[Catalyst-commits] r13796 - trunk/examples/CatalystAdvent/root/2010

[jester at dev.catalyst.perl.org]

Author: jester
Date: 2010-12-06 19:04:22 +0000 (Mon, 06 Dec 2010)
New Revision: 13796

Modified:
   trunk/examples/CatalystAdvent/root/2010/2.pod
Log:
Tweaks to Advent 2.pod


Modified: trunk/examples/CatalystAdvent/root/2010/2.pod
===================================================================
--- trunk/examples/CatalystAdvent/root/2010/2.pod	2010-12-06 18:48:59 UTC (rev 13795)
+++ trunk/examples/CatalystAdvent/root/2010/2.pod	2010-12-06 19:04:22 UTC (rev 13796)
@@ -4,9 +4,9 @@
 
 L<ElasticSearch|http://www.elasticsearch.com> is a search engine based on Lucene that has a number of really cool features that in my opinion, elevate it above a number of L<other|http://lucene.apache.org/solr/> L<search|http://sphinxsearch.com/> L<engines|http://www.rectangular.com/kinosearch/>.
 
-For instance, it's schema-less, which some would argue is a bad thing, but the way things are indexed (indexed "things" care called documents) in ElasticSearch allows the user to create a sort of per-document schema much like you would with MongoDB or other document-based storage engines.  It also has an "autodiscovery" features for other ElasticSearch instances on the network.  All you have to do is C<bin/elasticsearch> on the machines you want to cluster and poof, you have a distributed and fault tolerant index.
+For instance, it's schema-less, which some would argue is a bad thing, but the way things are indexed (indexed "things" care called documents) in ElasticSearch allows the user to create a sort of per-document schema much like you would with MongoDB or other document-based storage engines.  It also has an "autodiscovery" feature for other ElasticSearch instances on the network.  All you have to do is run C<bin/elasticsearch> on the machines you want to cluster and poof, you have a distributed and fault-tolerant index.
 
-So! moving forward, let's get into some code and set up.
+So! Let's get into some code and setup.
 
 =head1 Getting ElasticSearch
 
@@ -38,7 +38,7 @@
 
 =item C<index>
 
-Indexes your data.  Takes an index name, a document id (unique, autogenerated if you leave it out), and your data which should be in the form of a hashref.
+Indexes your data.  Takes an index name, a document id (unique, autogenerated if you leave it out), and your data, which should be in the form of a hashref.
 
 =item C<search>
 
@@ -46,11 +46,13 @@
 
 =back
 
-Okay.  So that's a basic ElasticSearch API.  There are plenty of L<examples|http://www.elasticsearch.com/docs/elasticsearch/rest_api/s> on the site you can check out if you feel you need to grok this more thoroughly.  Next, we figure out how to tie this thing to Catalyst.
+Okay.  So that's a basic ElasticSearch API.  There are plenty of L<examples|http://www.elasticsearch.com/docs/elasticsearch/rest_api/s> on the site you can check out if you feel you need to grok this more thoroughly. 
 
+Next, we figure out how to tie this thing to Catalyst.
+
 =head1 Catalyst::Model
 
-We will be using creating a small model to hook up our ElasticSearch model to our Catalyst application.  
+We will be creating a small model to hook up our ElasticSearch model to our Catalyst application.  
 
 Code:
 
@@ -245,7 +247,7 @@
 
 And a simple template to display them: 
 
-    <h2>Search results for <strong>"[% c.req.param('q') %]</strong>":</h2>
+    <h2>Search results for "<strong>[% c.req.param('q') %]</strong>":</h2>
     <ul>
     [% FOR result IN results %]
     <li>
@@ -262,7 +264,7 @@
 
 ElasticSearch is extremely customizable and tuneable.  You can get a GREAT deal of performance improvement by playing with the indexing options, ranking algorithms, storage and request transports.  All of this is documented again at the L<ElasticSearch|http://www.elasticsearch.com> web site. 
 
-One final thought, you can add the portion of the indexer code that actually inserts the document into the search index right after your "commit" portion of your data store for your application.  This way, you get virtually instantaneous indexing of your document upon its creation.
+One final thought: you can add the portion of the indexer code that actually inserts the document into the search index right after your "commit" portion of your data store for your application.  This way, you get virtually instantaneous indexing of your document upon its creation.
 
 Enjoy folks, I hope you find this as useful as I did!