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From tshi...@apache.org
Subject [3/5] drill git commit: Website sources in gh-pages branch
Date Sat, 29 Nov 2014 00:38:01 GMT
http://git-wip-us.apache.org/repos/asf/drill/blob/aa11ae38/css/syntax.css
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+.highlight  { background: #ffffff; }
+.highlight .c { color: #999988; font-style: italic } /* Comment */
+.highlight .err { color: #a61717; background-color: #e3d2d2 } /* Error */
+.highlight .k { font-weight: bold } /* Keyword */
+.highlight .o { font-weight: bold } /* Operator */
+.highlight .cm { color: #999988; font-style: italic } /* Comment.Multiline */
+.highlight .cp { color: #999999; font-weight: bold } /* Comment.Preproc */
+.highlight .c1 { color: #999988; font-style: italic } /* Comment.Single */
+.highlight .cs { color: #999999; font-weight: bold; font-style: italic } /* Comment.Special
*/
+.highlight .gd { color: #000000; background-color: #ffdddd } /* Generic.Deleted */
+.highlight .gd .x { color: #000000; background-color: #ffaaaa } /* Generic.Deleted.Specific
*/
+.highlight .ge { font-style: italic } /* Generic.Emph */
+.highlight .gr { color: #aa0000 } /* Generic.Error */
+.highlight .gh { color: #999999 } /* Generic.Heading */
+.highlight .gi { color: #000000; background-color: #ddffdd } /* Generic.Inserted */
+.highlight .gi .x { color: #000000; background-color: #aaffaa } /* Generic.Inserted.Specific
*/
+.highlight .go { color: #888888 } /* Generic.Output */
+.highlight .gp { color: #555555 } /* Generic.Prompt */
+.highlight .gs { font-weight: bold } /* Generic.Strong */
+.highlight .gu { color: #aaaaaa } /* Generic.Subheading */
+.highlight .gt { color: #aa0000 } /* Generic.Traceback */
+.highlight .kc { font-weight: bold } /* Keyword.Constant */
+.highlight .kd { font-weight: bold } /* Keyword.Declaration */
+.highlight .kp { font-weight: bold } /* Keyword.Pseudo */
+.highlight .kr { font-weight: bold } /* Keyword.Reserved */
+.highlight .kt { color: #445588; font-weight: bold } /* Keyword.Type */
+.highlight .m { color: #009999 } /* Literal.Number */
+.highlight .s { color: #d14 } /* Literal.String */
+.highlight .na { color: #008080 } /* Name.Attribute */
+.highlight .nb { color: #0086B3 } /* Name.Builtin */
+.highlight .nc { color: #445588; font-weight: bold } /* Name.Class */
+.highlight .no { color: #008080 } /* Name.Constant */
+.highlight .ni { color: #800080 } /* Name.Entity */
+.highlight .ne { color: #990000; font-weight: bold } /* Name.Exception */
+.highlight .nf { color: #990000; font-weight: bold } /* Name.Function */
+.highlight .nn { color: #555555 } /* Name.Namespace */
+.highlight .nt { color: #000080 } /* Name.Tag */
+.highlight .nv { color: #008080 } /* Name.Variable */
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+.highlight .mh { color: #009999 } /* Literal.Number.Hex */
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http://git-wip-us.apache.org/repos/asf/drill/blob/aa11ae38/download.html
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+---
+layout: page
+title: Download
+---
+<div class="download">
+            <h2>The latest release is Drill 0.6.0, released November 1, 2014</h2>
+          <br>
+            
+            <table>
+              <tr>
+                  <td><a href="http://www.apache.org/dyn/closer.cgi/incubator/drill/drill-0.6.0-incubating/apache-drill-0.6.0-incubating.tar.gz"
class="find" id="apachemirror" style="background-color: #4aaf4c;">FIND AN APACHE MIRROR</a></td>
+                    <td><a href="http://getdrill.org/drill/download/apache-drill-0.6.0-incubating.tar.gz"
rel="nofollow" class="dl" id="directdownload">DIRECT FILE DOWNLOAD</a></td>
