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  • Which version of ZFS allows shrinking of a pool?

    - by George Bailey
    I found a list of versions and their Solaris release numbers http://download.oracle.com/docs/cd/E19253-01/819-5461/appendixa-1/index.html I know that you can grow a pool by replacing drives with larger ones or adding new drives or mirrors to the pool. I heard that ZFS did not yet support shrinking pools by removing drives/mirrors. But that has probably been changed. Which version (if any) released the ability to shrink a pool?

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  • How to specify root's environment variable?

    - by Wendy
    I do rails development. In this app, I need to specify the environment variable LD_LIBRARY_PATH = /usr/local/oracle/lib But when I run the app with sudo script/server, it doesn't run because that library path is not in roots' env. What should I do to make it work? I tried to put the path under root ./bashrc and it didn't work.

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  • MySQL for SQL Server DBAs

    - by SQL3D
    I've been tasked with taking over the administration of a MySQL installation (running on Red Hat Linux) that will become fairly critical to our business in the near future. I was wondering if anyone could recommend some resources in regards to administering MySQL for DBAs already experienced with other relational database (SQL Server and some Oracle in my case). Specifically I'm looking for information around disaster recovery as well as high availability to start with, but I do want to get well rounded with the entire system. Thanks in advance, Dan

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  • Why can't we reach some (but not all) external web service via VPN connection?

    - by Paul Haldane
    At work (UK university) we use a set of Windows servers running WS2008R2 and RRAS which offer VPN service to students in our accommodation. We do this to associate the network connections with individuals. Before they've connected to the VPN all they can talk to is the stuff thats needed to setup the VPN and a local web site with documentation on how to connect. Medium term we'll probably replace this but it's what we're using at the moment. VPN on the 2008 servers allocates client a private (10.x) address. Access to external sites is through NAT on the campus routers (same as any other directly connected client on a private address). Non-VPN connections aren't seeing this problem. Older servers run WS 2003 and ISA2004. That setup works but has become unreliable under load. Big difference there was that we were allocating non-RFC1918 addresses to the clients (so no NAT required). Behaviour we're seeing is that once connected to the VPN, clients can reach local web sites (that is sites on the campus network) but only some external sites. It seems (but this may be chance) that the sites we can reach are Google ones (including YouTube). We certainly have trouble reaching Microsoft's Office 365 service (which is a pain because that's where mail for most of our students is). One odd bit of behaviour is that clients can fetch (using wget on a Windows 7 client) http://www.oracle.com/ (which gets a 301 redirect) but hangs when asked to fetch http://www.oracle.com/index.html (which is what the first URL redirects to). Access works reliably if we configure clients to use our local web proxies (Squid). My gut tells me that this is likely to be something in the chain dropping replies either based on HTTP inspection or the IP address in the reply. However I'm puzzled about why we're seeing this with the VPN clients. Plan for tomorrow (when I'm back in the office) is to setup a web server on external connection so that we can monitor behaviour at both ends of the conversation (hoping that the problem manifests itself with our test server). Any suggestions for things we should be looking at?

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  • Losing connection to server from several computers

    - by user3696358
    I have a PostgreSQL server running Oracle Linux. In my network I have several workstations each running different OS (Fedora, Ubuntu, Windows). Every once in a while I lose connection from the several workstations to the server while other workstations can connect with no problem. If I do service network restart from the server the problem is solved and everyone can work until the next time it returns. Any clues? Thank you, Ben.

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  • When RAID 10 is SLOWER than RAID 1, why?

    - by Paul
    We have a Dell 2950 with PERC and 14 external SAS 15K 73GB drives. An Oracle database job takes 3 hours to run with the drives set as hardware RAID 10 (striped across 7 mirrored pairs). The same job with the drives in RAID 1 takes only 1 hour. OS is Win 2008 R2 I think. Before we change the RAID level (with considerable downtime) on the production box, does anyone know why we're seeing this odd result, and if there's a better way to fix it?

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  • Has glassfish 2.1.1 a bug handling http request and handle them twice?

