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| author | Prashant Sharma <prashant.s@imaginea.com> | 2014-01-02 17:55:21 +0530 |
|---|---|---|
| committer | Prashant Sharma <prashant.s@imaginea.com> | 2014-01-02 17:55:21 +0530 |
| commit | 980afd280a331103ce7391adaf484dd497218741 (patch) | |
| tree | a3bef12d6c1296aa42930b8b91a07d8775831e6c /docs/spark-standalone.md | |
| parent | 3713f8129a618a633a7aca8c944960c3e7ac9d3b (diff) | |
| parent | 52ccf4f859d92ed9e86d3720a983ac2c4a1c23bf (diff) | |
| download | spark-980afd280a331103ce7391adaf484dd497218741.tar.gz spark-980afd280a331103ce7391adaf484dd497218741.tar.bz2 spark-980afd280a331103ce7391adaf484dd497218741.zip | |
Merge branch 'scripts-reorg' of github.com:shane-huang/incubator-spark into spark-915-segregate-scripts
Conflicts:
bin/spark-shell
core/pom.xml
core/src/main/scala/org/apache/spark/SparkContext.scala
core/src/main/scala/org/apache/spark/scheduler/cluster/mesos/CoarseMesosSchedulerBackend.scala
core/src/main/scala/org/apache/spark/ui/UIWorkloadGenerator.scala
core/src/test/scala/org/apache/spark/DriverSuite.scala
python/run-tests
sbin/compute-classpath.sh
sbin/spark-class
sbin/stop-slaves.sh
Diffstat (limited to 'docs/spark-standalone.md')
| -rw-r--r-- | docs/spark-standalone.md | 14 |
1 files changed, 7 insertions, 7 deletions
diff --git a/docs/spark-standalone.md b/docs/spark-standalone.md index f7f0b78908..c2ce23081a 100644 --- a/docs/spark-standalone.md +++ b/docs/spark-standalone.md @@ -28,7 +28,7 @@ the master's web UI, which is [http://localhost:8080](http://localhost:8080) by Similarly, you can start one or more workers and connect them to the master via: - ./spark-class org.apache.spark.deploy.worker.Worker spark://IP:PORT + ./sbin/spark-class org.apache.spark.deploy.worker.Worker spark://IP:PORT Once you have started a worker, look at the master's web UI ([http://localhost:8080](http://localhost:8080) by default). You should see the new node listed there, along with its number of CPUs and memory (minus one gigabyte left for the OS). @@ -70,12 +70,12 @@ To launch a Spark standalone cluster with the launch scripts, you need to create Once you've set up this file, you can launch or stop your cluster with the following shell scripts, based on Hadoop's deploy scripts, and available in `SPARK_HOME/bin`: -- `bin/start-master.sh` - Starts a master instance on the machine the script is executed on. -- `bin/start-slaves.sh` - Starts a slave instance on each machine specified in the `conf/slaves` file. -- `bin/start-all.sh` - Starts both a master and a number of slaves as described above. -- `bin/stop-master.sh` - Stops the master that was started via the `bin/start-master.sh` script. -- `bin/stop-slaves.sh` - Stops the slave instances that were started via `bin/start-slaves.sh`. -- `bin/stop-all.sh` - Stops both the master and the slaves as described above. +- `sbin/start-master.sh` - Starts a master instance on the machine the script is executed on. +- `sbin/start-slaves.sh` - Starts a slave instance on each machine specified in the `conf/slaves` file. +- `sbin/start-all.sh` - Starts both a master and a number of slaves as described above. +- `sbin/stop-master.sh` - Stops the master that was started via the `bin/start-master.sh` script. +- `sbin/stop-slaves.sh` - Stops the slave instances that were started via `bin/start-slaves.sh`. +- `sbin/stop-all.sh` - Stops both the master and the slaves as described above. Note that these scripts must be executed on the machine you want to run the Spark master on, not your local machine. |