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Posted to commits@spark.apache.org by sr...@apache.org on 2015/10/04 10:32:10 UTC
spark git commit: [SPARK-9570] [DOCS] Consistent recommendation for
submitting spark apps to YARN,
-master yarn --deploy-mode x vs -master yarn-x'.
Repository: spark
Updated Branches:
refs/heads/master 721e8b5f3 -> 82bbc2a5f
[SPARK-9570] [DOCS] Consistent recommendation for submitting spark apps to YARN, -master yarn --deploy-mode x vs -master yarn-x'.
Recommend `--master yarn --deploy-mode {cluster,client}` consistently in docs.
Follow-on to https://github.com/apache/spark/pull/8385
CC nssalian
Author: Sean Owen <so...@cloudera.com>
Closes #8968 from srowen/SPARK-9570.
Project: http://git-wip-us.apache.org/repos/asf/spark/repo
Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/82bbc2a5
Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/82bbc2a5
Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/82bbc2a5
Branch: refs/heads/master
Commit: 82bbc2a5f2c74604db59060cb5e462a057398ddd
Parents: 721e8b5
Author: Sean Owen <so...@cloudera.com>
Authored: Sun Oct 4 09:31:52 2015 +0100
Committer: Sean Owen <so...@cloudera.com>
Committed: Sun Oct 4 09:31:52 2015 +0100
----------------------------------------------------------------------
README.md | 2 +-
docs/running-on-yarn.md | 32 +++++++++++++++++---------------
docs/sql-programming-guide.md | 2 +-
docs/submitting-applications.md | 25 +++++++++++++++----------
4 files changed, 34 insertions(+), 27 deletions(-)
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http://git-wip-us.apache.org/repos/asf/spark/blob/82bbc2a5/README.md
----------------------------------------------------------------------
diff --git a/README.md b/README.md
index 76e29b4..4116ef3 100644
--- a/README.md
+++ b/README.md
@@ -59,7 +59,7 @@ will run the Pi example locally.
You can set the MASTER environment variable when running examples to submit
examples to a cluster. This can be a mesos:// or spark:// URL,
-"yarn-cluster" or "yarn-client" to run on YARN, and "local" to run
+"yarn" to run on YARN, and "local" to run
locally with one thread, or "local[N]" to run locally with N threads. You
can also use an abbreviated class name if the class is in the `examples`
package. For instance:
http://git-wip-us.apache.org/repos/asf/spark/blob/82bbc2a5/docs/running-on-yarn.md
----------------------------------------------------------------------
diff --git a/docs/running-on-yarn.md b/docs/running-on-yarn.md
index 0e25ccf..6d77db6 100644
--- a/docs/running-on-yarn.md
+++ b/docs/running-on-yarn.md
@@ -16,18 +16,19 @@ containers used by the application use the same configuration. If the configurat
Java system properties or environment variables not managed by YARN, they should also be set in the
Spark application's configuration (driver, executors, and the AM when running in client mode).
-There are two deploy modes that can be used to launch Spark applications on YARN. In `yarn-cluster` mode, the Spark driver runs inside an application master process which is managed by YARN on the cluster, and the client can go away after initiating the application. In `yarn-client` mode, the driver runs in the client process, and the application master is only used for requesting resources from YARN.
+There are two deploy modes that can be used to launch Spark applications on YARN. In `cluster` mode, the Spark driver runs inside an application master process which is managed by YARN on the cluster, and the client can go away after initiating the application. In `client` mode, the driver runs in the client process, and the application master is only used for requesting resources from YARN.
-Unlike [Spark standalone](spark-standalone.html) and [Mesos](running-on-mesos.html) modes, in which the master's address is specified in the `--master` parameter, in YARN mode the ResourceManager's address is picked up from the Hadoop configuration. Thus, the `--master` parameter is `yarn-client` or `yarn-cluster`.
+Unlike [Spark standalone](spark-standalone.html) and [Mesos](running-on-mesos.html) modes, in which the master's address is specified in the `--master` parameter, in YARN mode the ResourceManager's address is picked up from the Hadoop configuration. Thus, the `--master` parameter is `yarn`.
-To launch a Spark application in `yarn-cluster` mode:
+To launch a Spark application in `cluster` mode:
- $ ./bin/spark-submit --class path.to.your.Class --master yarn-cluster [options] <app jar> [app options]
+ $ ./bin/spark-submit --class path.to.your.Class --master yarn --deploy-mode cluster [options] <app jar> [app options]
For example:
$ ./bin/spark-submit --class org.apache.spark.examples.SparkPi \
- --master yarn-cluster \
+ --master yarn \
+ --deploy-mode cluster \
--driver-memory 4g \
--executor-memory 2g \
--executor-cores 1 \
@@ -37,16 +38,17 @@ For example:
The above starts a YARN client program which starts the default Application Master. Then SparkPi will be run as a child thread of Application Master. The client will periodically poll the Application Master for status updates and display them in the console. The client will exit once your application has finished running. Refer to the "Debugging your Application" section below for how to see driver and executor logs.
