tgravescs commented on a change in pull request #33537:
URL: https://github.com/apache/spark/pull/33537#discussion_r681758428
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File path: docs/submitting-applications.md
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@@ -162,9 +162,10 @@ The master URL passed to Spark can be in one of the
following formats:
<tr><th>Master URL</th><th>Meaning</th></tr>
<tr><td> <code>local</code> </td><td> Run Spark locally with one worker thread
(i.e. no parallelism at all). </td></tr>
<tr><td> <code>local[K]</code> </td><td> Run Spark locally with K worker
threads (ideally, set this to the number of cores on your machine). </td></tr>
-<tr><td> <code>local[K,F]</code> </td><td> Run Spark locally with K worker
threads and F maxFailures (see <a
href="configuration.html#scheduling">spark.task.maxFailures</a> for an
explanation of this variable) </td></tr>
+<tr><td> <code>local[K,F]</code> </td><td> Run Spark locally with K worker
threads and F maxFailures (see <a
href="configuration.html#scheduling">spark.task.maxFailures</a> for an
explanation of this variable). </td></tr>
<tr><td> <code>local[*]</code> </td><td> Run Spark locally with as many worker
threads as logical cores on your machine.</td></tr>
<tr><td> <code>local[*,F]</code> </td><td> Run Spark locally with as many
worker threads as logical cores on your machine and F maxFailures.</td></tr>
+<tr><td> <code>local-cluster[N,C,M]</code> </td><td> Run Spark cluster locally
with N number of workers, C cores per worker and M MiB of memory per worker.
Note that local-cluster mode is only for unit tests, to emulate a distributed
cluster in a single JVM.</td></tr>
Review comment:
Sorry I should have been more specific, I meant to start with the unit
test bit just to make sure users saw it first.
local-cluster mode is only for unit tests, it emulates a distributed cluster
in a single JVM with N number of workers, C cores per worker and M MiB of
memory per worker.
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