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><channel><title>Structured Data &#187; Performance</title> <atom:link href="http://structureddata.org/category/oracle/performance/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 – Set Processing vs Row Processing</title><link>http://structureddata.org/2010/07/20/the-core-performance-fundamentals-of-oracle-data-warehousing-%e2%80%93-set-processing-vs-row-processing/?utm_source=rss&amp;utm_medium=rss&amp;utm_campaign=the-core-performance-fundamentals-of-oracle-data-warehousing-%25e2%2580%2593-set-processing-vs-row-processing</link> <comments>http://structureddata.org/2010/07/20/the-core-performance-fundamentals-of-oracle-data-warehousing-%e2%80%93-set-processing-vs-row-processing/#comments</comments> <pubDate>Tue, 20 Jul 2010 09:00:38 +0000</pubDate> <dc:creator>Greg Rahn</dc:creator> <category><![CDATA[Data Warehousing]]></category> <category><![CDATA[Exadata]]></category> <category><![CDATA[Oracle]]></category> <category><![CDATA[Performance]]></category> <category><![CDATA[SQL Tuning]]></category> <category><![CDATA[VLDB]]></category> <category><![CDATA[Oracle Exadata]]></category> <category><![CDATA[row processing]]></category> <category><![CDATA[set processing]]></category><guid
isPermaLink="false">http://structureddata.org/?p=939</guid> <description><![CDATA[[back to Introduction] In over six years of doing data warehouse POCs and benchmarks for clients there is one area that I frequently see as problematic: &#8220;batch jobs&#8221;.  Most of the time these &#8220;batch jobs&#8221; take the form of some PL/SQL procedures and packages that generally perform some data load, transformation, processing or something similar.  The reason these are so problematic is that developers have hard-coded &#8220;slow&#8221; into them.  I&#8217;m generally certain these developers didn&#8217;t know they had done this when they coded their PL/SQL, but none the less it happened. So How Did &#8220;Slow&#8221; Get Hard-Coded Into My PL/SQL? Generally &#8220;slow&#8221; gets hard-coded into PL/SQL because the PL/SQL developer(s) took the business requirements and did a &#8220;literal translation&#8221; of each rule/requirement one at a time instead of looking at the &#8220;before picture&#8221; and the &#8220;after picture&#8221; and determining the most efficient way to make those data changes.  Many times this can surface as cursor based row-by-row processing, but it also can appear as PL/SQL just running a series of often poorly thought out SQL commands. Hard-Coded Slow Case Study The following is based on a true story. Only the facts names have been changed to protect the innocent. Here is [...]]]></description> <wfw:commentRss>http://structureddata.org/2010/07/20/the-core-performance-fundamentals-of-oracle-data-warehousing-%e2%80%93-set-processing-vs-row-processing/feed/</wfw:commentRss> <slash:comments>21</slash:comments> </item> <item><title>Oracle OpenWorld 2010: The Oracle Real-World Performance Group</title><link>http://structureddata.org/2010/07/13/oracle-openworld-2010-the-oracle-real-world-performance-group/?utm_source=rss&amp;utm_medium=rss&amp;utm_campaign=oracle-openworld-2010-the-oracle-real-world-performance-group</link> <comments>http://structureddata.org/2010/07/13/oracle-openworld-2010-the-oracle-real-world-performance-group/#comments</comments> <pubDate>Tue, 13 Jul 2010 14:01:53 +0000</pubDate> <dc:creator>Greg Rahn</dc:creator> <category><![CDATA[Exadata]]></category> <category><![CDATA[Oracle]]></category> <category><![CDATA[Performance]]></category> <category><![CDATA[Oracle Exadata]]></category> <category><![CDATA[Oracle OpenWorld 2010]]></category><guid