-To launch a Spark application in `yarn-client` mode, do the same, but replace `yarn-cluster` with `yarn-client`. The following shows how you can run `spark-shell` in `yarn-client` mode:
+To launch a Spark application in `client` mode, do the same, but replace `cluster` with `client`. The following shows how you can run `spark-shell` in `client` mode:
- $ ./bin/spark-shell --master yarn-client
+ $ ./bin/spark-shell --master yarn --deploy-mode client
## Adding Other JARs
-In `yarn-cluster` mode, the driver runs on a different machine than the client, so `SparkContext.addJar` won't work out of the box with files that are local to the client. To make files on the client available to `SparkContext.addJar`, include them with the `--jars` option in the launch command.
+In `cluster` mode, the driver runs on a different machine than the client, so `SparkContext.addJar` won't work out of the box with files that are local to the client. To make files on the client available to `SparkContext.addJar`, include them with the `--jars` option in the launch command.
$ ./bin/spark-submit --class my.main.Class \
- --master yarn-cluster \
+ --master yarn \
+ --deploy-mode cluster \
--jars my-other-jar.jar,my-other-other-jar.jar
my-main-jar.jar
app_arg1 app_arg2
@@ -129,8 +131,8 @@ If you need a reference to the proper location to put log files in the YARN so t
<td><code>spark.yarn.am.waitTime</code></td>
<td><code>100s</code></td>
<td>
- In <code>yarn-cluster</code> mode, time for the YARN Application Master to wait for the
- SparkContext to be initialized. In <code>yarn-client</code> mode, time for the YARN Application Master to wait
+ In <code>cluster</code> mode, time for the YARN Application Master to wait for the
+ SparkContext to be initialized. In <code>client</code> mode, time for the YARN Application Master to wait
for the driver to connect to it.
</td>
</tr>
@@ -268,8 +270,8 @@ If you need a reference to the proper location to put log files in the YARN so t
<td>
Add the environment variable specified by <code>EnvironmentVariableName</code> to the
Application Master process launched on YARN. The user can specify multiple of
- these and to set multiple environment variables. In <code>yarn-cluster</code> mode this controls
- the environment of the Spark driver and in <code>yarn-client</code> mode it only controls
+ these and to set multiple environment variables. In <code>cluster</code> mode this controls
+ the environment of the Spark driver and in <code>client</code> mode it only controls
the environment of the executor launcher.
</td>
</tr>
@@ -388,6 +390,6 @@ If you need a reference to the proper location to put log files in the YARN so t
# Important notes
- Whether core requests are honored in scheduling decisions depends on which scheduler is in use and how it is configured.
-- In `yarn-cluster` mode, the local directories used by the Spark executors and the Spark driver will be the local directories configured for YARN (Hadoop YARN config `yarn.nodemanager.local-dirs`). If the user specifies `spark.local.dir`, it will be ignored. In `yarn-client` mode, the Spark executors will use the local directories configured for YARN while the Spark driver will use those defined in `spark.local.dir`. This is because the Spark driver does not run on the YARN cluster in `yarn-client` mode, only the Spark executors do.
+- In `cluster` mode, the local directories used by the Spark executors and the Spark driver will be the local directories configured for YARN (Hadoop YARN config `yarn.nodemanager.local-dirs`). If the user specifies `spark.local.dir`, it will be ignored. In `client` mode, the Spark executors will use the local directories configured for YARN while the Spark driver will use those defined in `spark.local.dir`. This is because the Spark driver does not run on the YARN cluster in `client` mode, only the Spark executors do.
- The `--files` and `--archives` options support specifying file names with the # similar to Hadoop. For example you can specify: `--files localtest.txt#appSees.txt` and this will upload the file you have locally named `localtest.txt` into HDFS but this will be linked to by the name `appSees.txt`, and your application should use the name as `appSees.txt` to reference it when running on YARN.
-- The `--jars` option allows the `SparkContext.addJar` function to work if you are using it with local files and running in `yarn-cluster` mode. It does not need to be used if you are using it with HDFS, HTTP, HTTPS, or FTP files.
