Github user jiangxb1987 commented on a diff in the pull request:
https://github.com/apache/spark/pull/21898#discussion_r207710500
--- Diff:
core/src/test/scala/org/apache/spark/scheduler/BarrierTaskContextSuite.scala ---
@@ -0,0 +1,148 @@
+/*
+ * 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.scheduler
+
+import scala.util.Random
+
+import org.apache.spark._
+
+class BarrierTaskContextSuite extends SparkFunSuite with LocalSparkContext
{
+
+ test("global sync by barrier() call") {
+ val conf = new SparkConf()
+ // Init local cluster here so each barrier task runs in a separated
process, thus `barrier()`
+ // call is actually useful.
+ .setMaster("local-cluster[4, 1, 1024]")
+ .setAppName("test-cluster")
+ sc = new SparkContext(conf)
+ val rdd = sc.makeRDD(1 to 10, 4)
+ val rdd2 = rdd.barrier().mapPartitions { (it, context) =>
+ // Sleep for a random time before global sync.
+ Thread.sleep(Random.nextInt(1000))
+ context.barrier()
+ Seq(System.currentTimeMillis()).iterator
+ }
+
+ val times = rdd2.collect()
+ // All the tasks shall finish global sync within a short time slot.
+ assert(times.max - times.min <= 1000)
+ }
+
+ test("support multiple barrier() call within a single task") {
+ val conf = new SparkConf()
+ .setMaster("local-cluster[4, 1, 1024]")
+ .setAppName("test-cluster")
+ sc = new SparkContext(conf)
+ val rdd = sc.makeRDD(1 to 10, 4)
+ val rdd2 = rdd.barrier().mapPartitions { (it, context) =>
+ // Sleep for a random time before global sync.
+ Thread.sleep(Random.nextInt(1000))
+ context.barrier()
+ val time1 = System.currentTimeMillis()
+ // Sleep for a random time between two global syncs.
+ Thread.sleep(Random.nextInt(1000))
+ context.barrier()
+ val time2 = System.currentTimeMillis()
+ Seq((time1, time2)).iterator
+ }
+
+ val times = rdd2.collect()
+ // All the tasks shall finish the first round of global sync within a
short time slot.
+ val times1 = times.map(_._1)
+ assert(times1.max - times1.min <= 1000)
+
+ // All the tasks shall finish the second round of global sync within a
short time slot.
+ val times2 = times.map(_._2)
+ assert(times2.max - times2.min <= 1000)
+ }
+
+ test("throw exception on barrier() call timeout") {
+ val conf = new SparkConf()
+ .set("spark.barrier.sync.timeout", "1")
+ .set("spark.test.noStageRetry", "true")
+ .setMaster("local-cluster[4, 1, 1024]")
+ .setAppName("test-cluster")
+ sc = new SparkContext(conf)
+ val rdd = sc.makeRDD(1 to 10, 4)
+ val rdd2 = rdd.barrier().mapPartitions { (it, context) =>
+ // Task 3 shall sleep 2000ms to ensure barrier() call timeout
+ if (context.taskAttemptId == 3) {
+ Thread.sleep(2000)
+ }
+ context.barrier()
+ it
+ }
+
+ val error = intercept[SparkException] {
+ rdd2.collect()
+ }.getMessage
+ assert(error.contains("The coordinator didn't get all barrier sync
requests"))
+ assert(error.contains("within 1s"))
+ }
+
+ test("throw exception if barrier() call doesn't happen on every task") {
+ val conf = new SparkConf()
+ .set("spark.barrier.sync.timeout", "1")
+ .set("spark.test.noStageRetry", "true")
+ .setMaster("local-cluster[4, 1, 1024]")
+ .setAppName("test-cluster")
+ sc = new SparkContext(conf)
+ val rdd = sc.makeRDD(1 to 10, 4)
+ val rdd2 = rdd.barrier().mapPartitions { (it, context) =>
+ if (context.taskAttemptId != 0) {
+ context.barrier()
+ }
+ it
+ }
+
+ val error = intercept[SparkException] {
+ rdd2.collect()
+ }.getMessage
+ assert(error.contains("The coordinator didn't get all barrier sync
requests"))
+ assert(error.contains("within 1s"))
+ }
+
+ test("throw exception if the number of barrier() calls are not the same
on every task") {
+ val conf = new SparkConf()
+ .set("spark.barrier.sync.timeout", "1")
+ .set("spark.test.noStageRetry", "true")
+ .setMaster("local-cluster[4, 1, 1024]")
+ .setAppName("test-cluster")
+ sc = new SparkContext(conf)
+ val rdd = sc.makeRDD(1 to 10, 4)
+ val rdd2 = rdd.barrier().mapPartitions { (it, context) =>
+ try {
--- End diff --
This actually shows one kind of wrong use case that accidentally skipped a
`barrier()` call for a task. I updated the comment to show why we issue the
problem in a less straight forward way.
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