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Posted to commits@crunch.apache.org by bu...@apache.org on 2012/12/14 19:13:10 UTC
svn commit: r842377 - in /websites/staging/crunch/trunk/content: ./
crunch/index.html
Author: buildbot
Date: Fri Dec 14 18:13:08 2012
New Revision: 842377
Log:
Staging update by buildbot for crunch
Modified:
websites/staging/crunch/trunk/content/ (props changed)
websites/staging/crunch/trunk/content/crunch/index.html
Propchange: websites/staging/crunch/trunk/content/
------------------------------------------------------------------------------
--- cms:source-revision (original)
+++ cms:source-revision Fri Dec 14 18:13:08 2012
@@ -1 +1 @@
-1422001
+1422019
Modified: websites/staging/crunch/trunk/content/crunch/index.html
==============================================================================
--- websites/staging/crunch/trunk/content/crunch/index.html (original)
+++ websites/staging/crunch/trunk/content/crunch/index.html Fri Dec 14 18:13:08 2012
@@ -7,7 +7,7 @@
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<meta http-equiv="Content-Language" content="en" />
- <title>Apache Crunch - Apache Crunch <span>&trade;</span></title>
+ <title>Apache Crunch - Apache Crunch</title>
<link rel="stylesheet" href="/crunch/css/bootstrap-2.1.0.min.css" />
<link rel="stylesheet" href="/crunch/css/crunch.css" type="text/css">
@@ -115,7 +115,7 @@
<!-- CONTENT AREA -->
<div class="span10">
<h1 class="title">
- Apache Crunch <span>&trade;</span>
+ Apache Crunch
<small>Simple and Efficient MapReduce Pipelines</small>
@@ -130,7 +130,7 @@ easy to test, and efficient to run.</p>
</blockquote>
<hr />
<p>Running on top of <a href="http://hadoop.apache.org/mapreduce/">Hadoop MapReduce</a>, the Apache
-Crunch library is a simple Java API for tasks like joining and data aggregation
+Crunch <span>™</span> library is a simple Java API for tasks like joining and data aggregation
that are tedious to implement on plain MapReduce. The APIs are especially useful when
processing data that does not fit naturally into relational model, such as time series,
serialized object formats like protocol buffers or Avro records, and HBase rows and columns.