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• Enterprise Manager 12c: New DSS Demos Available

  - by Javier Puerta

  Enterprise Manager Cloud Control 12c Application Replay Demo Now Available! User Experience Monitoring with Enterprise Manager Cloud Control 12c and Real User Experience Insight 12R1 Now Available! Oracle Enterprise Manager Cloud Control 12c: Database Management Packs demo upgrade     Enterprise Manager Cloud Control 12c Application Replay Demo Now Available! We are pleased to announce the availability of the Oracle Application Replay demo that showcases some of the key capabilities of performing realistic, production scale testing of your web and packaged Oracle applications. This demo specifically focuses on capturing production web traffic from an E-Business Suite application and replaying the captured workload on a test E-Business Suite application to assess the impact of an application infrastructure change on the workload. The target audiences are application developers, quality assurance teams, IT managers and production control staff that deal in day-to-day change management activities and trouble shooting of production environments. Demo Highlights: Enterprise Manager 12c workflows for capturing application workload Seamless integration of Application Replay with Real User Experience Insight for application workload capture Enterprise Manager 12c centralized workflows for replaying captured application workloads in a test environment Demonstrates how to minimize risk when deploying a complex EBusiness Suite application infrastructure change. Rich reporting capability for performance analysis and problem detection User Experience Monitoring with Enterprise Manager Cloud Control 12c and Real User Experience Insight 12R1 Now Available! We are pleased to announce the availability of the Oracle Real User Experience Insight demo that showcases some of the key capabilities of user experience monitoring. This demo specifically focuses on business reporting, integrated performance diagnostics, tracking of customer journey’s through RUEI’s userflow tracking capabilities and it’s Key Performance Indicators tracking and configuration. Demo Highlights: Application-centric dashboard Integration with Oracle Enterprise Manager 12c – JVMD, ADP and BTM Session diagnostics and user session replay Monitoring through “Key Performance Indicators” (KPI) --- create alerts/incidents FUSION Application centric dashboards & integrated BI Oracle Enterprise Manager Cloud Control 12c: Database Management Packs demo upgrade DSS is pleased to announce an upgrade to the Oracle Enterprise Manager Cloud Control 12c: Database Management Packs demo. While retaining the content from the initial release of the demo—Diagnostic and Tuning Packs, Test Data Management and Data Masking, and Real Application Testing—the demo now includes a new Data Masking for Real Application Testing scenario. Demo Features: Diagnostic and Tuning Packs SQL Performance Analyzer Database Replay Data Masking Masking Real Application Testing workloads Testing pending Optimizer statistics Test Data Management

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• SQL Saturday 194 - Exeter

  - by Dave Ballantyne

  Many kudos goes to Jonathan and Annette Allen and the others on the team for confirming SQL Saturday 194 in Exeter on the 8th and 9th of March.  The event home page is here http://www.sqlsaturday.com/194/eventhome.aspx and I delighted that myself and Dave Morrison will be presenting a full day pre-con on the 8th on favourite subjects “TSQL and Internals”. Here is the full abstract : TSQL and internals - When faced with performance issues there are many lines of attack. Tuning the engine itself can get you so far, however for maximum effect you need to understand how the engine and how it translates SQL statements into performable actions. This is not a simple task, it is a massive task to deal with a multi-table join and the number of permutations can be immense. To back up this knowledge, we can create better performing TSQL and understand the impact that is has upon the engine and recognize the pitfalls and gotcha’s that exist in SQLServer. Ultimately, there is no ‘best way’ to perform a single task only many variations of ‘it depends’ , but now we can pick the most appropriate option for the required dataload. Over the years, there have been many myths and misconceptions have grown around the product, some have basis in older versions and some are just wrong. Continuing to build on the knowledge given so far these issue will be explored and broken down and proved or disproved. Finally we will look to the future and explore SQL Server 2012 and the new functionality that that brings and some of the common uses that we will be able to address. After completion of this days pre-con, attendees will have a more complete knowledge of execution plans, and how they relate to the physical and logical actions that SQLServer will be executing on their behalf. The attendees will also have a more rounded and fuller knowledge of TSQL and the implications of incorrectly defining a query. Dave is a fountain of knowledge on execution plans and optimizer internals and ,though i may flatter myself, I’m no shrinking violet when it comes to TSQL and such matters.  I hope that if you cant join us, then there are other pre-cons available from other experts in their fields that may ‘float you boat’ too.  The pre-con page is http://sqlsouthwest.co.uk/SQLSaturday_precon.htm Also, excitingly, this pre-con day is sponsored by Fusion-IO which is a great boon for the day. If you want a more of this then i am offering a 2 day TSQL course starting on the 19th of March. More details on this are available here

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• PhpMyAdmin Missing parameter:

  - by Ali

  Everything was working fine until this moment I want to create a new database and I'm receiving this error db_create.php: Missing parameter: new_db (FAQ 2.8) Also when I was trying to export my database I also receive the following error export.php: Missing parameter: what (FAQ 2.8) export.php: Missing parameter: export_type (FAQ 2.8) When I looked it FAQ 2.8 from the suggested link in PHPMYADMIN 2.8 I get "Missing parameters" errors, what can I do? Here are a few points to check: In config.inc.php, try to leave the $cfg['PmaAbsoluteUri'] directive empty. See also FAQ 4.7. Maybe you have a broken PHP installation or you need to upgrade your Zend Optimizer. See http://bugs.php.net/bug.php?id=31134. If you are using Hardened PHP with the ini directive varfilter.max_request_variables set to the default (200) or another low value, you could get this error if your table has a high number of columns. Adjust this setting accordingly. (Thanks to Klaus Dorninger for the hint). In the php.ini directive arg_separator.input, a value of ";" will cause this error. Replace it with "&;". If you are using Hardened-PHP, you might want to increase request limits. The directory specified in the php.ini directive session.save_path does not exist or is read-only. I did tried with php.ini to make sure that I've session.save_path = "/tmp" I'm using Mac Xserver and running with MAMP I did tried everything to restart my server and nothing help. Please if anyone help me to give me some suggestion. Apologize if I post in a wrong place.

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• eAccelerator Issue - Cache Directory Empty.