isPermaLink="false">http://structureddata.org/?p=958</guid> <description><![CDATA[Now that Oracle OpenWorld 2010 is just under 70 days away I thought I would take a moment to mention that the Oracle Real-World Performance Group will again be hosting three sessions.   This year I think we have a very exciting and informative lineup of sessions that are a must-attend for those wanting to see and hear Oracle Database performance insight right from Oracle&#8217;s own performance engineers.  Hope to see you there! And for those who are interested, there will likely be many discussions about the Oracle Database Machine and Oracle Exadata.  Very hot stuff! Session ID: S317164 (Monday 2:00PM﻿) Session Title: The Latest Real World Performance Challenges﻿ Session Abstract: Oracle&#8217;s Real-World Performance Group &#8212; the group that first presented at Oracle OpenWorld parallel query techniques with partitions, the index-less database, cardinality challenges with the optimizer, over-processed databases and connection storms &#8212; this year presents the performance issues before you experience them and how to plan for future projects with success. All topics discussed in this session come from the Real-World Performance Group&#8217;s observations and problem solving.﻿ Session ID: S317166﻿ (Monday 5:00PM﻿) Session Title: Real-World Performance Panel Session﻿ Session Abstract: This session is your chance, via written questions, to ask a [...]]]></description> <wfw:commentRss>http://structureddata.org/2010/07/13/oracle-openworld-2010-the-oracle-real-world-performance-group/feed/</wfw:commentRss> <slash:comments>1</slash:comments> </item> <item><title>Fully Exploiting Exadata</title><link>http://structureddata.org/2010/07/08/fully-exploiting-exadata/?utm_source=rss&amp;utm_medium=rss&amp;utm_campaign=fully-exploiting-exadata</link> <comments>http://structureddata.org/2010/07/08/fully-exploiting-exadata/#comments</comments> <pubDate>Thu, 08 Jul 2010 10:30:28 +0000</pubDate> <dc:creator>Greg Rahn</dc:creator> <category><![CDATA[Exadata]]></category> <category><![CDATA[Oracle]]></category> <category><![CDATA[Performance]]></category> <category><![CDATA[re-engineer]]></category><guid
isPermaLink="false">http://structureddata.org/?p=943</guid> <description><![CDATA[As a member of the Real-World Performance Group at Oracle I have participated in quite a number of Exadata POCs over the past two years. Often times those POCs are constrained in a number of ways: time, schema/app modifications, etc., because the objective is a proof, not a full blown migration. As a result there is often significant performance that is left on the table just waiting to be fully exploited &#8212; the kind of performance that really makes a database performance engineer excited &#8212; mind blowing performance. This includes, but is not limited to, data model changes, SQL query modifications and re-engineering batch processes. The reason these types of modifications get me so excited is that design decisions are often influenced by the then current deployment platform and with the Exadata powered Oracle Database Machine those restrictions are frequently lifted. You see, with Exadata the rules change, and so should your design decisions. Sure, you could just pluck-and-plop an existing Oracle data warehouse database onto an Oracle Database Machine and it would likely run much faster than it does on your current system, and you will be wowed, but you very well may shouting four letter expletives describing how [...]]]></description> <wfw:commentRss>http://structureddata.org/2010/07/08/fully-exploiting-exadata/feed/</wfw:commentRss> <slash:comments>7</slash:comments> </item> <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>The Core Performance Fundamentals Of Oracle Data Warehousing &#8211; Partitioning</title><link>http://structureddata.org/2010/01/25/the-core-performance-fundamentals-of-oracle-data-warehousing-partitioning/?utm_source=rss&amp;utm_medium=rss&amp;utm_campaign=the-core-performance-fundamentals-of-oracle-data-warehousing-partitioning</link> <comments>http://structureddata.org/2010/01/25/the-core-performance-fundamentals-of-oracle-data-warehousing-partitioning/#comments</comments> <pubDate>Mon, 25 Jan 2010 12:00:01 +0000</pubDate> <dc:creator>Greg Rahn</dc:creator> <category><![CDATA[Data Warehousing]]></category> <category><![CDATA[Oracle]]></category> <category><![CDATA[Performance]]></category> <category><![CDATA[VLDB]]></category> <category><![CDATA[managability]]></category> <category><![CDATA[partitioning]]></category><guid
