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Posted to commits@spark.apache.org by sr...@apache.org on 2017/07/10 06:36:01 UTC
[2/2] spark-website git commit: Use AMPLab direct link in FAQ
Use AMPLab direct link in FAQ
Project: http://git-wip-us.apache.org/repos/asf/spark-website/repo
Commit: http://git-wip-us.apache.org/repos/asf/spark-website/commit/04d5ce05
Tree: http://git-wip-us.apache.org/repos/asf/spark-website/tree/04d5ce05
Diff: http://git-wip-us.apache.org/repos/asf/spark-website/diff/04d5ce05
Branch: refs/heads/remove_ec2
Commit: 04d5ce05125b4c2de50dd74765a1ca0c64e72752
Parents: 74622a5
Author: Dongjoon Hyun <do...@apache.org>
Authored: Sun Jul 9 04:00:40 2017 -0700
Committer: Dongjoon Hyun <do...@apache.org>
Committed: Sun Jul 9 04:00:40 2017 -0700
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faq.md | 2 +-
site/docs/2.1.1/ec2-scripts.html | 161 ----------------------------------
site/faq.html | 2 +-
3 files changed, 2 insertions(+), 163 deletions(-)
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http://git-wip-us.apache.org/repos/asf/spark-website/blob/04d5ce05/faq.md
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diff --git a/faq.md b/faq.md
index c41de64..f1974c7 100644
--- a/faq.md
+++ b/faq.md
@@ -26,7 +26,7 @@ Spark is a fast and general processing engine compatible with Hadoop data. It ca
<p class="answer">No. Spark's operators spill data to disk if it does not fit in memory, allowing it to run well on any sized data. Likewise, cached datasets that do not fit in memory are either spilled to disk or recomputed on the fly when needed, as determined by the RDD's <a href="{{site.baseurl}}/docs/latest/scala-programming-guide.html#rdd-persistence">storage level</a>.
<p class="question">How can I run Spark on a cluster?</p>
-<p class="answer">You can use either the <a href="{{site.baseurl}}/docs/latest/spark-standalone.html">standalone deploy mode</a>, which only needs Java to be installed on each node, or the <a href="{{site.baseurl}}/docs/latest/running-on-mesos.html">Mesos</a> and <a href="{{site.baseurl}}/docs/latest/running-on-yarn.html">YARN</a> cluster managers. If you'd like to run on Amazon EC2, Spark provides <a href="{{site.baseurl}}/docs/latest/ec2-scripts.html">EC2 scripts</a> to automatically launch a cluster.</p>
+<p class="answer">You can use either the <a href="{{site.baseurl}}/docs/latest/spark-standalone.html">standalone deploy mode</a>, which only needs Java to be installed on each node, or the <a href="{{site.baseurl}}/docs/latest/running-on-mesos.html">Mesos</a> and <a href="{{site.baseurl}}/docs/latest/running-on-yarn.html">YARN</a> cluster managers. If you'd like to run on Amazon EC2, AMPLab provides <a href="https://github.com/amplab/spark-ec2#readme">EC2 scripts</a> to automatically launch a cluster.</p>
<p>Note that you can also run Spark locally (possibly on multiple cores) without any special setup by just passing <code>local[N]</code> as the master URL, where <code>N</code> is the number of parallel threads you want.</p>
http://git-wip-us.apache.org/repos/asf/spark-website/blob/04d5ce05/site/docs/2.1.1/ec2-scripts.html
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diff --git a/site/docs/2.1.1/ec2-scripts.html b/site/docs/2.1.1/ec2-scripts.html
deleted file mode 100644
index 320317f..0000000
--- a/site/docs/2.1.1/ec2-scripts.html
+++ /dev/null
@@ -1,161 +0,0 @@
-
-<!DOCTYPE html>
-<!--[if lt IE 7]> <html class="no-js lt-ie9 lt-ie8 lt-ie7"> <![endif]-->
-<!--[if IE 7]> <html class="no-js lt-ie9 lt-ie8"> <![endif]-->
-<!--[if IE 8]> <html class="no-js lt-ie9"> <![endif]-->
-<!--[if gt IE 8]><!--> <html class="no-js"> <!--<![endif]-->
- <head>
- <meta charset="utf-8">
- <meta http-equiv="X-UA-Compatible" content="IE=edge,chrome=1">
