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Posted to commits@kudu.apache.org by to...@apache.org on 2016/08/29 18:22:12 UTC
kudu-site git commit: Publish commit(s) from site source repo:
9f644a1 Add Boston CUG to meetup list
Repository: kudu-site
Updated Branches:
refs/heads/asf-site f49e8af0f -> 40648a098
Publish commit(s) from site source repo:
9f644a1 Add Boston CUG to meetup list
Site-Repo-Commit: 9f644a1ccf3ed8f97a6f89304ca519e9c1dd36b0
Project: http://git-wip-us.apache.org/repos/asf/kudu-site/repo
Commit: http://git-wip-us.apache.org/repos/asf/kudu-site/commit/40648a09
Tree: http://git-wip-us.apache.org/repos/asf/kudu-site/tree/40648a09
Diff: http://git-wip-us.apache.org/repos/asf/kudu-site/diff/40648a09
Branch: refs/heads/asf-site
Commit: 40648a098a8060638a306109f679c5d094b7b4dd
Parents: f49e8af
Author: Todd Lipcon <to...@cloudera.com>
Authored: Mon Aug 29 11:21:55 2016 -0700
Committer: Todd Lipcon <to...@cloudera.com>
Committed: Mon Aug 29 11:21:55 2016 -0700
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community.html | 2 ++
feed.xml | 2 +-
2 files changed, 3 insertions(+), 1 deletion(-)
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http://git-wip-us.apache.org/repos/asf/kudu-site/blob/40648a09/community.html
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diff --git a/community.html b/community.html
index 441a93d..c8fbb26 100644
--- a/community.html
+++ b/community.html
@@ -231,6 +231,8 @@ so that we can feature them.</p>
<ol>
<li>Thu, Oct 27, 2016. <a href="https://spark-summit.org/eu-2016/events/apache-kudu-and-spark-sql-for-fast-analytics-on-fast-data/">Spark Summit EU</a>. Brussels, Belgium.<br />
<em>Apache Kudu and Spark SQL</em>. Presented by Mike Percy.</li>
+ <li>Tue, Sep 6, 2016. <a href="http://www.meetup.com/Boston-Cloudera-User-Group/events/233452964/">Boston Cloudera User Group</a>. Boston, MA, USA.<br />
+ Apache Kudu 0.10 and Spark SQL. Presented by William Berkeley.</li>
<li>Thu, Aug 18, 2016. <a href="http://www.meetup.com/Boulder-Denver-Big-Data/events/232056701/">Boulder/Denver Big Data Meetup</a>. Broomfield, CO, USA.<br />
<em>Apache Kudu: New Apache Hadoop Storage for Fast Analytics on Fast Data</em>. Presented by Mike Percy.</li>
<li>Wed, Aug 17, 2016. <a href="http://www.meetup.com/Denver-Cloudera-User-Group/events/232782782/">Denver Cloudera User Group</a>. Greenwood Village, CO, USA.<br />
http://git-wip-us.apache.org/repos/asf/kudu-site/blob/40648a09/feed.xml
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diff --git a/feed.xml b/feed.xml
index ca1721d..222da78 100644
--- a/feed.xml
+++ b/feed.xml
@@ -1,4 +1,4 @@
-<?xml version="1.0" encoding="utf-8"?><feed xmlns="http://www.w3.org/2005/Atom"><generator uri="http://jekyllrb.com" version="2.5.3">Jekyll</generator><link href="/feed.xml" rel="self" type="application/atom+xml" /><link href="/" rel="alternate" type="text/html" /><updated>2016-08-22T23:37:03-07:00</updated><id>/</id><entry><title>New Range Partitioning Features in Kudu 0.10</title><link href="/2016/08/23/new-range-partitioning-features.html" rel="alternate" type="text/html" title="New Range Partitioning Features in Kudu 0.10" /><published>2016-08-23T00:00:00-07:00</published><updated>2016-08-23T00:00:00-07:00</updated><id>/2016/08/23/new-range-partitioning-features</id><content type="html" xml:base="/2016/08/23/new-range-partitioning-features.html"><p>Kudu 0.10 is shipping with a few important new features for range partitioning.
+<?xml version="1.0" encoding="utf-8"?><feed xmlns="http://www.w3.org/2005/Atom"><generator uri="http://jekyllrb.com" version="2.5.3">Jekyll</generator><link href="/feed.xml" rel="self" type="application/atom+xml" /><link href="/" rel="alternate" type="text/html" /><updated>2016-08-29T11:21:53-07:00</updated><id>/</id><entry><title>New Range Partitioning Features in Kudu 0.10</title><link href="/2016/08/23/new-range-partitioning-features.html" rel="alternate" type="text/html" title="New Range Partitioning Features in Kudu 0.10" /><published>2016-08-23T00:00:00-07:00</published><updated>2016-08-23T00:00:00-07:00</updated><id>/2016/08/23/new-range-partitioning-features</id><content type="html" xml:base="/2016/08/23/new-range-partitioning-features.html"><p>Kudu 0.10 is shipping with a few important new features for range partitioning.
These features are designed to make Kudu easier to scale for certain workloads,
like time series. This post will introduce these features, and discuss how to use
them to effectively design tables for scalability and performance.</p>