  - by Tom

  Hi all, Hoping someone can give me a hand with this. I've recently installated eAccelerator 0.9.6.1 - On a CentOS LAMP server. Had it working fine, using the /tmp/accelerator as the cache directory. php.ini set up: zend_extension="/usr/local/lib/php/extensions/no-debug-non-zts-20060613/eaccelerator.so" eaccelerator.shm_size="200" eaccelerator.cache_dir="/var/cache/eaccelerator" eaccelerator.enable="1" eaccelerator.optimizer="1" eaccelerator.check_mtime="1" eaccelerator.debug="0" eaccelerator.filter="" eaccelerator.shm_max="0" eaccelerator.shm_ttl="3600" eaccelerator.shm_prune_period="180" eaccelerator.shm_only="1" eaccelerator.compress="1" eaccelerator.compress_level="9" php -v output: PHP 5.2.12 (cli) (built: Feb 3 2010 00:34:28) Copyright (c) 1997-2009 The PHP Group Zend Engine v2.2.0, Copyright (c) 1998-2009 Zend Technologies with eAccelerator v0.9.6.1, Copyright (c) 2004-2010 eAccelerator, by eAccelerator with the ionCube PHP Loader v3.3.20, Copyright (c) 2002-2010, by ionCube Ltd. I had to remove the cache directory as I was testing something. Remade it, re-set permissions and found that eAccelerator was no longer creating cache files within the folder. I thought it might be down to ownership rights on the folder so chown'd it apache.apache and this made no difference. I recreated the directory in /var/cache instead and editted php.ini to point to the new cache dir location, chmod'd, chown'd etc. and still eAccelerator is not creating any of the cache files in the directory (just empty). Could someone suggest what I might be doing incorrectly here. I've read through numerous pages to try and troubleshoot the issue to no avail. Any help appreciated.

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• How to stop Firefox on an SSD from freezing when using the search box or submitting a form?

  - by sblair

  Firefox usually freezes for about a second whenever I search for something from the toolbar search box, when submitting a form, or when clearing the search box history. I suspect it has something to do with the auto-complete feature. Using Windows 7's Resource Monitor, the problem seems to be from the file: C:\Users\<username>\AppData\Roaming\Mozilla\Firefox\Profiles\<profile>\formhistory.sqlite-journal I believe this is a temporary file which caches database writes. The following screenshot shows the very high response times from six different searches, and that the queue length on drive C shoots off the scale: My Firefox profile is on an Intel X25-M G2 SSD. The problem doesn't seem to occur if I create a new profile on a hard disk drive. However, I'd like to know why the problem exists on the SSD in the first place (because it's an annoying problem which contradicts the reason I bought an SSD, and it might happen with other applications too), and how to prevent it. It still occurs if Firefox is started in safe mode, and with the recent beta versions. Updates: VACUUMing the Firefox profile databases does not help with this problem. The SSD Optimizer in the Intel SSD Toolbox does not help either.

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• After upgrading to 2008 R2 Enterprise and installing more RAM, Windows can only see 4.00 GB

  - by Tom Crane

  (I have also posted this on technet but I'm running out of ideas) I've upgraded from Windows Server 2008 R2 Standard to Enterprise in order to make use of more RAM. The server previously had 32GB of RAM. The upgrade from Standard to Enterprise, using DISM, seemed to go OK, so I powered down and installed the RAM. This a Dell Poweredge T710, I was taking it from 32GB to 72GB. The BIOS recognised the RAM, although I needed to change from "Advanced ECC" to "Optimizer" mode for it to use all of it. After rebooting, windows can see the RAM but in the system panel will display: Installed memory (RAM): 72.0 GB (4.00 GB usable) In the resource monitor, the remainder of the RAM is showing as reserved for hardware. I've tried various RAM configurations, including reverting it to the same chips and same configuration as before the upgrade, but always just 4.00 GB is showing up as usable. Following some threads on these forums I've gone into msconfig and set the maximum memory "by hand" but that doesn't fix the problem. BIOS doesn't seem to have anything that looks like memory remapping which is another suggestion that has come up. How do I make this RAM available to Windows? It was available before the upgrade, because I could use the full 32GB RAM the server had to start with. A screenshot (this is after reverting to the original RAM configuration) http://screencast.com/t/5FuzevdNb I don't know if it's related, but my remote desktop configuration has also disappeared: screencast.com/t/mYedomeQWS (the bottom half of this dialog should allow me to configure Remote Desktop, it was working before the upgrade but now it isn't).

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• Gifsicle: How to set it to not overwrite the original GIF file if the resulting modified GIF file is larger than the original?

  - by galacticninja

  About Gifsicle: Gifsicle is a command-line tool for creating, editing, and getting information about GIF images and animations. One of its features is (from its website): Optimize your animations! This stores only the changed portion of each frame, and can radically shrink your GIFs. You can also use transparency to make them even smaller. Gifsicle’s optimizer is pretty powerful, and usually reduces animations to within a couple bytes of the best commercial optimizers. I call Gifsicle through this .BAT file in the Right Click - 'Send to' Menu: @echo off :compressFile "C:\Programs\Compression Scripts\gifsicle\bin\gifsicle.exe" --batch -V -O3 %1% echo. echo. SHIFT if exist %1% goto compressFile PAUSE This animated GIF file, however: http://i.minus.com/i7WdodY5Zwot3.gif, when its compression is optimized with Gifsicle with the above commands, results in a larger-filesized GIF file. Gifsicle overwrites the original GIF file with the resulting larger-filesized GIF file. Initial filesize: 7.57 MiB (7,942,886 bytes). After running through the above commands with Gifsicle: 7.64 MiB (8,017,622 bytes). Is there a way to prevent Gifsicle from overwriting the original file if its output file is larger than the original file, while still overwriting the original file if the output file is smaller? Details: OS: Windows 7 Gifsicle version: 1.63, from the binary provided here: http://www.lcdf.org/gifsicle/ Gifsicle manual

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• High-performance Academic Server [closed]

  - by PHPsmith

  Suppose I want to build a server for the university's academic interests. The server is dedicated only to a site, where users (students and lecturers) just view and fill the academic data. But at a time (e.g. once a semester), about 12,000 students will access the site simultaneously. Due to limitation of resources, I have to build the server using free software (except for the operating system Windows 7, the university has been prepared). The hardware is also limited to the usual 4-core computers (eg, Ivy Bridge Intel Core i7-3770) with approximately 16GB of memory (DDR3 1600 MHz), equipped with an RJ-45 port (Intel 82 579 Gigabit Ethernet). With all these limitations, I have to choose the software (web server, database, etc) are appropriate for this purpose is achieved. I decided to create a site in PHP. Please help me by answering the following questions based on your expertise. (my prime candidate software to consider after googling) Web server which is faster & stable & secure, when implemented and optimized for PHP? And why? (nginx) PHP accelerator which is faster & stable & compatible with the selected web server? And why? (APC with Zend Optimizer+) Database which is faster & stable & secure, when implemented and optimized for selected web server and selected PHP accelerator? (MySQL) Are there any errors that have been or will be happening from my condition is? If there is, please enlighten me? Is there anything else I need to know in order to achieve this goal? If there is, please enlighten me? I understand that the performance also depends on the implementation of source-code program, so I assume it will create a site with the best efficiency (e.g. using AJAX).

