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Posted to commits@drill.apache.org by ts...@apache.org on 2015/05/17 08:51:35 UTC
[15/26] drill git commit: New homepage design
New homepage design
Project: http://git-wip-us.apache.org/repos/asf/drill/repo
Commit: http://git-wip-us.apache.org/repos/asf/drill/commit/0b09f9b5
Tree: http://git-wip-us.apache.org/repos/asf/drill/tree/0b09f9b5
Diff: http://git-wip-us.apache.org/repos/asf/drill/diff/0b09f9b5
Branch: refs/heads/gh-pages
Commit: 0b09f9b5cf03546f5297b36813c817fe11a98558
Parents: ca346ee
Author: Tomer Shiran <ts...@gmail.com>
Authored: Fri May 15 20:46:34 2015 -0700
Committer: Tomer Shiran <ts...@gmail.com>
Committed: Fri May 15 20:46:34 2015 -0700
----------------------------------------------------------------------
blog/_drafts/drill-1.0-released.md | 12 +++--
css/code.css | 4 +-
css/style.css | 78 +++++++++++++++++++------------
images/home-any.png | Bin 0 -> 55988 bytes
images/home-bi.png | Bin 0 -> 42034 bytes
images/home-coffee.jpg | Bin 0 -> 33977 bytes
images/home-json.png | Bin 0 -> 54424 bytes
index.html | 79 ++++++++++++++++++++++++++++++--
8 files changed, 136 insertions(+), 37 deletions(-)
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http://git-wip-us.apache.org/repos/asf/drill/blob/0b09f9b5/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
index b9cfbb7..c9fc5d8 100644
--- a/blog/_drafts/drill-1.0-released.md
+++ b/blog/_drafts/drill-1.0-released.md
@@ -31,12 +31,20 @@ Forest Hill, MD - 19 May 2015 - The Apache Software Foundation (ASF), the all-vo
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.”
+"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."
+"Apache Drill 1.0 raises the bar for secure, reliable and scalable SQL-on-Hadoop," said Piyush Bhargava, distinguished engineer, IT, Cisco Systems. "Because Drill integrates with existing data virtualization and visualization tools, we expect it will improve adoption of self-service data exploration and large-scale BI queries on our advanced Hadoop platform at Cisco."
+
+"Apache Drill closes a gap around self-service SQL queries in Hadoop, especially on complex, dynamic NoSQL data types," said Mike Foster, strategic alliances technology officer, Qlik. "Drill's performance advantages for Hadoop data access, combined with the Qlik associative experience, enables our customers to continue discovering business value from a wide range of data. Congrats to the Apache Drill community."
+
+"Apache Drill empowers people to access data that is traditionally difficult to work with," said Jeff Feng, product manager, Tableau. "Direct access within a centralized data repository and without pre-generating metadata definitions encourages data democracy which is essential for data-driven organizations. Additionally, Drill's instant and secure access to complex data formats, such as JSON, opens up extended analytical opportunities."
+
+"Congratulations to the Apache Drill community on the availability of 1.0," said Karl Van den Bergh, vice president, products and cloud, TIBCO. "Drill promises to bring low-latency access to data stored in Hadoop and HBase via standard SQL semantics. This innovation is in line with the value of Fast Data analysis, which TIBCO customers welcome and appreciate."
+
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.