+            <td><a href="http://doc.mapr.com/display/MapR/Step+1.+Install+the+MapR+Drill+ODBC+Driver"
rel="nofollow" class="dl">ODBC DRIVERS FOR DRILL*</a></td>    
+                </tr>
+            </table>
+   
+            <p style="margin-top:1px; padding-top:1px;"><strong>Release Notes:
</strong><a href="https://cwiki.apache.org/confluence/display/DRILL/Release+Notes">&nbsp;Click
here</a> &nbsp;&nbsp;|&nbsp;&nbsp;
+             <strong>Fork Drill 0.6 on GitHub: </strong><a href="https://github.com/apache/incubator-drill/tree/0.6.0-incubating"
rel="nofollow">&nbsp;Click here</a></p>
+           
+           <br>
+              
+
+              <!--<div style="border-top: solid 2px #1a6bc7; border-bottom: solid 2px
#1a6bc7;padding: 5px;">-->
+               <!--<div style="background: #e7e7e7; padding:1px 0px 0px 0px;">-->
+               <h2>Visit the Apache Drill Tutorial for sample datasets and code examples</h2><br>
+             <table>
+              <tr>
+              <td>&nbsp;</td>
+              
+              <td style="padding-left: 38px"><a href="https://cwiki.apache.org/confluence/display/DRILL/Apache+Drill+Tutorial"
rel="nofollow" target="_blank" class="find">DRILL TUTORIAL</a></td>    
+<td>&nbsp;</td>
+                </tr>
+                <tr>
+                   <td>&nbsp;</td>
+                    <td></td>
+                    <td>&nbsp;</td>
+                </tr>
+                
+                </table>    
+        <!--</div>-->
+                   <p style="margin-top:0px; padding-top:0px;"><strong>Don't
have Hadoop deployed? You can try <a href="https://www.mapr.com/products/mapr-sandbox-hadoop/download-sandbox-drill"
rel="nofollow">Drill with a VM</a>*</p>
+<br>
+
+                 
+                   <p style="margin-top:1px; padding-top:1px;"><strong>Previous
Drill releases: </strong><a href="https://cwiki.apache.org/confluence/display/DRILL/Apache+Drill+0.5.0+Release+Notes"
rel="nofollow">0.5.0</a> | <a href="https://cwiki.apache.org/confluence/display/DRILL/Apache+Drill+0.4.0+Release+Notes"
rel="nofollow">0.4.0</a></p>
+
+<br><br>
+      <p>*Please note that ODBC drivers and VM are provided by a third-party under
a non-Apache license.</p>
+</div>
+<script type="text/javascript">
+$('#directdownload').click(function(event) {
+  ga('send', 'event', 'Downloads', 'Direct', 'Direct Download');
+});
+$('#apachemirror').click(function(event) {
+  event.preventDefault();
+  var link = $(this);
+  ga('send', 'event', 'Downloads', 'Link', 'Apache Mirrors', {
+    'hitCallback': function () {
+      document.location = link.attr('href');
+    }
+  });
+});
+</script>
+

http://git-wip-us.apache.org/repos/asf/drill/blob/aa11ae38/faq.md
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+---
+layout: page
+title: Frequently Asked Questions
+---
+## What use cases should I consider using Drill for?
+
+Drill provides low latency SQL queries on large-scale datasets. Example use cases for Drill
include
+
+* Interactive data exploration/data discovery
+* Adhoc BI/reporting queries
+* Analytics on NoSQL data
+* Real time or Day zero analytics (i.e analyze data as it comes with no preparation/ETL)
+
+We expect Drill to be used in lot more use cases where low latency is required.
+
+## Does Drill replace Hive for batch processing? What about my OLTP applications?
+
+Drill complements batch-processing frameworks such as Hive, Pig, MapReduce to support low
latency queries. Drill at this point doesn't make an optimal choice for OLTP/operational applications
that require sub-second response times.
+            
+## There are lots of SQL on Hadoop technologies out there. How is Drill different?
+
+Drill takes a different approach to SQL-on-Hadoop than Hive and other related technologies.
