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From dma...@apache.org
Subject svn commit: r1810142 - in /ignite/site/trunk: events.html index.html
Date Fri, 29 Sep 2017 18:01:09 GMT
Author: dmagda
Date: Fri Sep 29 18:01:08 2017
New Revision: 1810142

URL: http://svn.apache.org/viewvc?rev=1810142&view=rev
Log:
Updated events

Modified:
    ignite/site/trunk/events.html
    ignite/site/trunk/index.html

Modified: ignite/site/trunk/events.html
URL: http://svn.apache.org/viewvc/ignite/site/trunk/events.html?rev=1810142&r1=1810141&r2=1810142&view=diff
==============================================================================
--- ignite/site/trunk/events.html (original)
+++ ignite/site/trunk/events.html Fri Sep 29 18:01:08 2017
@@ -154,7 +154,6 @@ under the License.
                     </div>
                     <p style="margin:0;">&nbsp;</p>
                 </section>
-
                 <section id="webinar-postgres-apacher-ignitetm" class="page-section news-section">
                     <div><h3 style="display:inline-block;">Postgres with Apache®
Ignite™: Faster Transactions and Analytics&nbsp;
                         <a href="/events.html#webinar-postgres-apacher-ignitetm"><i
class="fa fa-anchor"></i></a>
@@ -184,6 +183,38 @@ under the License.
                             <a class="a2a_button_twitter"></a>
                             <a class="a2a_button_linkedin"></a>
                             <a class="a2a_button_facebook"></a>
+                            <a class="a2a_dd" href="https://www.addtoany.com/share"></a>
+                        </div>
+                        <!-- AddToAny END -->
+                    </div>
+                    <p style="margin:0;">&nbsp;</p>
+                </section>
+                <section id="Big-Data-Developers-in-Paris-243327509" class="page-section
news-section">
+                    <div><h3 style="display:inline-block;">Giving a boost to
the Hadoop and Spark ecosystems with in-memory technologies&nbsp;
+                        <a href="/events.html#Big-Data-Developers-in-Paris-243327509"><i
class="fa fa-anchor"></i></a>
+                    </h3></div>
+                    <span class="news-date">Big Data & Data Science, Paris, Speaker
- Akmal Chaudhri</span><br/><br/>
+                    <span class="news-date">October 2, 2017</span>
+                    <p>
+                        In this talk, Akmal present how to speed up existing Hadoop and Spark
deployments by making Apache Ignite responsible for RAM utilization.
+                        No code modifications, no new architecture from scratch! Specifically,
this presentation will cover :
+                        Hadoop Accelerator, HDFS compliant In-Memory File System, MapReduce
Accelerator, Spark Shared RDDs, Spark SQL boost.
+
+                    </p>
+                    <div class="col-sm-12 col-md-9 col-xs-12 news-readmore">
+                        <p>
+                            <a href="https://www.meetup.com/preview/Big-Data-Developers-in-Paris/events/243327509"
target="_blank">Read more</a>
+                        </p>
+                    </div>
+                    <div class="col-sm-12 col-md-3 col-xs-12 ">
+
+                        <!-- AddToAny BEGIN -->
+                        <div class="a2a_kit a2a_kit_size_28 a2a_default_style news-socialmedia-icons"
+                             data-a2a-url="https://www.meetup.com/preview/Big-Data-Developers-in-Paris/events/243327509"
+                             data-a2a-title="Giving a boost to the Hadoop and Spark ecosystems
with in-memory technologies">
+                            <a class="a2a_button_twitter"></a>
+                            <a class="a2a_button_linkedin"></a>
+                            <a class="a2a_button_facebook"></a>
                             <a class="a2a_dd" href="https://www.addtoany.com/share"></a>
                         </div>
                         <!-- AddToAny END -->

Modified: ignite/site/trunk/index.html
URL: http://svn.apache.org/viewvc/ignite/site/trunk/index.html?rev=1810142&r1=1810141&r2=1810142&view=diff
==============================================================================
Binary files - no diff available.



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