b65bad65c3
https://issues.apache.org/jira/browse/SPARK-3591 The output after this patch: >doggie153:/opt/oss/spark-1.3.0-bin-hadoop2.4/bin # ./spark-submit --class org.apache.spark.examples.SparkPi --master yarn-cluster ../lib/spark-examples*.jar 15/03/31 21:15:25 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable 15/03/31 21:15:25 INFO RMProxy: Connecting to ResourceManager at doggie153/10.177.112.153:8032 15/03/31 21:15:25 INFO Client: Requesting a new application from cluster with 4 NodeManagers 15/03/31 21:15:25 INFO Client: Verifying our application has not requested more than the maximum memory capability of the cluster (8192 MB per container) 15/03/31 21:15:25 INFO Client: Will allocate AM container, with 896 MB memory including 384 MB overhead 15/03/31 21:15:25 INFO Client: Setting up container launch context for our AM 15/03/31 21:15:25 INFO Client: Preparing resources for our AM container 15/03/31 21:15:26 INFO Client: Uploading resource file:/opt/oss/spark-1.3.0-bin-hadoop2.4/lib/spark-assembly-1.4.0-SNAPSHOT-hadoop2.4.1.jar -> hdfs://doggie153:9000/user/root/.sparkStaging/application_1427257505534_0016/spark-assembly-1.4.0-SNAPSHOT-hadoop2.4.1.jar 15/03/31 21:15:27 INFO Client: Uploading resource file:/opt/oss/spark-1.3.0-bin-hadoop2.4/lib/spark-examples-1.3.0-hadoop2.4.0.jar -> hdfs://doggie153:9000/user/root/.sparkStaging/application_1427257505534_0016/spark-examples-1.3.0-hadoop2.4.0.jar 15/03/31 21:15:28 INFO Client: Setting up the launch environment for our AM container 15/03/31 21:15:28 INFO SecurityManager: Changing view acls to: root 15/03/31 21:15:28 INFO SecurityManager: Changing modify acls to: root 15/03/31 21:15:28 INFO SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(root); users with modify permissions: Set(root) 15/03/31 21:15:28 INFO Client: Submitting application 16 to ResourceManager 15/03/31 21:15:28 INFO YarnClientImpl: Submitted application application_1427257505534_0016 15/03/31 21:15:28 INFO Client: ... waiting before polling ResourceManager for application state 15/03/31 21:15:33 INFO Client: ... polling ResourceManager for application state 15/03/31 21:15:33 INFO Client: Application report for application_1427257505534_0016 (state: RUNNING) 15/03/31 21:15:33 INFO Client: client token: N/A diagnostics: N/A ApplicationMaster host: doggie157 ApplicationMaster RPC port: 0 queue: default start time: 1427807728307 final status: UNDEFINED tracking URL: http://doggie153:8088/proxy/application_1427257505534_0016/ user: root /cc andrewor14 Author: WangTaoTheTonic <wangtao111@huawei.com> Closes #5297 from WangTaoTheTonic/SPARK-3591 and squashes the following commits: c76d232 [WangTaoTheTonic] wrap lines 16c90a8 [WangTaoTheTonic] move up lines to avoid duplicate fea390d [WangTaoTheTonic] log failed/killed report, style and comment be1cc2e [WangTaoTheTonic] reword f0bc54f [WangTaoTheTonic] minor: expose appid in excepiton messages ba9b22b [WangTaoTheTonic] wrong config name e1a4013 [WangTaoTheTonic] revert to the old version and do some robust 19706c0 [WangTaoTheTonic] add a config to control whether to forget 0cbdce8 [WangTaoTheTonic] fire and forget for YARN cluster mode |
||
---|---|---|
.. | ||
_layouts | ||
_plugins | ||
css | ||
img | ||
js | ||
_config.yml | ||
api.md | ||
bagel-programming-guide.md | ||
building-spark.md | ||
cluster-overview.md | ||
configuration.md | ||
contributing-to-spark.md | ||
ec2-scripts.md | ||
graphx-programming-guide.md | ||
hadoop-third-party-distributions.md | ||
hardware-provisioning.md | ||
index.md | ||
java-programming-guide.md | ||
job-scheduling.md | ||
ml-guide.md | ||
mllib-classification-regression.md | ||
mllib-clustering.md | ||
mllib-collaborative-filtering.md | ||
mllib-data-types.md | ||
mllib-decision-tree.md | ||
mllib-dimensionality-reduction.md | ||
mllib-ensembles.md | ||
mllib-feature-extraction.md | ||
mllib-frequent-pattern-mining.md | ||
mllib-guide.md | ||
mllib-isotonic-regression.md | ||
mllib-linear-methods.md | ||
mllib-migration-guides.md | ||
mllib-naive-bayes.md | ||