@@ -44,5 +52,3 @@ 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/0b09f9b5/css/code.css
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diff --git a/css/code.css b/css/code.css
index b06c8d2..b0de98d 100644
--- a/css/code.css
+++ b/css/code.css
@@ -3,7 +3,7 @@ div.highlight pre, code {
border-radius: 0;
border: none;
border-left: 5px solid #494747;
- font-family: 'Source Code Pro', monospace;
+ font-family: Monaco,Menlo,Consolas,"Courier New",monospace;
font-size: 14px;
line-height: 24px;
overflow: auto;
@@ -21,7 +21,7 @@ code {
border-radius: 0;
border: none;
border-left: 5px;
- font-family: 'Source Code Pro', monospace;
+ font-family: font-family: Monaco,Menlo,Consolas,"Courier New",monospace;
font-size: 14px;
line-height: 24px;
overflow: auto;
http://git-wip-us.apache.org/repos/asf/drill/blob/0b09f9b5/css/style.css
----------------------------------------------------------------------
diff --git a/css/style.css b/css/style.css
index cc85454..e7ab7ef 100755
--- a/css/style.css
+++ b/css/style.css
@@ -442,7 +442,6 @@ span.strong {
.introWrapper {
border-bottom:1px solid #CCC;
- margin-bottom:50px;
}
table.intro {
@@ -456,7 +455,7 @@ table.intro td {
background-position:center 25px;
background-repeat:no-repeat;
background-size:25px auto;
- padding:65px 0 40px 0;
+ padding:65px 0 0 0;
position:relative;
vertical-align:top;
}
@@ -501,32 +500,6 @@ table.intro a {
font-weight: bold;
}
-.home_txt {
- text-align:center;
- padding-bottom:25px;
-}
-
-.home_txt h1 {
- font-size:36px;
- font-weight:normal;
- line-height:44px;
- margin:0;
-}
-
-.home_txt h2 {
- font-size:16px;
- font-weight:normal;
- line-height:24px;
-}
-
-.home_txt p {
- font-size:16px;
- font-weight:lighter;
- line-height:24px;
- margin:40px auto;
- width:770px;
-}
-
#blu {
display:table;
font-size:12px;
@@ -851,4 +824,51 @@ div.alertbar a{
div.alertbar div span{
font-size:65%;
color:#aa7;
-}
\ No newline at end of file
+}
+
+div.home-row{
+ border-bottom:solid 1px #ccc;
+ margin:0 auto;
+ text-align:center;
+}
+
+div.home-row div{
+ display:inline-block;
+ vertical-align:middle;
+ text-align:left;
+}
+
+div.home-row:nth-child(odd) div:nth-child(1){
+ width:300px;
+}
+
+div.home-row:nth-child(odd) div:nth-child(2){
+ margin-left:40px;
+ width:580px;
+}
+
+div.home-row:nth-child(even) div:nth-child(1){
+ width:580px;
+}
+
+div.home-row:nth-child(even) div:nth-child(2){
+ margin-left:40px;
+ width:300px;
+}
+
+.home-row h1 {
+ font-size:24px;
+ margin:24px 0;
+ font-weight:bold;
+}
+
+.home-row h2 {
+ font-size:20px;
+ margin:20px 0;
+ font-weight:bold;
+}
+
+.home-row p {
+ font-size:16px;
+ line-height:22px;
+}
http://git-wip-us.apache.org/repos/asf/drill/blob/0b09f9b5/images/home-any.png
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diff --git a/images/home-any.png b/images/home-any.png
new file mode 100644
index 0000000..71ddeb5
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http://git-wip-us.apache.org/repos/asf/drill/blob/0b09f9b5/images/home-bi.png
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diff --git a/images/home-bi.png b/images/home-bi.png
new file mode 100644
index 0000000..80bfccb
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http://git-wip-us.apache.org/repos/asf/drill/blob/0b09f9b5/images/home-coffee.jpg
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diff --git a/images/home-coffee.jpg b/images/home-coffee.jpg
new file mode 100644
index 0000000..da4f6e0
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http://git-wip-us.apache.org/repos/asf/drill/blob/0b09f9b5/images/home-json.png
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diff --git a/images/home-json.png b/images/home-json.png
new file mode 100644
index 0000000..b6cccea
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http://git-wip-us.apache.org/repos/asf/drill/blob/0b09f9b5/index.html
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diff --git a/index.html b/index.html
index a1eee46..03b787c 100755
--- a/index.html
+++ b/index.html
@@ -67,23 +67,95 @@ $(document).ready(function() {
<td class="ag">
<h1>Agility</h1>
<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 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 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>
</tbody>
</table>
</div>
+<div class="home-row">
+ <div><img src="{{ site.baseurl }}/images/home-any.png" style="width:300px" /></div>
+ <div>
+ <h1>Query any non-relational datastore (well, almost...)</h1>
+ <p>Drill supports a variety of NoSQL databases and file systems, including HBase, MongoDB, MapR-DB, HDFS, MapR-FS, S3, Azure Blob Storage, Google Cloud Storage, Swift, NAS and local files. A single query can join data from multiple datastores. For example, you could join a user profile collection in MongoDB with a directory of event logs in Hadoop.</p>
