Author: mujtaba
Date: Wed Jan 21 18:11:48 2015
New Revision: 1653619
URL: http://svn.apache.org/r1653619
Log:
Add who is using page
Modified:
phoenix/site/publish/images/using/all.jpeg
phoenix/site/publish/index.html
phoenix/site/publish/who_is_using.html
phoenix/site/source/src/site/markdown/index.md
phoenix/site/source/src/site/markdown/who_is_using.md
Modified: phoenix/site/publish/images/using/all.jpeg
URL:
http://svn.apache.org/viewvc/phoenix/site/publish/images/using/all.jpeg?rev=1653619&r1=1653618&r2=1653619&view=diff
==============================================================================
Binary files - no diff available.
Modified: phoenix/site/publish/index.html
URL:
http://svn.apache.org/viewvc/phoenix/site/publish/index.html?rev=1653619&r1=1653618&r2=1653619&view=diff
==============================================================================
--- phoenix/site/publish/index.html (original)
+++ phoenix/site/publish/index.html Wed Jan 21 18:11:48 2015
@@ -1,7 +1,7 @@
<!DOCTYPE html>
<!--
- Generated by Apache Maven Doxia at 2015-01-20
+ Generated by Apache Maven Doxia at 2015-01-21
Rendered using Reflow Maven Skin 1.1.0
(http://andriusvelykis.github.io/reflow-maven-skin)
-->
<html xml:lang="en" lang="en">
@@ -164,7 +164,7 @@
</tr>
</tbody>
</table>
- <p><span id="alerts" style="background-color:#ffc; text-align:
center;display: block;padding:10px; border-bottom: solid 1px #cc9">
<b>News:</b> Recently added: <a href="who_is_using.html">Who is using Apache
Phoenix?</a> (Jan 20, 2015) </span></p>
+ <p><span id="alerts" style="background-color:#ffc; text-align:
center;display: block;padding:10px; border-bottom: solid 1px #cc9">
<b>News:</b> Recently added: <a href="news.html">Who is using Apache
Phoenix?</a> (Jan 20, 2015) </span></p>
<hr />
</div>
</div>
Modified: phoenix/site/publish/who_is_using.html
URL:
http://svn.apache.org/viewvc/phoenix/site/publish/who_is_using.html?rev=1653619&r1=1653618&r2=1653619&view=diff
==============================================================================
--- phoenix/site/publish/who_is_using.html (original)
+++ phoenix/site/publish/who_is_using.html Wed Jan 21 18:11:48 2015
@@ -1,7 +1,7 @@
<!DOCTYPE html>
<!--
- Generated by Apache Maven Doxia at 2015-01-20
+ Generated by Apache Maven Doxia at 2015-01-21
Rendered using Reflow Maven Skin 1.1.0
(http://andriusvelykis.github.io/reflow-maven-skin)
-->
<html xml:lang="en" lang="en">
@@ -141,7 +141,7 @@
<td> <img src="images/using/hw.png" alt="" /> <br /><br /> Hortonworks
supports Apache Phoenix as a feature rich ANSI SQL interface for Apache HBase
in Hortonworks Data Platform (HDP). It plays a critical role for our customers
who want diverse choice for data access in Hadoop and want a simple interface
to build low-latency, large scale applications. Critical features, such as
secondary indexing have made Phoenix the API of choice for building these HBase
applications. <br /><br /> Devaraj Das<br /> Cofounder<br /> Hortonworks<br />
</td>
</tr>
<tr class="a">
- <td> <img src="images/using/sf.png" alt="" /> <br /><br /> Apache
Phoenix is the foundation of our big data stack allowing us to run interactive
queries against HBase data in a performant manner. In our Force.com platform,
we rely on Apache Phoenix to run interactive queries against big data residing
in HBase, leveraging<br /> - multi-tenant tables for customization and scale
out across our diverse customer schemas<br /> - aggregation to build roll-up
summaries<br /> - secondary indexes to improve performance<br /> <br /> Steven
Tamm<br /> CTO<br /> salesforce.com<br /> <br /> At Salesforce, Apache Phoenix
is the mainstay of our Platform Big Data architecture, goto market and and
product strategy.<br /><br /> We are looking to launch the first of numerous
Big Data products in upcoming Spring '15 release - Field Audit Trails. Field
Audit Trails delivers a new archiving service for our customer most critical
data audit trails allowing our customers to easily query and traverse
multi-billion record data sets.<br /><br /> Jonathan Bruce<br /> Director of