The goal for Drill is to bring the SQL ecosystem and performance of the relational systems
to Hadoop-scale data without compromising on the flexibility of Hadoop/NoSQL systems. Drill
provides a flexible query environment for users with the key capabilities as below.
+
+* Self-describing data support without centralized schema definitions/management
+* Support for complex/multi-structured data types
+* ANSI SQL support (not SQL "Like") & BI tool integration
+* Extensibility to go beyond Hadoop environments
+
+## What is self-describing data?
+
+Self-describing data is where schema is specified as part of the data itself. File formats
such as Parquet, JSON, ProtoBuf, XML, AVRO and NoSQL databases are all examples of self-describing
data. Some of these data formats also dynamic and complex in that every record in the data
can have its own set of columns/attributes and each column can be semi-structured/nested.
+
+## How does Drill support queries on self-describing data?
+
+Drill enables queries on self-describing data using the fundamental architectural foundations:
+
+* Dynamic schema discovery or late binding:  Drill allows performing queries directly on
self-describing data such as Files, HBase without defining overlay schema definitions in Hive
metastore.  The schema is discovered on the fly at the query time. With the dynamic schema
discovery, Drill makes it easy to support dynamic and rapidly evolving data models.
+* Flexible data model:  Drill is built from the ground up for complex/semi-structured data
commonly seen in Hadoop/NoSQL systems. Drill provides intuitive extensions to SQL to represent
and operate on complex data. The internal data model of Drill is hierarchical and columnar
with which it can represent and perform efficient SQL processing on complex data natively
without flattening into rows either at the design time or runtime.
+
+Together with the dynamic data discovery and a flexible data model that can handle complex
data types, Drill allows users to get fast and complete value from all their data.
+
+## But I already have schemas defined in Hive metastore? Can I use that with Drill?
+
+Yes, Hive also serves as data source for Drill. So you can simply point to the Hive metastore
from Drill and start performing low latency queries on Hive tables with no modifications.
+
+## Is Drill trying to be "anti-schema" or "anti-DBA"?
+
+Of course not! Central EDW schemas work great if data models are not changing often, value
of data is well understood and is ready to be operationalized for regular reporting purposes.
However, during data exploration and discovery phase, rigid modeling requirement poses challenges
and delays value from data, especially in the Hadoop/NoSQL environments where the data is
highly complex, dynamic and evolving fast. Few challenges include
+
+* Complex data models (eg: JSON)  are hard to map to relational paradigms
+* Centralized schemas are hard to keep up with when data models evolve fast
+* Static models defined for known questions are not enough for the diversity and volumes
of big data
+* Non-repetitive/ad hoc queries and short-term data exploration needs may not justify modeling
costs
+
+Drill is all about flexibility. The flexible schema management capabilities in Drill lets
users explore the data in its native format as it comes in directly and create models/structure
if needed in Hive metastore or using the CREATE TABLE/CREATE VIEW syntax within Drill.
+
+## What does a Drill query look like?
+
+Drill uses a de-centralized metadata model and relies on its storage plugins to provide with
the metadata. Drill supports queries on file system (distributed and local), HBase and Hive
tables. There is a storage plugin associated with each data source that is supported by Drill.
+
+Here is the anatomy of a Drill query.
+
+![]({{ site.baseurl }}/images/overview-img1.png)
+
+## Can I connect to Drill from my BI tools (Tableau, MicroStrategy, etc.)?
+
+Yes, Drill provides JDBC/ODBC drivers for integrating with BI/SQL based tools.
+
+## What SQL functionality can Drill support?
+
+Drill provides ANSI standard SQL (not SQL "Like" or Hive QL) with support for all key analytics
functionality such as SQL data types, joins, aggregations, filters, sort, sub-queries (including
correlated), joins in where clause etc. [Click here](https://cwiki.apache.org/confluence/display/DRILL/SQL+Overview)
for reference on SQL functionality in Drill.
+
+## What Hadoop distributions does Drill work with?
+
+Drill is not designed with a particular Hadoop distribution in mind and we expect it to work
with all Hadoop distributions that support Hadoop 2.3.x+ API. We have validated it so far
with Apache Hadoop/MapR/CDH/Amazon EMR distributions (Amazon EMR requires a custom configuration
required - contact <drill-user@incubator.apache.org> for questions.
