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| author | Matei Zaharia <matei@eecs.berkeley.edu> | 2012-11-16 20:48:35 -0800 |
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| committer | Matei Zaharia <matei@eecs.berkeley.edu> | 2012-11-16 20:49:02 -0800 |
| commit | 6adc7c965f35ede8fb09452e278b2f17981ff600 (patch) | |
| tree | 0c5e1a376ce518d24cfa5f7c75ae5674fad69450 /docs/running-on-mesos.md | |
| parent | c23a74df0ab1ab105a3ad6b70e93bc0aa614771d (diff) | |
| download | spark-6adc7c965f35ede8fb09452e278b2f17981ff600.tar.gz spark-6adc7c965f35ede8fb09452e278b2f17981ff600.tar.bz2 spark-6adc7c965f35ede8fb09452e278b2f17981ff600.zip | |
Doc fix
Diffstat (limited to 'docs/running-on-mesos.md')
| -rw-r--r-- | docs/running-on-mesos.md | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/docs/running-on-mesos.md b/docs/running-on-mesos.md index 97564d7426..f4a3eb667c 100644 --- a/docs/running-on-mesos.md +++ b/docs/running-on-mesos.md @@ -15,7 +15,7 @@ Spark can run on private clusters managed by the [Apache Mesos](http://incubator 6. Copy Spark and Mesos to the _same_ paths on all the nodes in the cluster (or, for Mesos, `make install` on every node). 7. Configure Mesos for deployment: * On your master node, edit `<prefix>/var/mesos/deploy/masters` to list your master and `<prefix>/var/mesos/deploy/slaves` to list the slaves, where `<prefix>` is the prefix where you installed Mesos (`/usr/local` by default). - * On all nodes, edit `<prefix>/var/mesos/deploy/mesos.conf` and add the line `master=HOST:5050`, where HOST is your master node. + * On all nodes, edit `<prefix>/var/mesos/conf/mesos.conf` and add the line `master=HOST:5050`, where HOST is your master node. * Run `<prefix>/sbin/mesos-start-cluster.sh` on your master to start Mesos. If all goes well, you should see Mesos's web UI on port 8080 of the master machine. * See Mesos's README file for more information on deploying it. 8. To run a Spark job against the cluster, when you create your `SparkContext`, pass the string `mesos://HOST:5050` as the first parameter, where `HOST` is the machine running your Mesos master. In addition, pass the location of Spark on your nodes as the third parameter, and a list of JAR files containing your JAR's code as the fourth (these will automatically get copied to the workers). For example: |