    - by marabol
    I'm using glassfish 2.1.1. I've watched a mysterious http/webservice-call handling. It seams an http request is handled by two different threads. After http basic authentication the first thread is faster. Persisting some data end, but writing response fails in glassfish internal. The second thread fails, because it tries to persist identical data and there are (unique) constrain failures. The response (the failure) of second thread was delivered to client. I don't won't discuss the behavior with the unique constrain failure. I've improve the webservice, so it can handle this better, because it could be happen anytime, that the client send the ws call a second time. But I think, glassfish 2.1.1 has an bug handling http request. Is there any known issue? Have I done an mistake? [#|2010-03-22T10:40:54.150+0000|INFO|sun-appserver2.1|javax.enterprise.system.core|_ThreadID=10;_ThreadName=main;|Starting Sun GlassFish Enterprise Server v2.1.1 ((v2.1 Patch06)(9.1_02 Patch12)) (build b31g-fcs) ...|#] ... [#|2010-03-22T11:18:44.220+0000|FINE|sun-appserver2.1|mypackage.module.security.auth.realm.YaJdbcRealm|_ThreadID=26;_ThreadName=httpSSLWorkerThread-8080-1;ClassName=mypackage.module.security.auth.realm.YaJdbcRealm;MethodName=authenticate;_RequestID=4d8f23e9-5106-4d64-b865-1638d7075bde;|JDBC authenticate successful for: 8002 groups:[roleUser]|#] [#|2010-03-22T11:18:44.220+0000|FINE|sun-appserver2.1|mypackage.module.security.auth.login.YaJdbcLoginModule|_ThreadID=26;_ThreadName=httpSSLWorkerThread-8080-1;ClassName=mypackage.module.security.auth.login.YaJdbcLoginModule;MethodName=authenticate;_RequestID=4d8f23e9-5106-4d64-b865-1638d7075bde;|JDBC login succeeded for: 8002 groups:[roleUser]|#] [#|2010-03-22T11:18:44.220+0000|FINE|sun-appserver2.1|mypackage.module.security.auth.realm.YaJdbcRealm|_ThreadID=39;_ThreadName=httpSSLWorkerThread-8080-2;ClassName=mypackage.module.security.auth.realm.YaJdbcRealm;MethodName=authenticate;_RequestID=4ca7e3e5-5ab7-41ec-b3c9-d9260b1164c9;|JDBC authenticate successful for: 8002 groups:[roleUser]|#] [#|2010-03-22T11:18:44.220+0000|FINE|sun-appserver2.1|mypackage.module.security.auth.login.YaJdbcLoginModule|_ThreadID=39;_ThreadName=httpSSLWorkerThread-8080-2;ClassName=mypackage.module.security.auth.login.YaJdbcLoginModule;MethodName=authenticate;_RequestID=4ca7e3e5-5ab7-41ec-b3c9-d9260b1164c9;|JDBC login succeeded for: 8002 groups:[roleUser]|#] [#|2010-03-22T11:18:44.220+0000|FINE|sun-appserver2.1|mypackage.MyWebService|_ThreadID=26;_ThreadName=httpSSLWorkerThread-8080-1;ClassName=mypackage.MyWebService;MethodName=enqueue;_RequestID=4d8f23e9-5106-4d64-b865-1638d7075bde;|Received WebService call to enqueue() from client 59|#] [#|2010-03-22T11:18:44.220+0000|FINE|sun-appserver2.1|mypackage.MyWebService|_ThreadID=39;_ThreadName=httpSSLWorkerThread-8080-2;ClassName=mypackage.MyWebService;MethodName=enqueue;_RequestID=4ca7e3e5-5ab7-41ec-b3c9-d9260b1164c9;|Received WebService call to enqueue() from client 59|#] ... [#|2010-03-22T11:18:44.267+0000|FINE|sun-appserver2.1|mypackage.MyWebService|_ThreadID=26;_ThreadName=httpSSLWorkerThread-8080-1;ClassName=mypackage.MyWebService;MethodName=enqueue;_RequestID=4d8f23e9-5106-4d64-b865-1638d7075bde;|Successfully