Github user tdas commented on a diff in the pull request:
https://github.com/apache/spark/pull/21560#discussion_r196609584
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/continuous/ContinuousCoalesceRDD.scala
---
@@ -0,0 +1,93 @@
+/*
+ * 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 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._
+
+case class ContinuousCoalesceRDDPartition(index: Int) extends Partition {
+ 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(var reader: ContinuousShuffleReadRDD, var
prev: RDD[InternalRow])
+ extends RDD[InternalRow](reader.context, Nil) {
+
+ override def getPartitions: Array[Partition] =
Array(ContinuousCoalesceRDDPartition(0))
+
+ override def compute(split: Partition, context: TaskContext):
Iterator[InternalRow] = {
+ assert(split.index == 0)
+ // lazy initialize endpoint so writer can send to it
+
reader.partitions(0).asInstanceOf[ContinuousShuffleReadPartition].endpoint
+
+ if
(!split.asInstanceOf[ContinuousCoalesceRDDPartition].writersInitialized) {
+ val rpcEnv = SparkEnv.get.rpcEnv
+ val outputPartitioner = new HashPartitioner(1)
+ val endpointRefs = reader.endpointNames.map { endpointName =>
+ rpcEnv.setupEndpointRef(rpcEnv.address, endpointName)
+ }
+
+ val threads = prev.partitions.map { prevSplit =>
+ new Thread() {
+ override def run(): Unit = {
+ TaskContext.setTaskContext(context)
+
+ val writer: ContinuousShuffleWriter = new
RPCContinuousShuffleWriter(
+ prevSplit.index, outputPartitioner, endpointRefs.toArray)
+
+ EpochTracker.initializeCurrentEpoch(
+
context.getLocalProperty(ContinuousExecution.START_EPOCH_KEY).toLong)
+ while (!context.isInterrupted() && !context.isCompleted()) {
+ writer.write(prev.compute(prevSplit,
context).asInstanceOf[Iterator[UnsafeRow]])
+ // Note that current epoch is a non-inheritable thread
local, so each writer thread
+ // can properly increment its own epoch without affecting
the main task thread.
+ EpochTracker.incrementCurrentEpoch()
+ }
+ }
+ }
+ }
+
+ context.addTaskCompletionListener { ctx =>
+ threads.foreach(_.interrupt())
+ }
+
+
split.asInstanceOf[ContinuousCoalesceRDDPartition].writersInitialized = true
+ threads.foreach(_.start())
+ }
+
+ reader.compute(reader.partitions(split.index), context)
+ }
+
+ override def getDependencies: Seq[Dependency[_]] = {
+ Seq(new NarrowDependency(prev) {
+ def getParents(id: Int): Seq[Int] = Seq(0)
--- End diff --
Should 1 partition of this class depend on all parant RDD partitions, and
not just the 0.
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