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• Outbound HTTP performance tuning recommendations

  - by Richard Gadsden

  I'll detail my exact setup below, but general recommendations for a better web-browsing experience will be useful. A nice checklist of things to try would be great! I have 600 users on a single site with an 8MB leased line. I get a lot of moans about the performance of "the internet" (ie web-browsing). What recommendations do the community have for speeding things up without just throwing more bandwidth at it? I expect I will end up buying some more, but good management tips are always valuable. My setup is this: Cisco PIX (515E) firewall on the edge of the network. It's just doing some basic NAT, and opening up a handful of ports to various bastion hosts (aka DMZ servers). The DMZ is just a switch that the servers are plugged into. ISA 2006 Enterprise array (two servers) connecting DMZ to the internal LAN, with WebSense Web Security filtering HTTP traffic so users can't look at porn or waste bandwidth on YouTube during working hours. I've done a few things - I've just switched my internal DNS over to use root hints, which halved DNS query latency from 500ms to 250ms. Well worth doing. I'm trying to cache more aggressively, but so much more of the internet is AJAXy and doesn't cache very well as compared to five years ago. Plus the 70GB of cache which felt like a lot a few years ago really isn't any more. I'm getting about 45% cache hits by number of requests, but only about 22% by size, ie larger objects are less likely to be cached. Latency seems to be part of the problem. Is that attributable to the bandwidth problem, or are there things I can look at to try to reduce latency even on heavily-loaded bandwidth?

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• SQL SERVER – Speed Up! – Parallel Processes and Unparalleled Performance – TechEd 2012 India

  - by pinaldave

  TechEd India 2012 is just around the corner and I will be presenting there on two different session. SQL Server Performance Tuning is a very challenging subject that requires expertise in Database Administration and Database Development. I always have enjoyed talking about SQL Server Performance tuning subject. Just like doctors I like to call my every attempt to improve the performance of SQL Server queries and database server as a practice too. I have been working with SQL Server for more than 8 years and I believe that many of the performance tuning concept I have mastered. However, performance tuning is not a simple subject. However there are occasions when I feel stumped, there are occasional when I am not sure what should be the next step. When I face situation where I cannot figure things out easily, it makes me most happy because I clearly see this as a learning opportunity. I have been presenting in TechEd India for last three years. This is my fourth time opportunity to present a technical session on SQL Server. Just like every other year, I decided to present something different, something which I have spend years of learning. This time, I am going to present about parallel processes. It is widely believed that more the CPU will improve performance of the server. It is true in many cases. However, there are cases when limiting the CPU usages have improved overall health of the server. I will be presenting on the subject of Parallel Processes and its effects. I have spent more than a year working on this subject only. After working on various queries on multi-CPU systems I have personally learned few things. In coming TechEd session, I am going to share my experience with parallel processes and performance tuning. Session Details Title: Speed Up! – Parallel Processes and Unparalleled Performance (Add to Calendar) Abstract: “More CPU More Performance” – A  very common understanding is that usage of multiple CPUs can improve the performance of the query. To get maximum performance out of any query – one has to master various aspects of the parallel processes. In this deep dive session, we will explore this complex subject with a very simple interactive demo. An attendee will walk away with proper understanding of CX_PACKET wait types, MAXDOP, parallelism threshold and various other concepts. Date and Time: March 23, 2012, 12:15 to 13:15 Location: Hotel Lalit Ashok - Kumara Krupa High Grounds, Bengaluru – 560001, Karnataka, India. Add to Calendar Please submit your questions in the comments area and I will be for sure discussing them during my session. If I pick your question to discuss during my session, here is your gift I commit right now – SQL Server Interview Questions and Answers Book. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology Tagged: TechEd, TechEdIn

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• Performance profiler for a java application

  - by Nitin Garg

  I need to optimize a java application. It makes some 3rd party calls. I need some good tool to accurately measure the time taken by individual api calls. To give an idea of complexity- the application takes a data source file containing 10 lakh rows, and it takes around one hour to complete the processing. As a part of processing , it makes some 3rd party calls (including some network calls). I need to identify which calls are taking more time then others, and based on that, find out a way to optimize the application. Any suggestions would be appreciated.

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• SQL 2008 Database tuning advisor won’t start

  - by Andrew Hancox

  For some reason I can't get DTA to connect to my development machine. It connects to a remote DB just fine but when I point it to my dev machine I get an error saying: Failed to initialize MSDB database for tuning (exit code: -1073741819). I'm pretty sure it's not a permissions issue since I've used profiler to capture what it's doing and all of the commands it's run so far look fine and are being run under my account which is associated with the sysadmin role, when I run them in sql management studio they go through fine. I'm pretty convinced that the problem is related to creating the objects in MSDB that are used by DTA but I tried creating these manually (I found scripts on the web) and it just seems to push the problem along the line slightly. I'm going out of my mind - have even tried reinstalling SQL but that's not fixed it. I'm using SQL 2008 with SP1 (10.0.2531) on windows server 2008 (patched up to date). SAVE ME!!!!!

