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Patrick Wendell authored
This simplifies the shell a bunch and passes all arguments through to spark-submit. There is a tiny incompatibility from 0.9.1 which is that you can't put `-c` _or_ `--cores`, only `--cores`. However, spark-submit will give a good error message in this case, I don't think many people used this, and it's a trivial change for users. Author: Patrick Wendell <pwendell@gmail.com> Closes #542 from pwendell/spark-shell and squashes the following commits: 9eb3e6f [Patrick Wendell] Updating Spark docs b552459 [Patrick Wendell] Andrew's feedback 97720fa [Patrick Wendell] Review feedback aa2900b [Patrick Wendell] SPARK-1619 Launch spark-shell with spark-submit
Patrick Wendell authoredThis simplifies the shell a bunch and passes all arguments through to spark-submit. There is a tiny incompatibility from 0.9.1 which is that you can't put `-c` _or_ `--cores`, only `--cores`. However, spark-submit will give a good error message in this case, I don't think many people used this, and it's a trivial change for users. Author: Patrick Wendell <pwendell@gmail.com> Closes #542 from pwendell/spark-shell and squashes the following commits: 9eb3e6f [Patrick Wendell] Updating Spark docs b552459 [Patrick Wendell] Andrew's feedback 97720fa [Patrick Wendell] Review feedback aa2900b [Patrick Wendell] SPARK-1619 Launch spark-shell with spark-submit
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title: Spark Standalone Mode
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In addition to running on the Mesos or YARN cluster managers, Spark also provides a simple standalone deploy mode. You can launch a standalone cluster either manually, by starting a master and workers by hand, or use our provided launch scripts. It is also possible to run these daemons on a single machine for testing.
Installing Spark Standalone to a Cluster
To install Spark Standalone mode, you simply place a compiled version of Spark on each node on the cluster. You can obtain pre-built versions of Spark with each release or build it yourself.
Starting a Cluster Manually
You can start a standalone master server by executing:
./sbin/start-master.sh
Once started, the master will print out a spark://HOST:PORT
URL for itself, which you can use to connect workers to it,
or pass as the "master" argument to SparkContext
. You can also find this URL on
the master's web UI, which is http://localhost:8080 by default.
Similarly, you can start one or more workers and connect them to the master via: