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Posted to commits@drill.apache.org by ts...@apache.org on 2015/05/17 08:51:29 UTC
[09/26] drill git commit: Improved home page text and blog spacing
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 <ts...@gmail.com>
Authored: Fri May 15 00:06:52 2015 -0700
Committer: Tomer Shiran <ts...@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(-)
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http://git-wip-us.apache.org/repos/asf/drill/blob/ca346ee0/_layouts/post.html
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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>
</header>
<div class="addthis_sharing_toolbox"></div>
http://git-wip-us.apache.org/repos/asf/drill/blob/ca346ee0/blog/_drafts/drill-1.0-released.md
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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 datastores.
+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 months.
+
+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 owners.
+
+\# \# \#
http://git-wip-us.apache.org/repos/asf/drill/blob/ca346ee0/css/style.css
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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 {
padding:0;
}
#header .scroller .item .tc h2 {
- font-size: 20px;
+ font-size: 18px;
}
#header .scroller .item .tc p {
http://git-wip-us.apache.org/repos/asf/drill/blob/ca346ee0/index.html
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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>
</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 NOW</span></a>
</div>
</div>
@@ -66,17 +66,17 @@ $(document).ready(function() {
<tr>
<td class="ag">
<h1>Agility</h1>
- <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>
<td class="fl">
<h1>Flexibility</h1>
- <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>
<td class="fam">
<h1>Familiarity</h1>
- <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>
</td>
</tr>
@@ -85,25 +85,21 @@ $(document).ready(function() {
</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>
+ <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 & 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">
+ <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" 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>
+ <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>
</div>