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• Exalytics and Oracle Business Intelligence Enterprise Edition (OBIEE) Partner Workshop

  - by mseika

  Workshop Description Oracle Fusion Middleware 11g is the #1 application infrastructure foundation. It enables enterprises to create and run agile and intelligent business applications and maximize IT efficiency by exploiting modern hardware and software architectures. Oracle Exalytics Business Intelligence Machine is the world’s first engineered system specifically designed to deliver high performance analysis, modeling and planning. Built using industry-standard hardware, market-leading business intelligence software and in-memory database technology, Oracle Exalytics is an optimized system that delivers unmatched speed, visualizations and scalability for Business Intelligence and Enterprise Performance Management applications. This FREE hands-on, partner workshop highlights both the hardware and software components that are engineered to work together to deliver Oracle Exalytics - an optimized version of the industry-leading Oracle TimesTen In-Memory Database with analytic extensions, a highly scalable Oracle server designed specifically for in-memory business intelligence, and Oracle’s proven Business Intelligence Foundation with enhanced visualization capabilities and performance optimizations. This workshop will provide hands-on experience with Oracle's latest engineered system. Topics covered will include TimesTen In-Memory Database and the new Summary Advisor for Exalytics, the technical details (including mobile features) of the latest release of visualization enhancements for OBI-EE, and technical updates on Essbase. After taking this course, you will be well prepared to architect, build, demo, and implement an end-to-end Exalytics solution. You will also be able to extend your current analytical and enterprise performance management application implementations with numerous Oracle technologies specifically enhanced to take advantage of the compute capacity and in-memory capabilities of Oracle Exalytics.If you are a BI or Data Warehouse Architect, developer or consultant, you don’t want to miss this 3-day workshop. Register Now! Presentations Exalytics Architectural Overview Upgrade and Lifecycle Management Times Ten for Exalytics Summary Advisor Utility Essbase and EPM System on Exalytics Dashboard and Analysis Interactions OBIEE 11.1.1.6 Features and Advanced Topics Lab OutlineThe labs showcase Oracle Exalytics core components and functionality and provide expertise of Oracle Business Intelligence 11.1.1.6 new features and updates from prior releases. The hands-on activities are based on an Oracle VirtualBox image with software and training samples pre-installed. Lab Environment Setup Creating and Working with Oracle TimesTen In-Memory Database Running Summary Advisor Utility Working with Exalytics Visualization Features – Dashboard and Analysis Interactions Audience Oracle Partners BI and EPM Application Developers and Implementers System Integrators and Solution Consultants Data Warehouse Developers Enterprise Architects Prerequisites Experience and understanding of OBIEE 11g is required Previous attendance of Oracle Business Intelligence Foundation Suite Workshop or BIEE 11gIntroduction Workshop is highly recommended Good understanding of data warehousing and data modeling for reporting and analysis purpose Strong experience with database technologies preferred Equipment RequirementsThis workshop requires attendees to provide their own laptops for this class.Attendee laptops must meet the following minimum hardware/software requirements: Hardware Minimum 8GB RAM 60 GB free space (includes staging) USB 2.0 port (at least one available) It is strongly recommended that you bring a mouse. You will be working in a development environment and using the mouse heavily. Software One of the following operating systems: 64-bit Windows host/laptop OS 64-bit host/laptop OS with a Windows VM (XP, Server, or Win 7, BIC2g, etc.) Internet Explorer 7.x/8.x or Firefox 3.5.x WINRAR or 7ziputility to unzip workshop files: Download-able from http://www.win-rar.com/download.html Download-able from http://www.7zip.com/ Oracle VirtualBox 4.0.2 or higher Downloadable from http://www.virtualbox.org/wiki/Downloads CPU virtualization mode needs to be enabled. We will provide guidance on the day of the workshop. Attendees will be given a VirtualBox image containing a pre-installed Oracle Exalytics environment. Schedule This workshop is 3 days. - Times vary by country!9:00am: Sign-in and technical setup 9:30am: Workshop starts 5:00pm: Workshop ends Oracle Exalytics and Business Intelligence (OBIEE) Workshop December 11-13, 2012: Oracle BVP, Birmingham, UK Register Here. Questions? Send email to: [email protected] Oracle Platform Technologies Enablement Services

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• Performance Tuning a High-Load Apache Server

