On my master grep native /root/spark/conf/spark-env.sh
SPARK_SUBMIT_LIBRARY_PATH="$SPARK_SUBMIT_LIBRARY_PATH:/root/ephemeral-hdfs/l ib/native/" $ ls /root/ephemeral-hdfs/lib/native/ libhadoop.a libhadoop.so libhadooputils.a libsnappy.so libsnappy.so.1.1.3 Linux-i386-32 libhadooppipes.a libhadoop.so.1.0.0 libhdfs.a libsnappy.so.1 Linux-amd64-64 From: Andrew Davidson <a...@santacruzintegration.com> Date: Tuesday, November 17, 2015 at 2:29 PM To: "user @spark" <user@spark.apache.org> Subject: Re: WARN LoadSnappy: Snappy native library not loaded > I forgot to mention. I am using spark-1.5.1-bin-hadoop2.6 > > From: Andrew Davidson <a...@santacruzintegration.com> > Date: Tuesday, November 17, 2015 at 2:26 PM > To: "user @spark" <user@spark.apache.org> > Subject: Re: WARN LoadSnappy: Snappy native library not loaded > >> FYI >> >> After 17 min. only 26112/228155 have succeeded >> >> This seems very slow >> >> Kind regards >> >> Andy >> >> >> >> From: Andrew Davidson <a...@santacruzintegration.com> >> Date: Tuesday, November 17, 2015 at 2:22 PM >> To: "user @spark" <user@spark.apache.org> >> Subject: WARN LoadSnappy: Snappy native library not loaded >> >> >>> 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 $*
