Search Results

Search found 12325 results on 493 pages for 'remote execution'.

facebook twitter digg google delicious technorati stumbleupon myspace wordpress linkedin gmail igoogle windows live tumblr viadeo yahoo buzz yahoo mail yahoo bookmarks favorites email print

Page 32/493 | < Previous Page | 28 29 30 31 32 33 34 35 36 37 38 39  | Next Page >

  • How to write to a remote domain

    - by user347743
    Hello, I have a domain www.example.com In the domain, www.example.com/write directory is chmod to 777. Now, suppose, if I want to create a new directory like www.example.com/write/new from www.some-domain.com, what should I be doing. I know PHP, Python. Please relate the answers to this.

    Read the article

  • Remotely managing Scheduled Tasks on another computer: Access Denied

    - by Eptin
    I need to remotely create new scheduled tasks from a Windows 7 computer in my company (which according to this Microsoft TechNet article I should be able to do. http://technet.microsoft.com/en-us/library/cc766266.aspx ) From within Task Scheduler, on the menu I click Action Connect to another Computer. I browse for the remote computer's name (I use Check Names to verify that the name is correct) and then I check 'Connect as another user' and enter \Administrator and the local admin password. Whenever I try this, I get the error message Task Scheduler: You do not have permission to access this computer Firewall isn't the problem I am able to use Remote Desktop with this username & password combo, so I would expect it to work when remotely managing as well. The remote computer has firewall exceptions for Remote Scheduled Tasks Management, Remote Service Management, and Remote Desktop among other things. Heck, I even tried turning off the firewall for that individual computer and it still didn't work. More details: I have administrative remote access to several other Windows 7 Enterprise computers, though I log in as the local Administrator (whose administrative rights are only recognized by that local machine, not by the domain). The computer I am managing from is on the domain, and also has administrative rights that are recognized on the domain. More experimentation: If I go the other way around and remote-desktop into the other machine and from there open task scheduler then 'connect to another computer', I am able to connect back to my main computer using the username & password that is recognized by an administrator on the domain, and successfully schedule a task on my main computer. So it's not a company firewall issue that's preventing anything from working. The only permissions requirement Microsoft talks about is "The user credentials that you use to connect to the remote computer must be a member of the Administrators group on the remote computer". I'm logging in as an Administrator on each of the local machines, so why doesn't it work?

    Read the article

  • How can I disable the IR/Remote Control on an HP Laptop?

    - by Steve Rowe
    I've seen this happen on 2 different HP laptops now. If I try to use them in the same room as a Media Center, the MCE TV remote keeps sending commands to the laptop. This can do anything from wake it up and turn it on to just moving the selection around. There is no obvious way to disable the IR sensor or at least its response to the remote. Does anyone know how to do this?

    Read the article

  • How to use psexec without admin privileges on target machine?

    - by HighCommander4
    Is it possible to use psexec to execute a command on a remote machine without having admin privileges on the remote machine? I tried running psexec \\<machine> -u <username> -p <password>, where <username> and <password> are non-admin credentials, but I get an "access denied" error I can remote desktop into the remote machine with the same credentials without any problems. My local machine is running Windows 7 Enterprise 64-bit, and the remote machine is running Windows Server 2008 64-bit. I do have admin privileges on the local machine. EDIT: To all the people who are downvoting this question: I am not trying to circumvent any sort of security measure. I can already run the process on the remote machine by remote desktop-ing into the remote machine and running it. I'm simply looking for a command-line way to do something I can already do through a GUI.

    Read the article

  • What is the usual procedure for working with remote Git repositories?

    - by James
    A slightly open question regarding best practices, I can find lots of functional guides for git but not much info about standard ordering of operations etc: Whats the standard/nice way of working with remote repositories, specifically for making a change and taking it all the way back to the remote master. Can someone provide a step-by-step list of procedures they normally follow when doing this. i.e. something like: 1) clone repo 2) create new local branch of head 3) make changes locally and commit to local branch 4) ...