isPermaLink="false">http://structureddata.org/?p=816</guid> <description><![CDATA[[back to Introduction] Partitioning is an essential performance feature for an Oracle data warehouse because partition elimination (or partition pruning) generally results in the elimination of a significant amount of table data to be scanned. This results in a need for less system resources and improved query performance. Someone once told me &#8220;the fastest I/O is the one that never happens.&#8221; This is precisely the reason that partitioning is a must for Oracle data warehouses &#8211; it&#8217;s a huge I/O eliminator. I frequently refer to partition elimination as the anti-index. An index is used to find a small amount data that is required; partitioning is used to eliminate vasts amounts of data that is not required. Main Uses For Partitioning I would classify the main reasons to use partitioning in your Oracle data warehouse into these four areas: Data Elimination Partition-Wise Joins Manageability (Partition Exchange Load, Local Indexes, etc.) Information Lifecycle Management (ILM) Partitioning Basics The most common partitioning design pattern found in Oracle data warehouses is to partition the fact tables by range (or interval) on the event date/time column. This allows for partition elimination of all the data not in the desired time window in queries. For example: If I have a [...]]]></description> <wfw:commentRss>http://structureddata.org/2010/01/25/the-core-performance-fundamentals-of-oracle-data-warehousing-partitioning/feed/</wfw:commentRss> <slash:comments>10</slash:comments> </item> <item><title>The Core Performance Fundamentals Of Oracle Data Warehousing &#8211; Table Compression</title><link>http://structureddata.org/2010/01/19/the-core-performance-fundamentals-of-oracle-data-warehousing-table-compression/?utm_source=rss&amp;utm_medium=rss&amp;utm_campaign=the-core-performance-fundamentals-of-oracle-data-warehousing-table-compression</link> <comments>http://structureddata.org/2010/01/19/the-core-performance-fundamentals-of-oracle-data-warehousing-table-compression/#comments</comments> <pubDate>Tue, 19 Jan 2010 12:00:55 +0000</pubDate> <dc:creator>Greg Rahn</dc:creator> <category><![CDATA[Data Warehousing]]></category> <category><![CDATA[Oracle]]></category> <category><![CDATA[Performance]]></category> <category><![CDATA[VLDB]]></category> <category><![CDATA[compression]]></category> <category><![CDATA[data warehouse]]></category><guid
isPermaLink="false">http://structureddata.org/?p=787</guid> <description><![CDATA[[back to Introduction] Editor&#8217;s note: This blog post does not cover Exadata Hybrid Columnar Compression. The first thing that comes to most people&#8217;s mind when database table compression is mentioned is the savings it yields in terms of disk space. While reducing the footprint of data on disk is relevant, I would argue it is the lesser of the benefits for data warehouses. Disk capacity is very cheap and generally plentiful, however, disk bandwidth (scan speed) is proportional to the number of spindles, no mater what the disk capacity and thus is more expensive. Table compression reduces the footprint on the disk drives that a given data set occupies so the amount of physical data that must be read off the disk platters is reduced when compared to the uncompressed version. For example, if 4000 GB of raw data can compress to 1000 GB, it can be read off the same disk drives 4X as fast because it is reading and transferring 1/4 of the data off the spindles (relative to the uncompressed size). Likewise, table compression allows for the database buffer cache to contain more data without having to increase the memory allocation because more rows can be stored [...]]]></description> <wfw:commentRss>http://structureddata.org/2010/01/19/the-core-performance-fundamentals-of-oracle-data-warehousing-table-compression/feed/</wfw:commentRss> <slash:comments>8</slash:comments> </item> <item><title>The Core Performance Fundamentals Of Oracle Data Warehousing – Balanced Hardware Configuration</title><link>http://structureddata.org/2009/12/22/the-core-performance-fundamentals-of-oracle-data-warehousing-balanced-hardware-configuration/?utm_source=rss&amp;utm_medium=rss&amp;utm_campaign=the-core-performance-fundamentals-of-oracle-data-warehousing-balanced-hardware-configuration</link> <comments>http://structureddata.org/2009/12/22/the-core-performance-fundamentals-of-oracle-data-warehousing-balanced-hardware-configuration/#comments</comments> <pubDate>Tue, 22 Dec 2009 22:00:54 +0000</pubDate> <dc:creator>Greg Rahn</dc:creator> <category><![CDATA[Data Warehousing]]></category> <category><![CDATA[Oracle]]></category> <category><![CDATA[Performance]]></category> <category><![CDATA[VLDB]]></category> <category><![CDATA[capacity planing]]></category> <category><![CDATA[data warehouse]]></category> <category><![CDATA[io bandwidth]]></category> <category><![CDATA[scan rate]]></category><guid
