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• Worker process reached its allowed processing time

  - by Confused

  We are experiencing this issue approximately once a month. It is very hard to pinpoint the cause so any help would be appreciated. This causes the App pool to stop and brings the site down. We have gone through all log files and have concluded nothing. We are using the 2.0.3 version on IIS 6.

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• C# Process flow - Datastream, XML and datagrid

  - by Farstucker

  Im looking for some advice/suggestions on how I should setup the work flow of a small application Im building. When the application is launched the datagrid will be populated via the XML file. Once running the application will receive a datastream that I hope to update the file and datagrid. So Im curious what you would suggest on how I setup the workflow (ie, split the data from the data stream and simultaneously populate the file and grid or would you suggest populating the XML file first and setting up a timer to have the grid read the file?) Im really looking for optimal performance.

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• Excel process not ending in Cluster environment

  - by Vasanth

  When we try to close excel object, it fails to close to cluster environment. The same is working fine in QA and UAT environment. public bool KillExcelProcess() { try { object misValue = System.Reflection.Missing.Value; wbObj.Save(); wbObj.Close(true, misValue, misValue); appC.Workbooks.Close(); appC.Quit(); System.Runtime.InteropServices.Marshal.ReleaseComObject(objSheet); System.Runtime.InteropServices.Marshal.ReleaseComObject(wbObj); System.Runtime.InteropServices.Marshal.ReleaseComObject(appC); wbObj = null; appC = null; } catch (Exception ex) { //throw ex; } finally { System.Threading.Thread.Sleep(5000); GC.Collect(); } return true; Calling function #endregion try { log.Info("CloseExcelService (MeasureSavingsComputeBO) Starts ..."); exConverter.KillExcelProcess(); while (true) { try { File.Delete(strFilename); break; } catch (Exception ex) { } }

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• simple process rollback question

  - by OckhamsRazor

  hi folks! while revising for an exam, i came across this simple question asking about rollbacks in processes. i understand how rollbacks occur, but i need some validation on my answer. The question: my confusion results from the fact that there is interprocess communication between the processes. does that change anything in terms of where to rollback? my answer would be R13, R23, R32 and R43. any help is greatly appreciated! thanks!

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• Measuring CPU clocks consumed by a process

  - by hasanatkazmi

  Hi, I have written a program in C. Its a program created as result of a research. I want to compute exact CPU cycles which program consumes. Exact number of cycles. Any idea how can I find that?

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• Finding process count in Linux via command line

  - by Moev4

  I was looking for the best way to find the number of running processes with the same name via the command line in Linux. For example if I wanted to find the number of bash processes running and get "5". Currently I have a script that does a 'pidof ' and then does a count on the tokenized string. This works fine but I was wondering if there was a better way that can be done entirely via the command line. Thanks in advance for your help.

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• Linux process memory consumption in bytes (not Kbytes)

  - by Rui

  In Linux is there any way to check processes memory measured on bytes (using top or ps for example). Not in kbytes, but bytes. Thanks in advance!

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• Deployment process

  - by Balaji

  We are having a massive system having around 15 servers hosting .Net WCF services, mvc application etc. When we do a deployment (out of office hours) we have to uninstall and install everything on the live servers. This takes lot of time and if something goes wrong we have to rollback everything. can you please suggest something different to this? like Deply into a other environment (whenever you like) and switch the URL to point to new servers [This comes with the overhead of cost of maintaining 2 copies of production (active and passive)] any other ideas please.

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• How to permanently "renice" a process on Mac OS X (or iOS, etc)?

  - by mralexgray

  I use a nice (free) process manager called ATMonitor for Mac OS X that has a lot of cool hidden features... one of which is being able to click on a running process.. and set the "renice" from +20 (less priority) to -20 (highest priority). The best part.... it sticks between restarts... SO you want XYZ to get full attention all the time.. you set it once and it's done... I want to do the same thing (renice a process) on an iPad running a particular daemon.. and I don't know how to set a renice permanently. I can do it once, and it works fine... But the setting is lost on a reboot. I read somewhere.. Now, as for permanently resetting the priority of a process, this can't be done directly. You can fake it, however, with a shell script that starts the app and then immediately renice's it. Give that script a ".command" extension and it will be double-clickable in the GUI. Not very elegant, but it gets the job done. But as it says.. not very elegant, and I dont think this is how ATMonitor does it.... I found this thread.... http://superuser.com and they gave a way to do it as a launch argument, but no apparent way to save it as a persistent value... for instance - if the program wasn't going to be started by launchd... How do I set a permanent renice level, per executable binary, independent of it's PID, when, how or why it was launched?

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• how i can identify which process is making UDP traffic on linux?

  - by boos

  my machine is continously making udp dns traffic request. what i need to know is the PID of the process generating this traffic. The normal way in TCP connection is to use netstat/lsof and get the process associated at the pid. Is UDP the connection is stateles, so, when i call netastat/lsof i can see it only if the UDP socket is opened and it's sending traffic. I have tried with lsof -i UDP and with nestat -anpue but i cant be able to find wich process is doing that request because i need to call lsof/netstat exactly when the udp traffic is sended, if i call lsof/netstat before/after the udp datagram is sended is impossible to view the opened UDP socket. call netstat/lsof exactly when 3/4 udp packet is sended is IMPOSSIBLE. how i can identify the infamous process ? I have already inspected the traffic to try to identify the sended PID from the content of the packet, but is not possible to identify it from the contect of the traffic. anyone can help me ? I'm root on this machine FEDORA 12 Linux noise.company.lan 2.6.32.16-141.fc12.x86_64 #1 SMP Wed Jul 7 04:49:59 UTC 2010 x86_64 x86_64 x86_64 GNU/Linux

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• Windows XP Domain Logon takes between 40 - 60 minutes

  - by Bryan

  Windows XP Clients, fully patched, with Symantec Endpoint Protection 11 client Windows 2008 R2 domain Roaming profiles Folder Redirection applied to Documents, AppData & Desktop I've enabled userenv logging, and logged on just after 17:00 last night. The user shell hadn't appeared at 17:45 when I left last night. When I arrived this morning, I checked the log file and found the following. USERENV(3f8.e7c) 17:02:18:296 LogExtSessionStatus: Successfully logged Extension Session data USERENV(654.a30) 17:04:09:468 ImpersonateUser: Failed to impersonate user with 5. USERENV(654.a30) 17:04:09:468 GetUserNameAndDomain Failed to impersonate user USERENV(654.a30) 17:04:09:468 GetUserDNSDomainName: Domain name is NT Authority. No DNS domain name available. USERENV(c8c.cb8) 17:04:09:781 LibMain: Process Name: C:\Program Files\Symantec\Symantec Endpoint Protection\SescLU.exe USERENV(cd0.cd4) 17:04:10:781 LibMain: Process Name: C:\PROGRA~1\Symantec\LIVEUP~1\LUCOMS~1.EXE USERENV(d08.c84) 17:07:09:609 LibMain: Process Name: C:\Program Files\Symantec\Symantec Endpoint Protection\SescLU.exe USERENV(cbc.cc0) 17:07:10:625 LibMain: Process Name: C:\Program Files\Symantec\LiveUpdate\luall.exe USERENV(db0.db4) 17:07:10:781 LibMain: Process Name: C:\PROGRA~1\Symantec\LIVEUP~1\LUCOMS~1.EXE USERENV(e00.e0c) 17:07:11:062 LibMain: Process Name: C:\Program Files\Symantec\LiveUpdate\LuCallbackProxy.exe USERENV(e20.e34) 17:07:11:203 LibMain: Process Name: C:\Program Files\Symantec\LiveUpdate\LuCallbackProxy.exe USERENV(e40.e50) 17:07:11:406 LibMain: Process Name: C:\Program Files\Symantec\LiveUpdate\LuCallbackProxy.exe USERENV(efc.54c) 17:07:11:656 LibMain: Process Name: C:\Program Files\Symantec\LiveUpdate\LuCallbackProxy.exe USERENV(ccc.df0) 17:08:45:687 LibMain: Process Name: C:\Program Files\Symantec\Symantec Endpoint Protection\SescLU.exe USERENV(e24.e20) 17:08:45:937 LibMain: Process Name: C:\Program Files\Symantec\LiveUpdate\luall.exe USERENV(ff0.ff4) 17:08:46:078 LibMain: Process Name: C:\PROGRA~1\Symantec\LIVEUP~1\LUCOMS~1.EXE USERENV(32c.cd0) 17:08:46:265 LibMain: Process Name: C:\Program Files\Symantec\LiveUpdate\LuCallbackProxy.exe USERENV(cc4.3d4) 17:08:46:406 LibMain: Process Name: C:\Program Files\Symantec\LiveUpdate\LuCallbackProxy.exe USERENV(434.4d0) 17:08:46:593 LibMain: Process Name: C:\Program Files\Symantec\LiveUpdate\LuCallbackProxy.exe USERENV(f2c.ac) 17:08:46:828 LibMain: Process Name: C:\Program Files\Symantec\LiveUpdate\LuCallbackProxy.exe USERENV(d60.d7c) 17:09:40:265 LibMain: Process Name: C:\Program Files\Symantec\Symantec Endpoint Protection\SescLU.exe USERENV(d94.d98) 17:09:40:531 LibMain: Process Name: C:\PROGRA~1\Symantec\LIVEUP~1\LUCOMS~1.EXE USERENV(bc4.3c4) 17:10:52:765 LibMain: Process Name: C:\Program Files\Symantec\Symantec Endpoint Protection\SescLU.exe USERENV(37c.90c) 17:10:52:984 LibMain: Process Name: C:\Program Files\Symantec\LiveUpdate\luall.exe USERENV(580.540) 17:10:53:109 LibMain: Process Name: C:\PROGRA~1\Symantec\LIVEUP~1\LUCOMS~1.EXE USERENV(c18.c30) 17:10:53:312 LibMain: Process Name: C:\Program Files\Symantec\LiveUpdate\LuCallbackProxy.exe USERENV(c44.288) 17:10:53:468 LibMain: Process Name: C:\Program Files\Symantec\LiveUpdate\LuCallbackProxy.exe USERENV(a34.cf4) 17:10:53:656 LibMain: Process Name: C:\Program Files\Symantec\LiveUpdate\LuCallbackProxy.exe USERENV(d3c.d4c) 17:10:53:890 LibMain: Process Name: C:\Program Files\Symantec\LiveUpdate\LuCallbackProxy.exe USERENV(970.948) 17:15:09:468 LibMain: Process Name: C:\Program Files\Symantec\Symantec Endpoint Protection\SescLU.exe USERENV(150.9dc) 17:15:09:734 LibMain: Process Name: C:\PROGRA~1\Symantec\LIVEUP~1\LUCOMS~1.EXE USERENV(f90.cec) 17:20:38:718 LibMain: Process Name: C:\Program Files\Symantec\Symantec Endpoint Protection\SescLU.exe USERENV(d8c.d70) 17:20:38:984 LibMain: Process Name: C:\PROGRA~1\Symantec\LIVEUP~1\LUCOMS~1.EXE USERENV(9a0.fa0) 17:26:07:953 LibMain: Process Name: C:\Program Files\Symantec\Symantec Endpoint Protection\SescLU.exe USERENV(844.51c) 17:26:08:218 LibMain: Process Name: C:\PROGRA~1\Symantec\LIVEUP~1\LUCOMS~1.EXE USERENV(d00.9ac) 17:31:19:453 LibMain: Process Name: C:\Program Files\Symantec\Symantec Endpoint Protection\SescLU.exe USERENV(ad4.624) 17:31:19:718 LibMain: Process Name: C:\PROGRA~1\Symantec\LIVEUP~1\LUCOMS~1.EXE USERENV(654.694) 17:31:46:390 ImpersonateUser: Failed to impersonate user with 5. USERENV(654.694) 17:31:46:390 GetUserNameAndDomain Failed to impersonate user USERENV(654.694) 17:31:46:390 GetUserDNSDomainName: Domain name is NT Authority. No DNS domain name available. USERENV(af8.610) 17:36:48:625 LibMain: Process Name: C:\Program Files\Symantec\Symantec Endpoint Protection\SescLU.exe USERENV(aa4.dfc) 17:36:48:906 LibMain: Process Name: C:\PROGRA~1\Symantec\LIVEUP~1\LUCOMS~1.EXE USERENV(2dc.5c8) 17:42:17:812 LibMain: Process Name: C:\Program Files\Symantec\Symantec Endpoint Protection\SescLU.exe USERENV(f70.8ac) 17:42:18:078 LibMain: Process Name: C:\PROGRA~1\Symantec\LIVEUP~1\LUCOMS~1.EXE USERENV(d50.c30) 17:47:47:062 LibMain: Process Name: C:\Program Files\Symantec\Symantec Endpoint Protection\SescLU.exe USERENV(c2c.c3c) 17:47:47:328 LibMain: Process Name: C:\PROGRA~1\Symantec\LIVEUP~1\LUCOMS~1.EXE USERENV(ef0.4cc) 17:53:16:234 LibMain: Process Name: C:\Program Files\Symantec\Symantec Endpoint Protection\SescLU.exe USERENV(cd4.c84) 17:53:16:500 LibMain: Process Name: C:\PROGRA~1\Symantec\LIVEUP~1\LUCOMS~1.EXE USERENV(828.8c4) 17:58:45:484 LibMain: Process Name: C:\Program Files\Symantec\Symantec Endpoint Protection\SescLU.exe USERENV(a24.b30) 17:58:45:750 LibMain: Process Name: C:\PROGRA~1\Symantec\LIVEUP~1\LUCOMS~1.EXE I've seen posts suggesting that it may be Windows Desktop Search 3.01 that is causing this, so I've removed that. I've removed the policy, 'Always wait for the network at startup or logon', thinking that might have helped. I'm running out of ideas. Has anyone seen this before?