Product Management<br /> salesforce.com<br /> </td>
+ <td> <img src="images/using/sf.png" alt="" /> <br /><br /> Apache
Phoenix is the foundation of our big data stack allowing us to run interactive
queries against HBase data in a performant manner. In our Force.com platform,
we rely on Apache Phoenix to run interactive queries against big data residing
in HBase, leveraging<br /> <li> multi-tenant tables for customization and scale
out across our diverse customer schemas</li> <li> aggregation to build roll-up
summaries</li> <li> secondary indexes to improve performance</li> <br /> Steven
Tamm<br /> CTO<br /> salesforce.com<br /> <br /> At Salesforce, Apache Phoenix
is the mainstay of our Platform Big Data architecture, goto market and and
product strategy.<br /><br /> We are looking to launch the first of numerous
Big Data products in upcoming Spring '15 release - Field Audit Trails. Field
Audit Trails delivers a new archiving service for our customer most critical
data audit trails allowing our customers to easily query and tra
verse multi-billion record data sets.<br /><br /> Jonathan Bruce<br />
Director of Product Management<br /> salesforce.com<br /> </td>
</tr>
<tr class="b">
<td> <img src="images/using/cn.png" alt="" /> <br /><br /> At CertusNet
we utilize HBase for Gigabytes level data storage and processing per five
minutes. We found Phoenix most appropriate for easy-to-use sql layer and JDBC
query support, even more highlighting secondary-indexes support, cause we are
expecting both query performance and data manipulation load balancing for our
HBase processing architecture.<br /> "For us, the most valuable feature
are index support and query convenience for our HBase data processing."<br
/><br /> Fulin Sun<br /> Software Enginneer<br /> CertusNet<br /> </td>
@@ -150,7 +150,11 @@
<td> <img src="images/using/teoco.png" alt="" /> <br /><br /> TEOCO is
a leading provider of assurance and analytics solutions to communications
service providers worldwide.<br /> At Teoco we use Phoenix to provide fast
access to customers activity records. The system is required to manage tens of
billions of records per day.<br /><br /> Phoenix allows us easy and rapid
development using it's SQL interface while maintaining HBase performance and
throughput. It's saves the need to handle and manage lower level operations,
and allows clean and maintainable code.<br /><br /> Cahana Ori<br /> Director
of Research and Development<br /> TEOCO<br /> </td>
</tr>
<tr class="b">
- <td> <img src="images/using/ab.png" alt="" /> <br /><br /> At Alibaba
there're two main scenarios of using Phoenix:<br /><br /> 1. Large dataset with
relatively small result set, say 10 thousands of records or so. We choose to
use Phoenix in this kind of scenario because it's much more easier for user to
use than HBase native api, meantime it supports orderby/groupby syntax<br /><br
/> 2. Large dataset with large result set, it might be millions of records in
the result set even after PrimaryKey filter, and often along with lots of
aggregation/orderby/groupby invocation. We choose to use Pheonix in this kind
of scenario because Pheonix makes it possible to do complicated query in HBase,
and it supports more and more features in traditional DB like oracle, which
makes it much more easier for our user to migrate there BI query onto HBase<br
/><br /> Jaywong<br /> Software Engineer<br /> Alibaba<br /> </td>
+ <td> <img src="images/using/ab.png" alt="" /> <br /><br /> At Alibaba
there're two main scenarios of using Phoenix:<br /><br />
+ <ol style="list-style-type: decimal">
+ <li> Large dataset with relatively small result set, say 10 thousands
of records or so. We choose to use Phoenix in this kind of scenario because
it's much more easier for user to use than HBase native api, meantime it
supports orderby/groupby syntax</li>
+ <li> Large dataset with large result set, it might be millions of
records in the result set even after PrimaryKey filter, and often along with
lots of aggregation/orderby/groupby invocation. We choose to use Pheonix in