+
+## How does Drill achieve performance?
+
+Drill is built from the ground up for performance on large-scale datasets. The key architectural
components that help in achieving performance include. 
+
+* Distributed query optimization & execution
+* Columnar execution
+* Vectorization
+* Runtime compilation & code generation
+* Optimistic/pipelined execution
+
+## Does Drill support multi-tenant/high concurrency environments?
+
+Drill is built to support several 100s of queries at any given point. Clients can submit
requests to any node running Drillbit service in the cluster (no master-slave concept). To
support more users, you simply have to add more nodes to the cluster.
+
+## Do I need to load data into Drill to start querying it?
+
+No. Drill can query data "in situ".
+    
+## What is the best way to get started with Drill?
+
+The best way to get started is to just try it out. It just takes a few minutes even if you
do not have a cluster. Here is a good place to start: [Apache Drill in 10 minutes](https://cwiki.apache.org/confluence/display/DRILL/Apache+Drill+in+10+Minutes).
+
+## How can I ask questions and provide feedback?
+
+Please post your questions and feedback on <drill-user@incubator.apache.org>. We are
happy to have you try out Drill and help with any questions!
+
+## How can I contribute to Drill?
+
+Please refer to the [Get Involved]({{ site.baseurl }}/community/#getinvolved) page on how
to get involved with Drill.
\ No newline at end of file

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+---
+layout: null
+---
+<?xml version="1.0" encoding="UTF-8"?>
+<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom">
+  <channel>
+    <title>{{ site.title | xml_escape }}</title>
+    <description>{{ site.description | xml_escape }}</description>
+    <link>{{ site.url }}{{ site.baseurl }}/</link>
+    <atom:link href="{{ "/feed.xml" | prepend: site.baseurl | prepend: site.url }}" rel="self"
type="application/rss+xml"/>
+    <pubDate>{{ site.time | date_to_rfc822 }}</pubDate>
+    <lastBuildDate>{{ site.time | date_to_rfc822 }}</lastBuildDate>
+    <generator>Jekyll v{{ jekyll.version }}</generator>
+    {% for post in site.posts limit:10 %}
+      <item>
+        <title>{{ post.title | xml_escape }}</title>
+        <description>{{ post.content | xml_escape }}</description>
+        <pubDate>{{ post.date | date_to_rfc822 }}</pubDate>
+        <link>{{ post.url | prepend: site.baseurl | prepend: site.url }}</link>
+        <guid isPermaLink="true">{{ post.url | prepend: site.baseurl | prepend: site.url
}}</guid>
+        {% for tag in post.tags %}
+        <category>{{ tag | xml_escape }}</category>
+        {% endfor %}
+        {% for cat in post.categories %}
+        <category>{{ cat | xml_escape }}</category>
+        {% endfor %}
+      </item>
+    {% endfor %}
+  </channel>
+</rss>

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+<?xml version="1.0" standalone="no"?>
+<!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd"
>
+<svg xmlns="http://www.w3.org/2000/svg">
+<metadata>Generated by IcoMoon</metadata>
+<defs>
+<font id="icomoon" horiz-adv-x="1024">
+<font-face units-per-em="1024" ascent="960" descent="-64" />
+<missing-glyph horiz-adv-x="1024" />
+<glyph unicode="&#x20;" d="" horiz-adv-x="512" />
+<glyph unicode="&#xe600;" d="M192 576l-192-192 384-384 640 640-192 192-448-448z" />
+<glyph unicode="&#xe601;" d="M960 179.264l-268.992 268.736 268.992 268.736-179.264
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268.864 268.864 268.736-268.864z" />
+</font></defs></svg>
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+---
+layout: default
+---
+<div id="header" class="mw">
+
+<div class="nav-circlepop">
+  <a class="aLeft prev"><span class="icon-wrap"></span></a>
+  <a class="aRight next"><span class="icon-wrap"></span></a>
+</div>
+
+<div class="dots">
+</div>
+
+<div class="scroller">
+  <div class="item">
+    <div class="tc">
+      <h1>Apache Drill</h1>
+      <h1 style="font-size:20px">Self-Service Data Exploration</h1>
+      <a href="{{ site.baseurl }}/download/" class="btn btn-1 btn-1c"><span>NOW
READY FOR DOWNLOAD</span></a>
