Merge remote-tracking branch 'origin/master' into nan

project/MimaExcludes.scala

@@ -64,6 +64,9 @@ object MimaExcludes {
             excludePackage("org.apache.spark.sql.execution"),
             // Parquet support is considered private.
             excludePackage("org.apache.spark.sql.parquet"),
+            // The old JSON RDD is removed in favor of streaming Jackson
+            ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.json.JsonRDD$"),
+            ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.json.JsonRDD"),
             // local function inside a method
             ProblemFilters.exclude[MissingMethodProblem](
               "org.apache.spark.sql.SQLContext.org$apache$spark$sql$SQLContext$$needsConversion$1")

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

@@ -19,6 +19,8 @@ package org.apache.spark.sql.catalyst.expressions.codegen
 
 import org.apache.spark.sql.catalyst.expressions._
 
+import scala.collection.mutable.ArrayBuffer
+
 // MutableProjection is not accessible in Java
 abstract class BaseMutableProjection extends MutableProjection
 
@@ -45,10 +47,41 @@ object GenerateMutableProjection extends CodeGenerator[Seq[Expression], () => Mu
           else
             ${ctx.setColumn("mutableRow", e.dataType, i, evaluationCode.primitive)};
         """
-    }.mkString("\n")
+    }
+    // collect projections into blocks as function has 64kb codesize limit in JVM
+    val projectionBlocks = new ArrayBuffer[String]()
+    val blockBuilder = new StringBuilder()
+    for (projection <- projectionCode) {
+      if (blockBuilder.length > 16 * 1000) {
+        projectionBlocks.append(blockBuilder.toString())
+        blockBuilder.clear()
+      }
+      blockBuilder.append(projection)
+    }
+    projectionBlocks.append(blockBuilder.toString())
+
+    val (projectionFuns, projectionCalls) = {
+      // inline execution if codesize limit was not broken
+      if (projectionBlocks.length == 1) {
+        ("", projectionBlocks.head)
+      } else {
+        (
+          projectionBlocks.zipWithIndex.map { case (body, i) =>
+            s"""
+               |private void apply$i(InternalRow i) {
+               |  $body
+               |}
+             """.stripMargin
+          }.mkString,
+          projectionBlocks.indices.map(i => s"apply$i(i);").mkString("\n")
+        )
+      }
+    }
+
     val mutableStates = ctx.mutableStates.map { case (javaType, variableName, initialValue) =>
       s"private $javaType $variableName = $initialValue;"
     }.mkString("\n      ")
+
     val code = s"""
       public Object generate($exprType[] expr) {
         return new SpecificProjection(expr);
@@ -75,9 +108,11 @@ object GenerateMutableProjection extends CodeGenerator[Seq[Expression], () => Mu
           return (InternalRow) mutableRow;
         }
 
+        $projectionFuns
+
         public Object apply(Object _i) {
           InternalRow i = (InternalRow) _i;
-          $projectionCode
+          $projectionCalls
 
           return mutableRow;
         }

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

@@ -29,7 +29,7 @@ import org.apache.spark.sql.types.{DataTypeTestUtils, NullType, StructField, Str
 /**
  * Additional tests for code generation.
  */
-class CodeGenerationSuite extends SparkFunSuite {
+class CodeGenerationSuite extends SparkFunSuite with ExpressionEvalHelper {
 
   test("multithreaded eval") {
     import scala.concurrent._
@@ -56,10 +56,10 @@ class CodeGenerationSuite extends SparkFunSuite {
       val rowOrdering = RowOrdering.forSchema(Seq(dataType, dataType))
       val genOrdering = GenerateOrdering.generate(
         BoundReference(0, dataType, nullable = true).asc ::
-        BoundReference(1, dataType, nullable = true).asc :: Nil)
+          BoundReference(1, dataType, nullable = true).asc :: Nil)
       val rowType = StructType(
         StructField("a", dataType, nullable = true) ::
-        StructField("b", dataType, nullable = true) :: Nil)
+          StructField("b", dataType, nullable = true) :: Nil)
       val maybeDataGenerator = RandomDataGenerator.forType(rowType, nullable = false)
       assume(maybeDataGenerator.isDefined)
       val randGenerator = maybeDataGenerator.get
@@ -81,4 +81,16 @@ class CodeGenerationSuite extends SparkFunSuite {
       }
     }
   }
+
+  test("SPARK-8443: split wide projections into blocks due to JVM code size limit") {
+    val length = 5000
+    val expressions = List.fill(length)(EqualTo(Literal(1), Literal(1)))
+    val plan = GenerateMutableProjection.generate(expressions)()
+    val actual = plan(new GenericMutableRow(length)).toSeq
+    val expected = Seq.fill(length)(true)
+
+    if (!checkResult(actual, expected)) {
+      fail(s"Incorrect Evaluation: expressions: $expressions, actual: $actual, expected: $expected")
+    }
+  }
 }