this kind of scenario because Pheonix makes it possible to do complicated query
in HBase, and it supports more and more features in traditional DB like oracle,
which makes it much more easier for our user to migrate there BI query onto
HBase</li>
+ </ol><br /> Jaywong<br /> Software Engineer<br /> Alibaba<br /> </td>
</tr>
</tbody>
</table>
@@ -160,7 +164,11 @@
<table border="0" class="bodyTable table table-striped table-hover">
<tbody>
<tr class="a">
- <td> <img src="images/using/ebay.png" alt="" /> <br /><br /> We have
been exploring Phoenix since July, 2014 and have successfully achieved couple
of analytics use cases with huge data set. We were able to achieve read/write
performance in ms even slicing and dicing data in many dimensions.<br /><br />
1. Path or Flow analysis<br /> This use case was very specific and targeted for
core mobile native apps where we were trying to find user behavior with many
dimension App, Version, device , OS version, carrier etc. This was offline
process where we process and aggregate daily data and load once in phoenix
schema.<br /><br /> 2. Real Time analytics data trend.<br /> This is near real
time aggregation of tracking data to find trend of events with
multi-dimensional. It does write aggregated data to hBase + Phoenix
continuously (at present 12k-15k/s records) and read for report generation at
the same time.<br /><br /> Jogendar Singh<br /> Engineering Manager, Mobile
Platform<br />
ebay<br /> </td>
+ <td> <img src="images/using/ebay.png" alt="" /> <br /><br /> We have
been exploring Phoenix since July, 2014 and have successfully achieved couple
of analytics use cases with huge data set. We were able to achieve read/write
performance in ms even slicing and dicing data in many dimensions.<br /><br />
+ <ol style="list-style-type: decimal">
+ <li> Path or Flow analysis<br /> This use case was very specific and
targeted for core mobile native apps where we were trying to find user behavior
with many dimension App, Version, device , OS version, carrier etc. This was
offline process where we process and aggregate daily data and load once in
phoenix schema.</li>
+ <li> Real Time analytics data trend.<br /> This is near real time
aggregation of tracking data to find trend of events with multi-dimensional. It
does write aggregated data to hBase + Phoenix continuously (at present
12k-15k/s records) and read for report generation at the same time.</li>
+ </ol><br /> Jogendar Singh<br /> Engineering Manager, Mobile
Platform<br /> ebay<br /> </td>
</tr>
<tr class="b">
<td> <img src="images/using/ss.png" alt="" /> <br /><br /> At Sift
Science we use Phoenix to power our OLAP infrastructure. This influences our
machine learning feature engineering which is critical in the model training
pipeline. Having a simple SQL-based interface also allows us to expose data
insights outside of the engineering organization. Finally, running Phoenix on
top of our existing HBase infrastructure gives us the ability to scale our
ad-hoc query needs. <br /><br /> Andrey Gusev<br /> Tech Lead, Machine Learning
Infrastructure<br /> Sift Science<br /> </td>
Modified: phoenix/site/source/src/site/markdown/index.md
URL:
http://svn.apache.org/viewvc/phoenix/site/source/src/site/markdown/index.md?rev=1653619&r1=1653618&r2=1653619&view=diff
==============================================================================
--- phoenix/site/source/src/site/markdown/index.md (original)
+++ phoenix/site/source/src/site/markdown/index.md Wed Jan 21 18:11:48 2015
@@ -45,7 +45,7 @@
<span id="alerts" style="background-color:#ffc; text-align: center;display:
block;padding:10px; border-bottom: solid 1px #cc9">
<strong>News:</strong>
-Recently added: <a href="who_is_using.html">Who is using Apache Phoenix?</a>
(Jan 20, 2015)
+Recently added: <a href="news.html">Who is using Apache Phoenix?</a> (Jan 20,
2015)
</span>
<hr/>
@@ -55,7 +55,7 @@ Recently added: <a href="who_is_using.ht
Apache Phoenix is a relational database layer over HBase delivered as a
client-embedded JDBC driver targeting low latency queries over HBase data.