- <title>Running Spark on EC2 - Spark 2.1.1 Documentation</title>
-
-
-
- <meta http-equiv="refresh" content="0; url=https://github.com/amplab/spark-ec2#readme">
- <link rel="canonical" href="https://github.com/amplab/spark-ec2#readme" />
-
-
- <link rel="stylesheet" href="css/bootstrap.min.css">
- <style>
- body {
- padding-top: 60px;
- padding-bottom: 40px;
- }
- </style>
- <meta name="viewport" content="width=device-width">
- <link rel="stylesheet" href="css/bootstrap-responsive.min.css">
- <link rel="stylesheet" href="css/main.css">
-
- <script src="js/vendor/modernizr-2.6.1-respond-1.1.0.min.js"></script>
-
- <link rel="stylesheet" href="css/pygments-default.css">
-
-
-
- </head>
- <body>
- <!--[if lt IE 7]>
- <p class="chromeframe">You are using an outdated browser. <a href="http://browsehappy.com/">Upgrade your browser today</a> or <a href="http://www.google.com/chromeframe/?redirect=true">install Google Chrome Frame</a> to better experience this site.</p>
- <![endif]-->
-
- <!-- This code is taken from http://twitter.github.com/bootstrap/examples/hero.html -->
-
- <div class="navbar navbar-fixed-top" id="topbar">
- <div class="navbar-inner">
- <div class="container">
- <div class="brand"><a href="index.html">
- <img src="img/spark-logo-hd.png" style="height:50px;"/></a><span class="version">2.1.1</span>
- </div>
- <ul class="nav">
- <!--TODO(andyk): Add class="active" attribute to li some how.-->
- <li><a href="index.html">Overview</a></li>
-
- <li class="dropdown">
- <a href="#" class="dropdown-toggle" data-toggle="dropdown">Programming Guides<b class="caret"></b></a>
- <ul class="dropdown-menu">
- <li><a href="quick-start.html">Quick Start</a></li>
- <li><a href="programming-guide.html">Spark Programming Guide</a></li>
- <li class="divider"></li>
- <li><a href="streaming-programming-guide.html">Spark Streaming</a></li>
- <li><a href="sql-programming-guide.html">DataFrames, Datasets and SQL</a></li>
- <li><a href="structured-streaming-programming-guide.html">Structured Streaming</a></li>
- <li><a href="ml-guide.html">MLlib (Machine Learning)</a></li>
- <li><a href="graphx-programming-guide.html">GraphX (Graph Processing)</a></li>
- <li><a href="sparkr.html">SparkR (R on Spark)</a></li>
- </ul>
- </li>
-
- <li class="dropdown">
- <a href="#" class="dropdown-toggle" data-toggle="dropdown">API Docs<b class="caret"></b></a>
- <ul class="dropdown-menu">
- <li><a href="api/scala/index.html#org.apache.spark.package">Scala</a></li>
- <li><a href="api/java/index.html">Java</a></li>
- <li><a href="api/python/index.html">Python</a></li>
- <li><a href="api/R/index.html">R</a></li>
- </ul>
- </li>
-
- <li class="dropdown">
- <a href="#" class="dropdown-toggle" data-toggle="dropdown">Deploying<b class="caret"></b></a>
- <ul class="dropdown-menu">
- <li><a href="cluster-overview.html">Overview</a></li>
- <li><a href="submitting-applications.html">Submitting Applications</a></li>
- <li class="divider"></li>
- <li><a href="spark-standalone.html">Spark Standalone</a></li>
- <li><a href="running-on-mesos.html">Mesos</a></li>
- <li><a href="running-on-yarn.html">YARN</a></li>
- </ul>
- </li>
-
- <li class="dropdown">
- <a href="api.html" class="dropdown-toggle" data-toggle="dropdown">More<b class="caret"></b></a>
- <ul class="dropdown-menu">
- <li><a href="configuration.html">Configuration</a></li>
- <li><a href="monitoring.html">Monitoring</a></li>
- <li><a href="tuning.html">Tuning Guide</a></li>
- <li><a href="job-scheduling.html">Job Scheduling</a></li>
- <li><a href="security.html">Security</a></li>
- <li><a href="hardware-provisioning.html">Hardware Provisioning</a></li>
- <li class="divider"></li>
- <li><a href="building-spark.html">Building Spark</a></li>