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• Ubuntu + LigHTTPd: Server requests taking ages

  - by ctrl_freak

  I've had an issue since upgrading my distro a couple of weeks ago from hardy; receiving data after making a request has increasing intervals of nothing, as you can see from the picture below. http://i49.tinypic.com/2w5lvr9.png I have since reinstalled fresh from an Ubuntu 10.04 Server (i386) disk, but am still having the same issues. I'm running on a LigHTTPd, MySQL, PHP5 stack. The surprising thing is, that local browsing using lynx is super fast, as expected. Initially, after reinstalling, I copied over the old configuration files from the previous installation, but have since reinstalled LigHTTPd and rebuilt the config file from scratch. The only correlation I could find, was that I attempted installation of ionCube and Zend Optimizer for a script I was testing, however I would think that it could no longer impact seeing I had reinstalled the OS. I have also removed Suhosin just in case, however it had no impact. I'm thinking it possibly has something to do with networking, but I wouldn't know where to start. The server is manually assigned an IP by it's MAC address on the router. The fact that the time seems to be exponential (to a point) worries me. I've tried strace'ing the LigHTTPd and MySQL processes, however I couldn't see anything obvious, not that I'd really know what I'm looking for. RAM and CPU usage don't seem to be out of the ordinary, but I can't say its perfect.. I'm hoping someone has experienced the same, or can point me in a direction, as searching has proved fruitless as I don't know anything specific. Config files can be posted, if requested.

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• “Query cost (relative to the batch)” <> Query cost relative to batch

  - by Dave Ballantyne

  OK, so that is quite a contradictory title, but unfortunately it is true that a common misconception is that the query with the highest percentage relative to batch is the worst performing.  Simply put, it is a lie, or more accurately we dont understand what these figures mean. Consider the two below simple queries: SELECT * FROM Person.BusinessEntity JOIN Person.BusinessEntityAddress ON Person.BusinessEntity.BusinessEntityID = Person.BusinessEntityAddress.BusinessEntityID go SELECT * FROM Sales.SalesOrderDetail JOIN Sales.SalesOrderHeader ON Sales.SalesOrderDetail.SalesOrderID = Sales.SalesOrderHeader.SalesOrderID After executing these and looking at the plans, I see this : So, a 13% / 87% split ,  but 13% / 87% of WHAT ? CPU ? Duration ? Reads ? Writes ? or some magical weighted algorithm ?  In a Profiler trace of the two we can find the metrics we are interested in. CPU and duration are well out but what about reads (210 and 1935)? To save you doing the maths, though you are more than welcome to, that’s a 90.2% / 9.8% split.  Close, but no cigar. Lets try a different tact.  Looking at the execution plan the “Estimated Subtree cost” of query 1 is 0.29449 and query 2 its 1.96596.  Again to save you the maths that works out to 13.03% and 86.97%, round those and thats the figures we are after.  But, what is the worrying word there ? “Estimated”.  So these are not “actual”  execution costs,  but what’s the problem in comparing the estimated costs to derive a meaning of “Most Costly”.  Well, in the case of simple queries such as the above , probably not a lot.  In more complicated queries , a fair bit. By modifying the second query to also show the total number of lines on each order SELECT *,COUNT(*) OVER (PARTITION BY Sales.SalesOrderDetail.SalesOrderID) FROM Sales.SalesOrderDetail JOIN Sales.SalesOrderHeader ON Sales.SalesOrderDetail.SalesOrderID = Sales.SalesOrderHeader.SalesOrderID The split in percentages is now 6% / 94% and the profiler metrics are : Even more of a discrepancy. Estimates can be out with actuals for a whole host of reasons,  scalar UDF’s are a particular bug bear of mine and in-fact the cost of a udf call is entirely hidden inside the execution plan.  It always estimates to 0 (well, a very small number). Take for instance the following udf Create Function dbo.udfSumSalesForCustomer(@CustomerId integer) returns money as begin Declare @Sum money Select @Sum= SUM(SalesOrderHeader.TotalDue) from Sales.SalesOrderHeader where CustomerID = @CustomerId return @Sum end If we have two statements , one that fires the udf and another that doesn't: Select CustomerID from Sales.Customer order by CustomerID go Select CustomerID,dbo.udfSumSalesForCustomer(Customer.CustomerID) from Sales.Customer order by CustomerID The costs relative to batch is a 50/50 split, but the has to be an actual cost of firing the udf. Indeed profiler shows us : No where even remotely near 50/50!!!! Moving forward to window framing functionality in SQL Server 2012 the optimizer sees ROWS and RANGE ( see here for their functional differences) as the same ‘cost’ too SELECT SalesOrderDetailID,SalesOrderId, SUM(LineTotal) OVER(PARTITION BY salesorderid ORDER BY Salesorderdetailid RANGE unbounded preceding) from Sales.SalesOrderdetail go SELECT SalesOrderDetailID,SalesOrderId, SUM(LineTotal) OVER(PARTITION BY salesorderid ORDER BY Salesorderdetailid Rows unbounded preceding) from Sales.SalesOrderdetail By now it wont be a great display to show you the Profiler trace reads a *tiny* bit different. So moral of the story, Percentage relative to batch can give a rough ‘finger in the air’ measurement, but dont rely on it as fact.

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• What makes them click ?

  - by Piet

  The other day (well, actually some weeks ago while relaxing at the beach in Kos) I read ‘Neuro Web Design - What makes them click?’ by Susan Weinschenk. (http://neurowebbook.com) The book is a fast and easy read (no unnecessary filler) and a good introduction on how your site’s visitors can be steered in the direction you want them to go. The Obvious The book handles some of the more known/proven techniques, like for example that ratings/testimonials of other people can help sell your product or service. Another well known technique it talks about is inducing a sense of scarcity/urgency in the visitor. Only 2 seats left! Buy now and get 33% off! It’s not because these are known techniques that they stop working. Luckily 2/3rd of the book handles less obvious techniques, otherwise it wouldn’t be worth buying. The Not So Obvious A less known influencing technique is reciprocity. And then I’m not talking about swapping links with another website, but the fact that someone is more likely to do something for you after you did something for them first. The book cites some studies (I always love the facts and figures) and gives some actual examples of how to implement this in your site’s design, which is less obvious when you think about it. Want to know more ? Buy the book! Other interesting sources For a more general introduction to the same principles, I’d suggest ‘Yes! 50 Secrets from the Science of Persuasion’. ‘Yes!…’ cites some of the same studies (it seems there’s a rather limited pool of studies covering this subject), but of course doesn’t show how to implement these techniques in your site’s design. I read ‘Yes!…’ last year, making ‘Neuro Web Design’ just a little bit less interesting. !!!Always make sure you’re able to measure your changes. If you haven’t yet, check out the advanced segmentation in Google Analytics (don’t be afraid because it says ‘beta’, it works just fine) and Google Website Optimizer. Worth Buying? Can I recommend it ? Sure, why not. I think it can be useful for anyone who ever had to think about the design or content of a site. You don’t have to be a marketing guy to want a site you’re involved with to be successful. The content/filler ratio is excellent too: you don’t need to wade through dozens of pages to filter out the interesting bits. (unlike ‘The Design of Sites’, which contains too much useless info and because it’s in dead-tree format, you can’t google it) If you like it, you might also check out ‘Yes! 50 Secrets from the Science of Persuasion’. Tip for people living in Europe: check Amazon UK for your book buying needs. Because of the low UK Pound exchange rate, it’s usually considerably cheaper and faster to get a book delivered to your doorstep by Amazon UK compared to having to order it at the local book store or web-shop.