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• ParallelWork: Feature rich multithreaded fluent task execution library for WPF

  - by oazabir

  ParallelWork is an open source free helper class that lets you run multiple work in parallel threads, get success, failure and progress update on the WPF UI thread, wait for work to complete, abort all work (in case of shutdown), queue work to run after certain time, chain parallel work one after another. It’s more convenient than using .NET’s BackgroundWorker because you don’t have to declare one component per work, nor do you need to declare event handlers to receive notification and carry additional data through private variables. You can safely pass objects produced from different thread to the success callback. Moreover, you can wait for work to complete before you do certain operation and you can abort all parallel work while they are in-flight. If you are building highly responsive WPF UI where you have to carry out multiple job in parallel yet want full control over those parallel jobs completion and cancellation, then the ParallelWork library is the right solution for you. I am using the ParallelWork library in my PlantUmlEditor project, which is a free open source UML editor built on WPF. You can see some realistic use of the ParallelWork library there. Moreover, the test project comes with 400 lines of Behavior Driven Development flavored tests, that confirms it really does what it says it does. The source code of the library is part of the “Utilities” project in PlantUmlEditor source code hosted at Google Code. The library comes in two flavors, one is the ParallelWork static class, which has a collection of static methods that you can call. Another is the Start class, which is a fluent wrapper over the ParallelWork class to make it more readable and aesthetically pleasing code. ParallelWork allows you to start work immediately on separate thread or you can queue a work to start after some duration. You can start an immediate work in a new thread using the following methods: void StartNow(Action doWork, Action onComplete) void StartNow(Action doWork, Action onComplete, Action<Exception> failed) For example, ParallelWork.StartNow(() => { workStartedAt = DateTime.Now; Thread.Sleep(howLongWorkTakes); }, () => { workEndedAt = DateTime.Now; }); Or you can use the fluent way Start.Work: Start.Work(() => { workStartedAt = DateTime.Now; Thread.Sleep(howLongWorkTakes); }) .OnComplete(() => { workCompletedAt = DateTime.Now; }) .Run(); Besides simple execution of work on a parallel thread, you can have the parallel thread produce some object and then pass it to the success callback by using these overloads: void StartNow<T>(Func<T> doWork, Action<T> onComplete) void StartNow<T>(Func<T> doWork, Action<T> onComplete, Action<Exception> fail) For example, ParallelWork.StartNow<Dictionary<string, string>>( () => { test = new Dictionary<string,string>(); test.Add("test", "test"); return test; }, (result) => { Assert.True(result.ContainsKey("test")); }); Or, the fluent way: Start<Dictionary<string, string>>.Work(() => { test = new Dictionary<string, string>(); test.Add("test", "test"); return test; }) .OnComplete((result) => { Assert.True(result.ContainsKey("test")); }) .Run(); You can also start a work to happen after some time using these methods: DispatcherTimer StartAfter(Action onComplete, TimeSpan duration) DispatcherTimer StartAfter(Action doWork,Action onComplete,TimeSpan duration) You can use this to perform some timed operation on the UI thread, as well as perform some operation in separate thread after some time. ParallelWork.StartAfter( () => { workStartedAt = DateTime.Now; Thread.Sleep(howLongWorkTakes); }, () => { workCompletedAt = DateTime.Now; }, waitDuration); Or, the fluent way: Start.Work(() => { workStartedAt = DateTime.Now; Thread.Sleep(howLongWorkTakes); }) .OnComplete(() => { workCompletedAt = DateTime.Now; }) .RunAfter(waitDuration);   There are several overloads of these functions to have a exception callback for handling exceptions or get progress update from background thread while work is in progress. For example, I use it in my PlantUmlEditor to perform background update of the application. // Check if there's a newer version of the app Start<bool>.Work(() => { return UpdateChecker.HasUpdate(Settings.Default.DownloadUrl); }) .OnComplete((hasUpdate) => { if (hasUpdate) { if (MessageBox.Show(Window.GetWindow(me), "There's a newer version available. Do you want to download and install?", "New version available", MessageBoxButton.YesNo, MessageBoxImage.Information) == MessageBoxResult.Yes) { ParallelWork.StartNow(() => { var tempPath = System.IO.Path.Combine( Environment.GetFolderPath(Environment.SpecialFolder.ApplicationData), Settings.Default.SetupExeName); UpdateChecker.DownloadLatestUpdate(Settings.Default.DownloadUrl, tempPath); }, () => { }, (x) => { MessageBox.Show(Window.GetWindow(me), "Download failed. When you run next time, it will try downloading again.", "Download failed", MessageBoxButton.OK, MessageBoxImage.Warning); }); } } }) .OnException((x) => { MessageBox.Show(Window.GetWindow(me), x.Message, "Download failed", MessageBoxButton.OK, MessageBoxImage.Exclamation); }); The above code shows you how to get exception callbacks on the UI thread so that you can take necessary actions on the UI. Moreover, it shows how you can chain two parallel works to happen one after another. Sometimes you want to do some parallel work when user does some activity on the UI. For example, you might want to save file in an editor while user is typing every 10 second. In such case, you need to make sure you don’t start another parallel work every 10 seconds while a work is already queued. You need to make sure you start a new work only when there’s no other background work going on. Here’s how you can do it: private void ContentEditor_TextChanged(object sender, EventArgs e) { if (!ParallelWork.IsAnyWorkRunning()) { ParallelWork.StartAfter(SaveAndRefreshDiagram, TimeSpan.FromSeconds(10)); } } If you want to shutdown your application and want to make sure no parallel work is going on, then you can call the StopAll() method. ParallelWork.StopAll(); If you want to wait for parallel works to complete without a timeout, then you can call the WaitForAllWork(TimeSpan timeout). It will block the current thread until the all parallel work completes or the timeout period elapses. result = ParallelWork.WaitForAllWork(TimeSpan.FromSeconds(1)); The result is true, if all parallel work completed. If it’s false, then the timeout period elapsed and all parallel work did not complete. For details how this library is built and how it works, please read the following codeproject article: ParallelWork: Feature rich multithreaded fluent task execution library for WPF http://www.codeproject.com/KB/WPF/parallelwork.aspx If you like the article, please vote for me.

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• Complex type support in process flow &ndash; XMLTYPE

  - by shawn

      Before OWB 11.2 release, there are only 5 simple data types supported in process flow: DATE, BOOLEAN, INTEGER, FLOAT and STRING. A new complex data type – XMLTYPE is added in 11.2, in order to support complex data being passed between the process flow activities. In this article we will give a simple example to illustrate the usage of the new type and some related editors.     Suppose there is a bookstore that uses XML format orders as shown below (we use the simplest form for the illustration purpose), then we can create a process flow to handle the order, take the order as the input, then extract necessary information, and generate a confirmation email to the customer automatically. <order id=’0001’>     <customer>         <name>Tom</name>         <email>[email protected]</email>     </customer>     <book id=’Java_001’>         <quantity>3</quantity>     </book> </order>     Considering a simple user case here: we use an input parameter/variable with XMLTYPE to hold the XML content of the order; then we can use an Assign activity to retrieve the email info from the order; after that, we can create an email activity to send the email (Other activities might be added in practical case, but will not be described here). 1) Set XML content value     For testing purpose, we will create a variable to hold the sample order, and then this will be used among the process flow activities. When the variable is of XMLTYPE and the “Literal” value is set the true, the advance editor will be enabled.     Click the “Advance Editor” shown as above, a simple xml editor will popup. The editor has basic features like syntax highlight and check as shown below:     We can also do the basic validation or validation against schema with the editor by selecting the normalized schema. With this, it will be easier to provide the value for XMLTYPE variables. 2) Extract information from XML content     After setting the value, we need to extract the email information with the Assign activity. In process flow, an enhanced expression builder is used to help users construct the XPath for extracting values from XML content. When the variable’s literal value is set the false, the advance editor is enabled.     Click the button, the advance editor will popup, as shown below:     The editor is based on the expression builder (which is often used in mapping etc), an XPath lib panel is appended which provides some help information on how to write the XPath. The expression used here is: “XMLTYPE.EXTRACT(XML_ORDER,'/order/customer/email/text()').getStringVal()”, which uses ‘/order/customer/email/text()’ as the XPath to extract the email info from the XML document.     A variable called “EMAIL_ADDR” is created with String data type to hold the value extracted.     Then we bind the “VARIABLE” parameter of Assign activity to “EMAIL_ADDR” variable, which means the value of the “EMAIL_ADDR” activity will be set to the result of the “VALUE” parameter of Assign activity. 3) Use the extracted information in Email activity     We bind the “TO_ADDRESS” parameter of the email activity to the “EMAIL_ADDR” variable created in above step.     We can also extract other information from the xml order directly through the expression, for example, we can set the “MESSAGE_BODY” with value “'Dear '||XMLTYPE.EXTRACT(XML_ORDER,'/order/customer/name/text()').getStringVal()||chr(13)||chr(10)||'   You have ordered '||XMLTYPE.EXTRACT(XML_ORDER,'/order/book/quantity/text()').getStringVal()||' '||XMLTYPE.EXTRACT(XML_ORDER,'/order/book/@id').getStringVal()”. This expression will extract the customer name, the quantity and the book id from the order to compose the message body.     To make the email activity work, we need provide some other necessary information, Such as “SMTP_SERVER” (which is the SMTP server used to send the emails, like “mail.bookstore.com”. The default PORT number is set to 25. You need to change the value accordingly), “FROM_ADDRESS” and “SUBJECT”. Then the process flow is ready to go.     After deploying the process flow package, we can simply run the process flow to check if the result is as expected (An email will be sent to the specified email address with proper subject and message body).     Note: In oracle 11g, there is an enhanced security feature - ACL (Access Control List), which restrict the network access within db, so we need to edit the list to allow UTL_SMTP work if you are using oracle 11g. Refer to chapter “Access Control Lists for UTL_TCP/HTTP/SMTP” and “Managing Fine-Grained Access to External Network Services” for more details.       In previous releases, XMLTYPE already exists in other OWB objects, like mapping/transformation etc. When the mapping/transformation is dragged into a process flow, the parameters with XMLTYPE are mapped to STRING. Now with the XMLTYPE support in process flow, the XMLTYPE will map to XMLTYPE in a more natural way, and we can leverage the new data type for the design.

