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><channel><title>Structured Data &#187; Parallel Execution</title> <atom:link href="http://structureddata.org/category/oracle/parallel-execution/feed/" rel="self" type="application/rss+xml" /><link>http://structureddata.org</link> <description>Oracle Database Performance and Scalability Blog</description> <lastBuildDate>Mon, 06 Sep 2010 04:50:38 +0000</lastBuildDate> <language>en</language> <sy:updatePeriod>hourly</sy:updatePeriod> <sy:updateFrequency>1</sy:updateFrequency> <generator>http://wordpress.org/?v=3.0.1</generator> <item><title>The Core Performance Fundamentals Of Oracle Data Warehousing &#8211; Parallel Execution</title><link>http://structureddata.org/2010/04/19/the-core-performance-fundamentals-of-oracle-data-warehousing-parallel-execution/?utm_source=rss&amp;utm_medium=rss&amp;utm_campaign=the-core-performance-fundamentals-of-oracle-data-warehousing-parallel-execution</link> <comments>http://structureddata.org/2010/04/19/the-core-performance-fundamentals-of-oracle-data-warehousing-parallel-execution/#comments</comments> <pubDate>Mon, 19 Apr 2010 15:00:25 +0000</pubDate> <dc:creator>Greg Rahn</dc:creator> <category><![CDATA[Data Warehousing]]></category> <category><![CDATA[Oracle]]></category> <category><![CDATA[Parallel Execution]]></category> <category><![CDATA[Performance]]></category> <category><![CDATA[VLDB]]></category> <category><![CDATA[parallel query]]></category> <category><![CDATA[scalability]]></category><guid
isPermaLink="false">http://structureddata.org/?p=818</guid> <description><![CDATA[[back to Introduction] Leveraging Oracle&#8217;s Parallel Execution (PX) in your Oracle data warehouse is probably the most important feature/technology one can use to speed up operations on large data sets.  PX is not, however, &#8220;go fast&#8221; magic pixi dust for any old operation (if thats what you think, you probably don&#8217;t understand the parallel computing paradigm). With Oracle PX, a large task is broken up into smaller parts, sub-tasks if you will, and each sub-task is then worked on in parallel.  The goal of Oracle PX: divide and conquer.  This allows a significant amount of hardware resources to be engaged in solving a single problem and is what allows the Oracle database to scale up and out when working with large data sets. I though I&#8217;d touch on some basics and add my observations but this is by far not an exhaustive write up on Oracle&#8217;s Parallel Execution.  There is an entire chapter in the Oracle Database documentation on PX as well as several white papers.  I&#8217;ve listed all these in the Resources section at the bottom of this post.  Read them, but as always, feel free to post questions/comments here.  Discussion adds great value. A Basic Example of Parallel Execution [...]]]></description> <wfw:commentRss>http://structureddata.org/2010/04/19/the-core-performance-fundamentals-of-oracle-data-warehousing-parallel-execution/feed/</wfw:commentRss> <slash:comments>8</slash:comments> </item> <item><title>Oracle Parallel Execution: Interconnect Myths And Misunderstandings</title><link>http://structureddata.org/2009/07/06/oracle-parallel-execution-interconnect-myths-and-misunderstandings/?utm_source=rss&amp;utm_medium=rss&amp;utm_campaign=oracle-parallel-execution-interconnect-myths-and-misunderstandings</link> <comments>http://structureddata.org/2009/07/06/oracle-parallel-execution-interconnect-myths-and-misunderstandings/#comments</comments> <pubDate>Tue, 07 Jul 2009 00:00:17 +0000</pubDate> <dc:creator>Greg Rahn</dc:creator> <category><![CDATA[Data Warehousing]]></category> <category><![CDATA[Oracle]]></category> <category><![CDATA[Parallel Execution]]></category> <category><![CDATA[Performance]]></category> <category><![CDATA[VLDB]]></category> <category><![CDATA[interconnect traffic]]></category> <category><![CDATA[parallel query]]></category><guid
isPermaLink="false">http://structureddata.org/?p=602</guid> <description><![CDATA[A number of weeks back I had come across a paper/presentation by Riyaj Shamsudeen entitled Battle of the Nodes: RAC Performance Myths (avaiable here). As I was looking through it I saw one example that struck me as very odd (Myth #3 &#8211; Interconnect Performance) and I contacted him about it. After further review Riyaj commented that he had made a mistake in his analysis and offered up a new example. I thought I&#8217;d take the time to discuss this as parallel execution seems to be one of those areas where many misconceptions and misunderstandings exist. The Original Example I thought I&#8217;d quickly discuss why I questioned the initial example. The original query Riyaj cited is this one: select /*+ full(tl) parallel (tl,4) */ avg (n1), max (n1), avg (n2), max (n2), max (v1) from t_large tl; As you can see this is a very simple single table aggregation without a group by. The reason that I questioned the validity of this example in the context of interconnect performance is that the parallel execution servers (parallel query slaves) will each return exactly one row from the aggregation and then send that single row to the query coordinator (QC) which will [...]]]></description> <wfw:commentRss>http://structureddata.org/2009/07/06/oracle-parallel-execution-interconnect-myths-and-misunderstandings/feed/</wfw:commentRss> <slash:comments>15</slash:comments> </item> </channel> </rss>
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