Github user mateiz commented on a diff in the pull request:
https://github.com/apache/spark/pull/50#discussion_r10201080
--- Diff:
core/src/test/scala/org/apache/spark/storage/FlatmapIteratorSuite.scala ---
@@ -0,0 +1,83 @@
+/*
+ * 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.storage
+
+import org.scalatest.FunSuite
+import org.apache.spark.{SharedSparkContext, SparkConf, LocalSparkContext,
SparkContext}
+
+
+class FlatmapIteratorSuite extends FunSuite with LocalSparkContext {
+ /* Tests the ability of Spark to deal with user provided iterators from
flatMap
+ * calls, that may generate more data then available memory. In any
+ * memory based persistance Spark will unroll the iterator into an
ArrayBuffer
+ * for caching, however in the case that the use defines DISK_ONLY
persistance,
+ * the iterator will be fed directly to the serializer and written to
disk.
+ *
+ * This also tests the ObjectOutputStream reset rate. When serializing
using the
+ * Java serialization system, the serializer caches objects to prevent
writing redundant
+ * data, however that stops GC of those objects. By calling 'reset' you
flush that
+ * info from the serializer, and allow old objects to be GC'd
+ */
+ test("Flatmap Iterator to Disk") {
+ val sconf = new SparkConf().setMaster("local-cluster[1,1,512]")
+ .setAppName("iterator_to_disk_test")
+ sc = new SparkContext(sconf)
+ try {
+ val expand_size = 100
+ val data = sc.parallelize( (1 to 5).toSeq ).
+ flatMap( x => Stream.range(0, expand_size) )
+ var persisted = data.persist(StorageLevel.DISK_ONLY)
+ println(persisted.count())
+ assert( persisted.count() == 500)
+ assert( persisted.filter( _==1 ).count() == 5 )
--- End diff --
Also in ScalaTest, you can use `===` instead of `==` to get nicer error
messages (e.g. "expected 5 but got 4" instead of "assertion failed: false").
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