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<h1 class="entry-title"><a href="/2021/01/28/apache-kudu-1-14-0-release.html">Apache Kudu 1.14.0 Released</a></h1>
<p class="meta">Posted 28 Jan 2021 by Grant Henke</p>
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<p>The Apache Kudu team is happy to announce the release of Kudu 1.14.0!</p>
<p>The new release adds several new features and improvements, including the
following:</p>
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<h1 class="entry-title"><a href="/2021/01/15/bloom-filter-predicate.html">Optimized joins & filtering with Bloom filter predicate in Kudu</a></h1>
<p class="meta">Posted 15 Jan 2021 by Bankim Bhavsar</p>
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<p>Note: This is a cross-post from the Cloudera Engineering Blog
<a href="https://blog.cloudera.com/optimized-joins-filtering-with-bloom-filter-predicate-in-kudu/">Optimized joins &amp; filtering with Bloom filter predicate in Kudu</a></p>
<p>Cloudera’s CDP Runtime version 7.1.5 maps to Apache Kudu 1.13 and upcoming Apache Impala 4.0</p>
<h2 id="introduction">Introduction</h2>
<p>In database systems one of the most effective ways to improve performance is to avoid doing
unnecessary work, such as network transfers and reading data from disk. One of the ways Apache
Kudu achieves this is by supporting column predicates with scanners. Pushing down column predicate
filters to Kudu allows for optimized execution by skipping reading column values for filtered out
rows and reducing network IO between a client, like the distributed query engine Apache Impala, and
Kudu. See the documentation on
<a href="https://docs.cloudera.com/runtime/latest/impala-reference/topics/impala-runtime-filtering.html">runtime filtering in Impala</a>
for details.</p>
<p>CDP Runtime 7.1.5 and CDP Public Cloud added support for Bloom filter column predicate pushdown in
Kudu and the associated integration in Impala.</p>
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<h1 class="entry-title"><a href="/2020/09/21/apache-kudu-1-13-0-release.html">Apache Kudu 1.13.0 released</a></h1>
<p class="meta">Posted 21 Sep 2020 by Attila Bukor</p>
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<p>The Apache Kudu team is happy to announce the release of Kudu 1.13.0!</p>
<p>The new release adds several new features and improvements, including the
following:</p>
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<h1 class="entry-title"><a href="/2020/08/11/fine-grained-authz-ranger.html">Fine-Grained Authorization with Apache Kudu and Apache Ranger</a></h1>
<p class="meta">Posted 11 Aug 2020 by Attila Bukor</p>
</header>
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<p>When Apache Kudu was first released in September 2016, it didn’t support any
kind of authorization. Anyone who could access the cluster could do anything
they wanted. To remedy this, coarse-grained authorization was added along with
authentication in Kudu 1.3.0. This meant allowing only certain users to access
Kudu, but those who were allowed access could still do whatever they wanted. The
only way to achieve finer-grained access control was to limit access to Apache
Impala where access control <a href="/2019/04/22/fine-grained-authorization-with-apache-kudu-and-impala.html">could be enforced</a> by
fine-grained policies in Apache Sentry. This method limited how Kudu could be
accessed, so we saw a need to implement fine-grained access control in a way
that wouldn’t limit access to Impala only.</p>
<p>Kudu 1.10.0 integrated with Apache Sentry to enable finer-grained authorization
policies. This integration was rather short-lived as it was deprecated in Kudu
1.12.0 and will be completely removed in Kudu 1.13.0.</p>
<p>Most recently, since 1.12.0 Kudu supports fine-grained authorization by
integrating with Apache Ranger 2.1 and later. In this post, we’ll cover how this
works and how to set it up.</p>
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<h1 class="entry-title"><a href="/2020/07/30/building-near-real-time-big-data-lake.html">Building Near Real-time Big Data Lake</a></h1>
<p class="meta">Posted 30 Jul 2020 by Boris Tyukin</p>
</header>
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<p>Note: This is a cross-post from the Boris Tyukin’s personal blog <a href="https://boristyukin.com/building-near-real-time-big-data-lake-part-2/">Building Near Real-time Big Data Lake: Part 2</a></p>
<p>This is the second part of the series. In <a href="https://boristyukin.com/building-near-real-time-big-data-lake-part-i/">Part 1</a>
I wrote about our use-case for the Data Lake architecture and shared our success story.</p>
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<h3>Recent posts</h3>
<ul>
<li> <a href="/2021/01/28/apache-kudu-1-14-0-release.html">Apache Kudu 1.14.0 Released</a> </li>
<li> <a href="/2021/01/15/bloom-filter-predicate.html">Optimized joins & filtering with Bloom filter predicate in Kudu</a> </li>
<li> <a href="/2020/09/21/apache-kudu-1-13-0-release.html">Apache Kudu 1.13.0 released</a> </li>
<li> <a href="/2020/08/11/fine-grained-authz-ranger.html">Fine-Grained Authorization with Apache Kudu and Apache Ranger</a> </li>
<li> <a href="/2020/07/30/building-near-real-time-big-data-lake.html">Building Near Real-time Big Data Lake</a> </li>
<li> <a href="/2020/05/18/apache-kudu-1-12-0-release.html">Apache Kudu 1.12.0 released</a> </li>
<li> <a href="/2019/11/20/apache-kudu-1-11-1-release.html">Apache Kudu 1.11.1 released</a> </li>
<li> <a href="/2019/11/20/apache-kudu-1-10-1-release.html">Apache Kudu 1.10.1 released</a> </li>
<li> <a href="/2019/07/09/apache-kudu-1-10-0-release.html">Apache Kudu 1.10.0 Released</a> </li>
<li> <a href="/2019/04/30/location-awareness.html">Location Awareness in Kudu</a> </li>
<li> <a href="/2019/04/22/fine-grained-authorization-with-apache-kudu-and-impala.html">Fine-Grained Authorization with Apache Kudu and Impala</a> </li>
<li> <a href="/2019/03/19/testing-apache-kudu-applications-on-the-jvm.html">Testing Apache Kudu Applications on the JVM</a> </li>
<li> <a href="/2019/03/15/apache-kudu-1-9-0-release.html">Apache Kudu 1.9.0 Released</a> </li>
<li> <a href="/2019/03/05/transparent-hierarchical-storage-management-with-apache-kudu-and-impala.html">Transparent Hierarchical Storage Management with Apache Kudu and Impala</a> </li>
<li> <a href="/2018/12/11/call-for-posts.html">Call for Posts</a> </li>
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