Apache Spark with Cassandra's Behavior

I am writing a standalone Spark program that receives its data from Cassandra. I followed the examples and created RDD via newAPIHadoopRDD () and the ColumnFamilyInputFormat class. An RDD is thrown, but I get a NotSerializableException when I call the RDD.groupByKey () method:

public static void main(String[] args) {
    SparkConf sparkConf = new SparkConf();
    sparkConf.setMaster("local").setAppName("Test");
    JavaSparkContext ctx = new JavaSparkContext(sparkConf);

    Job job = new Job();
    Configuration jobConf = job.getConfiguration();
    job.setInputFormatClass(ColumnFamilyInputFormat.class);

    ConfigHelper.setInputInitialAddress(jobConf, host);
    ConfigHelper.setInputRpcPort(jobConf, port);
    ConfigHelper.setOutputInitialAddress(jobConf, host);
    ConfigHelper.setOutputRpcPort(jobConf, port);
    ConfigHelper.setInputColumnFamily(jobConf, keySpace, columnFamily, true);
    ConfigHelper.setInputPartitioner(jobConf,"Murmur3Partitioner");
    ConfigHelper.setOutputPartitioner(jobConf,"Murmur3Partitioner");

    SlicePredicate predicate = new SlicePredicate();
    SliceRange sliceRange = new SliceRange();
    sliceRange.setFinish(new byte[0]);
    sliceRange.setStart(new byte[0]);
    predicate.setSlice_range(sliceRange);
    ConfigHelper.setInputSlicePredicate(jobConf, predicate);

    JavaPairRDD<ByteBuffer, SortedMap<ByteBuffer, IColumn>> rdd =
    spark.newAPIHadoopRDD(jobConf,
    ColumnFamilyInputFormat.class.asSubclass(org.apache.hadoop.mapreduce.InputFormat.class),
    ByteBuffer.class, SortedMap.class);

    JavaPairRDD<ByteBuffer, Iterable<SortedMap<ByteBuffer, IColumn>>> groupRdd = rdd.groupByKey();
    System.out.println(groupRdd.count());
}

An exception:

java.io.NotSerializableException: java.nio.HeapByteBuffer java.io.ObjectOutputStream.writeObject0 (ObjectOutputStream.java:1164) java.io.ObjectOutputStream.defaultWriteFields(ObjectOutputStream.java:1518) java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1483) java.io.ObjectOutputStream.writeOrdinaryObject(ObjectOutputStream.java:1400) java.io.ObjectOutputStream.writeObject0 (ObjectOutputStream.java:1158) java.io.ObjectOutputStream.writeObject(ObjectOutputStream.java:330) org.apache.spark.serializer.JavaSerializationStream.writeObject(JavaSerializer.scala: 42) at org.apache.spark.storage.DiskBlockObjectWriter.write(BlockObjectWriter.scala: 179) at org.apache.spark.scheduler.ShuffleMapTask $$ anonfun $runTask $1.apply(ShuffleMapTask.scala: 161) at org.apache.spark.scheduler.ShuffleMapTask $$ anonfun $runTask $1.apply(ShuffleMapTask.scala: 158) scala.collection.Iterator $class.foreach(Iterator.scala: 727) at org.apache.spark.InterruptibleIterator.foreach(InterruptibleIterator.scala: 28) org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala: 158) org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala: 99) at org.apache.spark.scheduler.Task.run(Task.scala: 51) at org.apache.spark.executor.Executor $TaskRunner.run(Executor.scala: 187) java.util.concurrent.ThreadPoolExecutor $Worker.runTask(ThreadPoolExecutor.java:895) java.util.concurrent.ThreadPoolExecutor $Worker.run(ThreadPoolExecutor.java:918) java.lang.Thread.run(Thread.java:662)

, , - . , reduceByKey() :

JavaPairRDD<ByteBuffer, SortedMap<ByteBuffer, IColumn>> reducedRdd = rdd.reduceByKey(
    new Function2<SortedMap<ByteBuffer, IColumn>, SortedMap<ByteBuffer, IColumn>, sortedMap<ByteBuffer, IColumn>>() {
        public SortedMap<ByteBuffer, IColumn> call(SortedMap<ByteBuffer, IColumn> arg0,
            SortedMap<ByteBuffer, IColumn> arg1) throws Exception {
            SortedMap<ByteBuffer, IColumn> sortedMap = new TreeMap<ByteBuffer, IColumn>(arg0.comparator());
            sortedMap.putAll(arg0);
            sortedMap.putAll(arg1);
            return sortedMap;
        }
    }
);

:

  • 1.0.0--hadoop1
  • Cassandra 1.2.12
  • Java 1.6

- , ? , ?

,

+4
1

, , ByteBuffers. , RDD.

DataStax Cassandra Spark,

+4

Source: https://habr.com/ru/post/1546003/


All Articles