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| <article class="h-entry post-text"><header><h3 class="p-name entry-title"><a href="posts/impala-25-performance-overview/" class="u-url">Impala 2.5 performance overview</a></h3> |
| <div class="metadata"> |
| <p class="byline author vcard"><span class="byline-name fn"> |
| <a href="authors/mostafa-mokhtar/">Mostafa Mokhtar</a> |
| </span></p> |
| <p class="dateline"><a href="posts/impala-25-performance-overview/" rel="bookmark"><time class="published dt-published" datetime="2016-05-24T23:00:00-07:00" title="2016-05-24 23:00">2016-05-24 23:00</time></a></p> |
| </div> |
| </header><div class="p-summary entry-summary"> |
| <p>Impala has proven to be a high-performance analytics query engine since the beginning. Even as an |
| initial production release in 2013, it demonstrated performance 2x faster than a traditional DBMS, |
| and each subsequent release has continued to demonstrate the wide performance gap between Impala’s |
| analytic-database architecture and SQL-on-Apache Hadoop alternatives. Today, we are excited to |
| continue that track record via some important performance gains for Impala 2.5 (with more to come on |
| the roadmap), summarized below.</p> |
| |
| <p>Overall, compared to Impala 2.3, in Impala 2.5:</p> |
| |
| <ul> |
| <li>TPC-DS queries run on average 4.3x faster.</li> |
| <li>TPC-H queries run 2.2x faster on flat tables, and 1.71x faster on nested tables.</li> |
| </ul> |
| <div style="margin-bottom:5px"> |
| <strong> |
| <a href="https://www.slideshare.net/slideshow/hug-meetup-impala-25-performance-overview/61689036" title="Hug meetup impala 2.5 performance overview" target="_blank">Hug meetup impala 2.5 performance |
| overview</a> |
| </strong> |
| from |
| <strong> |
| <a href="https://www.slideshare.net/MostafaMokhtar1" target="_blank">Mostafa Mokhtar</a> |
| </strong> |
| </div> |
| </div> |
| </article><hr> |
| <article class="h-entry post-text"><header><h3 class="p-name entry-title"><a href="posts/nested-types-in-impala/" class="u-url">Nested Types in Impala</a></h3> |
| <div class="metadata"> |
| <p class="byline author vcard"><span class="byline-name fn"> |
| <a href="authors/alex-behm/">Alex Behm</a> |
| <a href="authors/marcel-kornacker/">Marcel Kornacker</a> |
| <a href="authors/skye-wanderman-milne/">Skye Wanderman-Milne</a> |
| </span></p> |
| <p class="dateline"><a href="posts/nested-types-in-impala/" rel="bookmark"><time class="published dt-published" datetime="2015-03-24T23:00:00-07:00" title="2015-03-24 23:00">2015-03-24 23:00</time></a></p> |
| </div> |
| </header><div class="p-summary entry-summary"> |
| <p>This document discusses nested data types in Impala, including structs, maps, and arrays. It |
| provides an example schema using these types, describes Impala's SQL syntax extensions for querying |
| nested data, and discusses techniques for advanced querying capabilities like correlated subqueries. |
| The execution model materializes minimal nested structures in memory and uses new execution nodes to |
| handle nested data types.</p> |
| |
| <div style="margin-bottom:5px"> |
| <strong> |
| <a href="https://www.slideshare.net/slideshow/nested-types-in-impala-55344174/55344174" title="Nested Types in Impala" target="_blank">Nested Types in Impala</a> |
| </strong> |
| from |
| <strong> |
| <a href="https://www.slideshare.net/cloudera" target="_blank">Cloudera, Inc.</a> |
| </strong> |
| </div> |
| |
| <p><i>Presented in Impala Meetup, PA, March 24th, 2015</i></p> |
| </div> |
| </article><hr> |
| <article class="h-entry post-text"><header><h3 class="p-name entry-title"><a href="posts/impala-a-modern-open-source-sql-engine-for-hadoop/" class="u-url">Impala: A Modern, Open-Source SQL Engine for Hadoop</a></h3> |
| <div class="metadata"> |
| <p class="byline author vcard"><span class="byline-name fn"> |
| <a href="authors/impala-dev/">Impala Dev</a> |
| </span></p> |
| <p class="dateline"><a href="posts/impala-a-modern-open-source-sql-engine-for-hadoop/" rel="bookmark"><time class="published dt-published" datetime="2015-01-05T23:00:00-07:00" title="2015-01-05 23:00">2015-01-05 23:00</time></a></p> |
| </div> |
| </header><div class="p-summary entry-summary"> |
| <p> |
| <i>Presented at |
| <a href="https://www.cidrdb.org/cidr2015/program.html" target="_blank">The Conference on |
| Innovative Data Systems Research (CIDR) 2015</a>. |
| </i> |
| </p> |
| |
| <h4>ABSTRACT</h4> |
| <p>Cloudera Impala is a modern, open-source MPP SQL engine architected from the ground up for the |
| Hadoop data processing environment. Impala provides low latency and high concurrency for BI/analytic |
| read-mostly queries on Hadoop, not delivered by batch frameworks such as Apache Hive. This paper |
| presents Impala from a user’s perspective, gives an overview of its architecture and main components |
| and briefly demonstrates its superior performance compared against other popular SQL-on-Hadoop |
| systems.</p> |
| |
| <p> |
| <a href="https://www.cidrdb.org/cidr2015/Papers/CIDR15_Paper28.pdf" target="_blank">Paper</a> | |
| <a href="https://www.cidrdb.org/cidr2015/Slides/28_CIDR15_Slides_Paper28.pdf" target="_blank">Slides</a> |
| </p> |
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| </article> |
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