svn commit: r842377 - in /websites/staging/crunch/trunk/content: ./ crunch/index.html

[buildbot]

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 
&lt;span&gt;&amp;trade;&lt;/span&gt;</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 &lt;span&gt;&amp;trade;&lt;/span&gt;
+            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>&trade;</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.