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From tshi...@apache.org
Subject [09/26] drill git commit: Improved home page text and blog spacing
Date Sun, 17 May 2015 06:51:29 GMT
Improved home page text and blog spacing

Project: http://git-wip-us.apache.org/repos/asf/drill/repo
Commit: http://git-wip-us.apache.org/repos/asf/drill/commit/ca346ee0
Tree: http://git-wip-us.apache.org/repos/asf/drill/tree/ca346ee0
Diff: http://git-wip-us.apache.org/repos/asf/drill/diff/ca346ee0

Branch: refs/heads/gh-pages
Commit: ca346ee0c4867ef298d49cdeeee952c62419d286
Parents: 7cf162a
Author: Tomer Shiran <tshiran@gmail.com>
Authored: Fri May 15 00:06:52 2015 -0700
Committer: Tomer Shiran <tshiran@gmail.com>
Committed: Fri May 15 00:06:52 2015 -0700

 _layouts/post.html                 |  4 +--
 blog/_drafts/drill-1.0-released.md | 48 +++++++++++++++++++++++++++++++++
 css/style.css                      |  2 +-
 index.html                         | 36 +++++++++++--------------
 4 files changed, 67 insertions(+), 23 deletions(-)

diff --git a/_layouts/post.html b/_layouts/post.html
index d98656c..454343a 100644
--- a/_layouts/post.html
+++ b/_layouts/post.html
@@ -19,9 +19,9 @@ layout: default
     {% else %}
       {% assign alias = page.authors[0] %}
       {% assign author = site.data.authors[alias] %}
-      <strong>Author:</strong> {{ author.name }} ({{ author.title}}, {{ author.org}})
+      <strong>Author:</strong> {{ author.name }} ({{ author.title}}, {{ author.org}})<br
     {% endif %}
-{% unless page.nodate %}<br/><strong>Date:</strong> {{ page.date | date:
"%b %-d, %Y" }}{% endunless %}
+{% unless page.nodate %}<strong>Date:</strong> {{ page.date | date: "%b %-d,
%Y" }}{% endunless %}
 {% if page.meta %}{{ page.meta }}{% endif %}</p>
   <div class="addthis_sharing_toolbox"></div>