  - by futureal

  I am looking to understand some server performance problems I am seeing with a (for us) heavily loaded web server. The environment is as follows: Debian Lenny (all stable packages + patched to security updates) Apache 2.2.9 PHP 5.2.6 Amazon EC2 large instance The behavior we're seeing is that the web typically feels responsive, but with a slight delay to begin handling a request -- sometimes a fraction of a second, sometimes 2-3 seconds in our peak usage times. The actual load on the server is being reported as very high -- often 10.xx or 20.xx as reported by top. Further, running other things on the server during these times (even vi) is very slow, so the load is definitely up there. Oddly enough Apache remains very responsive, other than that initial delay. We have Apache configured as follows, using prefork: StartServers 5 MinSpareServers 5 MaxSpareServers 10 MaxClients 150 MaxRequestsPerChild 0 And KeepAlive as: KeepAlive On MaxKeepAliveRequests 100 KeepAliveTimeout 5 Looking at the server-status page, even at these times of heavy load we are rarely hitting the client cap, usually serving between 80-100 requests and many of those in the keepalive state. That tells me to rule out the initial request slowness as "waiting for a handler" but I may be wrong. Amazon's CloudWatch monitoring tells me that even when our OS is reporting a load of 15, our instance CPU utilization is between 75-80%. Example output from top: top - 15:47:06 up 31 days, 1:38, 8 users, load average: 11.46, 7.10, 6.56 Tasks: 221 total, 28 running, 193 sleeping, 0 stopped, 0 zombie Cpu(s): 66.9%us, 22.1%sy, 0.0%ni, 2.6%id, 3.1%wa, 0.0%hi, 0.7%si, 4.5%st Mem: 7871900k total, 7850624k used, 21276k free, 68728k buffers Swap: 0k total, 0k used, 0k free, 3750664k cached The majority of the processes look like: 24720 www-data 15 0 202m 26m 4412 S 9 0.3 0:02.97 apache2 24530 www-data 15 0 212m 35m 4544 S 7 0.5 0:03.05 apache2 24846 www-data 15 0 209m 33m 4420 S 7 0.4 0:01.03 apache2 24083 www-data 15 0 211m 35m 4484 S 7 0.5 0:07.14 apache2 24615 www-data 15 0 212m 35m 4404 S 7 0.5 0:02.89 apache2 Example output from vmstat at the same time as the above: procs -----------memory---------- ---swap-- -----io---- -system-- ----cpu---- r b swpd free buff cache si so bi bo in cs us sy id wa 8 0 0 215084 68908 3774864 0 0 154 228 5 7 32 12 42 9 6 21 0 198948 68936 3775740 0 0 676 2363 4022 1047 56 16 9 15 23 0 0 169460 68936 3776356 0 0 432 1372 3762 835 76 21 0 0 23 1 0 140412 68936 3776648 0 0 280 0 3157 827 70 25 0 0 20 1 0 115892 68936 3776792 0 0 188 8 2802 532 68 24 0 0 6 1 0 133368 68936 3777780 0 0 752 71 3501 878 67 29 0 1 0 1 0 146656 68944 3778064 0 0 308 2052 3312 850 38 17 19 24 2 0 0 202104 68952 3778140 0 0 28 90 2617 700 44 13 33 5 9 0 0 188960 68956 3778200 0 0 8 0 2226 475 59 17 6 2 3 0 0 166364 68956 3778252 0 0 0 21 2288 386 65 19 1 0 And finally, output from Apache's server-status: Server uptime: 31 days 2 hours 18 minutes 31 seconds Total accesses: 60102946 - Total Traffic: 974.5 GB CPU Usage: u209.62 s75.19 cu0 cs0 - .0106% CPU load 22.4 requests/sec - 380.3 kB/second - 17.0 kB/request 107 requests currently being processed, 6 idle workers C.KKKW..KWWKKWKW.KKKCKK..KKK.KKKK.KK._WK.K.K.KKKKK.K.R.KK..C.C.K K.C.K..WK_K..KKW_CK.WK..W.KKKWKCKCKW.W_KKKKK.KKWKKKW._KKK.CKK... KK_KWKKKWKCKCWKK.KKKCK.......................................... ................................................................ From my limited experience I draw the following conclusions/questions: We may be allowing far too many KeepAlive requests I do see some time spent waiting for IO in the vmstat although not consistently and not a lot (I think?) so I am not sure this is a big concern or not, I am less experienced with vmstat Also in vmstat, I see in some iterations a number of processes waiting to be served, which is what I am attributing the initial page load delay on our web server to, possibly erroneously We serve a mixture of static content (75% or higher) and script content, and the script content is often fairly processor intensive, so finding the right balance between the two is important; long term we want to move statics elsewhere to optimize both servers but our software is not ready for that today I am happy to provide additional information if anybody has any ideas, the other note is that this is a high-availability production installation so I am wary of making tweak after tweak, and is why I haven't played with things like the KeepAlive value myself yet.

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• SQL SERVER – Improve Performance by Reducing IO – Creating Covered Index

  - by pinaldave

  This blog post is in the response of the T-SQL Tuesday #004: IO by Mike Walsh. The subject of this month is IO. Here is my quick blog post on how Cover Index can Improve Performance by Reducing IO. Let us kick off this post with disclaimers about Index. Index is a very complex subject and [...]

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• High Performance Storage Systems for SQL Server

  Rod Colledge turns his pessimistic mindset to storage systems, and describes the best way to configure the storage systems of SQL Servers for both performance and reliability. Even Rod gets a glint in his eye when he then goes on to describe the dazzling speed of solid-state storage, though he is quick to identify the risks.

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• Compute Scalars, Expressions and Execution Plan Performance

  - by Paul White

  The humble Compute Scalar is one of the least well-understood of the execution plan operators, and usually the last place people look for query performance problems. It often appears in execution plans with a very low (or even zero) cost, which goes some way to explaining why people ignore it. Some readers will already know that a Compute Scalar can contain a call to a user-defined function, and that any T-SQL function with a BEGIN…END block in its definition can have truly disastrous consequences...(read more)

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• Can frequent state changes decrease rendering performance?

  - by Miro

  Can frequent texture and shader binding decrease rendering performance? "Frequent" binding example: for object for material in object render part of object using that material "Low count" binding example: for material for object in material render part of object using that material I'm planning to use an octree later and with this "low count" method of rendering it can drastically increase memory consumption. So is it good idea?

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• Let the RAM improves performance

  - by user1717079

  I have a low profile machine but with a lot of fast RAM, 4 Gb, which is really an amount of memory that i probably will never use, not even an half, since i just use this machine for coding and browsing the web. The HDD is really slow and so the overall performance are bad when booting, caching or starting new program, I'm wondering if Ubuntu can provide some setting or utility to solve this situation and let my system rely more on the RAM usage.