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• Using SQL Execution Plans to discover the Swedish alphabet

  - by Rob Farley

  SQL Server is quite remarkable in a bunch of ways. In this post, I’m using the way that the Query Optimizer handles LIKE to keep it SARGable, the Execution Plans that result, Collations, and PowerShell to come up with the Swedish alphabet. SARGability is the ability to seek for items in an index according to a particular set of criteria. If you don’t have SARGability in play, you need to scan the whole index (or table if you don’t have an index). For example, I can find myself in the phonebook easily, because it’s sorted by LastName and I can find Farley in there by moving to the Fs, and so on. I can’t find everyone in my suburb easily, because the phonebook isn’t sorted that way. I can’t even find people who have six letters in their last name, because also the book is sorted by LastName, it’s not sorted by LEN(LastName). This is all stuff I’ve looked at before, including in the talk I gave at SQLBits in October 2010. If I try to find everyone who’s names start with F, I can do that using a query a bit like: SELECT LastName FROM dbo.PhoneBook WHERE LEFT(LastName,1) = 'F'; Unfortunately, the Query Optimizer doesn’t realise that all the entries that satisfy LEFT(LastName,1) = 'F' will be together, and it has to scan the whole table to find them. But if I write: SELECT LastName FROM dbo.PhoneBook WHERE LastName LIKE 'F%'; then SQL is smart enough to understand this, and performs an Index Seek instead. To see why, I look further into the plan, in particular, the properties of the Index Seek operator. The ToolTip shows me what I’m after: You’ll see that it does a Seek to find any entries that are at least F, but not yet G. There’s an extra Predicate in there (a Residual Predicate if you like), which checks that each LastName is really LIKE F% – I suppose it doesn’t consider that the Seek Predicate is quite enough – but most of the benefit is seen by its working out the Seek Predicate, filtering to just the “at least F but not yet G” section of the data. This got me curious though, particularly about where the G comes from, and whether I could leverage it to create the Swedish alphabet. I know that in the Swedish language, there are three extra letters that appear at the end of the alphabet. One of them is ä that appears in the word Västerås. It turns out that Västerås is quite hard to find in an index when you’re looking it up in a Swedish map. I talked about this briefly in my five-minute talk on Collation from SQLPASS (the one which was slightly less than serious). So by looking at the plan, I can work out what the next letter is in the alphabet of the collation used by the column. In other words, if my alphabet were Swedish, I’d be able to tell what the next letter after F is – just in case it’s not G. It turns out it is… Yes, the Swedish letter after F is G. But I worked this out by using a copy of my PhoneBook table that used the Finnish_Swedish_CI_AI collation. I couldn’t find how the Query Optimizer calculates the G, and my friend Paul White (@SQL_Kiwi) tells me that it’s frustratingly internal to the QO. He’s particularly smart, even if he is from New Zealand. To investigate further, I decided to do some PowerShell, leveraging the Get-SqlPlan function that I blogged about recently (make sure you also have the SqlServerCmdletSnapin100 snap-in added). I started by indicating that I was going to use Finnish_Swedish_CI_AI as my collation of choice, and that I’d start whichever letter cam straight after the number 9. I figure that this is a cheat’s way of guessing the first letter of the alphabet (but it doesn’t actually work in Unicode – luckily I’m using varchar not nvarchar. Actually, there are a few aspects of this code that only work using ASCII, so apologies if you were wanting to apply it to Greek, Japanese, etc). I also initialised my $alphabet variable. $collation = 'Finnish_Swedish_CI_AI'; $firstletter = '9'; $alphabet = ''; Now I created the table for my test. A single field would do, and putting a Clustered Index on it would suffice for the Seeks. Invoke-Sqlcmd -server . -data tempdb -query "create table dbo.collation_test (col varchar(10) collate $collation primary key);" Now I get into the looping. $c = $firstletter; $stillgoing = $true; while ($stillgoing) { I construct the query I want, seeking for entries which start with whatever $c has reached, and get the plan for it: $query = "select col from dbo.collation_test where col like '$($c)%';"; [xml] $pl = get-sqlplan $query "." "tempdb"; At this point, my $pl variable is a scary piece of XML, representing the execution plan. A bit of hunting through it showed me that the EndRange element contained what I was after, and that if it contained NULL, then I was done. $stillgoing = ($pl.ShowPlanXML.BatchSequence.Batch.Statements.StmtSimple.QueryPlan.RelOp.IndexScan.SeekPredicates.SeekPredicateNew.SeekKeys.EndRange -ne $null); Now I could grab the value out of it (which came with apostrophes that needed stripping), and append that to my $alphabet variable.   if ($stillgoing)   {  $c=$pl.ShowPlanXML.BatchSequence.Batch.Statements.StmtSimple.QueryPlan.RelOp.IndexScan.SeekPredicates.SeekPredicateNew.SeekKeys.EndRange.RangeExpressions.ScalarOperator.ScalarString.Replace("'","");     $alphabet += $c;   } Finally, finishing the loop, dropping the table, and showing my alphabet! } Invoke-Sqlcmd -server . -data tempdb -query "drop table dbo.collation_test;"; $alphabet; When I run all this, I see that the Swedish alphabet is ABCDEFGHIJKLMNOPQRSTUVXYZÅÄÖ, which matches what I see at Wikipedia. Interesting to see that the letters on the end are still there, even with Case Insensitivity. Turns out they’re not just “letters with accents”, they’re letters in their own right. I’m sure you gave up reading long ago, and really aren’t that fazed about the idea of doing this using PowerShell. I chose PowerShell because I’d already come up with an easy way of grabbing the estimated plan for a query, and PowerShell does allow for easy navigation of XML. I find the most interesting aspect of this as the fact that the Query Optimizer uses the next letter of the alphabet to maintain the SARGability of LIKE. I’m hoping they do something similar for a whole bunch of operations. Oh, and the fact that you know how to find stuff in the IKEA catalogue. Footnote: If you are interested in whether this works in other languages, you might want to consider the following screenshot, which shows that in principle, it should work with Japanese. It might be a bit harder to run this in PowerShell though, as I’m not sure how it translates. In Hiragana, the Japanese alphabet starts ?, ?, ?, ?, ?, ...

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• Same SELECT used in an INSERT has different execution plan

