnd.head, expectedAnd, exprAnd.dataType)) {
+      fail(
+        s"Incorrect Evaluation: expressions: $exprAnd, actual: $actualAnd, expected: $expectedAnd")
+    }
+  }
 }

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

@@ -2067,7 +2067,11 @@ class DataFrameSuite extends QueryTest with SharedSQLContext {
       .count
   }
 
-  testQuietly("SPARK-19372: Filter can be executed w/o generated code due to JVM code size limit") {
+  // The fix of SPARK-21720 avoid an exception regarding JVM code size limit
+  // TODO: When we make a threshold of splitting statements (1024) configurable,
+  // we will re-enable this with max threshold to cause an exception
+  // See https://github.com/apache/spark/pull/18972/files#r150223463
+  ignore("SPARK-19372: Filter can be executed w/o generated code due to JVM code size limit") {
     val N = 400
     val rows = Seq(Row.fromSeq(Seq.fill(N)("string")))
     val schema = StructType(Seq.tabulate(N)(i => StructField(s"_c$i", StringType)))