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• Brendan Gregg's "Systems Performance: Enterprise and the Cloud"

  - by user12608550

  Long ago, the prerequisite UNIX performance book was Adrian Cockcroft's 1994 classic, Sun Performance and Tuning: Sparc & Solaris, later updated in 1998 as Java and the Internet. As Solaris evolved to include the invaluable DTrace observability features, new essential performance references have been published, such as Solaris Performance and Tools: DTrace and MDB Techniques for Solaris 10 and OpenSolaris (2006)  by McDougal, Mauro, and Gregg, and DTrace: Dynamic Tracing in Oracle Solaris, Mac OS X and FreeBSD (2011), also by Mauro and Gregg. Much has occurred in Solaris Land since those books appeared, notably Oracle's acquisition of Sun Microsystems in 2010 and the demise of the OpenSolaris community. But operating system technologies have continued to improve markedly in recent years, driven by stunning advances in multicore processor architecture, virtualization, and the massive scalability requirements of cloud computing. A new performance reference was needed, and I eagerly waited for something that thoroughly covered modern, distributed computing performance issues from the ground up. Well, there's a new classic now, authored yet again by Brendan Gregg, former Solaris kernel engineer at Sun and now Lead Performance Engineer at Joyent. Systems Performance: Enterprise and the Cloud is a modern, very comprehensive guide to general system performance principles and practices, as well as a highly detailed reference for specific UNIX and Linux observability tools used to examine and diagnose operating system behaviour.  It provides thorough definitions of terms, explains performance diagnostic Best Practices and "Worst Practices" (called "anti-methods"), and covers key observability tools including DTrace, SystemTap, and all the traditional UNIX utilities like vmstat, ps, iostat, and many others. The book focuses on operating system performance principles and expands on these with respect to Linux (Ubuntu, Fedora, and CentOS are cited), and to Solaris and its derivatives [1]; it is not directed at any one OS so it is extremely useful as a broad performance reference. The author goes beyond the intricacies of performance analysis and shows how to interpret and visualize statistical information gathered from the observability tools.  It's often difficult to extract understanding from voluminous rows of text output, and techniques are provided to assist with summarizing, visualizing, and interpreting the performance data. Gregg includes myriad useful references from the system performance literature, including a "Who's Who" of contributors to this great body of diagnostic tools and methods. This outstanding book should be required reading for UNIX and Linux system administrators as well as anyone charged with diagnosing OS performance issues.  Moreover, the book can easily serve as a textbook for a graduate level course in operating systems [2]. [1] Solaris 11, of course, and Joyent's SmartOS (developed from OpenSolaris) [2] Gregg has taught system performance seminars for many years; I have also taught such courses...this book would be perfect for the OS component of an advanced CS curriculum.

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• Increase Performance of VS 2010 by using a SSD

  - by System.Data

  After searching on the internet for performance improvements when using Visual Studio 2010 with a solid state hard drive, I heard a lot of different opinions. A lot of people said that there isn't really a benefit when using a SSD, but in contrast others said the exact opposite. I am a bit confused with the contrasting opinions and I cannot really make a decision whether buying a SSD would make a difference. What are your experiences with this issue and which SSD did you use?

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• Using DB_PARAMS to Tune the EP_LOAD_SALES Performance

  - by user702295

  The DB_PARAMS table can be used to tune the EP_LOAD_SALES performance.  The AWR report supplied shows 16 CPUs so I imaging that you can run with 8 or more parallel threads.  This can be done by setting the following DB_PARAMS parameters.  Note that most of parameter changes are just changing a 2 or 4 into an 8: DBHintEp_Load_SalesUseParallel = TRUE DBHintEp_Load_SalesUseParallelDML = TRUE DBHintEp_Load_SalesInsertErr = + parallel(@T_SRC_SALES@ 8) full(@T_SRC_SALES@) DBHintEp_Load_SalesInsertLd  = + parallel(@T_SRC_SALES@ 8) DBHintEp_Load_SalesMergeSALES_DATA = + parallel(@T_SRC_SALES_LD@ 8) full(@T_SRC_SALES_LD@) DBHintMdp_AddUpdateIs_Fictive0SD = + parallel(s 8 ) DBHintMdp_AddUpdateIs_Fictive2SD = + parallel(s 8 )

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• DB2 increase bufferpool size and compressed tables not equal better performance. Why?

  - by Mestika

  Hi, I’m working on tuning and increasing the performance of my IBM DB2 version 9.7 database. I’ve been searching around the net for the last couple of days and learned that if I created my tables in COMPRESS mode and created one more bufferpool and set both of them to access 1024mb, then the performance in my queries should increase because of the less I/Os to the disks. However, when I run my time analysis, the performance Decrease. I added the new additions to my regular database with the indexes I’ve used all the time. Each time I search google I come up with the statement that: Increased bufferpool size and several bufferpools AND a table compression SHOULD prove to get better performance. I’m very puzzled about the total unexpected result. Are there some tuning mechanisms I’ve forgot or does anyone have a explanation for this odd behavior? Sincerely Mestika

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• Performance Enhancement in Full-Text Search Query

