Address comments

Author: dongjoon-hyun

core/src/test/scala/org/apache/spark/scheduler/WorkerDecommissionExtendedSuite.scala

@@ -32,17 +32,17 @@ import org.apache.spark.scheduler.cluster.StandaloneSchedulerBackend
 class WorkerDecommissionExtendedSuite extends SparkFunSuite with LocalSparkContext {
   private val conf = new org.apache.spark.SparkConf()
     .setAppName(getClass.getName)
-    .set(SPARK_MASTER, "local-cluster[10,1,512]")
+    .set(SPARK_MASTER, "local-cluster[5,1,512]")
     .set(EXECUTOR_MEMORY, "512m")
     .set(DYN_ALLOCATION_ENABLED, true)
     .set(DYN_ALLOCATION_SHUFFLE_TRACKING_ENABLED, true)
-    .set(DYN_ALLOCATION_INITIAL_EXECUTORS, 10)
+    .set(DYN_ALLOCATION_INITIAL_EXECUTORS, 5)
     .set(WORKER_DECOMMISSION_ENABLED, true)
 
   test("Worker decommission and executor idle timeout") {
     sc = new SparkContext(conf.set(DYN_ALLOCATION_EXECUTOR_IDLE_TIMEOUT.key, "10s"))
     withSpark(sc) { sc =>
-      TestUtils.waitUntilExecutorsUp(sc, 10, 60000)
+      TestUtils.waitUntilExecutorsUp(sc, 5, 60000)
       val rdd1 = sc.parallelize(1 to 10, 2)
       val rdd2 = rdd1.map(x => (1, x))
       val rdd3 = rdd2.reduceByKey(_ + _)
@@ -54,10 +54,10 @@ class WorkerDecommissionExtendedSuite extends SparkFunSuite with LocalSparkConte
     }
   }
 
-  test("Decommission 9 executors from 10 executors in total") {
+  test("Decommission 4 executors from 5 executors in total") {
     sc = new SparkContext(conf)
     withSpark(sc) { sc =>
-      TestUtils.waitUntilExecutorsUp(sc, 10, 60000)
+      TestUtils.waitUntilExecutorsUp(sc, 5, 60000)
       val rdd1 = sc.parallelize(1 to 100000, 200)
       val rdd2 = rdd1.map(x => (x % 100, x))
       val rdd3 = rdd2.reduceByKey(_ + _)