+ <p>Drill’s datastore-aware optimizer automatically restructures a query plan to leverage the datastore’s internal processing capabilities. In addition, Drill supports 'data locality', so it’s a good idea to co-locate Drill and the datastore on the same nodes.</p>
+ </div>
+</div>
+
+<div class="home-row">
+ <div>
+ <h1>Kiss the overhead goodbye and enjoy data agility</h1>
+ <p>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. There's no need to load the data, create and maintain schemas, or transform the data before it can be processed. Instead, simply include the path to a Hadoop directory, MongoDB collection or S3 bucket in the SQL query.</p>
+ <p>Drill leverages advanced query compilation and re-compilation techniques to maximize performance without requiring up-front schema knowledge.</p>
+ </div>
+ <div><pre style='background:#f3f5f7;color:#2a333c;border:solid 1px #aaa; font-family: Monaco,Menlo,Consolas,"Courier New",monospace; font-size: 12px;
+ line-height: 1.5;'>SELECT * FROM <span style="font-weight:bold;color:#000;text-decoration: underline">dfs.root.`/web/logs`</span>;
+
+SELECT country, count(*)
+ FROM <span style="font-weight:bold;color:#000;text-decoration: underline;">mongodb.web.users</span>
+ GROUP BY country;
+
+SELECT timestamp
+ FROM <span style="font-weight:bold;color:#000;text-decoration: underline">s3.root.`clicks.json`</span>
+ WHERE user_id = 'jdoe';</pre></div>
+</div>
+
+<div class="home-row">
+ <div><img src="{{ site.baseurl }}/images/home-json.png" style="width:250px" /></div>
+ <div>
+ <h1>Treat your data like a table even when it’s not</h1>
+ <p>Drill features a JSON data model that enables it to query complex/nested data and rapidly evolving structure commonly seen in modern applications and non-relational datastores. Drill also provides intuitive extensions to SQL so that the user can easily query complex data.
+ <p>Drill is the only columnar query engine that supports complex data. It features an in-memory shredded columnar representation for complex data which allows Drill to achieve columnar speed with the flexibility of an internal JSON document model.</p>
+ </div>
+</div>
+
+<div class="home-row">
+ <div>
+ <h1>Keep using the BI tools you love</h1>
+ <p>Drill supports standard SQL. Business users, analysts and data scientists can use standard BI/analytics tools such as Tableau, Qlik, 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.</p>
+ <p>Drill’s virtual datasets allow even the most complex, non-relational data to be mapped into BI-friendly structures which users can explore and visualize using their tool of choice.</p>
+ </div>
+ <div><img src="{{ site.baseurl }}/images/home-bi.png" style="width:300px" /></div>
+</div>
+
+<div class="home-row">
+ <div><div><pre style='background:#f3f5f7;color:#2a333c;border:solid 1px #aaa; font-family: Monaco,Menlo,Consolas,"Courier New",monospace; font-size: 12px;
+ line-height: 1.5;'>$ curl j.mp/drill-latest -o drill.tgz
+$ tar xzf drill.tgz
+$ cd apache-drill-1.0.0
+$ bin/drill-embedded
+</pre></div></div>
+ <div>
+ <h1>Scale from one laptop to 1000s of servers</h1>
+ <p>We made it easy to download and run Drill on your laptop. It runs on Mac, Windows and Linux, and within a minute or two you’ll be exploring your data. When you’re ready for prime time, deploy Drill on a cluster of commodity servers and take advantage of the world’s most scalable and high performance execution engine.
+ <p>Drill’s symmetrical architecture (all nodes are the same) and simple installation makes it easy to deploy and operate very large clusters.</p>
+ </div>
+</div>
+
+<div class="home-row">
+ <div>
+ <h1>No more waiting for coffee</h1>
+ <p>Drill isn’t the world’s first query engine, but it’s the first that combines both flexibility and speed. To achieve this, Drill features a radically different architecture that enables record-breaking performance without sacrificing the flexibility offered by the JSON document model. For example:<ul>
+<li>Columnar execution engine (the first ever to support complex data!)</li>
+<li>Data-driven compilation and recompilation at execution time</li>
+<li>Specialized memory management that reduces memory footprint and eliminates garbage collections</li>
+<li>Locality-aware exeucution that reduces network traffic when Drill is co-located with the datastore</li>
+<li>Advanced cost-based optimizer that pushes processing into the datastore when possible</li></ul></p>
+ </div>
+ <div><img src="{{ site.baseurl }}/images/home-coffee.jpg" style="width:300px" /></div>
+</div>
+
+
+
+<!--
<div class="home_txt mw">
<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>
@@ -103,3 +175,4 @@ $(document).ready(function() {
<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>
+-->