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author | shane-huang <shengsheng.huang@intel.com> | 2013-09-23 11:28:58 +0800 |
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committer | shane-huang <shengsheng.huang@intel.com> | 2013-09-23 11:28:58 +0800 |
commit | dfbdc9ddb773e2b1149e6a6c661f14b631b692d0 (patch) | |
tree | 0e53db325cc8b7985a197d9b13d7adf9208e5c0f /docs/spark-standalone.md | |
parent | 834686b108ce31cbee531d89de6c6e80913448f4 (diff) | |
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added spark-class and spark-executor to sbin
Signed-off-by: shane-huang <shengsheng.huang@intel.com>
Diffstat (limited to 'docs/spark-standalone.md')
-rw-r--r-- | docs/spark-standalone.md | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/docs/spark-standalone.md b/docs/spark-standalone.md index 81cdbefd0c..9d4ad1ec8d 100644 --- a/docs/spark-standalone.md +++ b/docs/spark-standalone.md @@ -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). |