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• SQL SERVER – Guest Post – Glenn Berry – Wait Type – Day 26 of 28

  - by pinaldave

  Glenn Berry works as a Database Architect at NewsGator Technologies in Denver, CO. He is a SQL Server MVP, and has a whole collection of Microsoft certifications, including MCITP, MCDBA, MCSE, MCSD, MCAD, and MCTS. He is also an Adjunct Faculty member at University College – University of Denver, where he has been teaching since 2000. He is one wonderful blogger and often blogs at here. I am big fan of the Dynamic Management Views (DMV) scripts of Glenn. His script are extremely popular and the reality is that he has inspired me to start this series with his famous DMV which I have mentioned in very first  wait stats blog post (I had forgot to request his permission to re-use the script but when asked later on his whole hearty approved it). Here is is his excellent blog post on this subject of wait stats: Analyzing cumulative wait stats in SQL Server 2005 and above has become a popular and effective technique for diagnosing performance issues and further focusing your troubleshooting and diagnostic  efforts.  Rather than just guessing about what resource(s) that SQL Server is waiting on, you can actually find out by running a relatively simple DMV query. Once you know what resources that SQL Server is spending the most time waiting on, you can run more specific queries that focus on that resource to get a better idea what is causing the problem. I do want to throw out a few caveats about using wait stats as a diagnostic tool. First, they are most useful when your SQL Server instance is experiencing performance problems. If your instance is running well, with no indication of any resource pressure from other sources, then you should not worry that much about what the top wait types are. SQL Server will always be waiting on some resource, but many wait types are quite benign, and can be safely ignored. In spite of this, I quite often see experienced DBAs obsessing over the top wait type, even when their SQL Server instance is running extremely well. Second, I often see DBAs jump to the wrong conclusion based on seeing a particular well-known wait type. A good example is CXPACKET waits. People typically jump to the conclusion that high CXPACKET waits means that they should immediately change their instance-level MADOP setting to 1. This is not always the best solution. You need to consider your workload type, and look carefully for any important “missing” indexes that might be causing the query optimizer to use a parallel plan to compensate for the missing index. In this case, correcting the index problem is usually a better solution than changing MAXDOP, since you are curing the disease rather than just treating the symptom. Finally, you should get in the habit of clearing out your cumulative wait stats with the  DBCC SQLPERF(‘sys.dm_os_wait_stats’, CLEAR); command. This is especially important if you have made an configuration or index changes, or if your workload has changed recently. Otherwise, your cumulative wait stats will be polluted with the old stats from weeks or months ago (since the last time SQL Server was started or the stats were cleared).  If you make a change to your SQL Server instance, or add an index, you should clear out your wait stats, and then wait a while to see what your new top wait stats are. At any rate, enjoy Pinal Dave’s series on Wait Stats. This blog post has been written by Glenn Berry (Twitter | Blog) Read all the post in the Wait Types and Queue series. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, Readers Contribution, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology

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• A temporary disagreement

  - by Tony Davis

  Last month, Phil Factor caused a furore amongst some MVPs with an article that attempted to offer simple advice to developers regarding the use of table variables, versus local and global temporary tables, in their code. Phil makes clear that the table variables do come with some fairly major limitations.no distribution statistics, no parallel query plans for queries that modify table variables.but goes on to suggest that for reasonably small-scale strategic uses, and with a bit of due care and testing, table variables are a "good thing". Not everyone shares his opinion; in fact, I imagine he was rather aghast to learn that there were those felt his article was akin to pulling the pin out of a grenade and tossing it into the database; table variables should be avoided in almost all cases, according to their advice, in favour of temp tables. In other words, a fairly major feature of SQL Server should be more-or-less 'off limits' to developers. The problem with temp tables is that, because they are scoped either in the procedure or the connection, it is easy to allow them to hang around for too long, eating up precious memory and bulking up the shared tempdb database. Unless they are explicitly dropped, global temporary tables, and local temporary tables created within a connection rather than within a stored procedure, will persist until the connection is closed or, with connection pooling, until the connection is reused. It's also quite common with ASP.NET applications to have connection leaks, as Bill Vaughn explains in his chapter in the "SQL Server Deep Dives" book, meaning that the web page exits without closing the connection object, maybe due to an error condition. This will then hang around in the heap for what might be hours before picked up by the garbage collector. Table variables are much safer in this regard, since they are batch-scoped and so are cleaned up automatically once the batch is complete, which also means that they are intuitive to use for the developer because they conform to scoping rules that are closer to those in procedural code. On the surface then, an ideal way to deal with issues related to tempdb memory hogging. So why did Phil qualify his recommendation to use Table Variables? This is another of those cases where, like scalar UDFs and table-valued multi-statement UDFs, developers can sometimes get into trouble with a relatively benign-looking feature, due to way it's been implemented in SQL Server. Once again the biggest problem is how they are handled internally, by the SQL Server query optimizer, which can make very poor choices for JOIN orders and so on, in the absence of statistics, especially when joining to tables with highly-skewed data. The resulting execution plans can be horrible, as will be the resulting performance. If the JOIN is to a large table, that will hurt. Ideally, Microsoft would simply fix this issue so that developers can't get burned in this way; they've been around since SQL Server 2000, so Microsoft has had a bit of time to get it right. As I commented in regard to UDFs, when developers discover issues like with such standard features, the database becomes an alien planet to them, where death lurks around each corner, and they continue to avoid these "killer" features years after the problems have been eventually resolved. In the meantime, what is the right approach? Is it to say "hammers can kill, don't ever use hammers", or is it to try to explain, as Phil's article and follow-up blog post have tried to do, what the feature was intended for, why care must be applied in its use, and so enable developers to make properly-informed decisions, without requiring them to delve deep into the inner workings of SQL Server? Cheers, Tony.