+- The `--jars` option allows the `SparkContext.addJar` function to work if you are using it with local files and running in `cluster` mode. It does not need to be used if you are using it with HDFS, HTTP, HTTPS, or FTP files.
http://git-wip-us.apache.org/repos/asf/spark/blob/82bbc2a5/docs/sql-programming-guide.md
----------------------------------------------------------------------
diff --git a/docs/sql-programming-guide.md b/docs/sql-programming-guide.md
index a1cbc7d..30206c6 100644
--- a/docs/sql-programming-guide.md
+++ b/docs/sql-programming-guide.md
@@ -1585,7 +1585,7 @@ on all of the worker nodes, as they will need access to the Hive serialization a
(SerDes) in order to access data stored in Hive.
Configuration of Hive is done by placing your `hive-site.xml` file in `conf/`. Please note when running
-the query on a YARN cluster (`yarn-cluster` mode), the `datanucleus` jars under the `lib_managed/jars` directory
+the query on a YARN cluster (`cluster` mode), the `datanucleus` jars under the `lib_managed/jars` directory
and `hive-site.xml` under `conf/` directory need to be available on the driver and all executors launched by the
YARN cluster. The convenient way to do this is adding them through the `--jars` option and `--file` option of the
`spark-submit` command.
http://git-wip-us.apache.org/repos/asf/spark/blob/82bbc2a5/docs/submitting-applications.md
----------------------------------------------------------------------
diff --git a/docs/submitting-applications.md b/docs/submitting-applications.md
index 915be0f..ac2a14e 100644
--- a/docs/submitting-applications.md
+++ b/docs/submitting-applications.md
@@ -103,7 +103,8 @@ run it with `--help`. Here are a few examples of common options:
export HADOOP_CONF_DIR=XXX
./bin/spark-submit \
--class org.apache.spark.examples.SparkPi \
- --master yarn-cluster \ # can also be yarn-client for client mode
+ --master yarn \
+ --deploy-mode cluster \ # can be client for client mode
--executor-memory 20G \
--num-executors 50 \
/path/to/examples.jar \
@@ -122,21 +123,25 @@ The master URL passed to Spark can be in one of the following formats:
<table class="table">
<tr><th>Master URL</th><th>Meaning</th></tr>
-<tr><td> local </td><td> Run Spark locally with one worker thread (i.e. no parallelism at all). </td></tr>
-<tr><td> local[K] </td><td> Run Spark locally with K worker threads (ideally, set this to the number of cores on your machine). </td></tr>
-<tr><td> local[*] </td><td> Run Spark locally with as many worker threads as logical cores on your machine.</td></tr>
-<tr><td> spark://HOST:PORT </td><td> Connect to the given <a href="spark-standalone.html">Spark standalone
+<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[*]</code> </td><td> Run Spark locally with as many worker threads as logical cores on your machine.</td></tr>
+<tr><td> <code>spark://HOST:PORT</code> </td><td> Connect to the given <a href="spark-standalone.html">Spark standalone
cluster</a> master. The port must be whichever one your master is configured to use, which is 7077 by default.
</td></tr>
-<tr><td> mesos://HOST:PORT </td><td> Connect to the given <a href="running-on-mesos.html">Mesos</a> cluster.
+<tr><td> <code>mesos://HOST:PORT</code> </td><td> Connect to the given <a href="running-on-mesos.html">Mesos</a> cluster.
The port must be whichever one your is configured to use, which is 5050 by default.
Or, for a Mesos cluster using ZooKeeper, use <code>mesos://zk://...</code>.
</td></tr>
-<tr><td> yarn-client </td><td> Connect to a <a href="running-on-yarn.html"> YARN </a> cluster in
-client mode. The cluster location will be found based on the HADOOP_CONF_DIR or YARN_CONF_DIR variable.
+<tr><td> <code>yarn</code> </td><td> Connect to a <a href="running-on-yarn.html"> YARN </a> cluster in
+ <code>client</code> or <code>cluster</code> mode depending on the value of <code>--deploy-mode</code>.
+ The cluster location will be found based on the <code>HADOOP_CONF_DIR</code> or <code>YARN_CONF_DIR</code> variable.
</td></tr>
-<tr><td> yarn-cluster </td><td> Connect to a <a href="running-on-yarn.html"> YARN </a> cluster in
-cluster mode. The cluster location will be found based on the HADOOP_CONF_DIR or YARN_CONF_DIR variable.
+<tr><td> <code>yarn-client</code> </td><td> Equivalent to <code>yarn</code> with <code>--deploy-mode client</code>,
+ which is preferred to `yarn-client`
+</td></tr>
+<tr><td> <code>yarn-cluster</code> </td><td> Equivalent to <code>yarn</code> with <code>--deploy-mode cluster</code>,
+ which is preferred to `yarn-cluster`
</td></tr>
</table>
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