  - by amacias

  A customer complained that a query and its INSERT counterpart had different execution plans, and of course, the INSERT was slower. First lets look at the SELECT : SELECT ua_tr_rundatetime,        ua_ch_treatmentcode,        ua_tr_treatmentcode,        ua_ch_cellid,        ua_tr_cellid FROM   (SELECT DISTINCT CH.treatmentcode AS UA_CH_TREATMENTCODE,                         CH.cellid        AS UA_CH_CELLID         FROM    CH,                 DL         WHERE  CH.contactdatetime > SYSDATE - 5                AND CH.treatmentcode = DL.treatmentcode) CH_CELLS,        (SELECT DISTINCT T.treatmentcode AS UA_TR_TREATMENTCODE,                         T.cellid        AS UA_TR_CELLID,                         T.rundatetime   AS UA_TR_RUNDATETIME         FROM    T,                 DL         WHERE  T.treatmentcode = DL.treatmentcode) TRT_CELLS WHERE  CH_CELLS.ua_ch_treatmentcode(+) = TRT_CELLS.ua_tr_treatmentcode;  The query has 2 DISTINCT subqueries.  The execution plan shows one with DISTICT Placement transformation applied and not the other. The view in Step 5 has the prefix VW_DTP which means DISTINCT Placement. -------------------------------------------------------------------- | Id  | Operation                    | Name            | Cost (%CPU) -------------------------------------------------------------------- |   0 | SELECT STATEMENT             |                 |   272K(100) |*  1 |  HASH JOIN OUTER             |                 |   272K  (1) |   2 |   VIEW                       |                 |  4408   (1) |   3 |    HASH UNIQUE               |                 |  4408   (1) |*  4 |     HASH JOIN                |                 |  4407   (1) |   5 |      VIEW                    | VW_DTP_48BAF62C |  1660   (2) |   6 |       HASH UNIQUE            |                 |  1660   (2) |   7 |        TABLE ACCESS FULL     | DL              |  1644   (1) |   8 |      TABLE ACCESS FULL       | T               |  2744   (1) |   9 |   VIEW                       |                 |   267K  (1) |  10 |    HASH UNIQUE               |                 |   267K  (1) |* 11 |     HASH JOIN                |                 |   267K  (1) |  12 |      PARTITION RANGE ITERATOR|                 |   266K  (1) |* 13 |       TABLE ACCESS FULL      | CH              |   266K  (1) |  14 |      TABLE ACCESS FULL       | DL              |  1644   (1) -------------------------------------------------------------------- Query Block Name / Object Alias (identified by operation id): -------------------------------------------------------------    1 - SEL$1    2 - SEL$AF418D5F / TRT_CELLS@SEL$1    3 - SEL$AF418D5F    5 - SEL$F6AECEDE / VW_DTP_48BAF62C@SEL$48BAF62C    6 - SEL$F6AECEDE    7 - SEL$F6AECEDE / DL@SEL$3    8 - SEL$AF418D5F / T@SEL$3    9 - SEL$2        / CH_CELLS@SEL$1   10 - SEL$2   13 - SEL$2        / CH@SEL$2   14 - SEL$2        / DL@SEL$2 Predicate Information (identified by operation id): ---------------------------------------------------    1 - access("CH_CELLS"."UA_CH_TREATMENTCODE"="TRT_CELLS"."UA_TR_TREATMENTCODE")    4 - access("T"."TREATMENTCODE"="ITEM_1")   11 - access("CH"."TREATMENTCODE"="DL"."TREATMENTCODE")   13 - filter("CH"."CONTACTDATETIME">SYSDATE@!-5) The outline shows PLACE_DISTINCT(@"SEL$3" "DL"@"SEL$3") indicating that the QB3 is the one that got the transformation. Outline Data -------------   /*+       BEGIN_OUTLINE_DATA       IGNORE_OPTIM_EMBEDDED_HINTS       OPTIMIZER_FEATURES_ENABLE('11.2.0.3')       DB_VERSION('11.2.0.3')       ALL_ROWS       OUTLINE_LEAF(@"SEL$2")       OUTLINE_LEAF(@"SEL$F6AECEDE")       OUTLINE_LEAF(@"SEL$AF418D5F") PLACE_DISTINCT(@"SEL$3" "DL"@"SEL$3")       OUTLINE_LEAF(@"SEL$1")       OUTLINE(@"SEL$48BAF62C")       OUTLINE(@"SEL$3")       NO_ACCESS(@"SEL$1" "TRT_CELLS"@"SEL$1")       NO_ACCESS(@"SEL$1" "CH_CELLS"@"SEL$1")       LEADING(@"SEL$1" "TRT_CELLS"@"SEL$1" "CH_CELLS"@"SEL$1")       USE_HASH(@"SEL$1" "CH_CELLS"@"SEL$1")       FULL(@"SEL$2" "CH"@"SEL$2")       FULL(@"SEL$2" "DL"@"SEL$2")       LEADING(@"SEL$2" "CH"@"SEL$2" "DL"@"SEL$2")       USE_HASH(@"SEL$2" "DL"@"SEL$2")       USE_HASH_AGGREGATION(@"SEL$2")       NO_ACCESS(@"SEL$AF418D5F" "VW_DTP_48BAF62C"@"SEL$48BAF62C")       FULL(@"SEL$AF418D5F" "T"@"SEL$3")       LEADING(@"SEL$AF418D5F" "VW_DTP_48BAF62C"@"SEL$48BAF62C" "T"@"SEL$3")       USE_HASH(@"SEL$AF418D5F" "T"@"SEL$3")       USE_HASH_AGGREGATION(@"SEL$AF418D5F")       FULL(@"SEL$F6AECEDE" "DL"@"SEL$3")       USE_HASH_AGGREGATION(@"SEL$F6AECEDE")       END_OUTLINE_DATA   */ The 10053 shows there is a comparative of cost with and without the transformation. This means the transformation belongs to Cost-Based Query Transformations (CBQT). In SEL$3 the optimization of the query block without the transformation is 6659.73 and with the transformation is 4408.41 so the transformation is kept. GBP/DP: Checking validity of GBP/DP for query block SEL$3 (#3) DP: Checking validity of distinct placement for query block SEL$3 (#3) DP: Using search type: linear DP: Considering distinct placement on query block SEL$3 (#3) DP: Starting iteration 1, state space = (5) : (0) DP: Original query DP: Costing query block. DP: Updated best state, Cost = 6659.73 DP: Starting iteration 2, state space = (5) : (1) DP: Using DP transformation in this iteration. DP: Transformed query DP: Costing query block. DP: Updated best state, Cost = 4408.41 DP: Doing DP on the original QB. DP: Doing DP on the preserved QB. In SEL$2 the cost without the transformation is less than with it so it is not kept. GBP/DP: Checking validity of GBP/DP for query block SEL$2 (#2) DP: Checking validity of distinct placement for query block SEL$2 (#2) DP: Using search type: linear DP: Considering distinct placement on query block SEL$2 (#2) DP: Starting iteration 1, state space = (3) : (0) DP: Original query DP: Costing query block. DP: Updated best state, Cost = 267936.93 DP: Starting iteration 2, state space = (3) : (1) DP: Using DP transformation in this iteration. DP: Transformed query DP: Costing query block. DP: Not update best state, Cost = 267951.66 To the same query an INSERT INTO is added and the result is a very different execution plan. INSERT  INTO cc               (ua_tr_rundatetime,                ua_ch_treatmentcode,                ua_tr_treatmentcode,                ua_ch_cellid,                ua_tr_cellid)SELECT ua_tr_rundatetime,       ua_ch_treatmentcode,       ua_tr_treatmentcode,       ua_ch_cellid,       ua_tr_cellidFROM   (SELECT DISTINCT CH.treatmentcode AS UA_CH_TREATMENTCODE,                        CH.cellid        AS UA_CH_CELLID        FROM    CH,                DL        WHERE  CH.contactdatetime > SYSDATE - 5               AND CH.treatmentcode = DL.treatmentcode) CH_CELLS,       (SELECT DISTINCT T.treatmentcode AS UA_TR_TREATMENTCODE,                        T.cellid        AS UA_TR_CELLID,                        T.rundatetime   AS UA_TR_RUNDATETIME        FROM    T,                DL        WHERE  T.treatmentcode = DL.treatmentcode) TRT_CELLSWHERE  CH_CELLS.ua_ch_treatmentcode(+) = TRT_CELLS.ua_tr_treatmentcode;----------------------------------------------------------| Id  | Operation                     | Name | Cost (%CPU)----------------------------------------------------------|   0 | INSERT STATEMENT              |      |   274K(100)|   1 |  LOAD TABLE CONVENTIONAL      |      |            |*  2 |   HASH JOIN OUTER             |      |   274K  (1)|   3 |    VIEW                       |      |  6660   (1)|   4 |     SORT UNIQUE               |      |  6660   (1)|*  5 |      HASH JOIN                |      |  6659   (1)|   6 |       TABLE ACCESS FULL       | DL   |  1644   (1)|   7 |       TABLE ACCESS FULL       | T    |  2744   (1)|   8 |    VIEW                       |      |   267K  (1)|   9 |     SORT UNIQUE               |      |   267K  (1)|* 10 |      HASH JOIN                |      |   267K  (1)|  11 |       PARTITION RANGE ITERATOR|      |   266K  (1)|* 12 |        TABLE ACCESS FULL      | CH   |   266K  (1)|  13 |       TABLE ACCESS FULL       | DL   |  1644   (1)----------------------------------------------------------Query Block Name / Object Alias (identified by operation id):-------------------------------------------------------------   1 - SEL$1   3 - SEL$3 / TRT_CELLS@SEL$1   4 - SEL$3   6 - SEL$3 / DL@SEL$3   7 - SEL$3 / T@SEL$3   8 - SEL$2 / CH_CELLS@SEL$1   9 - SEL$2  12 - SEL$2 / CH@SEL$2  13 - SEL$2 / DL@SEL$2Predicate Information (identified by operation id):---------------------------------------------------   2 - access("CH_CELLS"."UA_CH_TREATMENTCODE"="TRT_CELLS"."UA_TR_TREATMENTCODE")   5 - access("T"."TREATMENTCODE"="DL"."TREATMENTCODE")  10 - access("CH"."TREATMENTCODE"="DL"."TREATMENTCODE")  12 - filter("CH"."CONTACTDATETIME">SYSDATE@!-5)Outline Data-------------  /*+      BEGIN_OUTLINE_DATA      IGNORE_OPTIM_EMBEDDED_HINTS      OPTIMIZER_FEATURES_ENABLE('11.2.0.3')      DB_VERSION('11.2.0.3')      ALL_ROWS      OUTLINE_LEAF(@"SEL$2")      OUTLINE_LEAF(@"SEL$3")      OUTLINE_LEAF(@"SEL$1")      OUTLINE_LEAF(@"INS$1")      FULL(@"INS$1" "CC"@"INS$1")      NO_ACCESS(@"SEL$1" "TRT_CELLS"@"SEL$1")      NO_ACCESS(@"SEL$1" "CH_CELLS"@"SEL$1")      LEADING(@"SEL$1" "TRT_CELLS"@"SEL$1" "CH_CELLS"@"SEL$1")      USE_HASH(@"SEL$1" "CH_CELLS"@"SEL$1")      FULL(@"SEL$2" "CH"@"SEL$2")      FULL(@"SEL$2" "DL"@"SEL$2")      LEADING(@"SEL$2" "CH"@"SEL$2" "DL"@"SEL$2")      USE_HASH(@"SEL$2" "DL"@"SEL$2")      USE_HASH_AGGREGATION(@"SEL$2")      FULL(@"SEL$3" "DL"@"SEL$3")      FULL(@"SEL$3" "T"@"SEL$3")      LEADING(@"SEL$3" "DL"@"SEL$3" "T"@"SEL$3")      USE_HASH(@"SEL$3" "T"@"SEL$3")      USE_HASH_AGGREGATION(@"SEL$3")      END_OUTLINE_DATA  */ There is no DISTINCT Placement view and no hint.The 10053 trace shows a new legend "DP: Bypassed: Not SELECT"implying that this is a transformation that it is possible only for SELECTs. GBP/DP: Checking validity of GBP/DP for query block SEL$3 (#4) DP: Checking validity of distinct placement for query block SEL$3 (#4) DP: Bypassed: Not SELECT. GBP/DP: Checking validity of GBP/DP for query block SEL$2 (#3) DP: Checking validity of distinct placement for query block SEL$2 (#3) DP: Bypassed: Not SELECT. In 12.1 (and hopefully in 11.2.0.4 when released) the restriction on applying CBQT to some DMLs and DDLs (like CTAS) is lifted.This is documented in BugTag Note:10013899.8 Allow CBQT for some DML / DDLAnd interestingly enough, it is possible to have a one-off patch in 11.2.0.3. SQL> select DESCRIPTION,OPTIMIZER_FEATURE_ENABLE,IS_DEFAULT     2  from v$system_fix_control where BUGNO='10013899'; DESCRIPTION ---------------------------------------------------------------- OPTIMIZER_FEATURE_ENABLE  IS_DEFAULT ------------------------- ---------- enable some transformations for DDL and DML statements 11.2.0.4                           1

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• ?12c database ????Adaptive Execution Plans ????????

  - by Liu Maclean(???)