diff --git a/blog/_drafts/drill-1.0-released.md b/blog/_drafts/drill-1.0-released.md
new file mode 100644
index 0000000..b9cfbb7
--- /dev/null
+++ b/blog/_drafts/drill-1.0-released.md
@@ -0,0 +1,48 @@
+layout: post
+title: "Drill 1.0 Released"
+code: drill-1.0-released
+excerpt: Drill 1.0 is now available, representing a major milestone for the Drill community.
Drill in now production-ready, making it easier than ever to explore and analyze data in non-relational
+authors: ["tshiran", "jnadeau"]
+We embarked on the Drill project in late 2012 with two primary objectives:
+* Revolutionize the query engine by enabling low-latency queries on Big Data while getting
rid of all the 'overhead' - namely, the need to load data, create and maintain schemas, transform
data, etc. We wanted to develop a system that would support the speed and agility at which
modern organizations want (or need) to operate in this era.
+* Unlock the data housed in non-relational datastores like NoSQL, Hadoop and cloud storage,
making it available not only to developers, but also business users, analysts, data scientists
and anyone else who can write a SQL query or use a BI tool. Non-relational datastores are
capturing an increasing share of the world's data, and it's incredibly hard to explore and
analyze this data.
+Today we're happy to announce the availability of Drill 1.0, our first production-ready release.
Drill 1.0 includes many performance and reliability enhancements over previous releases.
+We would not have been able to reach this milestone without the tremendous effort by all
the [committers]({{ site.baseurl }}/team/) and contributors, and we would like to congratulate
the entire community on achieving this milestone. While 1.0 is an exciting milestone, it's
really just the beginning of the journey. We'll release 1.1 next month, and continue with
our 4-6 week release cycle, so you can count on many additional enhancements over the coming
+We have inlcluded the press release issued by the Apache Software Foundation below.
+Happy Drilling!  
+Tomer Shiran and Jacques Nadeau
+<hr />
+# The Apache Software Foundation Announces Apache™ Drill™ 1.0
+## Open Source schema-free SQL query engine revolutionizes data exploration and analytics
for Apache Hadoop®, NoSQL and Cloud storage 
+Forest Hill, MD - 19 May 2015 - The Apache Software Foundation (ASF), the all-volunteer developers,
stewards, and incubators of more than 350 Open Source projects and initiatives, announced
today the availability of Apache™ Drill™ 1.0, the schema-free SQL query engine for Apache
Hadoop®, NoSQL and Cloud storage.
+"The production-ready 1.0 release represents a significant milestone for the Drill project,"
said Tomer Shiran, member of the Apache Drill Project Management Committee. "It is the outcome
of almost three years of development involving dozens of engineers from numerous companies.
Apache Drill's flexibility and ease-of-use have attracted thousands of users, and the enterprise-grade
reliability, security and performance in the 1.0 release will further accelerate adoption."
+With the exponential growth of data in recent years, and the shift towards rapid application
development, new data is increasingly being stored in non-relational, schema-free datastores
including Hadoop, NoSQL and Cloud storage. Apache Drill enables analysts, business users,
data scientists and developers to explore and analyze this data without sacrificing the flexibility
and agility offered by these datastores. Drill processes the data in-situ without requiring
users to define schemas or transform data.
+"Drill introduces the JSON document model to the world of SQL-based analytics and BI" said
Jacques Nadeau, Vice President of Apache Drill. "This enables users to query fixed-schema,
evolving-schema and schema-free data stored in a variety of formats and datastores. The architecture
of relational query engines and databases is built on the assumption that all data has a simple
and static structure that’s known in advance, and this 40-year-old assumption is simply
no longer valid. We designed Drill from the ground up to address the new reality.”
+Apache Drill's architecture is unique in many ways. It is the only columnar execution engine
that supports complex and schema-free data, and the only execution engine that performs data-driven
query compilation (and re-compilation, also known as schema discovery) during query execution.
These unique capabilities enable Drill to achieve record-breaking performance with the flexibility
offered by the JSON document model.
+"Drill's columnar execution engine and optimizer take full advantage of Apache Parquet's
columnar storage to achieve maximum performance," said Julien Le Dem, Technical Lead of Data
Processing at Twitter and Vice President of Apache Parquet. "The Drill team has been a key
contributor to the Parquet project, including recent enhancements to Parquet types and vectorization.
The Drill team’s involvement in the Parquet community is instrumental in driving the standard."
+Availability and Oversight
+Apache Drill 1.0 is available immediately as a free download from http://drill.apache.org/download/.
Documentation is available at http://drill.apache.org/docs/. As with all Apache products,
Apache Drill software is released under the Apache License v2.0, and is overseen by a self-selected
team of active contributors to the project. A Project Management Committee (PMC) guides the
project's day-to-day operations, including community development and product releases. For
ways to become involved with Apache Drill, visit http://drill.apache.org/ and @ApacheDrill
on Twitter.
+About The Apache Software Foundation (ASF)
+Established in 1999, the all-volunteer Foundation oversees more than 350 leading Open Source
projects, including Apache HTTP Server --the world's most popular Web server software. Through
the ASF's meritocratic process known as "The Apache Way," more than 500 individual Members
and 4,500 Committers successfully collaborate to develop freely available enterprise-grade
software, benefiting millions of users worldwide: thousands of software solutions are distributed
under the Apache License; and the community actively participates in ASF mailing lists, mentoring
initiatives, and ApacheCon, the Foundation's official user conference, trainings, and expo.
The ASF is a US 501(c)(3) charitable organization, funded by individual donations and corporate
sponsors including Bloomberg, Budget Direct, Cerner, Citrix, Cloudera, Comcast, Facebook,
Google, Hortonworks, HP, IBM, InMotion Hosting, iSigma, Matt Mullenweg, Microsoft, Pivotal,
Produban, WANdisco, and Yahoo. For more information, visit ht
 tp://www.apache.org/ or follow @TheASF on Twitter.
+© The Apache Software Foundation. "Apache", "Apache Drill", "Drill", "Apache Hadoop", "Hadoop",
"Apache Parquet", "Parquet", and "ApacheCon", are registered trademarks or trademarks of The
Apache Software Foundation. All other brands and trademarks are the property of their respective
+\# \# \#

diff --git a/css/style.css b/css/style.css
index aa8cfb5..cc85454 100755
--- a/css/style.css
+++ b/css/style.css
@@ -316,7 +316,7 @@ a.anchor {
 #header .scroller .item .tc h2 {
-  font-size: 20px;
+  font-size: 18px;
 #header .scroller .item .tc p {