isPermaLink="false">http://structureddata.org/2009/12/13/the-core-performance-fundamentals-of-oracle-data-warehousing-balanced-hardware-configuration/</guid> <description><![CDATA[[back to Introduction] If you want to build a house that will stand the test of time, you need to build on a solid foundation. The same goes for architecting computer systems that run databases. If the underlying hardware is not sized appropriately it will likely lead to people blaming software. All too often I see data warehouse systems that are poorly architected for the given workload requirements. I frequently tell people, &#8220;you can&#8217;t squeeze blood from a turnip&#8220;, meaning if the hardware resources are not there for the software to use, how can you expect the software to scale? Undersizing data warehouse systems has become an epidemic with open platforms &#8211; platforms that let you run on any brand and configuration of hardware. This problem has been magnified over time as the size of databases have grown significantly, and generally outpacing the experience of those managing them. This has caused the &#8220;big three&#8221; database vendors to come up with suggested or recommended hardware configurations for their database platforms: Oracle: Optimized Warehouse Initiative Microsoft: SQL Server Fast Track Data Warehouse IBM: Balanced Configuration Unit (BCU)   Simply put, the reasoning behind those initiatives was to help customers architect systems that [...]]]></description> <wfw:commentRss>http://structureddata.org/2009/12/22/the-core-performance-fundamentals-of-oracle-data-warehousing-balanced-hardware-configuration/feed/</wfw:commentRss> <slash:comments>16</slash:comments> </item> <item><title>The Core Performance Fundamentals Of Oracle Data Warehousing &#8211; Introduction</title><link>http://structureddata.org/2009/12/14/the-core-performance-fundamentals-of-oracle-data-warehousing-introduction/?utm_source=rss&amp;utm_medium=rss&amp;utm_campaign=the-core-performance-fundamentals-of-oracle-data-warehousing-introduction</link> <comments>http://structureddata.org/2009/12/14/the-core-performance-fundamentals-of-oracle-data-warehousing-introduction/#comments</comments> <pubDate>Mon, 14 Dec 2009 16:00:20 +0000</pubDate> <dc:creator>Greg Rahn</dc:creator> <category><![CDATA[Data Warehousing]]></category> <category><![CDATA[Exadata]]></category> <category><![CDATA[Oracle]]></category> <category><![CDATA[Performance]]></category> <category><![CDATA[VLDB]]></category> <category><![CDATA[data warehouse]]></category><guid
isPermaLink="false">http://structureddata.org/?p=668</guid> <description><![CDATA[At the 2009 Oracle OpenWorld Unconference back in October I lead a chalk and talk session entitled The Core Performance Fundamentals Of Oracle Data Warehousing. Since this was a chalk and talk I spared the audience any powerpoint slides but I had several people request that make it into a presentation so they could share it with others. After some thought, I decided that a series of blog posts would probably be a better way to share this information, especially since I tend to use slides as a speaking outline, not a condensed version of a white paper. This will be the first of a series of posts discussing what I consider to be the key features and technologies behind well performing Oracle data warehouses. Introduction As an Oracle database performance engineer who has done numerous customer data warehouse benchmarks and POCs over the past 5+ years, I&#8217;ve seen many data warehouse systems that have been plagued with problems on nearly every DBMS commonly used in data warehousing. Interestingly enough, many of these systems were facing many of the same problems. I&#8217;ve compiled a list of topics that I consider to be key features and/or technologies for Oracle data warehouses: [...]]]