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• ODI 11g – Oracle Multi Table Insert

  - by David Allan

  With the IKM Oracle Multi Table Insert you can generate Oracle specific DML for inserting into multiple target tables from a single query result – without reprocessing the query or staging its result. When designing this to exploit the IKM you must split the problem into the reusable parts – the select part goes in one interface (I named SELECT_PART), then each target goes in a separate interface (INSERT_SPECIAL and INSERT_REGULAR). So for my statement below… /*INSERT_SPECIAL interface */ insert  all when 1=1 And (INCOME_LEVEL > 250000) then into SCOTT.CUSTOMERS_NEW (ID, NAME, GENDER, BIRTH_DATE, MARITAL_STATUS, INCOME_LEVEL, CREDIT_LIMIT, EMAIL, USER_CREATED, DATE_CREATED, USER_MODIFIED, DATE_MODIFIED) values (ID, NAME, GENDER, BIRTH_DATE, MARITAL_STATUS, INCOME_LEVEL, CREDIT_LIMIT, EMAIL, USER_CREATED, DATE_CREATED, USER_MODIFIED, DATE_MODIFIED) /* INSERT_REGULAR interface */ when 1=1  then into SCOTT.CUSTOMERS_SPECIAL (ID, NAME, GENDER, BIRTH_DATE, MARITAL_STATUS, INCOME_LEVEL, CREDIT_LIMIT, EMAIL, USER_CREATED, DATE_CREATED, USER_MODIFIED, DATE_MODIFIED) values (ID, NAME, GENDER, BIRTH_DATE, MARITAL_STATUS, INCOME_LEVEL, CREDIT_LIMIT, EMAIL, USER_CREATED, DATE_CREATED, USER_MODIFIED, DATE_MODIFIED) /*SELECT*PART interface */ select        CUSTOMERS.EMAIL EMAIL,     CUSTOMERS.CREDIT_LIMIT CREDIT_LIMIT,     UPPER(CUSTOMERS.NAME) NAME,     CUSTOMERS.USER_MODIFIED USER_MODIFIED,     CUSTOMERS.DATE_MODIFIED DATE_MODIFIED,     CUSTOMERS.BIRTH_DATE BIRTH_DATE,     CUSTOMERS.MARITAL_STATUS MARITAL_STATUS,     CUSTOMERS.ID ID,     CUSTOMERS.USER_CREATED USER_CREATED,     CUSTOMERS.GENDER GENDER,     CUSTOMERS.DATE_CREATED DATE_CREATED,     CUSTOMERS.INCOME_LEVEL INCOME_LEVEL from    SCOTT.CUSTOMERS   CUSTOMERS where    (1=1) Firstly I create a SELECT_PART temporary interface for the query to be reused and in the IKM assignment I state that it is defining the query, it is not a target and it should not be executed. Then in my INSERT_SPECIAL interface loading a target with a filter, I set define query to false, then set true for the target table and execute to false. This interface uses the SELECT_PART query definition interface as a source. Finally in my final interface loading another target I set define query to false again, set target table to true and execute to true – this is the go run it indicator! To coordinate the statement construction you will need to create a package with the select and insert statements. With 11g you can now execute the package in simulation mode and preview the generated code including the SQL statements. Hopefully this helps shed some light on how you can leverage the Oracle MTI statement. A similar IKM exists for Teradata. The ODI IKM Teradata Multi Statement supports this multi statement request in 11g, here is an extract from the paper at www.teradata.com/white-papers/born-to-be-parallel-eb3053/ Teradata Database offers an SQL extension called a Multi-Statement Request that allows several distinct SQL statements to be bundled together and sent to the optimizer as if they were one. Teradata Database will attempt to execute these SQL statements in parallel. When this feature is used, any sub-expressions that the different SQL statements have in common will be executed once, and the results shared among them. It works in the same way as the ODI MTI IKM, multiple interfaces orchestrated in a package, each interface contributes some SQL, the last interface in the chain executes the multi statement.

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• SQL SERVER – Simple Demo of New Cardinality Estimation Features of SQL Server 2014

  - by Pinal Dave

  SQL Server 2014 has new cardinality estimation logic/algorithm. The cardinality estimation logic is responsible for quality of query plans and majorly responsible for improving performance for any query. This logic was not updated for quite a while, but in the latest version of SQL Server 2104 this logic is re-designed. The new logic now incorporates various assumptions and algorithms of OLTP and warehousing workload. Cardinality estimates are a prediction of the number of rows in the query result. The query optimizer uses these estimates to choose a plan for executing the query. The quality of the query plan has a direct impact on improving query performance. ~ Souce MSDN Let us see a quick example of how cardinality improves performance for a query. I will be using the AdventureWorks database for my example. Before we start with this demonstration, remember that even though you have SQL Server 2014 to see the effect of new cardinality estimates, you will need your database compatibility mode set to 120 which is for SQL Server 2014. If your server instance of SQL Server 2014 but you have set up your database compatibility mode to 110 or any other earlier version, you will get performance from your query like older version of SQL Server. Now we will execute following query in two different compatibility mode and see its performance. (Note that my SQL Server instance is of version 2014). USE AdventureWorks2014 GO -- ------------------------------- -- NEW Cardinality Estimation ALTER DATABASE AdventureWorks2014 SET COMPATIBILITY_LEVEL = 120 GO EXEC [dbo].[uspGetManagerEmployees] 44 GO -- ------------------------------- -- Old Cardinality Estimation ALTER DATABASE AdventureWorks2014 SET COMPATIBILITY_LEVEL = 110 GO EXEC [dbo].[uspGetManagerEmployees] 44 GO Result of Statistics IO Compatibility level 120 Table ‘Person’. Scan count 0, logical reads 6, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0. Table ‘Employee’. Scan count 2, logical reads 7, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0. Table ‘Worktable’. Scan count 0, logical reads 0, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0. Table ‘Worktable’. Scan count 2, logical reads 7, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0. Compatibility level 110 Table ‘Worktable’. Scan count 2, logical reads 7, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0. Table ‘Person’. Scan count 0, logical reads 137, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0. Table ‘Employee’. Scan count 2, logical reads 7, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0. Table ‘Worktable’. Scan count 0, logical reads 0, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0. You will notice in the case of compatibility level 110 there 137 logical read from table person where as in the case of compatibility level 120 there are only 6 physical reads from table person. This drastically improves the performance of the query. If we enable execution plan, we can see the same as well. I hope you will find this quick example helpful. You can read more about this in my latest Pluralsight Course. Reference: Pinal Dave (http://blog.SQLAuthority.com)Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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• PASS Summit 2011 &ndash; Part IV

