SPARK-1305: Support persisting RDD's directly to Tachyon

Move the PR#468 of apache-incubator-spark to the apache-spark
"Adding an option to persist Spark RDD blocks into Tachyon."

Author: Haoyuan Li <haoyuan@cs.berkeley.edu>
Author: RongGu <gurongwalker@gmail.com>

Closes #158 from RongGu/master and squashes the following commits:

72b7768 [Haoyuan Li] merge master
9f7fa1b [Haoyuan Li] fix code style
ae7834b [Haoyuan Li] minor cleanup
a8b3ec6 [Haoyuan Li] merge master branch
e0f4891 [Haoyuan Li] better check offheap.
55b5918 [RongGu] address matei's comment on the replication of offHeap storagelevel
7cd4600 [RongGu] remove some logic code for tachyonstore's replication
51149e7 [RongGu] address aaron's comment on returning value of the remove() function in tachyonstore
8adfcfa [RongGu] address arron's comment on inTachyonSize
120e48a [RongGu] changed the root-level dir name in Tachyon
5cc041c [Haoyuan Li] address aaron's comments
9b97935 [Haoyuan Li] address aaron's comments
d9a6438 [Haoyuan Li] fix for pspark
77d2703 [Haoyuan Li] change python api.git status
3dcace4 [Haoyuan Li] address matei's comments
91fa09d [Haoyuan Li] address patrick's comments
589eafe [Haoyuan Li] use TRY_CACHE instead of MUST_CACHE
64348b2 [Haoyuan Li] update conf docs.
ed73e19 [Haoyuan Li] Merge branch 'master' of github.com:RongGu/spark-1
619a9a8 [RongGu] set number of directories in TachyonStore back to 64; added a TODO tag for duplicated code from the DiskStore
be79d77 [RongGu] find a way to clean up some unnecessay metods and classed to make the code simpler
49cc724 [Haoyuan Li] update docs with off_headp option
4572f9f [RongGu] reserving the old apply function API of StorageLevel
04301d3 [RongGu] rename StorageLevel.TACHYON to Storage.OFF_HEAP
c9aeabf [RongGu] rename the StorgeLevel.TACHYON as StorageLevel.OFF_HEAP
76805aa [RongGu] unifies the config properties name prefix; add the configs into docs/configuration.md
e700d9c [RongGu] add the SparkTachyonHdfsLR example and some comments
fd84156 [RongGu] use randomUUID to generate sparkapp directory name on tachyon;minor code style fix
939e467 [Haoyuan Li] 0.4.1-thrift from maven central
86a2eab [Haoyuan Li] tachyon 0.4.1-thrift is in the staging repo. but jenkins failed to download it. temporarily revert it back to 0.4.1
16c5798 [RongGu] make the dependency on tachyon as tachyon-0.4.1-thrift
eacb2e8 [RongGu] Merge branch 'master' of https://github.com/RongGu/spark-1
bbeb4de [RongGu] fix the JsonProtocolSuite test failure problem
6adb58f [RongGu] Merge branch 'master' of https://github.com/RongGu/spark-1
d827250 [RongGu] fix JsonProtocolSuie test failure
716e93b [Haoyuan Li] revert the version
ca14469 [Haoyuan Li] bump tachyon version to 0.4.1-thrift
2825a13 [RongGu] up-merging to the current master branch of the apache spark
6a22c1a [Haoyuan Li] fix scalastyle
8968b67 [Haoyuan Li] exclude more libraries from tachyon dependency to be the same as referencing tachyon-client.
77be7e8 [RongGu] address mateiz's comment about the temp folder name problem. The implementation followed mateiz's advice.
1dcadf9 [Haoyuan Li] typo
bf278fa [Haoyuan Li] fix python tests
e82909c [Haoyuan Li] minor cleanup
776a56c [Haoyuan Li] address patrick's and ali's comments from the previous PR
8859371 [Haoyuan Li] various minor fixes and clean up
e3ddbba [Haoyuan Li] add doc to use Tachyon cache mode.
fcaeab2 [Haoyuan Li] address Aaron's comment
e554b1e [Haoyuan Li] add python code
47304b3 [Haoyuan Li] make tachyonStore in BlockMananger lazy val; add more comments StorageLevels.
dc8ef24 [Haoyuan Li] add old storelevel constructor
e01a271 [Haoyuan Li] update tachyon 0.4.1
8011a96 [RongGu] fix a brought-in mistake in StorageLevel
70ca182 [RongGu] a bit change in comment
556978b [RongGu] fix the scalastyle errors
791189b [RongGu] "Adding an option to persist Spark RDD blocks into Tachyon." move the PR#468 of apache-incubator-spark to the apache-spark