+    </div>
+  </div>
+</div>
+
+</div><!-- header -->
+
+
+        <div class="mw introWrapper">
+            <table class="intro" cellpadding="0" cellspacing="0" align="center" width="940">
+                <td class="ag">
+                    <h1>Agility</h1>
+                    <p>Get faster insights from big data with no IT intervention</p>
+                    <span><a href="#agility">LEARN MORE</a></span>
+                </td>
+                <td class="fl">
+                    <h1>Flexibility</h1>
+                    <p>Analyze semi-structured/nested data coming from NoSQL applications</p>
+                    <span><a href="#flexibility">LEARN MORE</a></span>
+                </td>
+                <td class="fa">
+                    <h1>Familiarity</h1>
+                    <p>Leverage existing SQL skillsets, BI tools and Apache Hive deployments</p>
+                    <span><a href="#familiarity">LEARN MORE</a></span>
+                </td>
+            </table>
+        </div>
+
+        <div class="home_txt mw">
+            <h2>Apache Drill is an open source, low latency SQL query engine for Hadoop
and NoSQL.</h2>
+            <p>
+            	Modern big data applications such as social, mobile, web and IoT deal with a
larger number of users and larger amount of data than the traditional transactional applications.
The datasets associated with these applications evolve rapidly, are often self-describing
and can include complex types such as JSON and Parquet. Apache Drill is built from the ground
up to provide low latency queries natively on such rapidly evolving multi-structured datasets
at scale.
+            </p>
+
+            <a name="agility" class="anchor"></a>
+            <h1>Day-Zero Analytics &amp; Rapid<br>Application Development</h1>
+			<!-- <h2>Evolution towards Self-Service Data Exploration</h2> -->
+
+            <img src="images/home-img1.jpg" alt="Day-Zero Analytics & Rapid Application
Development" width="606">
+
+            <p>
+            	Apache Drill provides direct queries on self-describing and semi-structured
data in files (such as JSON, Parquet) and HBase tables without needing to specify metadata
definitions in a centralized store such as Hive metastore. This means that the users can explore
live data on their own as it arrives on Hadoop versus spending weeks or months on data preparation,
modeling and ETL and subsequent schema management. 
+         	</p>
+
+            <a name="flexibility" class="anchor"></a>
+            <h1>Purpose-built for semi-structured/nested data</h1>
+			<!-- <h2>A Flexible Data Model for Modern Apps</h2> -->
+
+            <img src="images/home-img2.jpg" alt="Purpose-built for semi-structured/nested
data" width="635">
+
+            <p>
+				Drill provides a JSON-like internal data model to represent and process data. The flexibility
of this data model allows Drill to query, without flattening, both simple and complex/nested
data types as well as constantly changing application-driven schemas commonly seen with Hadoop/NoSQL
applications. Drill also provides intuitive extensions to SQL to work with complex/nested
data types.
+            </p>
+
+            <a name="familiarity" class="anchor"></a>
+            <h1>Compatibility with existing SQL environments<br>and Apache Hive
deployments</h1>
+
+            <br><br>
+
+            <img src="images/home-img3.jpg" width="380" alt="Compatibility with existing
SQL environments and Apache Hive deployments">
+
+            <p>
+            	With Drill, businesses can minimize switching costs and learning curves for
users with the familiar ANSI SQL syntax. Analysts can continue to use familiar BI/analytics
tools that assume and auto-generate ANSI SQL code to interact with Hadoop data by leveraging
the standard JDBC/ODBC interfaces that Drill exposes. Users can also plug-and-play with Hive
environments to enable ad-hoc low latency queries on existing Hive tables and reuse Hive's
metadata, hundreds of file formats and UDFs out-of-the-box.
+            </p>
+
+        </div>
+


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