Apache Phoenix takes your SQL query, compiles it into a series of HBase scans,
and orchestrates the running of those scans to produce regular JDBC result
sets. The table metadata is stored in an HBase table and versioned, such that
snapshot queries over prior versions will automatically use the correct schema.
Direct use of the HBase API, along with coprocessors and custom filters,
results in [performance](performance.html) on the order of milliseconds for
small queries, or seconds for tens of millions of rows.
<p align="center">
-<br/>Who is using Apache Phoenix? Read more <a
href="news.html">here...</a><br/>
+<br/>Who is using Apache Phoenix? Read more <a
href="who_is_using.html">here...</a><br/>
<img src="images/using/all.jpeg"/>
</p>
## Mission
Modified: phoenix/site/source/src/site/markdown/who_is_using.md
URL:
http://svn.apache.org/viewvc/phoenix/site/source/src/site/markdown/who_is_using.md?rev=1653619&r1=1653618&r2=1653619&view=diff
==============================================================================
--- phoenix/site/source/src/site/markdown/who_is_using.md (original)
+++ phoenix/site/source/src/site/markdown/who_is_using.md Wed Jan 21 18:11:48
2015
@@ -30,10 +30,10 @@ Apache Phoenix is the foundation of our
run interactive queries against HBase data in a performant manner. In
our Force.com platform, we rely on Apache Phoenix to run interactive
queries against big data residing in HBase, leveraging<br/>
-- multi-tenant tables for customization and scale out across our
-diverse customer schemas<br/>
-- aggregation to build roll-up summaries<br/>
-- secondary indexes to improve performance<br/>
+<li> multi-tenant tables for customization and scale out across our
+diverse customer schemas</li>
+<li> aggregation to build roll-up summaries</li>
+<li> secondary indexes to improve performance</li>
<br/>
Steven Tamm<br/>
CTO<br/>
@@ -100,18 +100,20 @@ TEOCO<br/>
At Alibaba there're two main scenarios of using Phoenix:<br/><br/>
-1. Large dataset with relatively small result set, say 10 thousands of
+<ol>
+<li> Large dataset with relatively small result set, say 10 thousands of
records or so. We choose to use Phoenix in this kind of scenario
because it's much more easier for user to use than HBase native api,
-meantime it supports orderby/groupby syntax<br/><br/>
+meantime it supports orderby/groupby syntax</li>
-2. Large dataset with large result set, it might be millions of
+<li> Large dataset with large result set, it might be millions of
records in the result set even after PrimaryKey filter, and often
along with lots of aggregation/orderby/groupby invocation. We choose
to use Pheonix in this kind of scenario because Pheonix makes it
possible to do complicated query in HBase, and it supports more and
more features in traditional DB like oracle, which makes it much more
-easier for our user to migrate there BI query onto HBase<br/><br/>
+easier for our user to migrate there BI query onto HBase</li>
+</ol><br/>
Jaywong<br/>
Software Engineer<br/>
@@ -133,18 +135,18 @@ achieved couple of analytics use cases w
able to achieve read/write performance in ms even slicing and dicing
data in many dimensions.<br/><br/>
-1. Path or Flow analysis<br/>
+<ol><li> Path or Flow analysis<br/>
This use case was very specific and targeted for core mobile native
apps where we were trying to find user behavior with many dimension
App, Version, device , OS version, carrier etc. This was offline
process where we process and aggregate daily data and load once in
-phoenix schema.<br/><br/>
+phoenix schema.</li>
-2. Real Time analytics data trend.<br/>
+<li> Real Time analytics data trend.<br/>
This is near real time aggregation of tracking data to find trend of
events with multi-dimensional. It does write aggregated data to hBase
+ Phoenix continuously (at present 12k-15k/s records) and read for
-report generation at the same time.<br/><br/>
+report generation at the same time.</li></ol><br/>
Jogendar Singh<br/>
Engineering Manager, Mobile Platform<br/>
