Github user tdas commented on a diff in the pull request:
https://github.com/apache/spark/pull/21337#discussion_r189130600
--- Diff:
sql/core/src/test/scala/org/apache/spark/sql/streaming/continuous/shuffle/ContinuousShuffleReadSuite.scala
---
@@ -0,0 +1,137 @@
+/*
+ * 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.shuffle
+
+import org.apache.spark.{TaskContext, TaskContextImpl}
+import org.apache.spark.sql.catalyst.expressions.{GenericInternalRow,
UnsafeProjection}
+import org.apache.spark.sql.streaming.StreamTest
+import org.apache.spark.sql.types.{DataType, IntegerType}
+
+class ContinuousShuffleReadSuite extends StreamTest {
+
+ private def unsafeRow(value: Int) = {
+ UnsafeProjection.create(Array(IntegerType : DataType))(
+ new GenericInternalRow(Array(value: Any)))
+ }
+
+ var ctx: TaskContextImpl = _
+
+ override def beforeEach(): Unit = {
+ super.beforeEach()
+ ctx = TaskContext.empty()
+ TaskContext.setTaskContext(ctx)
+ }
+
+ override def afterEach(): Unit = {
+ ctx.markTaskCompleted(None)
+ TaskContext.unset()
+ ctx = null
+ super.afterEach()
+ }
+
+ test("receiver stopped with row last") {
+ val rdd = new ContinuousShuffleReadRDD(sparkContext, numPartitions = 1)
+ val endpoint =
rdd.partitions(0).asInstanceOf[ContinuousShuffleReadPartition].endpoint
+ endpoint.askSync[Unit](ReceiverEpochMarker())
+ endpoint.askSync[Unit](ReceiverRow(unsafeRow(111)))
+
+ ctx.markTaskCompleted(None)
+ val receiver =
rdd.partitions(0).asInstanceOf[ContinuousShuffleReadPartition].receiver
+ eventually(timeout(streamingTimeout)) {
+ assert(receiver.stopped.get())
+ }
+ }
+
+ test("receiver stopped with marker last") {
+ val rdd = new ContinuousShuffleReadRDD(sparkContext, numPartitions = 1)
+ val endpoint =
rdd.partitions(0).asInstanceOf[ContinuousShuffleReadPartition].endpoint
+ endpoint.askSync[Unit](ReceiverRow(unsafeRow(111)))
+ endpoint.askSync[Unit](ReceiverEpochMarker())
+
+ ctx.markTaskCompleted(None)
+ val receiver =
rdd.partitions(0).asInstanceOf[ContinuousShuffleReadPartition].receiver
+ eventually(timeout(streamingTimeout)) {
+ assert(receiver.stopped.get())
+ }
+ }
+
+ test("one epoch") {
+ val rdd = new ContinuousShuffleReadRDD(sparkContext, numPartitions = 1)
+ val endpoint =
rdd.partitions(0).asInstanceOf[ContinuousShuffleReadPartition].endpoint
+ endpoint.askSync[Unit](ReceiverRow(unsafeRow(111)))
+ endpoint.askSync[Unit](ReceiverRow(unsafeRow(222)))
+ endpoint.askSync[Unit](ReceiverRow(unsafeRow(333)))
+ endpoint.askSync[Unit](ReceiverEpochMarker())
+
+ val iter = rdd.compute(rdd.partitions(0), ctx)
+ assert(iter.next().getInt(0) == 111)
+ assert(iter.next().getInt(0) == 222)
+ assert(iter.next().getInt(0) == 333)
+ assert(!iter.hasNext)
+ }
+
+ test("multiple epochs") {
+ val rdd = new ContinuousShuffleReadRDD(sparkContext, numPartitions = 1)
+ val endpoint =
rdd.partitions(0).asInstanceOf[ContinuousShuffleReadPartition].endpoint
+ endpoint.askSync[Unit](ReceiverRow(unsafeRow(111)))
+ endpoint.askSync[Unit](ReceiverEpochMarker())
+ endpoint.askSync[Unit](ReceiverRow(unsafeRow(222)))
+ endpoint.askSync[Unit](ReceiverRow(unsafeRow(333)))
+ endpoint.askSync[Unit](ReceiverEpochMarker())
+
+ val firstEpoch = rdd.compute(rdd.partitions(0), ctx)
+ assert(firstEpoch.next().getInt(0) == 111)
+ assert(!firstEpoch.hasNext)
+
+ val secondEpoch = rdd.compute(rdd.partitions(0), ctx)
+ assert(secondEpoch.next().getInt(0) == 222)
+ assert(secondEpoch.next().getInt(0) == 333)
+ assert(!secondEpoch.hasNext)
+ }
+
+ test("empty epochs") {
+ val rdd = new ContinuousShuffleReadRDD(sparkContext, numPartitions = 1)
+ val endpoint =
rdd.partitions(0).asInstanceOf[ContinuousShuffleReadPartition].endpoint
+ endpoint.askSync[Unit](ReceiverEpochMarker())
+ endpoint.askSync[Unit](ReceiverEpochMarker())
+ endpoint.askSync[Unit](ReceiverRow(unsafeRow(111)))
+ endpoint.askSync[Unit](ReceiverEpochMarker())
+ endpoint.askSync[Unit](ReceiverEpochMarker())
+
+ assert(rdd.compute(rdd.partitions(0), ctx).isEmpty)
+ assert(rdd.compute(rdd.partitions(0), ctx).isEmpty)
+ val thirdEpoch = rdd.compute(rdd.partitions(0), ctx)
+ assert(thirdEpoch.next().getInt(0) == 111)
+ assert(rdd.compute(rdd.partitions(0), ctx).isEmpty)
+ assert(rdd.compute(rdd.partitions(0), ctx).isEmpty)
+ }
+
+ test("multiple partitions") {
+ val rdd = new ContinuousShuffleReadRDD(sparkContext, numPartitions = 5)
+ for (p <- rdd.partitions) {
--- End diff --
I would rather add data to all the partitions all at once, and try to read
from all the partitions. This would test that each partition has their own
distinct receivers correctly configured. Thats the real point of a
multi-partition test.
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