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

@@ -27,7 +27,7 @@ import org.apache.spark.api.java.JavaRDD
 import org.apache.spark.deploy.SparkHadoopUtil
 import org.apache.spark.rdd.RDD
 import org.apache.spark.sql.jdbc.{JDBCPartition, JDBCPartitioningInfo, JDBCRelation}
-import org.apache.spark.sql.json.{JsonRDD, JSONRelation}
+import org.apache.spark.sql.json.JSONRelation
 import org.apache.spark.sql.parquet.ParquetRelation2
 import org.apache.spark.sql.sources.{LogicalRelation, ResolvedDataSource}
 import org.apache.spark.sql.types.StructType
@@ -236,17 +236,8 @@ class DataFrameReader private[sql](sqlContext: SQLContext) {
    */
   def json(jsonRDD: RDD[String]): DataFrame = {
     val samplingRatio = extraOptions.getOrElse("samplingRatio", "1.0").toDouble
-    if (sqlContext.conf.useJacksonStreamingAPI) {
-      sqlContext.baseRelationToDataFrame(
-        new JSONRelation(() => jsonRDD, None, samplingRatio, userSpecifiedSchema)(sqlContext))
-    } else {
-      val columnNameOfCorruptJsonRecord = sqlContext.conf.columnNameOfCorruptRecord
-      val appliedSchema = userSpecifiedSchema.getOrElse(
-        JsonRDD.nullTypeToStringType(
-          JsonRDD.inferSchema(jsonRDD, 1.0, columnNameOfCorruptJsonRecord)))
-      val rowRDD = JsonRDD.jsonStringToRow(jsonRDD, appliedSchema, columnNameOfCorruptJsonRecord)
-      sqlContext.internalCreateDataFrame(rowRDD, appliedSchema)
-    }
+    sqlContext.baseRelationToDataFrame(
+      new JSONRelation(() => jsonRDD, None, samplingRatio, userSpecifiedSchema)(sqlContext))
   }
 
   /**

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

@@ -401,9 +401,6 @@ private[spark] object SQLConf {
     "spark.sql.useSerializer2",
     defaultValue = Some(true), isPublic = false)
 
-  val USE_JACKSON_STREAMING_API = booleanConf("spark.sql.json.useJacksonStreamingAPI",
-    defaultValue = Some(true), doc = "<TODO>")
-
   object Deprecated {
     val MAPRED_REDUCE_TASKS = "mapred.reduce.tasks"
   }
@@ -473,8 +470,6 @@ private[sql] class SQLConf extends Serializable with CatalystConf {
 
   private[spark] def useSqlSerializer2: Boolean = getConf(USE_SQL_SERIALIZER2)
 
-  private[spark] def useJacksonStreamingAPI: Boolean = getConf(USE_JACKSON_STREAMING_API)
-
   private[spark] def autoBroadcastJoinThreshold: Int = getConf(AUTO_BROADCASTJOIN_THRESHOLD)
 
   private[spark] def defaultSizeInBytes: Long =

sql/core/src/main/scala/org/apache/spark/sql/json/JSONRelation.scala

@@ -157,51 +157,27 @@ private[sql] class JSONRelation(
     }
   }
 
-  private val useJacksonStreamingAPI: Boolean = sqlContext.conf.useJacksonStreamingAPI
-
   override val needConversion: Boolean = false
 
   override lazy val schema = userSpecifiedSchema.getOrElse {
-    if (useJacksonStreamingAPI) {
-      InferSchema(
-        baseRDD(),
-        samplingRatio,
-        sqlContext.conf.columnNameOfCorruptRecord)
-    } else {
-      JsonRDD.nullTypeToStringType(
-        JsonRDD.inferSchema(
-          baseRDD(),
-          samplingRatio,
-          sqlContext.conf.columnNameOfCorruptRecord))
-    }
+    InferSchema(
+      baseRDD(),
+      samplingRatio,
+      sqlContext.conf.columnNameOfCorruptRecord)
   }
 
   override def buildScan(): RDD[Row] = {
-    if (useJacksonStreamingAPI) {
-      JacksonParser(
-        baseRDD(),
-        schema,
-        sqlContext.conf.columnNameOfCorruptRecord).map(_.asInstanceOf[Row])
-    } else {
-      JsonRDD.jsonStringToRow(
-        baseRDD(),
-        schema,
-        sqlContext.conf.columnNameOfCorruptRecord).map(_.asInstanceOf[Row])
-    }
+    JacksonParser(
+      baseRDD(),
+      schema,
+      sqlContext.conf.columnNameOfCorruptRecord).map(_.asInstanceOf[Row])
   }
 
   override def buildScan(requiredColumns: Seq[Attribute], filters: Seq[Expression]): RDD[Row] = {
-    if (useJacksonStreamingAPI) {
-      JacksonParser(
-        baseRDD(),
-        StructType.fromAttributes(requiredColumns),
-        sqlContext.conf.columnNameOfCorruptRecord).map(_.asInstanceOf[Row])
-    } else {
-      JsonRDD.jsonStringToRow(
-        baseRDD(),
-        StructType.fromAttributes(requiredColumns),
-        sqlContext.conf.columnNameOfCorruptRecord).map(_.asInstanceOf[Row])
-    }
+    JacksonParser(
+      baseRDD(),
+      StructType.fromAttributes(requiredColumns),
+      sqlContext.conf.columnNameOfCorruptRecord).map(_.asInstanceOf[Row])
   }
 
   override def insert(data: DataFrame, overwrite: Boolean): Unit = {