  - by Tara Kizer

  This is the final blog for my PASS Summit 2011 series.  Well okay, a mini-series, I guess. On the last day of the conference, I attended Keith Elmore’ and Boris Baryshnikov’s (both from Microsoft) “Introducing the Microsoft SQL Server Code Named “Denali” Performance Dashboard Reports, Jeremiah Peschka’s (blog|twitter) “Rewrite your T-SQL for Great Good!”, and Kimberly Tripp’s (blog|twitter) “Isolated Disasters in VLDBs”. Keith and Boris talked about the lifecycle of a session, figuring out the running time and the waiting time.  They pointed out the transient nature of the reports.  You could be drilling into it to uncover a problem, but the session may have ended by the time you’ve drilled all of the way down.  Also, the reports are for troubleshooting live problems and not historical ones.  You can use Management Data Warehouse for historical troubleshooting.  The reports provide similar benefits to the Activity Monitor, however Activity Monitor doesn’t provide context sensitive drill through. One thing I learned in Keith’s and Boris’ session was that the buffer cache hit ratio should really never be below 87% due to the read-ahead mechanism in SQL Server.  When a page is read, it will read the entire extent.  So for every page read, you get 7 more read.  If you need any of those 7 extra pages, well they are already in cache.  I had a lot of fun in Jeremiah’s session about refactoring code plus I learned a lot.  His slides were visually presented in a fun way, which just made for a more upbeat presentation.  Jeremiah says that before you start refactoring, you should look at your system.  Investigate missing or too many indexes, out-of-date statistics, and other areas that could be leading to your code running slow.  He talked about code standards.  He suggested using common abbreviations for aliases instead of one-letter aliases.  I’m a big offender of one-letter aliases, but he makes a good point.  He said that join order does not matter to the optimizer, but it does matter to those who have to read your code.  Now let’s get into refactoring! Eliminate useless things – useless/unneeded joins and columns.  If you don’t need it, get rid of it! Instead of using DISTINCT/JOIN, replace with EXISTS Simplify your conditions; use UNION or better yet UNION ALL instead of OR to avoid a scan and use indexes for each union query Branching logic – instead of IF this, IF that, and on and on…use dynamic SQL (sp_executesql, please!) or use a parameterized query in the application Correlated subqueries – YUCK! Replace with a join Eliminate repeated patterns Last, but certainly not least, was Kimberly’s session.  Kimberly is my favorite speaker.  I attended her two-day pre-conference seminar at PASS Summit 2005 as well as a SQL Immersion Event last December.  Did I mention she’s my favorite speaker?  Okay, enough of that. Kimberly’s session was packed with demos.  I had seen some of it in the SQL Immersion Event, but it was very nice to get a refresher on these, especially since I’ve got a VLDB with some growing pains.  One key takeaway from her session is the idea to use a log shipping solution with a load delay, such as 6, 8, or 24 hours behind the primary.  In the case of say an accidentally dropped table in a VLDB, we could retrieve it from the secondary database rather than waiting an eternity for a restore to complete.  Kimberly let us know that in SQL Server 2012 (it finally has a name!), online rebuilds are supported even if there are LOB columns in your table.  This will simplify custom code that intelligently figures out if an online rebuild is possible. There was actually one last time slot for sessions that day, but I had an airplane to catch and my kids to see!

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• PASS Summit 2011 &ndash; Part II

  - by Tara Kizer

  I arrived in Seattle last Monday afternoon to attend PASS Summit 2011.  I had really wanted to attend Gail Shaw’s (blog|twitter) and Grant Fritchey’s (blog|twitter) pre-conference seminar “All About Execution Plans” on Monday, but that would have meant flying out on Sunday which I couldn’t do.  On Tuesday, I attended Allan Hirt’s (blog|twitter) pre-conference seminar entitled “A Deep Dive into AlwaysOn: Failover Clustering and Availability Groups”.  Allan is a great speaker, and his seminar was packed with demos and information about AlwaysOn in SQL Server 2012.  Unfortunately, I have lost my notes from this seminar and the presentation materials are only available on the pre-con DVD.  Hmpf! On Wednesday, I attended Gail Shaw’s “Bad Plan! Sit!”, Andrew Kelly’s (blog|twitter) “SQL 2008 Query Statistics”, Dan Jones’ (blog|twitter) “Improving your PowerShell Productivity”, and Brent Ozar’s (blog|twitter) “BLITZ! The SQL – More One Hour SQL Server Takeovers”.  In Gail’s session, she went over how to fix bad plans and bad query patterns.  Update your stale statistics! How to fix bad plans Use local variables – optimizer can’t sniff it, so it’ll optimize for “average” value Use RECOMPILE (at the query or stored procedure level) – CPU hit OPTIMIZE FOR hint – most common value you’ll pass How to fix bad query patterns Don’t use them – ha! Catch-all queries Use dynamic SQL OPTION (RECOMPILE) Multiple execution paths Split into multiple stored procedures OPTION (RECOMPILE) Modifying parameter values Use local variables Split into outer and inner procedure OPTION (RECOMPILE) She also went into “last resort” and “very last resort” options, but those are risky unless you know what you are doing.  For the average Joe, she wouldn’t recommend these.  Examples are query hints and plan guides. While I enjoyed Andrew’s session, I didn’t take any notes as it was familiar material.  Andrew is a great speaker though, and I’d highly recommend attending his sessions in the future. Next up was Dan’s PowerShell session.  I need to look into profiles, manifests, function modules, and function import scripts more as I just didn’t quite grasp these concepts.  I am attending a PowerShell training class at the end of November, so maybe that’ll help clear it up.  I really enjoyed the Excel integration demo.  It was very cool watching PowerShell build the spreadsheet in real-time.  I must look into this more!  On a side note, I am jealous of Dan’s hair.  Fabulous hair! Brent’s session showed us how to quickly gather information about a server that you will be taking over database administration duties for.  He wrote a script to do a fast health check and then later wrapped it into a stored procedure, sp_Blitz.  I can’t wait to use this at my work even on systems where I’ve been the primary DBA for years, maybe there’s something I’ve overlooked.  We are using EPM to help standardize our environment and uncover problems, but sp_Blitz will definitely still help us out.  He even provides a cloud-based update feature, sp_BlitzUpdate, for sp_Blitz so you don’t have to constantly update it when he makes a change.  I think I’ll utilize his update code for some other challenges that we face at my work.

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• Where should you put constants and why?