finished WebService call to enqueue() from client 59|#] [#|2010-03-22T11:18:44.329+0000|WARNING|sun-appserver2.1|javax.enterprise.system.container.ejb|_ThreadID=26;_ThreadName=httpSSLWorkerThread-8080-1;_RequestID=4d8f23e9-5106-4d64-b865-1638d7075bde;|invocation error on ejb endpoint MyWebService at /MyWebserviceService/MyWebservice : com.sun.xml.stream.XMLStreamException2 javax.xml.ws.WebServiceException: com.sun.xml.stream.XMLStreamException2 at com.sun.xml.ws.encoding.StreamSOAPCodec.encode(StreamSOAPCodec.java:111) at com.sun.xml.ws.encoding.SOAPBindingCodec.encode(SOAPBindingCodec.java:281) at com.sun.xml.ws.transport.http.HttpAdapter.encodePacket(HttpAdapter.java:320) at com.sun.xml.ws.transport.http.HttpAdapter.access$100(HttpAdapter.java:93) at com.sun.xml.ws.transport.http.HttpAdapter$HttpToolkit.handle(HttpAdapter.java:454) at com.sun.xml.ws.transport.http.HttpAdapter.handle(HttpAdapter.java:244) at com.sun.xml.ws.transport.http.servlet.ServletAdapter.handle(ServletAdapter.java:135) at com.sun.enterprise.webservice.Ejb3MessageDispatcher.handlePost(Ejb3MessageDispatcher.java:113) at com.sun.enterprise.webservice.Ejb3MessageDispatcher.invoke(Ejb3MessageDispatcher.java:87) at com.sun.enterprise.webservice.EjbWebServiceServlet.dispatchToEjbEndpoint(EjbWebServiceServlet.java:231) at com.sun.enterprise.webservice.EjbWebServiceServlet.service(EjbWebServiceServlet.java:157) at javax.servlet.http.HttpServlet.service(HttpServlet.java:847) at com.sun.enterprise.web.AdHocContextValve.invoke(AdHocContextValve.java:114) at org.apache.catalina.core.StandardPipeline.doInvoke(StandardPipeline.java:648) at org.apache.catalina.core.StandardPipeline.doInvoke(StandardPipeline.java:593) at org.apache.catalina.core.StandardPipeline.invoke(StandardPipeline.java:587) at com.sun.enterprise.web.WebPipeline.invoke(WebPipeline.java:87) at org.apache.catalina.core.StandardHostValve.invoke(StandardHostValve.java:222) at org.apache.catalina.core.StandardPipeline.doInvoke(StandardPipeline.java:648) at org.apache.catalina.core.StandardPipeline.doInvoke(StandardPipeline.java:593) at org.apache.catalina.core.StandardPipeline.invoke(StandardPipeline.java:587) at org.apache.catalina.core.ContainerBase.invoke(ContainerBase.java:1093) at org.apache.catalina.core.StandardEngineValve.invoke(StandardEngineValve.java:166) at org.apache.catalina.core.StandardPipeline.doInvoke(StandardPipeline.java:648) at org.apache.catalina.core.StandardPipeline.doInvoke(StandardPipeline.java:593) at org.apache.catalina.core.StandardPipeline.invoke(StandardPipeline.java:587) at org.apache.catalina.core.ContainerBase.invoke(ContainerBase.java:1093) at org.apache.coyote.tomcat5.CoyoteAdapter.service(CoyoteAdapter.java:291) at com.sun.enterprise.web.connector.grizzly.DefaultProcessorTask.invokeAdapter(DefaultProcessorTask.java:666) at com.sun.enterprise.web.connector.grizzly.comet.CometEngine.executeServlet(CometEngine.java:616) at com.sun.enterprise.web.connector.grizzly.comet.CometEngine.handle(CometEngine.java:362) at com.sun.enterprise.web.connector.grizzly.comet.CometAsyncFilter.doFilter(CometAsyncFilter.java:84) at