3 files changed, 133 insertions, 1 deletions

diff --git a/examples/src/main/scala/org/apache/spark/examples/SparkPi.scala b/examples/src/main/scala/org/apache/spark/examples/SparkPi.scala
index e5a09ecec0..d3babc3ed1 100644
--- a/examples/src/main/scala/org/apache/spark/examples/SparkPi.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/SparkPi.scala
@@ -18,8 +18,8 @@
 package org.apache.spark.examples
 
 import scala.math.random
+
 import org.apache.spark._
-import SparkContext._
 
 /** Computes an approximation to pi */
 object SparkPi {
diff --git a/examples/src/main/scala/org/apache/spark/examples/SparkTachyonHdfsLR.scala b/examples/src/main/scala/org/apache/spark/examples/SparkTachyonHdfsLR.scala
new file mode 100644
index 0000000000..53b303d658
--- /dev/null
+++ b/examples/src/main/scala/org/apache/spark/examples/SparkTachyonHdfsLR.scala
@@ -0,0 +1,80 @@
+/*
+ * 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.examples
+
+import java.util.Random
+import scala.math.exp
+import org.apache.spark.util.Vector
+import org.apache.spark._
+import org.apache.spark.deploy.SparkHadoopUtil
+import org.apache.spark.scheduler.InputFormatInfo
+import org.apache.spark.storage.StorageLevel
+
+/**
+ * Logistic regression based classification.
+ * This example uses Tachyon to persist rdds during computation.
+ */
+object SparkTachyonHdfsLR {
+  val D = 10   // Numer of dimensions
+  val rand = new Random(42)
+
+  case class DataPoint(x: Vector, y: Double)
+
+  def parsePoint(line: String): DataPoint = {
+    val tok = new java.util.StringTokenizer(line, " ")
+    var y = tok.nextToken.toDouble
+    var x = new Array[Double](D)
+    var i = 0
+    while (i < D) {
+      x(i) = tok.nextToken.toDouble; i += 1
+    }
+    DataPoint(new Vector(x), y)
+  }
+
+  def main(args: Array[String]) {
+    if (args.length < 3) {
+      System.err.println("Usage: SparkTachyonHdfsLR <master> <file> <iters>")
+      System.exit(1)
+    }
+    val inputPath = args(1)
+    val conf = SparkHadoopUtil.get.newConfiguration()
+    val sc = new SparkContext(args(0), "SparkTachyonHdfsLR",
+      System.getenv("SPARK_HOME"), SparkContext.jarOfClass(this.getClass), Map(),
+      InputFormatInfo.computePreferredLocations(
+        Seq(new InputFormatInfo(conf, classOf[org.apache.hadoop.mapred.TextInputFormat], inputPath))
+      ))
+    val lines = sc.textFile(inputPath)
+    val points = lines.map(parsePoint _).persist(StorageLevel.OFF_HEAP)
+    val ITERATIONS = args(2).toInt
+
+    // Initialize w to a random value
+    var w = Vector(D, _ => 2 * rand.nextDouble - 1)
+    println("Initial w: " + w)
+
+    for (i <- 1 to ITERATIONS) {
+      println("On iteration " + i)
+      val gradient = points.map { p =>
+        (1 / (1 + exp(-p.y * (w dot p.x))) - 1) * p.y * p.x
+      }.reduce(_ + _)
+      w -= gradient
+    }
+
+    println("Final w: " + w)
+    System.exit(0)
+  }
+}
diff --git a/examples/src/main/scala/org/apache/spark/examples/SparkTachyonPi.scala b/examples/src/main/scala/org/apache/spark/examples/SparkTachyonPi.scala
new file mode 100644
index 0000000000..ce78f0876e
--- /dev/null
+++ b/examples/src/main/scala/org/apache/spark/examples/SparkTachyonPi.scala
@@ -0,0 +1,52 @@
+/*
+ * 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.examples
+
+import scala.math.random
+
+import org.apache.spark._
+import org.apache.spark.storage.StorageLevel
+
+/**
+ *  Computes an approximation to pi
+ *  This example uses Tachyon to persist rdds during computation.
+ */
+object SparkTachyonPi {
+  def main(args: Array[String]) {
+    if (args.length == 0) {
+      System.err.println("Usage: SparkTachyonPi <master> [<slices>]")
+      System.exit(1)
+    }
+    val spark = new SparkContext(args(0), "SparkTachyonPi",
+      System.getenv("SPARK_HOME"), SparkContext.jarOfClass(this.getClass))
+    
+    val slices = if (args.length > 1) args(1).toInt else 2
+    val n = 100000 * slices
+    
+    val rdd = spark.parallelize(1 to n, slices)
+    rdd.persist(StorageLevel.OFF_HEAP)
+    val count = rdd.map { i =>
+      val x = random * 2 - 1
+      val y = random * 2 - 1
+      if (x * x + y * y < 1) 1 else 0
+    }.reduce(_ + _)
+    println("Pi is roughly " + 4.0 * count / n)
+    
+    spark.stop()
+  }
+}