diff --git a/index.html b/index.html
index 7ad2709..a1eee46 100755
--- a/index.html
+++ b/index.html
@@ -49,7 +49,7 @@ $(document).ready(function() {
         <div class="slide"><a class="various fancybox.iframe" href="//www.youtube.com/watch?v=6pGeQOXDdD8"><img
src="{{ site.baseurl }}/images/thumbnail-6pGeQOXDdD8.jpg" class="thumbnail" /><img src="{{
site.baseurl }}/images/play-mq.png" class="play" /></a><div class="title">High
Performance with a JSON Data Model</div></div>
       <h1 class="main-headline">Apache Drill</h1>
-      <h2 id="sub-headline">Schema-free SQL Query Engine <br class="mobile-break"
/> for Hadoop and NoSQL</h2>
+      <h2 id="sub-headline">Schema-free SQL Query Engine <br class="mobile-break"
/> for Hadoop, NoSQL and Cloud Storage</h2>
       <a href="{{ site.baseurl }}/download/" class="download-headline btn btn-1 btn-1c"><span>DOWNLOAD
@@ -66,17 +66,17 @@ $(document).ready(function() {
         <td class="ag">
-          <p>Get faster insights from big data with no IT intervention</p>
+          <p>Get faster insights without the overhead (data loading, schema creation
and maintenance, transformations, etc.)</p>
           <span><a href="#agility">LEARN MORE</a></span>
         <td class="fl">
-          <p>Analyze semi-structured/nested data coming from NoSQL applications</p>
+          <p>Analyze the multi-structured and nested data in non-relational datatastores
directly without transforming or restricting the data</p>
           <span><a href="#flexibility">LEARN MORE</a></span>
         <td class="fam">
-          <p>Leverage existing SQL skillsets, BI tools and Apache Hive deployments</p>
+          <p>Leverage your existing SQL skillsets and BI tools including Tableau, Qlikview,
MicroStrategy, Spotfire, Excel and more</p>
           <span><a href="#familiarity">LEARN MORE</a></span>
@@ -85,25 +85,21 @@ $(document).ready(function() {
 <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>
+  <p>The 40-year monopoly of the relational database is over. The explosion of data
in recent years and the shift towards rapid application development have led to the rise of
non-relational datastores including Hadoop, NoSQL and cloud storage. Organizations are increasingly
leveraging these systems for new and existing applications due to their flexibility, scalability
and price advantages. Drill is built from the ground up to enable business users, analysts,
data scientists and developers to explore and analyze the data in these systems while maintaining
their unique agility and flexibility advantages.</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"
+  <h1>Agility</h1>
+  <img src="images/home-img1.jpg" alt="Agility" 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 define and maintain schemas
in a centralized store such as Hive metastore. This means that  users can explore live data
on their own as it arrives versus spending weeks or months on data preparation, modeling,
ETL and subsequent schema management.</p>
+  <p>Drill is unlike any other query engine. Traditional query engines demand significant
IT intervention before data can be queried. Drill gets rid of all that overhead so that users
can just query the raw data in-situ at record speeds. There's no need to load the data, create
and maintain schemas, or transform the data before it can be processed. For example, the user
can directly query Hadoop directories, MongoDB collections, S3 buckets and more. Drill leverages
advanced query compilation and re-compilation techniques to maximize performance without requiring
up-front schema knowledge.</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"
-  <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>
+  <h1>Flexibility</h1>
+  <img src="images/home-img2.jpg" alt="Agility" width="635" />
+  <p>Drill features a JSON data model that allows it to query, without flattening,
both simple and complex/nested data as well as rapidly evolving structures commonly seen with
modern applications and non-relational datastores. Drill also provides intuitive extensions
to SQL to work with complex/nested data. Drill achieves high performance via an in-memory
shredded columnar representation for complex data. In fact, Drill is the only columnar query
engine that supports complex data.</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>
+  <h1>Familiarity</h1>
+  <img src="images/home-img3.jpg" alt="familiarity" width="380" />
+  <p>Drill supports standard SQL. Business users, analysts and data scientists can
use standard BI/analytics tools such as Tableau, QlikView, MicroStrategy, Spotfire, SAS and
Excel to interact with non-relational datastores by leveraging Drill's JDBC and ODBC drivers.
Developers can leverage Drill's simple REST API in their custom applications to create beautiful
visualizations based on data in their non-relational datastores. 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>

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