com.sun.enterprise.web.connector.grizzly.async.DefaultAsyncExecutor.invokeFilters(DefaultAsyncExecutor.java:189) at com.sun.enterprise.web.connector.grizzly.async.DefaultAsyncExecutor.interrupt(DefaultAsyncExecutor.java:164) at com.sun.enterprise.web.connector.grizzly.async.AsyncProcessorTask.doTask(AsyncProcessorTask.java:92) at com.sun.enterprise.web.connector.grizzly.TaskBase.run(TaskBase.java:264) at com.sun.enterprise.web.connector.grizzly.ssl.SSLWorkerThread.run(SSLWorkerThread.java:106) Caused by: com.sun.xml.stream.XMLStreamException2 at com.sun.xml.stream.writers.XMLStreamWriterImpl.flush(XMLStreamWriterImpl.java:416) at com.sun.xml.ws.encoding.StreamSOAPCodec.encode(StreamSOAPCodec.java:109) ... 36 more Caused by: ClientAbortException: java.nio.channels.ClosedChannelException at org.apache.coyote.tomcat5.OutputBuffer.doFlush(OutputBuffer.java:385) at org.apache.coyote.tomcat5.OutputBuffer.flush(OutputBuffer.java:351) at org.apache.coyote.tomcat5.CoyoteOutputStream.flush(CoyoteOutputStream.java:176) at com.sun.xml.stream.writers.UTF8OutputStreamWriter.flush(UTF8OutputStreamWriter.java:153) at com.sun.xml.stream.writers.XMLStreamWriterImpl.flush(XMLStreamWriterImpl.java:414) ... 37 more Caused by: java.nio.channels.ClosedChannelException at sun.nio.ch.SocketChannelImpl.ensureWriteOpen(SocketChannelImpl.java:126) at sun.nio.ch.SocketChannelImpl.write(SocketChannelImpl.java:324) at com.sun.enterprise.web.connector.grizzly.OutputWriter.flushChannel(OutputWriter.java:91) at com.sun.enterprise.web.connector.grizzly.OutputWriter.flushChannel(OutputWriter.java:66) at com.sun.enterprise.web.connector.grizzly.SocketChannelOutputBuffer.flushChannel(SocketChannelOutputBuffer.java:172) at com.sun.enterprise.web.connector.grizzly.async.AsynchronousOutputBuffer.flushChannel(AsynchronousOutputBuffer.java:81) at com.sun.enterprise.web.connector.grizzly.SocketChannelOutputBuffer.flushBuffer(SocketChannelOutputBuffer.java:205) at com.sun.enterprise.web.connector.grizzly.async.AsynchronousOutputBuffer.flushBuffer(AsynchronousOutputBuffer.java:114) at com.sun.enterprise.web.connector.grizzly.SocketChannelOutputBuffer.flush(SocketChannelOutputBuffer.java:183) at com.sun.enterprise.web.connector.grizzly.async.AsynchronousOutputBuffer.flush(AsynchronousOutputBuffer.java:104) at com.sun.enterprise.web.connector.grizzly.DefaultProcessorTask.action(DefaultProcessorTask.java:1100) at org.apache.coyote.Response.action(Response.java:237) at org.apache.coyote.tomcat5.OutputBuffer.doFlush(OutputBuffer.java:381) ... 41 more |#] [#|2010-03-22T11:18:44.376+0000|WARNING|sun-appserver2.1|oracle.toplink.essentials.session.file:/mygf-211/domains/mydomain/applications/j2ee-apps/myear/myjar-myPu|_ThreadID=39;_ThreadName=httpSSLWorkerThread-8080-2;_RequestID=4ca7e3e5-5ab7-41ec-b3c9-d9260b1164c9;| Local Exception Stack: Exception [TOPLINK-4002] (Oracle TopLink Essentials - 2.1 (Build b31g-fcs (10/19/2009))): oracle.toplink.essentials.exceptions.DatabaseException Internal Exception: com.microsoft.sqlserver.jdbc.SQLServerException: Eine Zeile mit doppeltem Schlüssel kann in das 'dbo.MY_TABLE'-Objekt mit dem eindeutigen 'MY_INDEX'-Index nicht eingefügt werden.

