Github user rxin commented on a diff in the pull request:
https://github.com/apache/spark/pull/2931#discussion_r19454541
--- Diff:
streaming/src/test/scala/org/apache/spark/streaming/rdd/HDFSBackedBlockRDDSuite.scala
---
@@ -0,0 +1,163 @@
+/*
+ * 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.streaming.rdd
+
+import java.io.File
+import java.util.concurrent.atomic.AtomicInteger
+
+import org.apache.spark.{SparkConf, SparkContext}
+
+import scala.collection.mutable.ArrayBuffer
+import org.scalatest.{BeforeAndAfterAll, BeforeAndAfter, FunSuite}
+
+import com.google.common.io.Files
+import org.apache.hadoop.conf.Configuration
+
+import org.apache.spark.storage.{BlockManager, BlockId, StorageLevel,
StreamBlockId}
+import org.apache.spark.streaming.util.{WriteAheadLogFileSegment,
WriteAheadLogWriter}
+
+class HDFSBackedBlockRDDSuite extends FunSuite with BeforeAndAfter with
BeforeAndAfterAll {
+ val conf = new SparkConf()
+ .setMaster("local[2]")
+ .setAppName(this.getClass.getSimpleName)
+ val hadoopConf = new Configuration()
+ // Since the same BM is reused in all tests, use an atomic int to
generate ids
+ val idGenerator = new AtomicInteger(0)
+
+ var sparkContext: SparkContext = null
+ var blockManager: BlockManager = null
+ var file: File = null
+ var dir: File = null
+
+ before {
+ blockManager = sparkContext.env.blockManager
+ dir = Files.createTempDir()
+ file = new File(dir, "BlockManagerWrite")
+ }
+
+ after {
+ file.delete()
+ dir.delete()
+ }
+
+ override def beforeAll(): Unit = {
+ sparkContext = new SparkContext(conf)
+ }
+
+ override def afterAll(): Unit = {
+ // Copied from LocalSparkContext which can't be imported since
spark-core test-jar does not
+ // get imported properly by sbt even if it is created.
+ sparkContext.stop()
+ System.clearProperty("spark.driver.port")
+ }
+
+ test("Data available in BM and HDFS") {
+ testHDFSBackedRDD(5, 5, 20, 5)
+ }
+
+ test("Data available in in BM but not in HDFS") {
+ testHDFSBackedRDD(5, 0, 20, 5)
+ }
+
+ test("Data available in in HDFS and not in BM") {
+ testHDFSBackedRDD(0, 5, 20, 5)
+ }
+
+ test("Data partially available in BM, and the rest in HDFS") {
+ testHDFSBackedRDD(3, 2, 20, 5)
+ }
+
+ /**
+ * Write a bunch of events into the HDFS Block RDD. Put a part of all of
them to the
+ * BlockManager, so all reads need not happen from HDFS.
+ * @param total Total number of Strings to write
+ * @param blockCount Number of blocks to write (therefore, total # of
events per block =
+ * total/blockCount
+ */
+ private def testHDFSBackedRDD(
+ writeToBMCount: Int,
+ writeToHDFSCount: Int,
+ total: Int,
+ blockCount: Int
+ ) {
+ val countPerBlock = total / blockCount
+ val blockIds = (0 until blockCount).map { i =>
+ StreamBlockId(idGenerator.incrementAndGet(),
idGenerator.incrementAndGet())
+ }
+
+ val writtenStrings = generateData(total, countPerBlock)
+
+ if (writeToBMCount != 0) {
+ (0 until writeToBMCount).foreach { i =>
+ blockManager
+ .putIterator(blockIds(i), writtenStrings(i).iterator,
StorageLevel.MEMORY_ONLY_SER)
+ }
+ }
+
+ val segments = {
+ if (writeToHDFSCount != 0) {
+ // Generate some fake segments for the blocks in BM so the RDD
does not complain
+ generateFakeSegments(writeToBMCount) ++
+ writeDataToHDFS(writtenStrings.slice(writeToBMCount, blockCount),
+ blockIds.slice(writeToBMCount, blockCount))
+ } else {
+ generateFakeSegments(blockCount)
+ }
+ }
+
+ val rdd = new HDFSBackedBlockRDD[String](sparkContext, hadoopConf,
blockIds.toArray,
+ segments.toArray, false, StorageLevel.MEMORY_ONLY)
+
+ val dataFromRDD = rdd.collect()
+ // verify each partition is equal to the data pulled out
+ assert(writtenStrings.flatten === dataFromRDD)
+ }
+
+ /**
+ * Write data to HDFS and get a list of Seq of Seqs in which each Seq
represents the data that
+ * went into one block.
+ * @param count Number of Strings to write
+ * @param countPerBlock Number of Strings per block
+ * @return Seq of Seqs, each of these Seqs is one block
+ */
+ private def generateData(
+ count: Int,
+ countPerBlock: Int
+ ): Seq[Seq[String]] = {
+ val strings = (0 until count).map { _ =>
scala.util.Random.nextString(50)}
+ strings.grouped(countPerBlock).toSeq
+ }
+
+ private def writeDataToHDFS(
+ blockData: Seq[Seq[String]],
+ blockIds: Seq[BlockId]
+ ): Seq[WriteAheadLogFileSegment] = {
+ assert(blockData.size === blockIds.size)
+ val segments = new ArrayBuffer[WriteAheadLogFileSegment]()
+ val writer = new WriteAheadLogWriter(file.toString, hadoopConf)
+ blockData.zip(blockIds).foreach {
+ case (data, id) =>
+ segments += writer.write(blockManager.dataSerialize(id,
data.iterator))
+ }
+ writer.close()
+ segments
+ }
+
+ private def generateFakeSegments(count: Int):
Seq[WriteAheadLogFileSegment] = {
+ (0 until count).map { _ => new WriteAheadLogFileSegment("random", 0l,
0) }
--- End diff --
Seq.fill
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