></description> <wfw:commentRss>http://structureddata.org/2009/12/14/the-core-performance-fundamentals-of-oracle-data-warehousing-introduction/feed/</wfw:commentRss> <slash:comments>16</slash:comments> </item> <item><title>Top 10 Oracle 11gR2 New Features</title><link>http://structureddata.org/2009/09/09/top-10-oracle-11gr2-new-features/?utm_source=rss&amp;utm_medium=rss&amp;utm_campaign=top-10-oracle-11gr2-new-features</link> <comments>http://structureddata.org/2009/09/09/top-10-oracle-11gr2-new-features/#comments</comments> <pubDate>Wed, 09 Sep 2009 21:02:15 +0000</pubDate> <dc:creator>Greg Rahn</dc:creator> <category><![CDATA[11gR2]]></category> <category><![CDATA[Performance]]></category> <category><![CDATA[11.2]]></category> <category><![CDATA[database]]></category> <category><![CDATA[new features]]></category> <category><![CDATA[Oracle]]></category><guid
isPermaLink="false">http://structureddata.org/?p=664</guid> <description><![CDATA[In catching up on blog posts I see that Jonathan Lewis, Christian Antognini and Nuno Souto picked up on the deferred segment creation new feature in Oracle 11gR2. In keeping with the theme, I thought I&#8217;d put together the top 10 new features in Oracle Database 11g Release 2 (11.2) that I consider significant. Analytic Functions 2.0 Recursive WITH Clause Preprocessing Data for ORACLE_LOADER Access Driver in External Tables In-Memory Parallel Execution Auto Degree of Parallelism (Auto DOP) and Parallel Statement Queuing Significant Performance Improvement of MV On-Commit Fast Refresh Database Resource Manager Instance Caging ASM Intelligent Data Placement Database File System (DBFS) Hybrid Columnar Compression In future posts I&#8217;ll dive into some of these in more technical detail but for now I thought I&#8217;d throw my list out there to raise awareness of the things I am looking at as a database performance engineer.]]></description> <wfw:commentRss>http://structureddata.org/2009/09/09/top-10-oracle-11gr2-new-features/feed/</wfw:commentRss> <slash:comments>8</slash:comments> </item> <item><title>Oracle OpenWorld 2009: The Real-World Performance Group</title><link>http://structureddata.org/2009/07/20/oracle-openworld-2009-the-real-world-performance-group/?utm_source=rss&amp;utm_medium=rss&amp;utm_campaign=oracle-openworld-2009-the-real-world-performance-group</link> <comments>http://structureddata.org/2009/07/20/oracle-openworld-2009-the-real-world-performance-group/#comments</comments> <pubDate>Tue, 21 Jul 2009 04:25:00 +0000</pubDate> <dc:creator>Greg Rahn</dc:creator> <category><![CDATA[Exadata]]></category> <category><![CDATA[Oracle]]></category> <category><![CDATA[Performance]]></category> <category><![CDATA[VLDB]]></category> <category><![CDATA[openworld 2009]]></category> <category><![CDATA[oracle database machine]]></category> <category><![CDATA[Real-World Performance Group]]></category><guid
isPermaLink="false">http://structureddata.org/?p=647</guid> <description><![CDATA[Even though Oracle OpenWorld 2009 is a few months away, I thought I would take a moment to mention that the Oracle Real-World Performance Group will again be hosting three sessions. Hopefully you are no stranger to our Oracle database performance sessions and this year we have what I think will be a very exciting and enlightening session: The Terabyte Hour with the Real-World Performance Group. If you are the slightest bit interested in seeing just how fast the Oracle Database Machine really is and how it can devour flat files in no time, rip through and bend data at amazing speeds, this is the session for you. All the operations will be done live for you to observe. No smoke. No mirrors. Pure Exadata performance revealed.]]></description> <wfw:commentRss>http://structureddata.org/2009/07/20/oracle-openworld-2009-the-real-world-performance-group/feed/</wfw:commentRss> <slash:comments>6</slash:comments> </item> </channel> </rss>
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