  12c R1 ????SQL??????- Adaptive Execution Plans ????????,???????optimizer ??????(runtime)???????????????, ????????????????????? SQL???????? ????????????, ?????????????????????????????????????????????????????????????adaptive plan ????????????????????????????????????,?????subplan???????????????????? ??????, ???????? ???????????????,?????????, ?????? ???????????????”???”????, ???????????????????buffer ???????  ????????????,?????,??????????????????? ???optimizer ?????????????????????????,?????????????????????????????????????????plan???? ??12C?????????????, ???????????????????,?????? ???????????? ????????????2???: Dynamic Plans????: ???????????????????????;??????,???optimizer??????????subplans??????????????, ???????????????????,?????????????? Reoptimization????: ?Dynamic Plans????,Reoptimization??????????????????????Reoptimization??,?????????????????????????,??reoptimization????? OPTIMIZER_ADAPTIVE_REPORTING_ONLY ???? report-only????????????????TRUE,?????????report-only????,???????????????,??????????????? Dynamic Plans ??????????????,????????????????????????, ?????????????,???????????,????????????????????????????????????????? ?????????????final plan??????????????default plan, ??final plan?default plan???????,????????????? subplan ???????????????,???????????????????????? ??????,???????statistics collector ?buffer???????????statistics collector?????????????????,???????????????????????????? ?????????????????????????????????????????,??????????,?????????????? ???????????,???????buffer???? ???????????????,?????????????????????????????,??????buffer,??????final plan? ????????,???????????????????????,????????????????? ?V$SQL??????IS_RESOLVED_DYNAMIC_PLAN??????????final plan???default plan? ??????dynamic plan ???????SQL PLAN directives?????? declare cursor PLAN_DIRECTIVE_IDS is select directive_id from DBA_SQL_PLAN_DIRECTIVES; begin for z in PLAN_DIRECTIVE_IDS loop DBMS_SPD.DROP_SQL_PLAN_DIRECTIVE(z.directive_id); end loop; end; / explain plan for select /*MALCEAN*/ product_name from oe.order_items o, oe.product_information p where o.unit_price=15 and quantity>1 and p.product_id=o.product_id; select * from table(dbms_xplan.display()); Plan hash value: 1255158658 www.askmaclean.com ------------------------------------------------------------------------------------------------------- | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ------------------------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 4 | 128 | 7 (0)| 00:00:01 | | 1 | NESTED LOOPS | | | | | | | 2 | NESTED LOOPS | | 4 | 128 | 7 (0)| 00:00:01 | |* 3 | TABLE ACCESS FULL | ORDER_ITEMS | 4 | 48 | 3 (0)| 00:00:01 | |* 4 | INDEX UNIQUE SCAN | PRODUCT_INFORMATION_PK | 1 | | 0 (0)| 00:00:01 | | 5 | TABLE ACCESS BY INDEX ROWID| PRODUCT_INFORMATION | 1 | 20 | 1 (0)| 00:00:01 | ------------------------------------------------------------------------------------------------------- Predicate Information (identified by operation id): --------------------------------------------------- 3 - filter("O"."UNIT_PRICE"=15 AND "QUANTITY">1) 4 - access("P"."PRODUCT_ID"="O"."PRODUCT_ID") alter session set events '10053 trace name context forever,level 1'; OR alter session set events 'trace[SQL_Plan_Directive] disk highest'; select /*MALCEAN*/ product_name from oe.order_items o, oe.product_information p where o.unit_price=15 and quantity>1 and p.product_id=o.product_id; ---------------------------------------------------------------+-----------------------------------+ | Id | Operation | Name | Rows | Bytes | Cost | Time | ---------------------------------------------------------------+-----------------------------------+ | 0 | SELECT STATEMENT | | | | 7 | | | 1 | HASH JOIN | | 4 | 128 | 7 | 00:00:01 | | 2 | NESTED LOOPS | | | | | | | 3 | NESTED LOOPS | | 4 | 128 | 7 | 00:00:01 | | 4 | STATISTICS COLLECTOR | | | | | | | 5 | TABLE ACCESS FULL | ORDER_ITEMS | 4 | 48 | 3 | 00:00:01 | | 6 | INDEX UNIQUE SCAN | PRODUCT_INFORMATION_PK| 1 | | 0 | | | 7 | TABLE ACCESS BY INDEX ROWID | PRODUCT_INFORMATION | 1 | 20 | 1 | 00:00:01 | | 8 | TABLE ACCESS FULL | PRODUCT_INFORMATION | 1 | 20 | 1 | 00:00:01 | ---------------------------------------------------------------+-----------------------------------+ Predicate Information: ---------------------- 1 - access("P"."PRODUCT_ID"="O"."PRODUCT_ID") 5 - filter(("O"."UNIT_PRICE"=15 AND "QUANTITY">1)) 6 - access("P"."PRODUCT_ID"="O"."PRODUCT_ID") ===================================== SPD: BEGIN context at statement level ===================================== Stmt: ******* UNPARSED QUERY IS ******* SELECT /*+ OPT_ESTIMATE (@"SEL$1" JOIN ("P"@"SEL$1" "O"@"SEL$1") ROWS=13.000000 ) OPT_ESTIMATE (@"SEL$1" TABLE "O"@"SEL$1" ROWS=13.000000 ) */ "P"."PRODUCT_NAME" "PRODUCT_NAME" FROM "OE"."ORDER_ITEMS" "O","OE"."PRODUCT_INFORMATION" "P" WHERE "O"."UNIT_PRICE"=15 AND "O"."QUANTITY">1 AND "P"."PRODUCT_ID"="O"."PRODUCT_ID" Objects referenced in the statement PRODUCT_INFORMATION[P] 92194, type = 1 ORDER_ITEMS[O] 92197, type = 1 Objects in the hash table Hash table Object 92197, type = 1, ownerid = 6573730143572393221: No Dynamic Sampling Directives for the object Hash table Object 92194, type = 1, ownerid = 17822962561575639002: No Dynamic Sampling Directives for the object Return code in qosdInitDirCtx: ENBLD =================================== SPD: END context at statement level =================================== ======================================= SPD: BEGIN context at query block level ======================================= Query Block SEL$1 (#0) Return code in qosdSetupDirCtx4QB: NOCTX ===================================== SPD: END context at query block level ===================================== SPD: Return code in qosdDSDirSetup: NOCTX, estType = TABLE SPD: Generating finding id: type = 1, reason = 1, objcnt = 1, obItr = 0, objid = 92197, objtyp = 1, vecsize = 6, colvec = [4, 5, ], fid = 2896834833840853267 SPD: Inserted felem, fid=2896834833840853267, ftype = 1, freason = 1, dtype = 0, dstate = 0, dflag = 0, ver = YES, keep = YES SPD: qosdCreateFindingSingTab retCode = CREATED, fid = 2896834833840853267 SPD: qosdCreateDirCmp retCode = CREATED, fid = 2896834833840853267 SPD: Return code in qosdDSDirSetup: NOCTX, estType = TABLE SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = JOIN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SKIP_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = JOIN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Generating finding id: type = 1, reason = 1, objcnt = 1, obItr = 0, objid = 92197, objtyp = 1, vecsize = 6, colvec = [4, 5, ], fid = 2896834833840853267 SPD: Modified felem, fid=2896834833840853267, ftype = 1, freason = 1, dtype = 0, dstate = 0, dflag = 0, ver = YES, keep = YES SPD: Generating finding id: type = 1, reason = 1, objcnt = 1, obItr = 0, objid = 92194, objtyp = 1, vecsize = 2, colvec = [1, ], fid = 5618517328604016300 SPD: Modified felem, fid=5618517328604016300, ftype = 1, freason = 1, dtype = 0, dstate = 0, dflag = 0, ver = NO, keep = NO SPD: Generating finding id: type = 1, reason = 1, objcnt = 1, obItr = 0, objid = 92194, objtyp = 1, vecsize = 2, colvec = [1, ], fid = 1142802697078608149 SPD: Modified felem, fid=1142802697078608149, ftype = 1, freason = 1, dtype = 0, dstate = 0, dflag = 0, ver = NO, keep = NO SPD: Generating finding id: type = 1, reason = 2, objcnt = 2, obItr = 0, objid = 92194, objtyp = 1, vecsize = 0, obItr = 1, objid = 92197, objtyp = 1, vecsize = 0, fid = 1437680122701058051 SPD: Modified felem, fid=1437680122701058051, ftype = 1, freason = 2, dtype = 0, dstate = 0, dflag = 0, ver = NO, keep = NO select * from table(dbms_xplan.display_cursor(format=>'report')) ; ????report????adaptive plan Adaptive plan: ------------- This cursor has an adaptive plan, but adaptive plans are enabled for reporting mode only.  The plan that would be executed if adaptive plans were enabled is displayed below. ------------------------------------------------------------------------------------------ | Id  | Operation          | Name                | Rows  | Bytes | Cost (%CPU)| Time     | ------------------------------------------------------------------------------------------ |   0 | SELECT STATEMENT   |                     |       |       |     7 (100)|          | |*  1 |  HASH JOIN         |                     |     4 |   128 |     7   (0)| 00:00:01 | |*  2 |   TABLE ACCESS FULL| ORDER_ITEMS         |     4 |    48 |     3   (0)| 00:00:01 | |   3 |   TABLE ACCESS FULL| PRODUCT_INFORMATION |     1 |    20 |     1   (0)| 00:00:01 | ------------------------------------------------------------------------------------------ SQL> select SQL_ID,IS_RESOLVED_DYNAMIC_PLAN,sql_text from v$SQL WHERE SQL_TEXT like '%MALCEAN%' and sql_text not like '%like%'; SQL_ID IS -------------------------- -- SQL_TEXT -------------------------------------------------------------------------------- 6ydj1bn1bng17 Y select /*MALCEAN*/ product_name from oe.order_items o, oe.product_information p where o.unit_price=15 and quantity>1 and p.product_id=o.product_id ???? explain plan for ????default plan, ??????optimizer???final plan,??V$SQL.IS_RESOLVED_DYNAMIC_PLAN???Y,????????????? DBA_SQL_PLAN_DIRECTIVES?????????????SQL PLAN DIRECTIVES, ???12c? ???MMON?????DML ???column usage??????????,????SMON??? MMON????SGA??PLAN DIRECTIVES??? ?????DBMS_SPD.flush_sql_plan_directive???? select directive_id,type,reason from DBA_SQL_PLAN_DIRECTIVES / DIRECTIVE_ID TYPE REASON ----------------------------------- -------------------------------- ----------------------------- 10321283028317893030 DYNAMIC_SAMPLING JOIN CARDINALITY MISESTIMATE 4757086536465754886 DYNAMIC_SAMPLING JOIN CARDINALITY MISESTIMATE 16085268038103121260 DYNAMIC_SAMPLING JOIN CARDINALITY MISESTIMATE SQL> set pages 9999 SQL> set lines 300 SQL> col state format a5 SQL> col subobject_name format a11 SQL> col col_name format a11 SQL> col object_name format a13 SQL> select d.directive_id, o.object_type, o.object_name, o.subobject_name col_name, d.type, d.state, d.reason 2 from dba_sql_plan_directives d, dba_sql_plan_dir_objects o 3 where d.DIRECTIVE_ID=o.DIRECTIVE_ID 4 and o.object_name in ('ORDER_ITEMS') 5 order by d.directive_id; DIRECTIVE_ID OBJECT_TYPE OBJECT_NAME COL_NAME TYPE STATE REASON ------------ ------------ ------------- ----------- -------------------------------- ----- ------------------------------------- --- 1.8156E+19 COLUMN ORDER_ITEMS UNIT_PRICE DYNAMIC_SAMPLING NEW SINGLE TABLE CARDINALITY MISESTIMATE 1.8156E+19 TABLE ORDER_ITEMS DYNAMIC_SAMPLING NEW SINGLE TABLE CARDINALITY MISESTIMATE 1.8156E+19 COLUMN ORDER_ITEMS QUANTITY DYNAMIC_SAMPLING NEW SINGLE TABLE CARDINALITY MISESTIMATE DBA_SQL_PLAN_DIRECTIVES????? _BASE_OPT_DIRECTIVE ? _BASE_OPT_FINDING SELECT d.dir_own#, d.dir_id, d.f_id, decode(type, 1, 'DYNAMIC_SAMPLING', 'UNKNOWN'), decode(state, 1, 'NEW', 2, 'MISSING_STATS', 3, 'HAS_STATS', 4, 'CANDIDATE', 5, 'PERMANENT', 6, 'DISABLED', 'UNKNOWN'), decode(bitand(flags, 1), 1, 'YES', 'NO'), cast(d.created as timestamp), cast(d.last_modified as timestamp), -- Please see QOSD_DAYS_TO_UPDATE and QOSD_PLUS_SECONDS for more details -- about 6.5 cast(d.last_used as timestamp) - NUMTODSINTERVAL(6.5, 'day') FROM sys.opt_directive$ d ??dbms_spd??? SQL PLAN DIRECTIVES, SQL PLAN DIRECTIVES???retention ???53?: Package: DBMS_SPD This package provides subprograms for managing Sql Plan Directives(SPD). SPD are objects generated automatically by Oracle server. For example, if server detects that the single table cardinality estimated by optimizer is off from the actual number of rows returned when accessing the table, it will automatically create a directive to do dynamic sampling for the table. When any Sql statement referencing the table is compiled, optimizer will perform dynamic sampling for the table to get more accurate estimate. Notes: DBMSL_SPD is a invoker-rights package. The invoker requires ADMINISTER SQL MANAGEMENT OBJECT privilege for executing most of the subprograms of this package. Also the subprograms commit the current transaction (if any), perform the operation and commit it again. DBA view dba_sql_plan_directives shows all the directives created in the system and the view dba_sql_plan_dir_objects displays the objects that are included in the directives. -- Default value for SPD_RETENTION_WEEKS SPD_RETENTION_WEEKS_DEFAULT CONSTANT varchar2(4) := '53'; | STATE : NEW : Newly created directive. | : MISSING_STATS : The directive objects do not | have relevant stats. | : HAS_STATS : The objects have stats. | : PERMANENT : A permanent directive. Server | evaluated effectiveness and these | directives are useful. | | AUTO_DROP : YES : Directive will be dropped | automatically if not | used for SPD_RETENTION_WEEKS. | This is the default behavior. | NO : Directive will not be dropped | automatically. Procedure: flush_sql_plan_directive This procedure allows manually flushing the Sql Plan directives that are automatically recorded in SGA memory while executing sql statements. The information recorded in SGA are periodically flushed by oracle background processes. This procedure just provides a way to flush the information manually. ????”_optimizer_dynamic_plans”(enable dynamic plans)????????,???TRUE??DYNAMIC PLAN? ???FALSE???????????? ????,Dynamic Plan????????????Nested Loop?Hash Join???case ,????????Nested loop???????????HASH JOIN,?HASH JOIN????????????????? ????????subplan?????,???? pass?? ?join method???,?????STATISTICS COLLECTOR???cardinality?,???????HASH JOIN?????Nested Loop,????????????subplan?????access path; ???????Sales??????????????????,????HASH JOIN,??SUBPLAN??customers?????????;?????Nested Loop,???????cust_id?????Range Scan+Access by Rowid? Cardinality feedback Cardinality feedback????????11.2????,????????re-optimization???;  ???????????,Cardinality feedback?????????????????????????? ???????????????????,?????????????????,??????????Cardinality feedback????????????? ????????????????????????? ??????????????Cardinality feedback ??: ????????,???????????,??????????,????????????????selectivity ??? ????????????: ??????,?????????????????????????????????,??????????????????? ????????????????????????????????????????,?????????????????????????? ?????????,???????????????,?????????? ??????????Cardinality ????,??????join Cardinality ????????? Cardinality feedback???????cursor?,?Cursor???aged out????? SELECT /*+ gather_plan_statistics */ product_name FROM order_items o, product_information p WHERE o.unit_price = 15 AND quantity > 1 AND p.product_id = o.product_id Plan hash value: 1553478007 ---------------------------------------------------------------------------------------------------------------------------------------- | Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers | Reads | OMem | 1Mem | Used-Mem | ---------------------------------------------------------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 1 | | 13 |00:00:00.01 | 24 | 20 | | | | |* 1 | HASH JOIN | | 1 | 4 | 13 |00:00:00.01 | 24 | 20 | 2061K| 2061K| 429K (0)| |* 2 | TABLE ACCESS FULL| ORDER_ITEMS | 1 | 4 | 13 |00:00:00.01 | 7 | 6 | | | | | 3 | TABLE ACCESS FULL| PRODUCT_INFORMATION | 1 | 1 | 288 |00:00:00.01 | 17 | 14 | | | | ---------------------------------------------------------------------------------------------------------------------------------------- SELECT /*+ gather_plan_statistics */ product_name FROM order_items o, product_information p WHERE o.unit_price = 15 AND quantity > 1 AND p.product_id = o.product_id Plan hash value: 1553478007 ------------------------------------------------------------------------------------------------------------------------------- | Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers | OMem | 1Mem | Used-Mem | ------------------------------------------------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 1 | | 13 |00:00:00.01 | 24 | | | | |* 1 | HASH JOIN | | 1 | 13 | 13 |00:00:00.01 | 24 | 2061K| 2061K| 413K (0)| |* 2 | TABLE ACCESS FULL| ORDER_ITEMS | 1 | 13 | 13 |00:00:00.01 | 7 | | | | | 3 | TABLE ACCESS FULL| PRODUCT_INFORMATION | 1 | 288 | 288 |00:00:00.01 | 17 | | | | ------------------------------------------------------------------------------------------------------------------------------- Note ----- - statistics feedback used for this statement SQL> select count(*) from v$SQL where SQL_ID='cz0hg2zkvd10y'; COUNT(*) ---------- 2 SQL>select sql_ID,USE_FEEDBACK_STATS FROM V$SQL_SHARED_CURSOR where USE_FEEDBACK_STATS ='Y'; SQL_ID U ------------- - cz0hg2zkvd10y Y ????????Cardinality feedback????,???????????????????????????,????????????order_items???????? ????2??????plan hash value??