Provided Spark example expected output?

[mboyanna]

The provided Spark example from README for reading xz files is returning output where:

• number of lines don't match
• output comes out almost like bytestream: .... (4377758,�����b�H�n��8NĂ��6�z.RS��6�q>���@�⧚2u�oX�+�׃�,�=E�(�X�1͜���v郕����ch�U{0PT�Hz�1`uX荲�͉�2q�N�l{�c6��Z�\�� M��&��]s^���P��$��+u|��=���Xh�<|�*) (4377930,��KJ�0�Q0d������ִ��RVY(�o�����V�<I�8��M�6��cԖ�>,k) ... Is this expected format? Why are there fewer lines on the output than uncompressed input?

Here's the Spark/Scala code :

def readXzfile() {

val conf = new SparkConf(true).setAppName("XzUncompressExample").set("spark.shuffle.manager", "SORT").set("spark.serializer", "org.apache.spark.serializer.KryoSerializer").set("spark.akka.frameSize", "50").set("spark.storage.memoryFraction", "0.8").set("spark.cassandra.output.batch.size.rows", "6000").set("spark.executor.extraJavaOptions", "-XX:MaxJavaStackTraceDepth=-1").set("io.compression.codecs", "io.sensesecure.hadoop.xz.XZCodec");

val sc = new SparkContext(conf)

val hadoopConfiguration = new Configuration()

//val file = sc.textFile(fileName.getFileName)

//val rddOfXz = sc.newAPIHadoopFile("file:///Users/bparman/Perforce/testOldAnalyticsCommons10/gn-perseng/eg-analytics/analytics-commons/src/test/resources/*.xz", classOf[org.apache.hadoop.mapred.TextInputFormat], classOf[org.apache.hadoop.io.LongWritable], classOf[org.apache.hadoop.io.Text], conf)

val rddOfXz = sc.newAPIHadoopFile("/user/ubuntu/raw/*.xz", classOf[TextInputFormat], classOf[LongWritable], classOf[Text], hadoopConfiguration)

rddOfXz.foreach(println)

println("Total number of lines is "+rddOfXz.count())

rddOfXz.saveAsTextFile ("/user/ubuntu/uncompressed")

}

Here's my build file:

name := "detailed-commons"

organization := "com.mycompany.commons"

version := "1.0.2"

scalaVersion := "2.10.4"

libraryDependencies += "org.apache.spark" %% "spark-core" % "1.2.0" % "provided"

libraryDependencies += "org.apache.spark" % "spark-sql_2.10" % "1.2.0" % "provided"

libraryDependencies += "org.apache.spark" % "spark-hive_2.10" % "1.2.0" % "provided"

libraryDependencies += "com.datastax.spark" %% "spark-cassandra-connector" % "1.1.1"

libraryDependencies ++= Seq( ("io.sensesecure" % "hadoop-xz" % "1.4"). exclude("commons-beanutils", "commons-beanutils-core"). exclude("commons-collections", "commons-collections") )

publishTo := Some(Resolver.file("detailed-commons-assembly-1.0.2.jar", new File( Path.userHome.absolutePath+"/.ivy2/cache" )) )

[yongtang]

You may need to set the hadoop configuration for compression, not the spark configuration:

val hadoopConfiguration = new Configuration()
hadoopConfiguration.set("io.compression.codecs","io.sensesecure.hadoop.xz.XZCodec")

I tested on Spark 1.3.1 + Hadoop 2.6.0. If you use Spark 1.2.0, which typically bundled with Hadoop 2.4, you may also encounter other issues since hadoop-xz depends on hadoop 2.6. ---yongtang

[yongtang]

Closed for now. Please re-open if you encounter any other issues.