Github user tdas commented on a diff in the pull request: https://github.com/apache/spark/pull/21560#discussion_r198053471 --- Diff: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/continuous/ContinuousCoalesceRDD.scala --- @@ -0,0 +1,118 @@ +/* + * 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.sql.execution.streaming.continuous + +import java.util.UUID + +import org.apache.spark._ +import org.apache.spark.rdd.{CoalescedRDDPartition, RDD} +import org.apache.spark.sql.catalyst.InternalRow +import org.apache.spark.sql.catalyst.expressions.UnsafeRow +import org.apache.spark.sql.execution.streaming.continuous.shuffle._ +import org.apache.spark.util.ThreadUtils + +case class ContinuousCoalesceRDDPartition(index: Int) extends Partition { + // This flag will be flipped on the executors to indicate that the threads processing + // partitions of the write-side RDD have been started. These will run indefinitely + // asynchronously as epochs of the coalesce RDD complete on the read side. + private[continuous] var writersInitialized: Boolean = false +} + +/** + * RDD for continuous coalescing. Asynchronously writes all partitions of `prev` into a local + * continuous shuffle, and then reads them in the task thread using `reader`. + */ +class ContinuousCoalesceRDD( + context: SparkContext, + numPartitions: Int, + readerQueueSize: Int, + epochIntervalMs: Long, + prev: RDD[InternalRow]) + extends RDD[InternalRow](context, Nil) { + + override def getPartitions: Array[Partition] = + (0 until numPartitions).map(ContinuousCoalesceRDDPartition).toArray + + // When we support more than 1 target partition, we'll need to figure out how to pass in the + // required partitioner. + private val outputPartitioner = new HashPartitioner(1) + + private val readerEndpointNames = (0 until numPartitions).map { i => + s"ContinuousCoalesceRDD-part$i-${UUID.randomUUID()}" + } + + val readerRDD = new ContinuousShuffleReadRDD( --- End diff -- private
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