(??????????),?????2????child cursor??????gather_plan_statistics???actual : A-ROWS  estimate :E-ROWS????????? Automatic Re-optimization ???dynamic plan, Re-optimization???????????????  ?  ??????????????? ????????????????????????????????  ???????????,??????????????, ???????????????????? ???????????  Re-optimization??, ????????????????????? Re-optimization????dynamic plan??????????  dynamic plan????????????????????, ???????????????????? ????,??????????join order ??????????????,?????????????join order????? ??????,????????Re-optimization, ??Re-optimization ??????????????????? ?Oracle database 12c?,join statistics?????????????????????,??????????????????????Re-optimization???????????adaptive cursor sharing????? ????????????????,???????????? ????? ???????statistics collectors ????????????????????Re-optimization??????2?????????????,???????????????? ??????????????Re-optimization?????,?????????????????????? ???v$SQL??????IS_REOPTIMIZABLE?????????????????????Re-optimization,??????????Re-optimization???,?????Re-optimization ,???????reporting????? IS_REOPTIMIZABLE VARCHAR2(1) This columns shows whether the next execution matching this child cursor will trigger a reoptimization. The values are:   Y: If the next execution will trigger a reoptimization R: If the child cursor contains reoptimization information, but will not trigger reoptimization because the cursor was compiled in reporting mode N: If the child cursor has no reoptimization information ??1: select plan_table_output from table (dbms_xplan.display_cursor('gwf99gfnm0t7g',NULL,'ALLSTATS LAST')); SQL_ID  gwf99gfnm0t7g, child number 0 ------------------------------------- SELECT /*+ SFTEST gather_plan_statistics */ o.order_id, v.product_name FROM  orders o,   ( SELECT order_id, product_name FROM order_items o, product_information p     WHERE  p.product_id = o.product_id AND list_price < 50 AND min_price < 40  ) v WHERE o.order_id = v.order_id Plan hash value: 1906736282 ------------------------------------------------------------------------------------------------------------------------------------------- | Id  | Operation             | Name                | Starts | E-Rows | A-Rows |   A-Time   | Buffers | Reads  |  OMem |  1Mem | Used-Mem | ------------------------------------------------------------------------------------------------------------------------------------------- |   0 | SELECT STATEMENT      |                     |      1 |        |    269 |00:00:00.02 |    1336 |     18 |       |       |          | |   1 |  NESTED LOOPS         |                     |      1 |      1 |    269 |00:00:00.02 |    1336 |     18 |       |       |          | |   2 |   MERGE JOIN CARTESIAN|                     |      1 |      4 |   9135 |00:00:00.02 |      34 |     15 |       |       |          | |*  3 |    TABLE ACCESS FULL  | PRODUCT_INFORMATION |      1 |      1 |     87 |00:00:00.01 |      33 |     14 |       |       |          | |   4 |    BUFFER SORT        |                     |     87 |    105 |   9135 |00:00:00.01 |       1 |      1 |  4096 |  4096 | 4096  (0)| |   5 |     INDEX FULL SCAN   | ORDER_PK            |      1 |    105 |    105 |00:00:00.01 |       1 |      1 |       |       |          | |*  6 |   INDEX UNIQUE SCAN   | ORDER_ITEMS_UK      |   9135 |      1 |    269 |00:00:00.01 |    1302 |      3 |       |       |          | ------------------------------------------------------------------------------------------------------------------------------------------- Predicate Information (identified by operation id): ---------------------------------------------------    3 - filter(("MIN_PRICE"<40 AND "LIST_PRICE"<50))    6 - access("O"."ORDER_ID"="ORDER_ID" AND "P"."PRODUCT_ID"="O"."PRODUCT_ID") SQL_ID  gwf99gfnm0t7g, child number 1 ------------------------------------- SELECT /*+ SFTEST gather_plan_statistics */ o.order_id, v.product_name FROM  orders o,   ( SELECT order_id, product_name FROM order_items o, product_information p     WHERE  p.product_id = o.product_id AND list_price < 50 AND min_price < 40  ) v WHERE o.order_id = v.order_id Plan hash value: 35479787 -------------------------------------------------------------------------------------------------------------------------------------------- | Id  | Operation              | Name                | Starts | E-Rows | A-Rows |   A-Time   | Buffers | Reads  |  OMem |  1Mem | Used-Mem | -------------------------------------------------------------------------------------------------------------------------------------------- |   0 | SELECT STATEMENT       |                     |      1 |        |    269 |00:00:00.01 |      63 |      3 |       |       |          | |   1 |  NESTED LOOPS          |                     |      1 |    269 |    269 |00:00:00.01 |      63 |      3 |       |       |          | |*  2 |   HASH JOIN            |                     |      1 |    313 |    269 |00:00:00.01 |      42 |      3 |  1321K|  1321K| 1234K (0)| |*  3 |    TABLE ACCESS FULL   | PRODUCT_INFORMATION |      1 |     87 |     87 |00:00:00.01 |      16 |      0 |       |       |          | |   4 |    INDEX FAST FULL SCAN| ORDER_ITEMS_UK      |      1 |    665 |    665 |00:00:00.01 |      26 |      3 |       |       |          | |*  5 |   INDEX UNIQUE SCAN    | ORDER_PK            |    269 |      1 |    269 |00:00:00.01 |      21 |      0 |       |       |          | -------------------------------------------------------------------------------------------------------------------------------------------- Predicate Information (identified by operation id): ---------------------------------------------------    2 - access("P"."PRODUCT_ID"="O"."PRODUCT_ID")    3 - filter(("MIN_PRICE"<40 AND "LIST_PRICE"<50))    5 - access("O"."ORDER_ID"="ORDER_ID") Note -----    - statistics feedback used for this statement    SQL> select IS_REOPTIMIZABLE,child_number FROM V$SQL  A where A.SQL_ID='gwf99gfnm0t7g'; IS CHILD_NUMBER -- ------------ Y             0 N             1    1* select child_number,other_xml From v$SQL_PLAN  where SQL_ID='gwf99gfnm0t7g' and other_xml is not nul SQL> / CHILD_NUMBER OTHER_XML ------------ --------------------------------------------------------------------------------            1 <other_xml><info type="cardinality_feedback">yes</info><info type="db_version">1              2.1.0.1</info><info type="parse_schema"><![CDATA["OE"]]></info><info type="plan_              hash">35479787</info><info type="plan_hash_2">3382491761</info><outline_data><hi              nt><![CDATA[IGNORE_OPTIM_EMBEDDED_HINTS]]></hint><hint><![CDATA[OPTIMIZER_FEATUR              ES_ENABLE('12.1.0.1')]]></hint><hint><![CDATA[DB_VERSION('12.1.0.1')]]></hint><h              int><![CDATA[ALL_ROWS]]></hint><hint><![CDATA[OUTLINE_LEAF(@"SEL$F5BB74E1")]]></              hint><hint><![CDATA[MERGE(@"SEL$2")]]></hint><hint><![CDATA[OUTLINE(@"SEL$1")]]>              </hint><hint><![CDATA[OUTLINE(@"SEL$2")]]></hint><hint><![CDATA[FULL(@"SEL$F5BB7              4E1" "P"@"SEL$2")]]></hint><hint><![CDATA[INDEX_FFS(@"SEL$F5BB74E1" "O"@"SEL$2"              ("ORDER_ITEMS"."ORDER_ID" "ORDER_ITEMS"."PRODUCT_ID"))]]></hint><hint><![CDATA[I              NDEX(@"SEL$F5BB74E1" "O"@"SEL$1" ("ORDERS"."ORDER_ID"))]]></hint><hint><![CDATA[              LEADING(@"SEL$F5BB74E1" "P"@"SEL$2" "O"@"SEL$2" "O"@"SEL$1")]]></hint><hint><![C              DATA[USE_HASH(@"SEL$F5BB74E1" "O"@"SEL$2")]]></hint><hint><![CDATA[USE_NL(@"SEL$              F5BB74E1" "O"@"SEL$1")]]></hint></outline_data></other_xml>            0 <other_xml><info type="db_version">12.1.0.1</info><info type="parse_schema"><![C              DATA["OE"]]></info><info type="plan_hash">1906736282</info><info type="plan_hash              _2">2579473118</info><outline_data><hint><![CDATA[IGNORE_OPTIM_EMBEDDED_HINTS]]>              </hint><hint><![CDATA[OPTIMIZER_FEATURES_ENABLE('12.1.0.1')]]></hint><hint><![CD              ATA[DB_VERSION('12.1.0.1')]]></hint><hint><![CDATA[ALL_ROWS]]></hint><hint><![CD              ATA[OUTLINE_LEAF(@"SEL$F5BB74E1")]]></hint><hint><![CDATA[MERGE(@"SEL$2")]]></hi              nt><hint><![CDATA[OUTLINE(@"SEL$1")]]></hint><hint><![CDATA[OUTLINE(@"SEL$2")]]>              </hint><hint><![CDATA[FULL(@"SEL$F5BB74E1" "P"@"SEL$2")]]></hint><hint><![CDATA[              INDEX(@"SEL$F5BB74E1" "O"@"SEL$1" ("ORDERS"."ORDER_ID"))]]></hint><hint><![CDATA              [INDEX(@"SEL$F5BB74E1" "O"@"SEL$2" ("ORDER_ITEMS"."ORDER_ID" "ORDER_ITEMS"."PROD              UCT_ID"))]]></hint><hint><![CDATA[LEADING(@"SEL$F5BB74E1" "P"@"SEL$2" "O"@"SEL$1              " "O"@"SEL$2")]]></hint><hint><![CDATA[USE_MERGE_CARTESIAN(@"SEL$F5BB74E1" "O"@"              SEL$1")]]></hint><hint><![CDATA[USE_NL(@"SEL$F5BB74E1" "O"@"SEL$2")]]></hint></o              utline_data></other_xml> ??2: SELECT /*+gather_plan_statistics*/ * FROM customers WHERE cust_state_province='CA' AND country_id='US'; SELECT * FROM TABLE(DBMS_XPLAN.DISPLAY_CURSOR(FORMAT=>'ALLSTATS LAST')); PLAN_TABLE_OUTPUT ------------------------------------- SQL_ID b74nw722wjvy3, child number 0 ------------------------------------- select /*+gather_plan_statistics*/ * from customers where CUST_STATE_PROVINCE='CA' and country_id='US' Plan hash value: 1683234692 -------------------------------------------------------------------------------------------------- | Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers | Reads | -------------------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 1 | | 29 |00:00:00.01 | 17 | 14 | |* 1 | TABLE ACCESS FULL| CUSTOMERS | 1 | 8 | 29 |00:00:00.01 | 17 | 14 | -------------------------------------------------------------------------------------------------- Predicate Information (identified by operation id): --------------------------------------------------- 1 - filter(("CUST_STATE_PROVINCE"='CA' AND "COUNTRY_ID"='US')) SELECT SQL_ID, CHILD_NUMBER, SQL_TEXT, IS_REOPTIMIZABLE FROM V$SQL WHERE SQL_TEXT LIKE 'SELECT /*+gather_plan_statistics*/%'; SQL_ID CHILD_NUMBER SQL_TEXT I ------------- ------------ ----------- - b74nw722wjvy3 0 select /*+g Y ather_plan_ statistics* / * from cu stomers whe re CUST_STA TE_PROVINCE ='CA' and c ountry_id=' US' EXEC DBMS_SPD.FLUSH_SQL_PLAN_DIRECTIVE; SELECT TO_CHAR(d.DIRECTIVE_ID) dir_id, o.OWNER, o.OBJECT_NAME, o.SUBOBJECT_NAME col_name, o.OBJECT_TYPE, d.TYPE, d.STATE, d.REASON FROM DBA_SQL_PLAN_DIRECTIVES d, DBA_SQL_PLAN_DIR_OBJECTS o WHERE d.DIRECTIVE_ID=o.DIRECTIVE_ID AND o.OWNER IN ('SH') ORDER BY 1,2,3,4,5; DIR_ID OWNER OBJECT_NAME COL_NAME OBJECT TYPE STATE REASON ----------------------- ----- ------------- ----------- ------ ---------------- ----- ------------------------ 1484026771529551585 SH CUSTOMERS COUNTRY_ID COLUMN DYNAMIC_SAMPLING NEW SINGLE TABLE CARDINALITY MISESTIMATE 1484026771529551585 SH CUSTOMERS CUST_STATE_ COLUMN DYNAMIC_SAMPLING NEW SINGLE TABLE CARDINALITY PROVINCE MISESTIMATE 1484026771529551585 SH CUSTOMERS TABLE DYNAMIC_SAMPLING NEW SINGLE TABLE CARDINALITY MISESTIMATE SELECT /*+gather_plan_statistics*/ * FROM customers WHERE cust_state_province='CA' AND country_id='US'; ELECT * FROM TABLE(DBMS_XPLAN.DISPLAY_CURSOR(FORMAT=>'ALLSTATS LAST')); PLAN_TABLE_OUTPUT ------------------------------------- SQL_ID b74nw722wjvy3, child number 1 ------------------------------------- select /*+gather_plan_statistics*/ * from customers where CUST_STATE_PROVINCE='CA' and country_id='US' Plan hash value: 1683234692 ----------------------------------------------------------------------------------------- | Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers | ----------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 1 | | 29 |00:00:00.01 | 17 | |* 1 | TABLE ACCESS FULL| CUSTOMERS | 1 | 29 | 29 |00:00:00.01 | 17 | ----------------------------------------------------------------------------------------- Predicate Information (identified by operation id): --------------------------------------------------- 1 - filter(("CUST_STATE_PROVINCE"='CA' AND "COUNTRY_ID"='US')) Note ----- - cardinality feedback used for this statement SELECT SQL_ID, CHILD_NUMBER, SQL_TEXT, IS_REOPTIMIZABLE FROM V$SQL WHERE SQL_TEXT LIKE 'SELECT /*+gather_plan_statistics*/%'; SQL_ID CHILD_NUMBER SQL_TEXT I ------------- ------------ ----------- - b74nw722wjvy3 0 select /*+g Y ather_plan_ statistics* / * from cu stomers whe re CUST_STA TE_PROVINCE ='CA' and c ountry_id=' US' b74nw722wjvy3 1 select /*+g N ather_plan_ statistics* / * from cu stomers whe re CUST_STA TE_PROVINCE ='CA' and c ountry_id=' US' SELECT /*+gather_plan_statistics*/ CUST_EMAIL FROM CUSTOMERS WHERE CUST_STATE_PROVINCE='MA' AND COUNTRY_ID='US'; SELECT * FROM TABLE(DBMS_XPLAN.DISPLAY_CURSOR(FORMAT=>'ALLSTATS LAST')); PLAN_TABLE_OUTPUT ------------------------------------- SQL_ID 3tk6hj3nkcs2u, child number 0 ------------------------------------- Select /*+gather_plan_statistics*/ cust_email From customers Where cust_state_province='MA' And country_id='US' Plan hash value: 1683234692 ------------------------------------------------------------------------------- |Id | Operation | Name | Starts|E-Rows|A-Rows| A-Time |Buffers| ------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 1 | | 2 |00:00:00.01| 16 | |*1 | TABLE ACCESS FULL| CUSTOMERS | 1 | 2| 2 |00:00:00.01| 16 | ----------------------------------------------------------------------------- Predicate Information (identified by operation id): --------------------------------------------------- 1 - filter(("CUST_STATE_PROVINCE"='MA' AND "COUNTRY_ID"='US')) Note ----- - dynamic sampling used for this statement (level=2) - 1 Sql Plan Directive used for this statement EXEC DBMS_SPD.FLUSH_SQL_PLAN_DIRECTIVE; SELECT TO_CHAR(d.DIRECTIVE_ID) dir_id, o.OWNER, o.OBJECT_NAME, o.SUBOBJECT_NAME col_name, o.OBJECT_TYPE, d.TYPE, d.STATE, d.REASON FROM DBA_SQL_PLAN_DIRECTIVES d, DBA_SQL_PLAN_DIR_OBJECTS o WHERE d.DIRECTIVE_ID=o.DIRECTIVE_ID AND o.OWNER IN ('SH') ORDER BY 1,2,3,4,5; DIR_ID OW OBJECT_NA COL_NAME OBJECT TYPE STATE REASON ------------------- -- --------- ---------- ------- --------------- ------------- ------------------------ 1484026771529551585 SH CUSTOMERS COUNTRY_ID COLUMN DYNAMIC_SAMPLING MISSING_STATS SINGLE TABLE CARDINALITY MISESTIMATE 1484026771529551585 SH CUSTOMERS CUST_STATE_ COLUMN DYNAMIC_SAMPLING MISSING_STATS SINGLE TABLE CARDINALITY PROVINCE MISESTIMATE 1484026771529551585 SH CUSTOMERS TABLE DYNAMIC_SAMPLING MISSING_STATS SINGLE TABLE CARDINALITY MISESTIMATE