  - by Calvin Sun

  Ever since its first release, we are continuing consolidating and developing InnoDB Full-Text Search feature. There is one recent improvement that worth blogging about. It is an effort with MySQL Optimizer team that simplifies some common queries’ Query Plans and dramatically shorted the query time. I will describe the issue, our solution and the end result by some performance numbers to demonstrate our efforts in continuing enhancement the Full-Text Search capability. The Issue: As we had discussed in previous Blogs, InnoDB implements Full-Text index as reversed auxiliary tables. The query once parsed will be reinterpreted into several queries into related auxiliary tables and then results are merged and consolidated to come up with the final result. So at the end of the query, we’ll have all matching records on hand, sorted by their ranking or by their Doc IDs. Unfortunately, MySQL’s optimizer and query processing had been initially designed for MyISAM Full-Text index, and sometimes did not fully utilize the complete result package from InnoDB. Here are a couple examples: Case 1: Query result ordered by Rank with only top N results: mysql> SELECT FTS_DOC_ID, MATCH (title, body) AGAINST ('database') AS SCORE FROM articles ORDER BY score DESC LIMIT 1; In this query, user tries to retrieve a single record with highest ranking. It should have a quick answer once we have all the matching documents on hand, especially if there are ranked. However, before this change, MySQL would almost retrieve rankings for almost every row in the table, sort them and them come with the top rank result. This whole retrieve and sort is quite unnecessary given the InnoDB already have the answer. In a real life case, user could have millions of rows, so in the old scheme, it would retrieve millions of rows' ranking and sort them, even if our FTS already found there are two 3 matched rows. Apparently, the million ranking retrieve is done in vain. In above case, it should just ask for 3 matched rows' ranking, all other rows' ranking are 0. If it want the top ranking, then it can just get the first record from our already sorted result. Case 2: Select Count(*) on matching records: mysql> SELECT COUNT(*) FROM articles WHERE MATCH (title,body) AGAINST ('database' IN NATURAL LANGUAGE MODE); In this case, InnoDB search can find matching rows quickly and will have all matching rows. However, before our change, in the old scheme, every row in the table was requested by MySQL one by one, just to check whether its ranking is larger than 0, and later comes up a count. In fact, there is no need for MySQL to fetch all rows, instead InnoDB already had all the matching records. The only thing need is to call an InnoDB API to retrieve the count The difference can be huge. Following query output shows how big the difference can be: mysql> select count(*) from searchindex_inno where match(si_title, si_text) against ('people')  +----------+ | count(*) | +----------+ | 666877 | +----------+ 1 row in set (16 min 17.37 sec) So the query took almost 16 minutes. Let’s see how long the InnoDB can come up the result. In InnoDB, you can obtain extra diagnostic printout by turning on “innodb_ft_enable_diag_print”, this will print out extra query info: Error log: keynr=2, 'people' NL search Total docs: 10954826 Total words: 0 UNION: Searching: 'people' Processing time: 2 secs: row(s) 666877: error: 10 ft_init() ft_init_ext() keynr=2, 'people' NL search Total docs: 10954826 Total words: 0 UNION: Searching: 'people' Processing time: 3 secs: row(s) 666877: error: 10 Output shows it only took InnoDB only 3 seconds to get the result, while the whole query took 16 minutes to finish. So large amount of time has been wasted on the un-needed row fetching. The Solution: The solution is obvious. MySQL can skip some of its steps, optimize its plan and obtain useful information directly from InnoDB. Some of savings from doing this include: 1) Avoid redundant sorting. Since InnoDB already sorted the result according to ranking. MySQL Query Processing layer does not need to sort to get top matching results. 2) Avoid row by row fetching to get the matching count. InnoDB provides all the matching records. All those not in the result list should all have ranking of 0, and no need to be retrieved. And InnoDB has a count of total matching records on hand. No need to recount. 3) Covered index scan. InnoDB results always contains the matching records' Document ID and their ranking. So if only the Document ID and ranking is needed, there is no need to go to user table to fetch the record itself. 4) Narrow the search result early, reduce the user table access. If the user wants to get top N matching records, we do not need to fetch all matching records from user table. We should be able to first select TOP N matching DOC IDs, and then only fetch corresponding records with these Doc IDs. Performance Results and comparison with MyISAM The result by this change is very obvious. I includes six testing result performed by Alexander Rubin just to demonstrate how fast the InnoDB query now becomes when comparing MyISAM Full-Text Search. These tests are base on the English Wikipedia data of 5.4 Million rows and approximately 16G table. The test was performed on a machine with 1 CPU Dual Core, SSD drive, 8G of RAM and InnoDB_buffer_pool is set to 8 GB. Table 1: SELECT with LIMIT CLAUSE mysql> SELECT si_title, match(si_title, si_text) against('family') as rel FROM si WHERE match(si_title, si_text) against('family') ORDER BY rel desc LIMIT 10; InnoDB MyISAM Times Faster Time for the query 1.63 sec 3 min 26.31 sec 127 You can see for this particular query (retrieve top 10 records), InnoDB Full-Text Search is now approximately 127 times faster than MyISAM. Table 2: SELECT COUNT QUERY mysql>select count(*) from si where match(si_title, si_text) against('family‘); +----------+ | count(*) | +----------+ | 293955 | +----------+ InnoDB MyISAM Times Faster Time for the query 1.35 sec 28 min 59.59 sec 1289 In this particular case, where there are 293k matching results, InnoDB took only 1.35 second to get all of them, while take MyISAM almost half an hour, that is about 1289 times faster!. Table 3: SELECT ID with ORDER BY and LIMIT CLAUSE for selected terms mysql> SELECT <ID>, match(si_title, si_text) against(<TERM>) as rel FROM si_<TB> WHERE match(si_title, si_text) against (<TERM>) ORDER BY rel desc LIMIT 10; Term InnoDB (time to execute) MyISAM(time to execute) Times Faster family 0.5 sec 5.05 sec 10.1 family film 0.95 sec 25.39 sec 26.7 Pizza restaurant orange county California 0.93 sec 32.03 sec 34.4 President united states of America 2.5 sec 36.98 sec 14.8 Table 4: SELECT title and text with ORDER BY and LIMIT CLAUSE for selected terms mysql> SELECT <ID>, si_title, si_text, ... as rel FROM si_<TB> WHERE match(si_title, si_text) against (<TERM>) ORDER BY rel desc LIMIT 10; Term InnoDB (time to execute) MyISAM(time to execute) Times Faster family 0.61 sec 41.65 sec 68.3 family film 1.15 sec 47.17 sec 41.0 Pizza restaurant orange county california 1.03 sec 48.2 sec 46.8 President united states of america 2.49 sec 44.61 sec 17.9 Table 5: SELECT ID with ORDER BY and LIMIT CLAUSE for selected terms mysql> SELECT <ID>, match(si_title, si_text) against(<TERM>) as rel  FROM si_<TB> WHERE match(si_title, si_text) against (<TERM>) ORDER BY rel desc LIMIT 10; Term InnoDB (time to execute) MyISAM(time to execute) Times Faster family 0.5 sec 5.05 sec 10.1 family film 0.95 sec 25.39 sec 26.7 Pizza restaurant orange county califormia 0.93 sec 32.03 sec 34.4 President united states of america 2.5 sec 36.98 sec 14.8 Table 6: SELECT COUNT(*) mysql> SELECT count(*) FROM si_<TB> WHERE match(si_title, si_text) against (<TERM>) LIMIT 10; Term InnoDB (time to execute) MyISAM(time to execute) Times Faster family 0.47 sec 82 sec 174.5 family film 0.83 sec 131 sec 157.8 Pizza restaurant orange county califormia 0.74 sec 106 sec 143.2 President united states of america 1.96 sec 220 sec 112.2  Again, table 3 to table 6 all showing InnoDB consistently outperform MyISAM in these queries by a large margin. It becomes obvious the InnoDB has great advantage over MyISAM in handling large data search. Summary: These results demonstrate the great performance we could achieve by making MySQL optimizer and InnoDB Full-Text Search more tightly coupled. I think there are still many cases that InnoDB’s result info have not been fully taken advantage of, which means we still have great room to improve. And we will continuously explore the area, and get more dramatic results for InnoDB full-text searches. Jimmy Yang, September 29, 2012

