1 files changed, 0 insertions, 100 deletions
diff --git a/sql/core/src/main/scala/org/apache/spark/rdd/PartitionLocalRDDFunctions.scala b/sql/core/src/main/scala/org/apache/spark/rdd/PartitionLocalRDDFunctions.scala
deleted file mode 100644
index f1230e7526..0000000000
--- a/sql/core/src/main/scala/org/apache/spark/rdd/PartitionLocalRDDFunctions.scala
+++ /dev/null
@@ -1,100 +0,0 @@
-/*
- * Licensed to the Apache Software Foundation (ASF) under one or more
- * contributor license agreements.  See the NOTICE file distributed with
- * this work for additional information regarding copyright ownership.
- * The ASF licenses this file to You under the Apache License, Version 2.0
- * (the "License"); you may not use this file except in compliance with
- * the License.  You may obtain a copy of the License at
- *
- *    http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-package org.apache.spark.rdd
-
-import scala.language.implicitConversions
-
-import scala.reflect._
-import scala.collection.mutable.ArrayBuffer
-
-import org.apache.spark.{Aggregator, InterruptibleIterator, Logging}
-import org.apache.spark.util.collection.AppendOnlyMap
-
-/* Implicit conversions */
-import org.apache.spark.SparkContext._
-
-/**
- * Extra functions on RDDs that perform only local operations.  These can be used when data has
- * already been partitioned correctly.
- */
-private[spark] class PartitionLocalRDDFunctions[K: ClassTag, V: ClassTag](self: RDD[(K, V)])
-  extends Logging
-  with Serializable {
-
-  /**
-   * Cogroup corresponding partitions of `this` and `other`. These two RDDs should have
-   * the same number of partitions. Partitions of these two RDDs are cogrouped
-   * according to the indexes of partitions. If we have two RDDs and
-   * each of them has n partitions, we will cogroup the partition i from `this`
-   * with the partition i from `other`.
-   * This function will not introduce a shuffling operation.
-   */
-  def cogroupLocally[W](other: RDD[(K, W)]): RDD[(K, (Seq[V], Seq[W]))] = {
-    val cg = self.zipPartitions(other)((iter1:Iterator[(K, V)], iter2:Iterator[(K, W)]) => {
-      val map = new AppendOnlyMap[K, Seq[ArrayBuffer[Any]]]
-
-      val update: (Boolean, Seq[ArrayBuffer[Any]]) => Seq[ArrayBuffer[Any]] = (hadVal, oldVal) => {
-        if (hadVal) oldVal else Array.fill(2)(new ArrayBuffer[Any])
-      }
-
-      val getSeq = (k: K) => {
-        map.changeValue(k, update)
-      }
-
-      iter1.foreach { kv => getSeq(kv._1)(0) += kv._2 }
-      iter2.foreach { kv => getSeq(kv._1)(1) += kv._2 }
-
-      map.iterator
-    }).mapValues { case Seq(vs, ws) => (vs.asInstanceOf[Seq[V]], ws.asInstanceOf[Seq[W]])}
-
-    cg
-  }
-
-  /**
-   * Group the values for each key within a partition of the RDD into a single sequence.
-   * This function will not introduce a shuffling operation.
-   */
-  def groupByKeyLocally(): RDD[(K, Seq[V])] = {
-    def createCombiner(v: V) = ArrayBuffer(v)
-    def mergeValue(buf: ArrayBuffer[V], v: V) = buf += v
-    val aggregator = new Aggregator[K, V, ArrayBuffer[V]](createCombiner, mergeValue, _ ++ _)
-    val bufs = self.mapPartitionsWithContext((context, iter) => {
-      new InterruptibleIterator(context, aggregator.combineValuesByKey(iter, context))
-    }, preservesPartitioning = true)
-    bufs.asInstanceOf[RDD[(K, Seq[V])]]
-  }
-
-  /**
-   * Join corresponding partitions of `this` and `other`.
-   * If we have two RDDs and each of them has n partitions,
-   * we will join the partition i from `this` with the partition i from `other`.
-   * This function will not introduce a shuffling operation.
-   */
-  def joinLocally[W](other: RDD[(K, W)]): RDD[(K, (V, W))] = {
-    cogroupLocally(other).flatMapValues {
-      case (vs, ws) => for (v <- vs.iterator; w <- ws.iterator) yield (v, w)
-    }
-  }
-}
-
-private[spark] object PartitionLocalRDDFunctions {
-  implicit def rddToPartitionLocalRDDFunctions[K: ClassTag, V: ClassTag](rdd: RDD[(K, V)]) =
-    new PartitionLocalRDDFunctions(rdd)
-}
-
-