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authorshane-huang <shengsheng.huang@intel.com>2013-09-23 11:28:58 +0800
committershane-huang <shengsheng.huang@intel.com>2013-09-23 11:28:58 +0800
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Signed-off-by: shane-huang <shengsheng.huang@intel.com>
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@@ -25,7 +25,7 @@ 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).