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• OBIEE 11g 11.1.1.6.11 is Available For BI Enterprise and Exalytics

  - by p.anda

  (in via Ian & Martin) OBIEE 11g 11.1.1.6.11 is Available For BI Enterprise and Exalytics The Business Intelligence Enterprise Edition 11.1.1.6.11 patch set has been released and is available to download from My Oracle Support (https://support.oracle.com).Per the patch readme: This patch set is available for all customers who are using Oracle Business Intelligence Enterprise Edition 11.1.1.6.0, 11.1.1.6.1, 11.1.1.6.2, 11.1.1.6.2 BP1, 11.1.1.6.4, 11.1.1.6.5, 11.1.1.6.6, 11.1.1.6.7, 11.1.1.6.8, 11.1.1.6.9 and 11.1.1.6.10. Oracle Exalytics customers must only install this Oracle Business Intelligence patch set if it is certified for the specific Oracle Exalytics patch or patch set update that they are applying. For more information see Oracle Fusion Middleware Installation and Administration Guide for Oracle Exalytics In-Memory Machine and the Oracle Exalytics certification information. The Oracle Business Intelligence 11.1.1.6.11 patch set is comprised of the following patches: Patch 16747681 - 1 of 7 Oracle Business Intelligence Installer (BIINST)Patch 16747684 - 2 of 7 Oracle Real Time Decisions (RTD)Patch 16747692 - 3 of 7 Oracle Business Intelligence Publisher (BIP)Patch 16747699 - 4 of 7 Oracle Business Intelligence ADF Components (BIADFCOMPS)Patch 16747703 - 5 of 7 Enterprise Performance Management Components Installed from BI Installer 11.1.1.6.x (BIFNDNEPM)Patch 16717325 - 6 of 7 Oracle Business Intelligence: (OBIEE)Patch 16747708 - 7 of 7 Oracle Business Intelligence Platform Client Installers and MapViewer Note: - The Readme files for the above patches describe the bugs fixed in each patch, and any known bugs with the patch.- This patch is cumulative, and therefore, contains all of the fixes included in the earlier 11.1.1.6.2, 11.1.1.6.4, 11.1.1.6.5, 11.1.1.6.6, 11.1.1.6.7, 11.1.1.6.8, 11.1.1.6.9 and 11.1.1.6.10 patch sets.- However, lists of fixes from included patch sets need to be looked up in the respective patches' readme files, and are not included in the above patches' readme files.- The instructions to apply the above patches are identical, and are contained in the readme file for patch 16747681.- Please bear in mind, that the readme states to apply patch 13952743 for JDeveloper, too.