  - by Tim Meyer

  In our mostly large applications, we usually have a only few locations for constants: One class for GUI and internal contstants (Tab Page titles, Group Box titles, calculation factors, enumerations) One class for database tables and columns (this part is generated code) plus readable names for them (manually assigned) One class for application messages (logging, message boxes etc) The constants are usually separated into different structs in those classes. In our C++ applications, the constants are only defined in the .h file and the values are assigned in the .cpp file. One of the advantages is that all strings etc are in one central place and everybody knows where to find them when something must be changed. This is especially something project managers seem to like as people come and go and this way everybody can change such trivial things without having to dig into the application's structure. Also, you can easily change the title of similar Group Boxes / Tab Pages etc at once. Another aspect is that you can just print that class and give it to a non-programmer who can check if the captions are intuitive, and if messages to the user are too detailed or too confusing etc. However, I see certain disadvantages: Every single class is tightly coupled to the constants classes Adding/Removing/Renaming/Moving a constant requires recompilation of at least 90% of the application (Note: Changing the value doesn't, at least for C++). In one of our C++ projects with 1500 classes, this means around 7 minutes of compilation time (using precompiled headers; without them it's around 50 minutes) plus around 10 minutes of linking against certain static libraries. Building a speed optimized release through the Visual Studio Compiler takes up to 3 hours. I don't know if the huge amount of class relations is the source but it might as well be. You get driven into temporarily hard-coding strings straight into code because you want to test something very quickly and don't want to wait 15 minutes just for that test (and probably every subsequent one). Everybody knows what happens to the "I will fix that later"-thoughts. Reusing a class in another project isn't always that easy (mainly due to other tight couplings, but the constants handling doesn't make it easier.) Where would you store constants like that? Also what arguments would you bring in order to convince your project manager that there are better concepts which also comply with the advantages listed above? Feel free to give a C++-specific or independent answer. PS: I know this question is kind of subjective but I honestly don't know of any better place than this site for this kind of question. Update on this project I have news on the compile time thing: Following Caleb's and gbjbaanb's posts, I split my constants file into several other files when I had time. I also eventually split my project into several libraries which was now possible much easier. Compiling this in release mode showed that the auto-generated file which contains the database definitions (table, column names and more - more than 8000 symbols) and builds up certain hashes caused the huge compile times in release mode. Deactivating MSVC's optimizer for the library which contains the DB constants now allowed us to reduce the total compile time of your Project (several applications) in release mode from up to 8 hours to less than one hour! We have yet to find out why MSVC has such a hard time optimizing these files, but for now this change relieves a lot of pressure as we no longer have to rely on nightly builds only. That fact - and other benefits, such as less tight coupling, better reuseability etc - also showed that spending time splitting up the "constants" wasn't such a bad idea after all ;-)

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• Slow query with unexpected index scan

  - by zerkms

  Hello I have this query: SELECT * FROM sample INNER JOIN test ON sample.sample_number = test.sample_number INNER JOIN result ON test.test_number = result.test_number WHERE sampled_date BETWEEN '2010-03-17 09:00' AND '2010-03-17 12:00' the biggest table here is RESULT, contains 11.1M records. The left 2 tables about 1M. this query works slowly (more than 10 minutes) and returns about 800 records. executing plan shows clustered index scan (over it's PRIMARY KEY (result.result_number, which actually doesn't take part in query)) over all 11M records. RESULT.TEST_NUMBER is a clustered primary key. if I change 2010-03-17 09:00 to 2010-03-17 10:00 - i get about 40 records. it executes for 300ms. and plan shows index seek (over result.test_number index) if i replace * in SELECT clause to result.test_number (covered with index) - then all become fast in first case too. this points to hdd IO issues, but doesn't clarifies changing plan. so, any ideas? UPDATE: sampled_date is in table sample and covered by index. other fields from this query: test.sample_number is covered by index and result.test_number too. UPDATE 2: obviously than sql server in any reasons don't want to use index. i did a small experiment: i remove INNER JOIN with result, select all test.test_number and after that do SELECT * FROM RESULT WHERE TEST_NUMBER IN (...) this, of course, works fast. but i cannot get what is the difference and why query optimizer choose such inappropriate way to select data in 1st case.

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• Deleting JPA entity containing @CollectionOfElements throws ConstraintViolationException

  - by Lyle

  I'm trying to delete entities which contain lists of Integer, and I'm getting ConstraintViolationExceptions because of the foreign key on the table generated to hold the integers. It appears that the delete isn't cascading to the mapped collection. I've done quite a bit of searching, but all of the examples I've seen on how to accomplish this are in reference to a mapped collection of other entities which can be annotated; here I'm just storing a list of Integer. Here is the relevant excerpt from the class I'm storing: @Entity @Table(name="CHANGE_IDS") @GenericGenerator( name = "CHANGE_ID_GEN", strategy = "org.hibernate.id.enhanced.SequenceStyleGenerator", parameters = { @Parameter(name="sequence_name", value="course_changes_seq"), @Parameter(name="increment_size", value="5000"), @Parameter(name=" optimizer", value="pooled") } ) @NamedQueries ({ @NamedQuery( name="Changes.getByStatus", query= "SELECT c " + "FROM DChanges c " + "WHERE c.status = :status "), @NamedQuery( name="Changes.deleteByStatus", query= "DELETE " + "FROM Changes c " + "WHERE c.status = :status ") }) public class Changes { @Id @GeneratedValue(generator="CHANGE_ID_GEN") @Column(name = "ID") private final long id; @Enumerated(EnumType.STRING) @Column(name = "STATUS", length = 20, nullable = false) private final Status status; @Column(name="DOC_ID") @org.hibernate.annotations.CollectionOfElements @org.hibernate.annotations.IndexColumn(name="DOC_ID_ORDER") private List<Integer> docIds; } I'm deleting the Changes objects using a @NamedQuery: final Query deleteQuery = this.entityManager.createNamedQuery("Changes.deleteByStatus"); deleteQuery.setParameter("status", Status.POST_FLIP); final int deleted = deleteQuery.executeUpdate(); this.logger.info("Deleted " + deleted + " POST_FLIP Changes");

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• Prevent full table scan for query with multiple where clauses

  - by Dave Jarvis

  A while ago I posted a message about optimizing a query in MySQL. I have since ported the data and query to PostgreSQL, but now PostgreSQL has the same problem. The solution in MySQL was to force the optimizer to not optimize using STRAIGHT_JOIN. PostgreSQL offers no such option. Here is the explain: Here is the query: SELECT avg(d.amount) AS amount, y.year FROM station s, station_district sd, year_ref y, month_ref m, daily d LEFT JOIN city c ON c.id = 10663 WHERE -- Find all the stations within a specific unit radius ... -- 6371.009 * SQRT( POW(RADIANS(c.latitude_decimal - s.latitude_decimal), 2) + (COS(RADIANS(c.latitude_decimal + s.latitude_decimal) / 2) * POW(RADIANS(c.longitude_decimal - s.longitude_decimal), 2)) ) <= 50 AND -- Ignore stations outside the given elevations -- s.elevation BETWEEN 0 AND 2000 AND sd.id = s.station_district_id AND -- Gather all known years for that station ... -- y.station_district_id = sd.id AND -- The data before 1900 is shaky; insufficient after 2009. -- y.year BETWEEN 1980 AND 2000 AND -- Filtered by all known months ... -- m.year_ref_id = y.id AND m.month = 12 AND -- Whittled down by category ... -- m.category_id = '001' AND -- Into the valid daily climate data. -- m.id = d.month_ref_id AND d.daily_flag_id <> 'M' GROUP BY y.year It appears as though PostgreSQL is looking at the DAILY table first, which is simply not the right way to go about this query as there are nearly 300 million rows. How do I force PostgreSQL to start at the CITY table? Thank you!