mllib-optimization.md | ||
mllib-statistics.md | ||
monitoring.md | ||
programming-guide.md | ||
python-programming-guide.md | ||
quick-start.md | ||
README.md | ||
running-on-mesos.md | ||
running-on-yarn.md | ||
scala-programming-guide.md | ||
security.md | ||
spark-standalone.md | ||
sql-programming-guide.md | ||
storage-openstack-swift.md | ||
streaming-custom-receivers.md | ||
streaming-flume-integration.md | ||
streaming-kafka-integration.md | ||
streaming-kinesis-integration.md | ||
streaming-programming-guide.md | ||
submitting-applications.md | ||
tuning.md |
Welcome to the Spark documentation!
This readme will walk you through navigating and building the Spark documentation, which is included here with the Spark source code. You can also find documentation specific to release versions of Spark at http://spark.apache.org/documentation.html.
Read on to learn more about viewing documentation in plain text (i.e., markdown) or building the documentation yourself. Why build it yourself? So that you have the docs that corresponds to whichever version of Spark you currently have checked out of revision control.
Generating the Documentation HTML
We include the Spark documentation as part of the source (as opposed to using a hosted wiki, such as the github wiki, as the definitive documentation) to enable the documentation to evolve along with the source code and be captured by revision control (currently git). This way the code automatically includes the version of the documentation that is relevant regardless of which version or release you have checked out or downloaded.
In this directory you will find textfiles formatted using Markdown, with an ".md" suffix. You can read those text files directly if you want. Start with index.md.
The markdown code can be compiled to HTML using the Jekyll tool.
Jekyll
and a few dependencies must be installed for this to work. We recommend
installing via the Ruby Gem dependency manager. Since the exact HTML output
varies between versions of Jekyll and its dependencies, we list specific versions here
in some cases:
$ sudo gem install jekyll
$ sudo gem install jekyll-redirect-from
Execute jekyll
from the docs/
directory. Compiling the site with Jekyll will create a directory
called _site
containing index.html as well as the rest of the compiled files.
You can modify the default Jekyll build as follows:
# Skip generating API docs (which takes a while)
$ SKIP_API=1 jekyll build
# Serve content locally on port 4000
$ jekyll serve --watch
# Build the site with extra features used on the live page
$ PRODUCTION=1 jekyll build
Pygments
We also use pygments (http://pygments.org) for syntax highlighting in documentation markdown pages,
so you will also need to install that (it requires Python) by running sudo pip install Pygments
.
To mark a block of code in your markdown to be syntax highlighted by jekyll during the compile phase, use the following sytax:
{% highlight scala %}
// Your scala code goes here, you can replace scala with many other
// supported languages too.
{% endhighlight %}
Sphinx
We use Sphinx to generate Python API docs, so you will need to install it by running
sudo pip install sphinx
.
API Docs (Scaladoc and Sphinx)
You can build just the Spark scaladoc by running build/sbt unidoc
from the SPARK_PROJECT_ROOT directory.
Similarly, you can build just the PySpark docs by running make html
from the
SPARK_PROJECT_ROOT/python/docs directory. Documentation is only generated for classes that are listed as
public in __init__.py
.
When you run jekyll
in the docs
directory, it will also copy over the scaladoc for the various
Spark subprojects into the docs
directory (and then also into the _site
directory). We use a
jekyll plugin to run build/sbt unidoc
before building the site so if you haven't run it (recently) it
may take some time as it generates all of the scaladoc. The jekyll plugin also generates the
PySpark docs Sphinx.
NOTE: To skip the step of building and copying over the Scala and Python API docs, run SKIP_API=1 jekyll
.