Hi Joshua, What cluster manager are you using, standalone or YARN? (Note that standalone here does not mean local mode).
If standalone, you need to do `setMaster("spark://[CLUSTER_URL]:7077")`, where CLUSTER_URL is the machine that started the standalone Master. If YARN, you need to do `setMaster("yarn")`, assuming that all the Hadoop configurations files such as core-site.xml are already set up properly. -Andrew 2015-09-21 8:53 GMT-07:00 Hemant Bhanawat <hemant9...@gmail.com>: > When you specify master as local[2], it starts the spark components in a > single jvm. You need to specify the master correctly. > I have a default AWS EMR cluster (1 master, 1 slave) with Spark. When I > run a Spark process, it works fine -- but only on the master, as if it were > standalone. > > The web-UI and logging code shows only 1 executor, the localhost. > > How can I diagnose this? > > (I create *SparkConf, *in Python, with *setMaster('local[2]'). )* > > (Strangely, though I don't think that this causes the problem, there is > almost nothing spark-related on the slave machine:* /usr/lib/spark *has a > few jars, but that's it: *datanucleus-api-jdo.jar datanucleus-core.jar > datanucleus-rdbms.jar spark-yarn-shuffle.jar. *But this is an AWS EMR > cluster as created by* create-cluster*, so I would assume that the slave > and master are configured OK out-of the box.) > > Joshua >