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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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  • 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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  • 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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  • ADO.NET zombie transaction bug? How to ensure that commands will not be executed on implicit transac

    - by TN
    e.g. When deadlock occurs, following SQL commands are successfully executed, even if they have assigned SQL transaction that is after rollback. It seems, it is caused by a new implicit transaction that is created on SQL Server. Someone could expect that ADO.NET would throw an exception that the commands are being executed on a zombie transaction. However, such exception is not thrown. (I think this is a bug in ASP.NET.) Moreover, because of zombie transaction the final Dispose() silently ignores the rollback. Any ideas, how can I ensure that nobody can execute commands on implicit transaction? Or, how to check that transaction is zombie? I found that Commit() and Rollback() check for zombie transaction, however I can call them for a test:) I also found that also reading IsolationLevel will do the check, but I am not sure whether simple calling transaction.IsolationLevel.ToString(); will not be removed by a future optimizer. Or do you know any other safe way invoke a getter (without using reflection or IL emitting)?

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  • C# vs C - Big performance difference

    - by John
    I'm finding massive performance differences between similar code in C anc C#. The C code is: #include <stdio.h> #include <time.h> #include <math.h> main() { int i; double root; clock_t start = clock(); for (i = 0 ; i <= 100000000; i++){ root = sqrt(i); } printf("Time elapsed: %f\n", ((double)clock() - start) / CLOCKS_PER_SEC); } And the C# (console app) is: using System; using System.Collections.Generic; using System.Text; namespace ConsoleApplication2 { class Program { static void Main(string[] args) { DateTime startTime = DateTime.Now; double root; for (int i = 0; i <= 100000000; i++) { root = Math.Sqrt(i); } TimeSpan runTime = DateTime.Now - startTime; Console.WriteLine("Time elapsed: " + Convert.ToString(runTime.TotalMilliseconds/1000)); } } } With the above code, the C# completes in 0.328125 seconds (release version) and the C takes 11.14 seconds to run. The c is being compiled to a windows executable using mingw. I've always been under the assumption that C/C++ were faster or at least comparable to C#.net. What exactly is causing the C to run over 30 times slower? EDIT: It does appear that the C# optimizer was removing the root as it wasn't being used. I changed the root assignment to root += and printed out the total at the end. I've also compiled the C using cl.exe with the /O2 flag set for max speed. The results are now: 3.75 seconds for the C 2.61 seconds for the C# The C is still taking longer, but this is acceptable

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  • Upload using python script takes very long on one laptop as compared to another

    - by Engr Am
    I have a python 2.7 code which uses STORBINARY function for uploading files to an ftp server and RETRBINARY for downloading from this server. However, the issue is the upload is taking a very long time on three laptops from different brands as compared to a Dell laptop. The strange part is when I manually upload any file, it takes the same time on all the systems. The manual upload rate and upload rate with the python script is the same on the Dell Laptop. However, on every other brand of laptop (I have tried with IBM, Toshiba, Fujitsu-Siemens) the python script has a very low upload rate than the manual attempt. Also, on all these other laptops, the upload rate using the python script is the same (1Mbit/s) while the manual upload rate is approx. 8 Mbit/s. I have tried to vary the filesize for the upload to no avail. TCP Optimizer improved the download rate on all the systems but had no effect on the upload rate. Download rate using this script on all the systems is fine and same as the manual download rate. I have checked the server and it has more than 90% free space. The network connection is the same for all the laptops, and I try uploading only with one laptop at a time. All the laptops have almost the same system configurations, same operating system and approximately the same free drive space. If anything the Dell laptop is a little less in terms of processing power and RAM than 2 of the others, but I suppose this has no effect as I have checked many times to see how much was the CPU usage and network usage during these uploads and downloads, and I am sure that no other virus or program has been eating up my bandwidth. Here is the code ('ftp' and 'file_path' are inputs to the function): path,filename=os.path.split(file_path) filesize=os.path.getsize(file_path) deffilesize=(filesize/1024)/1024 f = open(file_path, "rb") upstart = time.clock() print ftp.storbinary("STOR "+filename, f) upende = time.clock()-upstart outname="Upload " f.close() return upende, deffilesize, outname

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  • How can I update a record using a correlated subquery?

    - by froadie
    I have a function that accepts one parameter and returns a table/resultset. I want to set a field in a table to the first result of that recordset, passing in one of the table's other fields as the parameter. If that's too complicated in words, the query looks something like this: UPDATE myTable SET myField = (SELECT TOP 1 myFunctionField FROM fn_doSomething(myOtherField) WHERE someCondition = 'something') WHERE someOtherCondition = 'somethingElse' In this example, myField and myOtherField are fields in myTable, and myFunctionField is a field return by fn_doSomething. This seems logical to me, but I'm getting the following strange error: 'myOtherField' is not a recognized OPTIMIZER LOCK HINTS option. Any idea what I'm doing wrong, and how I can accomplish this? *UPDATE: * Based on Anil Soman's answer, I realized that the function is expecting a string parameter and the field being passed is an integer. I'm not sure if this should be a problem as an explicit call to the function using an integer value works - e.g. fn_doSomething(12345) seems to automatically cast the number to an string. However, I tried to do an explicit cast: UPDATE myTable SET myField = (SELECT TOP 1 myFunctionField FROM fn_doSomething(CAST(myOtherField AS varchar(1000))) WHERE someCondition = 'something') WHERE someOtherCondition = 'somethingElse' Now I'm getting the following error: Line 5: Incorrect syntax near '('.

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