I started a spark POC. I created a ec2 cluster on AWS using spark-c2. I have 3 slaves. In general I am running into trouble even with small work loads. I am using IPython notebooks running on my spark cluster. Everything is painfully slow. I am using the standAlone cluster manager. I noticed that I am getting the following warning on my driver console. Any idea what the problem might be?
15/11/17 22:01:59 WARN MetricsSystem: Using default name DAGScheduler for source because spark.app.id is not set. 15/11/17 22:03:05 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable 15/11/17 22:03:05 WARN LoadSnappy: Snappy native library not loaded Here is an overview of my POS app. I have a file on hdfs containing about 5000 twitter status strings. tweetStrings = sc.textFile(dataURL) jTweets = (tweetStrings.map(lambda x: json.loads(x)).take(10)) Generated the following error ³error occurred while calling o78.partitions.: java.lang.OutOfMemoryError: GC overhead limit exceeded² Any idea what we need to do to improve new spark user¹s out of the box experience? Kind regards Andy export PYSPARK_PYTHON=python3.4 export PYSPARK_DRIVER_PYTHON=python3.4 export IPYTHON_OPTS="notebook --no-browser --port=7000 --log-level=WARN" MASTER_URL=spark://ec2-55-218-207-122.us-west-1.compute.amazonaws.com:7077 numCores=2 $SPARK_ROOT/bin/pyspark --master $MASTER_URL --total-executor-cores $numCores $*