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• The November OBIEE 11.1.1.6.6 Bundle Patch has been released

  - by inowodwo

  The November Oracle Business Intelligence Enterprise Edition - OBIEE 11.1.1.6.6 Bundle Patch is now available for download from My Oracle Support For OBIEE on 11.1.1.6.0, the plan is to run a monthly bundle patch 11.1.1.6.6 bundle patch includes 67 bug fixes. 11.1.1.6.6 bundle patch is cumulative, so it includes everything in 11.1.1.6.1, 11.1.1.6.2, 11.1.1.6.2BP1, 11.1.1.6.4 and 11.1.1.6.5. Please note that this release is only recommended for BI customers i.e. not customers on Fusion Apps Bundled Patch Details (1 of 7) Oracle Business Intelligence Installer. (patch number 15844023) (2 of 7) Oracle Real Time Decisions. (patch number 15844066) (3 of 7) Oracle Business Intelligence Publisher (patch number 14800665) (4 of 7) Oracle Business Intelligence ADF Components. (patch number 15843961) (5 of 7) Enterprise Performance Management Components Installed from BI Installer 11.1.1.6.x (patch number 15844096) (6 of 7) Oracle Business Intelligence (patch number 14791926) (7 of 7) Oracle Business Intelligence Platform Client Installers and MapViewer (patch number 15839347) 11.1.1.6.6 bundle patch is available for the supported platforms : Microsoft Windows (32-bit) Linux x86 (32-bit) Microsoft Windows x64 (64-bit) Linux x86-64 (64-bit) Oracle Solaris on SPARC (64-bit) Oracle Solaris on x86-64 (64-bit) IBM AIX PPC (64-bit) HPUX- IA (64-bit)

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• OBIEE 10g premier support ends Mid 2013

  - by THE

  To give all OBIEE users a fair warning ahead of time. Please be aware that the Premier Support product lifecycle for Oracle Business Intelligence Enterprise Edition and Oracle Business Intelligence Publisher 10.1.3.4.x is ending in July 2013 as of the  lifetime Support policy. Oracle Business Intelligence Enterprise Edition and Oracle Business Intelligence Publisher 10.1.3.4.x will be in Sustaining Support phase. "Sustaining Support" does NOT include: New program updates, fixes, security alerts, and critical patch updates New tax, legal and regulatory updates New upgrade scripts Certification with new third party products/versions 24 hour commitment and response guidelines for Severity 1 service requests as defined in the Severity Level section in the Oracle Technical Support Policies document linked below. We are encouraging you to move to OBIEE 11gR1. For more details please see the following documents on My Oracle Support ( https://support.oracle.com):"Premier Support Ends Dec 31 2011 for Oracle Fusion Middleware 10g 10.1.2 & 10.1.4" (  Doc ID 1290974.1)

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• OBIEE Capacity Planning

  - by THE

  I can not even recall how many times I was asked by a customer what size the machine should be bought to run our Software. Unfortunately Tech Support is not even the right address to answer that question, as a purchase decision is closely tied to the answer. Hence, Tech Support has been limited to the answer: "The biggest machine you can afford" . Many Customers were unhappy with that and have tried to get us to be more precise and that causes a lot of explanation and lengthy discussion. In the end no one is wiser or happier.  Therefore I am happy to report that at least for OBIEE the decision has just been made a whole lot easier. Have a look at the note Oracle BI EE 11g Architectural Deployment: Capacity Planning (Doc ID 1323646.1) The document attached to that note gives you a good overview for teh sizing of the machines that Oracle recommends to run OBIEE (be it a small installation or a bigger distributed installation) If you have any more questions about this topic and what machines we recommend, then get in contact with  Oracle Consulting or speak to your sales representative.

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• Merge sort versus quick sort performance

  - by Giorgio

  I have implemented merge sort and quick sort using C (GCC 4.4.3 on Ubuntu 10.04 running on a 4 GB RAM laptop with an Intel DUO CPU at 2GHz) and I wanted to compare the performance of the two algorithms. The prototypes of the sorting functions are: void merge_sort(const char **lines, int start, int end); void quick_sort(const char **lines, int start, int end); i.e. both take an array of pointers to strings and sort the elements with index i : start <= i <= end. I have produced some files containing random strings with length on average 4.5 characters. The test files range from 100 lines to 10000000 lines. I was a bit surprised by the results because, even though I know that merge sort has complexity O(n log(n)) while quick sort is O(n^2), I have often read that on average quick sort should be as fast as merge sort. However, my results are the following. Up to 10000 strings, both algorithms perform equally well. For 10000 strings, both require about 0.007 seconds. For 100000 strings, merge sort is slightly faster with 0.095 s against 0.121 s. For 1000000 strings merge sort takes 1.287 s against 5.233 s of quick sort. For 5000000 strings merge sort takes 7.582 s against 118.240 s of quick sort. For 10000000 strings merge sort takes 16.305 s against 1202.918 s of quick sort. So my question is: are my results as expected, meaning that quick sort is comparable in speed to merge sort for small inputs but, as the size of the input data grows, the fact that its complexity is quadratic will become evident? Here is a sketch of what I did. In the merge sort implementation, the partitioning consists in calling merge sort recursively, i.e. merge_sort(lines, start, (start + end) / 2); merge_sort(lines, 1 + (start + end) / 2, end); Merging of the two sorted sub-array is performed by reading the data from the array lines and writing it to a global temporary array of pointers (this global array is allocate only once). After each merge the pointers are copied back to the original array. So the strings are stored once but I need twice as much memory for the pointers. For quick sort, the partition function chooses the last element of the array to sort as the pivot and scans the previous elements in one loop. After it has produced a partition of the type start ... {elements <= pivot} ... pivotIndex ... {elements > pivot} ... end it calls itself recursively: quick_sort(lines, start, pivotIndex - 1); quick_sort(lines, pivotIndex + 1, end); Note that this quick sort implementation sorts the array in-place and does not require additional memory, therefore it is more memory efficient than the merge sort implementation. So my question is: is there a better way to implement quick sort that is worthwhile trying out? If I improve the quick sort implementation and perform more tests on different data sets (computing the average of the running times on different data sets) can I expect a better performance of quick sort wrt merge sort? EDIT Thank you for your answers. My implementation is in-place and is based on the pseudo-code I have found on wikipedia in Section In-place version: function partition(array, 'left', 'right', 'pivotIndex') where I choose the last element in the range to be sorted as a pivot, i.e. pivotIndex := right. I have checked the code over and over again and it seems correct to me. In order to rule out the case that I am using the wrong implementation I have uploaded the source code on github (in case you would like to take a look at it). Your answers seem to suggest that I am using the wrong test data. I will look into it and try out different test data sets. I will report as soon as I have some results.

