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
>
