Why doesn't Spark Standalone cluster use all available cores?

I have done the following configuration for Apache Spark 1.2.1 Standalone Cluster:

• Hadoop 2.6.0
• 2 nodes - one master and one slave - in a stand-alone cluster
• 3- node Cassandra
• total cores: 6 (2 masters, 4 slaves)
• total memory: 13 GB

I am running Spark in offline cluster manager as:

./spark-submit --class com.b2b.processor.ProcessSampleJSONFileUpdate \
               --conf num-executors=2 \
               --executor-memory 2g \
               --driver-memory 3g \
               --deploy-mode cluster \
               --supervise \
               --master spark://abc.xyz.net:7077 \ 
               hdfs://abc:9000/b2b/b2bloader-1.0.jar ds6_2000/*.json 

      

        
        
        
      

    

My work is doing well, i.e. reads data from files and inserts it into Cassandra.

Spark documentation says that a standalone cluster uses all available cores, but my cluster only uses 1 core per application. Also, after running an application on Spark UI, it shows Applications: 0 and Drivers: 1 running.

My request:

• Why doesn't it use all available 6 cores?
• Why customize a UI showing apps: 0 Launch?

Code:

public static void main(String[] args) throws Exception {

  String fileName = args[0];
  System.out.println("----->Filename : "+fileName);        

  Long now = new Date().getTime();

  SparkConf conf = new SparkConf(true)
           .setMaster("local")
           .setAppName("JavaSparkSQL_" +now)
           .set("spark.executor.memory", "1g")
           .set("spark.cassandra.connection.host", "192.168.1.65")
           .set("spark.cassandra.connection.native.port", "9042")
           .set("spark.cassandra.connection.rpc.port", "9160");

  JavaSparkContext ctx = new JavaSparkContext(conf);

  JavaRDD<String> input =  ctx.textFile("hdfs://abc.xyz.net:9000/dataLoad/resources/" + fileName,6);
  JavaRDD<DataInput> result = input.mapPartitions(new ParseJson()).filter(new FilterLogic());

  System.out.print("Count --> "+result.count());
  System.out.println(StringUtils.join(result.collect(), ","));

  javaFunctions(result).writerBuilder("ks","pt_DataInput",mapToRow(DataInput.class)).saveToCassandra();

}