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• Monitoring the wall time of a process on windows?

  - by Sean Madden

  Windows Task Manager has the ability to show the current CPU time of any given running process on windows, is there any way (not necessarily through Task Manager) to get the current wall time of a process? An example, let's say I have a script that reliably runs for about 45 minutes. Without adding a progress bar to the script, is there any way to figure out for how long it has been running? The math behind this seems pretty straight forward; WallTime = CurrentWallTime - WallTimeProcessStarted. Likewise, since the math is so simple, is there anyway to get the time that a process was started at?

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• Convert ddply {plyr} to Oracle R Enterprise, or use with Embedded R Execution

  - by Mark Hornick

  The plyr package contains a set of tools for partitioning a problem into smaller sub-problems that can be more easily processed. One function within {plyr} is ddply, which allows you to specify subsets of a data.frame and then apply a function to each subset. The result is gathered into a single data.frame. Such a capability is very convenient. The function ddply also has a parallel option that if TRUE, will apply the function in parallel, using the backend provided by foreach. This type of functionality is available through Oracle R Enterprise using the ore.groupApply function. In this blog post, we show a few examples from Sean Anderson's "A quick introduction to plyr" to illustrate the correpsonding functionality using ore.groupApply. To get started, we'll create a demo data set and load the plyr package. set.seed(1) d <- data.frame(year = rep(2000:2014, each = 3),         count = round(runif(45, 0, 20))) dim(d) library(plyr) This first example takes the data frame, partitions it by year, and calculates the coefficient of variation of the count, returning a data frame. # Example 1 res <- ddply(d, "year", function(x) {   mean.count <- mean(x$count)   sd.count <- sd(x$count)   cv <- sd.count/mean.count   data.frame(cv.count = cv)   }) To illustrate the equivalent functionality in Oracle R Enterprise, using embedded R execution, we use the ore.groupApply function on the same data, but pushed to the database, creating an ore.frame. The function ore.push creates a temporary table in the database, returning a proxy object, the ore.frame. D <- ore.push(d) res <- ore.groupApply (D, D$year, function(x) {   mean.count <- mean(x$count)   sd.count <- sd(x$count)   cv <- sd.count/mean.count   data.frame(year=x$year[1], cv.count = cv)   }, FUN.VALUE=data.frame(year=1, cv.count=1)) You'll notice the similarities in the first three arguments. With ore.groupApply, we augment the function to return the specific data.frame we want. We also specify the argument FUN.VALUE, which describes the resulting data.frame. From our previous blog posts, you may recall that by default, ore.groupApply returns an ore.list containing the results of each function invocation. To get a data.frame, we specify the structure of the result. The results in both cases are the same, however the ore.groupApply result is an ore.frame. In this case the data stays in the database until it's actually required. This can result in significant memory and time savings whe data is large. R> class(res) [1] "ore.frame" attr(,"package") [1] "OREbase" R> head(res)    year cv.count 1 2000 0.3984848 2 2001 0.6062178 3 2002 0.2309401 4 2003 0.5773503 5 2004 0.3069680 6 2005 0.3431743 To make the ore.groupApply execute in parallel, you can specify the argument parallel with either TRUE, to use default database parallelism, or to a specific number, which serves as a hint to the database as to how many parallel R engines should be used. The next ddply example uses the summarise function, which creates a new data.frame. In ore.groupApply, the year column is passed in with the data. Since no automatic creation of columns takes place, we explicitly set the year column in the data.frame result to the value of the first row, since all rows received by the function have the same year. # Example 2 ddply(d, "year", summarise, mean.count = mean(count)) res <- ore.groupApply (D, D$year, function(x) {   mean.count <- mean(x$count)   data.frame(year=x$year[1], mean.count = mean.count)   }, FUN.VALUE=data.frame(year=1, mean.count=1)) R> head(res)    year mean.count 1 2000 7.666667 2 2001 13.333333 3 2002 15.000000 4 2003 3.000000 5 2004 12.333333 6 2005 14.666667 Example 3 uses the transform function with ddply, which modifies the existing data.frame. With ore.groupApply, we again construct the data.frame explicilty, which is returned as an ore.frame. # Example 3 ddply(d, "year", transform, total.count = sum(count)) res <- ore.groupApply (D, D$year, function(x) {   total.count <- sum(x$count)   data.frame(year=x$year[1], count=x$count, total.count = total.count)   }, FUN.VALUE=data.frame(year=1, count=1, total.count=1)) > head(res)    year count total.count 1 2000 5 23 2 2000 7 23 3 2000 11 23 4 2001 18 40 5 2001 4 40 6 2001 18 40 In Example 4, the mutate function with ddply enables you to define new columns that build on columns just defined. Since the construction of the data.frame using ore.groupApply is explicit, you always have complete control over when and how to use columns. # Example 4 ddply(d, "year", mutate, mu = mean(count), sigma = sd(count),       cv = sigma/mu) res <- ore.groupApply (D, D$year, function(x) {   mu <- mean(x$count)   sigma <- sd(x$count)   cv <- sigma/mu   data.frame(year=x$year[1], count=x$count, mu=mu, sigma=sigma, cv=cv)   }, FUN.VALUE=data.frame(year=1, count=1, mu=1,sigma=1,cv=1)) R> head(res)    year count mu sigma cv 1 2000 5 7.666667 3.055050 0.3984848 2 2000 7 7.666667 3.055050 0.3984848 3 2000 11 7.666667 3.055050 0.3984848 4 2001 18 13.333333 8.082904 0.6062178 5 2001 4 13.333333 8.082904 0.6062178 6 2001 18 13.333333 8.082904 0.6062178 In Example 5, ddply is used to partition data on multiple columns before constructing the result. Realizing this with ore.groupApply involves creating an index column out of the concatenation of the columns used for partitioning. This example also allows us to illustrate using the ORE transparency layer to subset the data. # Example 5 baseball.dat <- subset(baseball, year > 2000) # data from the plyr package x <- ddply(baseball.dat, c("year", "team"), summarize,            homeruns = sum(hr)) We first push the data set to the database to get an ore.frame. We then add the composite column and perform the subset, using the transparency layer. Since the results from database execution are unordered, we will explicitly sort these results and view the first 6 rows. BB.DAT <- ore.push(baseball) BB.DAT$index <- with(BB.DAT, paste(year, team, sep="+")) BB.DAT2 <- subset(BB.DAT, year > 2000) X <- ore.groupApply (BB.DAT2, BB.DAT2$index, function(x) {   data.frame(year=x$year[1], team=x$team[1], homeruns=sum(x$hr))   }, FUN.VALUE=data.frame(year=1, team="A", homeruns=1), parallel=FALSE) res <- ore.sort(X, by=c("year","team")) R> head(res)    year team homeruns 1 2001 ANA 4 2 2001 ARI 155 3 2001 ATL 63 4 2001 BAL 58 5 2001 BOS 77 6 2001 CHA 63 Our next example is derived from the ggplot function documentation. This illustrates the use of ddply within using the ggplot2 package. We first create a data.frame with demo data and use ddply to create some statistics for each group (gp). We then use ggplot to produce the graph. We can take this same code, push the data.frame df to the database and invoke this on the database server. The graph will be returned to the client window, as depicted below. # Example 6 with ggplot2 library(ggplot2) df <- data.frame(gp = factor(rep(letters[1:3], each = 10)),                  y = rnorm(30)) # Compute sample mean and standard deviation in each group library(plyr) ds <- ddply(df, .(gp), summarise, mean = mean(y), sd = sd(y)) # Set up a skeleton ggplot object and add layers: ggplot() +   geom_point(data = df, aes(x = gp, y = y)) +   geom_point(data = ds, aes(x = gp, y = mean),              colour = 'red', size = 3) +   geom_errorbar(data = ds, aes(x = gp, y = mean,                                ymin = mean - sd, ymax = mean + sd),              colour = 'red', width = 0.4) DF <- ore.push(df) ore.tableApply(DF, function(df) {   library(ggplot2)   library(plyr)   ds <- ddply(df, .(gp), summarise, mean = mean(y), sd = sd(y))   ggplot() +     geom_point(data = df, aes(x = gp, y = y)) +     geom_point(data = ds, aes(x = gp, y = mean),                colour = 'red', size = 3) +     geom_errorbar(data = ds, aes(x = gp, y = mean,                                  ymin = mean - sd, ymax = mean + sd),                   colour = 'red', width = 0.4) }) But let's take this one step further. Suppose we wanted to produce multiple graphs, partitioned on some index column. We replicate the data three times and add some noise to the y values, just to make the graphs a little different. We also create an index column to form our three partitions. Note that we've also specified that this should be executed in parallel, allowing Oracle Database to control and manage the server-side R engines. The result of ore.groupApply is an ore.list that contains the three graphs. Each graph can be viewed by printing the list element. df2 <- rbind(df,df,df) df2$y <- df2$y + rnorm(nrow(df2)) df2$index <- c(rep(1,300), rep(2,300), rep(3,300)) DF2 <- ore.push(df2) res <- ore.groupApply(DF2, DF2$index, function(df) {   df <- df[,1:2]   library(ggplot2)   library(plyr)   ds <- ddply(df, .(gp), summarise, mean = mean(y), sd = sd(y))   ggplot() +     geom_point(data = df, aes(x = gp, y = y)) +     geom_point(data = ds, aes(x = gp, y = mean),                colour = 'red', size = 3) +     geom_errorbar(data = ds, aes(x = gp, y = mean,                                  ymin = mean - sd, ymax = mean + sd),                   colour = 'red', width = 0.4)   }, parallel=TRUE) res[[1]] res[[2]] res[[3]] To recap, we've illustrated how various uses of ddply from the plyr package can be realized in ore.groupApply, which affords the user explicit control over the contents of the data.frame result in a straightforward manner. We've also highlighted how ddply can be used within an ore.groupApply call.