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• Question about SQL Server HierarchyID depth-first performance

  - by AndalusianCat

  I am trying to implement hierarchyID in a table (dbo.[Message]) containing roughly 50,000 rows (will grow substantially in the future). However it takes 30-40 seconds to retrieve about 25 results. The root node is a filler in order to provide uniqueness, therefor every subsequent row is a child of that dummy row. I need to be able to traverse the table depth-first and have made the hierarchyID column (dbo.[Message].MessageID) the clustering primary key, have also added a computed smallint (dbo.[Message].Hierarchy) which stores the level of the node. Usage: A .Net application passes through a hierarchyID value into the database and I want to be able to retrieve all (if any) children AND parents of that node (besides the root, as it is filler). A simplified version of the query I am using: @MessageID hierarchyID /* passed in from application */ SELECT m.MessageID, m.MessageComment FROM dbo.[Message] as m WHERE m.Messageid.IsDescendantOf(@MessageID.GetAncestor((@MessageID.GetLevel()-1))) = 1 ORDER BY m.MessageID From what I understand, the index should be detected automatically without a hint. From searching forums I have seen people utilizing index hints, at least in the case of breadth-first indexes, as apparently CLR calls may be opaque to the query optimizer. I have spent the past few days trying to find a solution for this issue, but to no avail. I would greatly appreciate any assistance, and as this is my first post, I apologize in advance if this would be considered a 'noobish' question, I have read the MS documentation and searched countless forums, but have not came across a succinct description of the specific issue.

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• GCC emits extra code for boost::shared_ptr dereference

  - by Checkers

  I have the following code: #include <boost/shared_ptr.hpp> struct Foo { int a; }; static int A; void func_shared(const boost::shared_ptr<Foo> &foo) { A = foo->a; } void func_raw(Foo * const foo) { A = foo->a; } I thought the compiler would create identical code, but for shared_ptr version an extra seemingly redundant instruction is emitted. Disassembly of section .text: 00000000 <func_raw(Foo*)>: 0: 55 push ebp 1: 89 e5 mov ebp,esp 3: 8b 45 08 mov eax,DWORD PTR [ebp+8] 6: 5d pop ebp 7: 8b 00 mov eax,DWORD PTR [eax] 9: a3 00 00 00 00 mov ds:0x0,eax e: c3 ret f: 90 nop 00000010 <func_shared(boost::shared_ptr<Foo> const&)>: 10: 55 push ebp 11: 89 e5 mov ebp,esp 13: 8b 45 08 mov eax,DWORD PTR [ebp+8] 16: 5d pop ebp 17: 8b 00 mov eax,DWORD PTR [eax] 19: 8b 00 mov eax,DWORD PTR [eax] 1b: a3 00 00 00 00 mov ds:0x0,eax 20: c3 ret I'm just curious, is this necessary, or it is just an optimizer's shortcoming? Compiling with g++ 4.1.2, -O3 -NDEBUG.

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• Need help in tuning a sql-query

  - by Viper

  Hello, i need some help to boost this SQL-Statement. The execution time is around 125ms. During the runtime of my program this sql (better: equally structured sqls for different tables) will be called 300.000 times. The average row count in the tables lies around 10.000.000 rows and new rows (updates/inserts) will be added with a timestamp each day. Data which are interesting for this particular export-program lies in the last 1-3 days. Maybe this is helpful for an index to create. The data i need is the current valid row for a given id and the forerunner datarow to get the updates (if exists). We use a Oracle 11g database and Dot.Net Framework 3.5 SQL-Statement to boost: select ID_SOMETHING, -- Number(12) ID_CONTRIBUTOR, -- Char(4 Byte) DATE_VALID_FROM, -- DATE DATE_VALID_TO -- DATE from TBL_SOMETHING XID where ID_SOMETHING = :ID_INSTRUMENT and ID_CONTRIBUTOR = :ID_CONTRIBUTOR and DATE_VALID_FROM <= :EXPORT_DATE and DATE_VALID_TO >= :EXPORT_DATE order by DATE_VALID_FROM asc; Here i uploaded the current Explain-Plan for this query. I'm not a database expert so i don't know which index-type would fit best for this requirement. I have seen that there are many different possible index-types which could be applied. Maybe Oracle Optimizer Hints are helpful, too. Does anyone has a good idea for tuning this sql or can point me in a right direction?

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• Why is MySQL with InnoDB doing a table scan when key exists and choosing to examine 70 times more ro

  - by andysk

  Hello, I'm troubleshooting a query performance problem. Here's an expected query plan from explain: mysql> explain select * from table1 where tdcol between '2010-04-13:00:00' and '2010-04-14 03:16'; +----+-------------+--------------------+-------+---------------+--------------+---------+------+---------+-------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+-------------+--------------------+-------+---------------+--------------+---------+------+---------+-------------+ | 1 | SIMPLE | table1 | range | tdcol | tdcol | 8 | NULL | 5437848 | Using where | +----+-------------+--------------------+-------+---------------+--------------+---------+------+---------+-------------+ 1 row in set (0.00 sec) That makes sense, since the index named tdcol (KEY tdcol (tdcol)) is used, and about 5M rows should be selected from this query. However, if I query for just one more minute of data, we get this query plan: mysql> explain select * from table1 where tdcol between '2010-04-13 00:00' and '2010-04-14 03:17'; +----+-------------+--------------------+------+---------------+------+---------+------+-----------+-------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+-------------+--------------------+------+---------------+------+---------+------+-----------+-------------+ | 1 | SIMPLE | table1 | ALL | tdcol | NULL | NULL | NULL | 381601300 | Using where | +----+-------------+--------------------+------+---------------+------+---------+------+-----------+-------------+ 1 row in set (0.00 sec) The optimizer believes that the scan will be better, but it's over 70x more rows to examine, so I have a hard time believing that the table scan is better. Also, the 'USE KEY tdcol' syntax does not change the query plan. Thanks in advance for any help, and I'm more than happy to provide more info/answer questions.

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