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• SQL SERVER – Maximize Database Performance with DB Optimizer – SQL in Sixty Seconds #054

  - by Pinal Dave

  Performance tuning is an interesting concept and everybody evaluates it differently. Every developer and DBA have different opinion about how one can do performance tuning. I personally believe performance tuning is a three step process Understanding the Query Identifying the Bottleneck Implementing the Fix While, we are working with large database application and it suddenly starts to slow down. We are all under stress about how we can get back the database back to normal speed. Most of the time we do not have enough time to do deep analysis of what is going wrong as well what will fix the problem. Our primary goal at that time is to just fix the database problem as fast as we can. However, here is one very important thing which we need to keep in our mind is that when we do quick fix, it should not create any further issue with other parts of the system. When time is essence and we want to do deep analysis of our system to give us the best solution we often tend to make mistakes. Sometimes we make mistakes as we do not have proper time to analysis the entire system. Here is what I do when I face such a situation – I take the help of DB Optimizer. It is a fantastic tool and does superlative performance tuning of the system. Everytime when I talk about performance tuning tool, the initial reaction of the people is that they do not want to try this as they believe it requires lots of the learning of the tool before they use it. It is absolutely not true with the case of the DB optimizer. It is a very easy to use and self intuitive tool. Once can get going with the product, in no time. Here is a quick video I have build where I demonstrate how we can identify what index is missing for query and how we can quickly create the index. Entire three steps of the query tuning are completed in less than 60 seconds. If you are into performance tuning and query optimization you should download DB Optimizer and give it a go. Let us see the same concept in following SQL in Sixty Seconds Video: You can Download DB Optimizer and reproduce the same Sixty Seconds experience. Related Tips in SQL in Sixty Seconds: Performance Tuning – Part 1 of 2 – Getting Started and Configuration Performance Tuning – Part 2 of 2 – Analysis, Detection, Tuning and Optimizing What would you like to see in the next SQL in Sixty Seconds video? Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Database, Pinal Dave, PostADay, SQL, SQL Authority, SQL in Sixty Seconds, SQL Interview Questions and Answers, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, T SQL, Technology, Video Tagged: Identity

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• What's the largest (most complex) PHP algorithm ever implemented in a single monolithic PHP script?

  - by Alex R

  I'm working on a tool which converts PHP code to Scala. As one of the finishing touches, I'm in need of a really good (er, somewhat biased) benchmark. By dumb luck my first benchmark attempt was with some code which uses bcmath extensively, which unfortunately is 1000x slower in Java, making the Scala code 22x slower overall than the original PHP. So I'm looking for some meaningful PHP benchmark with the following characteristics: The source needs to be in a single file. I need it to be simple to setup - no databases, hard-to-find input files, etc. Simple text input and output preferred. It should not use features that are slow in Java (BigInteger, trigonometric functions, etc). It should not use exoteric or dynamic PHP functions (e.g. no "eval" or "variable vars"). It should not over-rely on built-in libraries, e.g. MD5, crypt, etc. It should not be I/O bound. A CPU-bound memory-hungry algorithm is preferred. Basically, intensive OO operations, integer and string manipulation, recursion, etc would be great. Thanks

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• Is there a PHP benchmark that meets these specific criteria? [closed]

  - by Alex R

  I'm working on a tool which converts PHP code to Scala. As one of the finishing touches, I'm in need of a really good (er, somewhat biased) benchmark. By dumb luck my first benchmark attempt was with some code which uses bcmath extensively, which unfortunately is 1000x slower in Java, making the Scala code 22x slower overall than the original PHP. So I'm looking for some meaningful PHP benchmark with the following characteristics: The PHP source needs to be in a single file. It should solve a real-world problem. No silly looping over empty methods etc. I need it to be simple to setup - no databases, hard-to-find input files, etc. Simple text input and output preferred. It should not use features that are slow in Java (BigInteger, trigonometric functions, etc). It should not use exoteric or dynamic PHP functions (e.g. no "eval" or "variable vars"). It should not over-rely on built-in libraries, e.g. MD5, crypt, etc. It should not be I/O bound. A CPU-bound memory-hungry algorithm is preferred. Basically, intensive OO operations, integer and string manipulation, recursion, etc would be great. Thanks

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• ATI proprietary driver performance?

  - by Axel

  I'm about to (at least, want to..) buy a laptop with an ATI Radeon HD 4250, and I haven't a good opinion on ATI's drivers. How is the actual performance of the open/proprietary driver (currently I have nVidia, and I'm very satisfied)? The intended use for the laptop is: watching videos, programming in Java/PHP/maybe Qt... but, I like to know if Compiz runs well. Yes, I'm a hardcore (?) programmer that uses Compiz. :P Someone has this GPU? Experiences? Thoughts? Thanks! :D

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