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• Launching php script through comman line - keeping terminal window open after execution

  - by somethis

  Oh, my girlfriend really likes it when I launch php scripts! There's something special about them, she says ... Thus, I coded this script to run throught the CLI (Command Line Interface) - so it's running locally, not on a web server. It launches just fine through right click open run in terminal but closes right after execution. **Is there a way to keep the terminal window open? Of course I can launch it through a terminal window - which would stay open - but I'm looking for a one click action. With bash scripts I use $SHELL but that didn't work (see code below). So far, the only thing I came up with is sleep(10); which gives me 10 seconds for my girl to check the output. I'd rather close the terminal window manually, though. #!/usr/bin/php -q <?php echo "Hello World \n"; # wait before closing terminal window sleep(10); # the following line doesn't work $SHELL; ?> (PHP 5.4.6-1ubuntu1.2 (cli) (built: Mar 11 2013 14:57:54) Copyright (c) 1997-2012 The PHP Group Zend Engine v2.4.0, Copyright (c) 1998-2012 Zend Technologies )

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• Execution plan warnings–All that glitters is not gold

  - by Dave Ballantyne

  In a previous post, I showed you the new execution plan warnings related to implicit and explicit warnings.  Pretty much as soon as i hit ’post’,  I noticed something rather odd happening. This statement : select top(10) SalesOrderHeader.SalesOrderID, SalesOrderNumberfrom Sales.SalesOrderHeaderjoin Sales.SalesOrderDetail on SalesOrderHeader.SalesOrderID = SalesOrderDetail.SalesOrderID   Throws the “Type conversion may affect cardinality estimation” warning.     Ive done no such conversion in my statement why would that be ?  Well, SalesOrderNumber is a computed column , “(isnull(N'SO'+CONVERT([nvarchar](23),[SalesOrderID],0),N'*** ERROR ***'))”,  so thats where the conversion is.   Wait!!! Am i saying that every type conversion will throw the warning ?  Thankfully, no.  It only appears for columns that are used in predicates ,even if the predicate / join condition is fine ,  and the column is indexed ( and/or , presumably has statistics).    Hopefully , this wont lead to to many wild goose chases, but is definitely something to bear in mind.  If you want to see this fixed then upvote my connect item here.

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• SSIS Catalog: How to use environment in every type of package execution

  - by Kevin Shyr

  Here is a good blog on how to create a SSIS Catalog and setting up environments.  http://sqlblog.com/blogs/jamie_thomson/archive/2010/11/13/ssis-server-catalogs-environments-environment-variables-in-ssis-in-denali.aspx Here I will summarize 3 ways I know so far to execute a package while using variables set up in SSIS Catalog environment. First way, we have SSIS project having reference to environment, and having one of the project parameter using a value set up in the environment called "Development".  With this set up, you are limited to calling the packages by right-clicking on the packages in the SSIS catalog list and select Execute, but you are free to choose absolute or relative path of the environment. The following screenshot shows the 2 available paths to your SSIS environments.  Personally, I use absolute path because of Option 3, just to keep everything simple for myself. The second option is to call through SQL Job.  This does require you to configure your project to already reference an environment and use its variable.  When a job step is set up, the configuration part will require you to select that reference again.  This is more useful when you want to automate the same package that needs to be run in different environments. The third option is the most important to me as I have a SSIS framework that calls hundreds of packages.  The main part of the stored procedure is in this post (http://geekswithblogs.net/LifeLongTechie/archive/2012/11/14/time-to-stop-using-ldquoexecute-package-taskrdquondash-a-way-to.aspx).  But the top part had to be modified to include the logic to use environment reference. CREATE PROCEDURE [AUDIT].[LaunchPackageExecutionInSSISCatalog] @PackageName NVARCHAR(255) , @ProjectFolder NVARCHAR(255) , @ProjectName NVARCHAR(255) , @AuditKey INT , @DisableNotification BIT , @PackageExecutionLogID INT , @EnvironmentName NVARCHAR(128) = NULL , @Use32BitRunTime BIT = FALSE AS BEGIN TRY DECLARE @execution_id BIGINT = 0; -- Create a package execution IF @EnvironmentName IS NULL BEGIN   EXEC [SSISDB].[catalog].[create_execution]     @package_name=@PackageName,     @execution_id=@execution_id OUTPUT,     @folder_name=@ProjectFolder,     @project_name=@ProjectName,     @use32bitruntime=@Use32BitRunTime; END ELSE BEGIN   DECLARE @EnvironmentID AS INT   SELECT @EnvironmentID = [reference_id]    FROM SSISDB.[internal].[environment_references] WITH(NOLOCK)    WHERE [environment_name] = @EnvironmentName     AND [environment_folder_name] = @ProjectFolder      EXEC [SSISDB].[catalog].[create_execution]     @package_name=@PackageName,     @execution_id=@execution_id OUTPUT,     @folder_name=@ProjectFolder,     @project_name=@ProjectName,     @reference_id=@EnvironmentID,     @use32bitruntime=@Use32BitRunTime; END

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• Work Execution in EAM

  - by Annemarie Provisero

  ADVISOR WEBCAST: Work Execution in EAM PRODUCT FAMILY: Manufacturing Enterprise Asset Management July 5, 2011 at 8 am PT, 9 am MT, 11 am ET The purpose of this webcast is to discuss EAM Work Order Management. This one-hour session is ideal for Functional Users, System Administrators, Database Administrators, and Customers with a basic knowledge of EAM and who raise or manage work orders and related processes. During this webcast, Zar will cover the various types of work orders and look at all the related activities associated with work orders including: setup, operations, tasks, work order transactions, relationship and planning. TOPICS WILL INCLUDE: Work Order Types (Routine, Planned Maintenance, Rebuild, Easy) Work Order statuses and other important setups Operations and Tasks Relationships Work Order Transactions Work Order Planning A short, live demonstration (only if applicable) and question and answer period will be included. Oracle Advisor Webcasts are dedicated to building your awareness around our products and services. This session does not replace offerings from Oracle Global Support Services. Click here to register for this session ------------------------------------------------------------------------------------------------------------- The above webcast is a service of the E-Business Suite Communities in My Oracle Support. For more information on other webcasts, please reference the Oracle Advisor Webcast Schedule.Click here to visit the E-Business Communities in My Oracle Support Note that all links require access to My Oracle Support.

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• Delay command execution over sockets

  - by David

  I've been trying to fix the game loop in a real time (tick delay) MUD. I realized using Thread.Sleep would seem clunky when the user spammed commands through their choice of client (Zmud, etc) e.g. east;south;southwest would wait three move ticks and then output everything from the past couple rooms. The game loop basically calls a Flush and Fill method for each socket during each tick (50ms) private void DoLoop() { Stopwatch stopWatch = new Stopwatch(); stopWatch.Start(); while (running) { // for each socket, flush and fill ConnectionMonitor.Update(); stopWatch.Stop(); WaitIfNeeded(stopWatch.ElapsedMilliseconds); stopWatch.Reset(); } } The Fill method fires the command events, but as mentioned before, they currently block using Thread.Sleep. I tried adding a "ready" flag to the state object that attempts to execute the command along with a queue of spammed commands, but it ends up executing one command and queuing up the rest i.e. each subsequent command executes something that got queued up that should've been executed before. I must be missing something about the timer. private readonly Queue<SpammedCommand> queuedCommands = new Queue<SpammedCommand>(); private bool ready = true; private void TryExecuteCommand(string input) { var commandContext = CommandContext.Create(input); var player = Server.Current.Database.Get<Player>(Session.Player.Key); var commandInfo = Server.Current.CommandLookup .FindCommand(commandContext.CommandName, player.IsAdmin); if (commandInfo != null) { if (!ready) { // queue command queuedCommands.Enqueue(new SpammedCommand() { Context = commandContext, Info = commandInfo }); return; } if (queuedCommands.Count > 0) { // queue the incoming command queuedCommands.Enqueue(new SpammedCommand() { Context = commandContext, Info = commandInfo, }); // dequeue and execute var command = queuedCommands.Dequeue(); command.Info.Command.Execute(Session, command.Context); setTimeout(command.Info.TickLength); return; } commandInfo.Command.Execute(Session, commandContext); setTimeout(commandInfo.TickLength); } else { Session.WriteLine("Command not recognized"); } } Finally, setTimeout was supposed to set the execution delay (TickLength) for that command, and makeReady just sets the ready flag on the state object to true. private void setTimeout(TickDelay tickDelay) { ready = false; var t = new System.Timers.Timer() { Interval = (long) tickDelay, AutoReset = false, }; t.Elapsed += makeReady; t.Start(); // fire this in tickDelay ms } // MAKE READYYYYY!!!! private void makeReady(object sender, System.Timers.ElapsedEventArgs e) { ready = true; } Am I missing something about the System.Timers.Timer created in setTimeout? How can I execute (and output) spammed commands per TickLength without using Thread.Sleep?

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• How do I notify Oracle that an IIS Worker Process is about to recycle?

  - by Brien

  I have an ASP.NET web application with an Oracle back end. The worker process recycling in IIS is set for 40 minutes, and when that occurs, the Oracle server sets a mutex lock while it cleans up all of its open connections. During this cleanup (up to a few minutes in duration), all DB requests get a timeout. Is there a way for IIS to notify Oracle that a worker process recycle is about to occur, so Oracle can be smarter about how it cleans up its resources without locking the entire database?

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• How do you measure the bandwidth used by a given process after it has completed, on Linux?

  - by Paul

  Is there a way to get a summary of how much bandwidth a given process used on Linux after the process completes? I do not want a monitor, I want something I can look at after the task has completed.. Ideally something like the "time" command or a profiler, but for network usage.

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