- <li><a href="http://spark.apache.org/contributing.html">Contributing to Spark</a></li>
- <li><a href="http://spark.apache.org/third-party-projects.html">Third Party Projects</a></li>
- </ul>
- </li>
- </ul>
- <!--<p class="navbar-text pull-right"><span class="version-text">v2.1.1</span></p>-->
- </div>
- </div>
- </div>
-
- <div class="container-wrapper">
-
-
- <div class="content" id="content">
-
- <h1 class="title">Running Spark on EC2</h1>
-
-
- <p>This document has been superseded and replaced by documentation at https://github.com/amplab/spark-ec2#readme</p>
-
-
- </div>
-
- <!-- /container -->
- </div>
-
- <script src="js/vendor/jquery-1.8.0.min.js"></script>
- <script src="js/vendor/bootstrap.min.js"></script>
- <script src="js/vendor/anchor.min.js"></script>
- <script src="js/main.js"></script>
-
- <!-- MathJax Section -->
- <script type="text/x-mathjax-config">
- MathJax.Hub.Config({
- TeX: { equationNumbers: { autoNumber: "AMS" } }
- });
- </script>
- <script>
- // Note that we load MathJax this way to work with local file (file://), HTTP and HTTPS.
- // We could use "//cdn.mathjax...", but that won't support "file://".
- (function(d, script) {
- script = d.createElement('script');
- script.type = 'text/javascript';
- script.async = true;
- script.onload = function(){
- MathJax.Hub.Config({
- tex2jax: {
- inlineMath: [ ["$", "$"], ["\\\\(","\\\\)"] ],
- displayMath: [ ["$$","$$"], ["\\[", "\\]"] ],
- processEscapes: true,
- skipTags: ['script', 'noscript', 'style', 'textarea', 'pre']
- }
- });
- };
- script.src = ('https:' == document.location.protocol ? 'https://' : 'http://') +
- 'cdn.mathjax.org/mathjax/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML';
- d.getElementsByTagName('head')[0].appendChild(script);
- }(document));
- </script>
- </body>
-</html>
http://git-wip-us.apache.org/repos/asf/spark-website/blob/04d5ce05/site/faq.html
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diff --git a/site/faq.html b/site/faq.html
index 584c12b..2f118ad 100644
--- a/site/faq.html
+++ b/site/faq.html
@@ -213,7 +213,7 @@ Spark is a fast and general processing engine compatible with Hadoop data. It ca
<p class="answer">No. Spark's operators spill data to disk if it does not fit in memory, allowing it to run well on any sized data. Likewise, cached datasets that do not fit in memory are either spilled to disk or recomputed on the fly when needed, as determined by the RDD's <a href="/docs/latest/scala-programming-guide.html#rdd-persistence">storage level</a>.
<p class="question">How can I run Spark on a cluster?</p>
-<p class="answer">You can use either the <a href="/docs/latest/spark-standalone.html">standalone deploy mode</a>, which only needs Java to be installed on each node, or the <a href="/docs/latest/running-on-mesos.html">Mesos</a> and <a href="/docs/latest/running-on-yarn.html">YARN</a> cluster managers. If you'd like to run on Amazon EC2, Spark provides <a href="/docs/latest/ec2-scripts.html">EC2 scripts</a> to automatically launch a cluster.</p>
+<p class="answer">You can use either the <a href="/docs/latest/spark-standalone.html">standalone deploy mode</a>, which only needs Java to be installed on each node, or the <a href="/docs/latest/running-on-mesos.html">Mesos</a> and <a href="/docs/latest/running-on-yarn.html">YARN</a> cluster managers. If you'd like to run on Amazon EC2, AMPLab provides <a href="https://github.com/amplab/spark-ec2#readme">EC2 scripts</a> to automatically launch a cluster.</p>
<p>Note that you can also run Spark locally (possibly on multiple cores) without any special setup by just passing <code>local[N]</code> as the master URL, where <code>N</code> is the number of parallel threads you want.</p>
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