    Read the article

  • Virtual PC in Remote Desktop session runs very slowly??

    - by Michael Bray
    I have a VPN to my work which is quite fast... I Remote Desktop to my work PC, which is running a Microsoft Virtual PC. Working with the PC while I'm actually at work isn't too bad, but when I try to interact with it over the remote desktop, it is VERY slow to respond. Even simple typing can be slow, but screen painting and response time is painfully obvious. Any suggestions to help speed it up?

    Read the article

  • 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.

    Read the article

  • 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 ?, ?, ?, ?, ?, ...

    Read the article

  • 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

    Read the article

  • ?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

    Read the article

  • Adding user groups from a remote domain server to permissions of a remote desktop terminal server fails. why?

    - by doveyg
    I have 3 computers, two of which are servers running Windows Server 2008 and another running Windows 7. One of the servers has the following roles installed; Active Directory, DHCP and DNS. The other server has a Terminal Server role installed. I am trying to log-on to the Terminal Server via Remote Desktop using the Windows 7 machine with credentials from the Active Directory server. Sounds simple enough, right? Well, no. Whenever I try to add users or groups from the Active Directory Domain server to the Terminal Server's permissions for RDP it seems to ignore, or forget, them. Though the various methods I was able to find it either adds a strange sting of numbers after the user group or the logo to the left has a question mark on it, reopening the dialogue box replaces the user group with the name of the Domain. I am confident I have the Domain setup correctly as I am able to log-on to users in the Active Directory from other computers I have put in the Domain, and when I attempt to browse the user objects from the Domain I am prompted with a username/password field and am able to view the structure of Active Directory objects. Please advise.

    Read the article

  • DNS issue for internal website routing internet connection from remote location

    - by Michael Paul
    I have an issue that I could use some help with. Our company has a main location and a remote location. Previously, the remote location was connected to the main location through an internet connection VPN tunnel. The connection was pitifully slow at 1.5Mbps, so we upgraded it with a 75Mbps direct link. That meant the remote location lost it's internet access, so we routed their access through the main office internet connection. Everything works perfect except for one thing. The website we host is not accessible from the remote location unless the IP address is used. If I do NSLOOKUP on our website address from a machine connected to the main location network, it resolves correctly to the inside IP address. However, if I do the same from a remote location machine, it resolves to the website's outside IP address. Our internal DNS server(s) have a pointer and CNAME records set up, and everything was working perfectly before the connection was upgraded. In addition, the remote location has a domain controller, DNS server and DHCP server to service these requests at the remote location and prevent these requests from getting routed back and forth over the link. So I think was it happening is that for some reason the DNS server at the remote location is not resolving our website name correctly and passing the requests on to the routers, which then push the request out to the internet DNS system. That resolves the name to our external IP. This is purely a DNS issue, everything else works just fine. I am just stumped on this one. Any ideas on how to fix this? Edit: I forgot to mention that at the remote side of the link is a Cisco ASA-5505 and at the main office there is a Cisco ASA-5510. The link is connected between these 2 devices and the routing is handled in the 5510. Thanks, Michael

    Read the article

  • 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.

    Read the article

  • 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 )

    Read the article

  • 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.

    Read the article

  • 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

    Read the article

  • 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.

    Read the article

  • How do I copy a python function to a remote machine and then execute it?

    - by Hugh
    I'm trying to create a construct in Python 3 that will allow me to easily execute a function on a remote machine. Assuming I've already got a python tcp server that will run the functions it receives, running on the remote server, I'm currently looking at using a decorator like @execute_on(address, port) This would create the necessary context required to execute the function it is decorating and then send the function and context to the tcp server on the remote machine, which then executes it. Firstly, is this somewhat sane? And if not could you recommend a better approach? I've done some googling but haven't found anything that meets these needs. I've got a quick and dirty implementation for the tcp server and client so fairly sure that'll work. I can get a string representation the function (e.g. func) being passed to the decorator by import inspect string = inspect.getsource(func) which can then be sent to the server where it can be executed. The problem is, how do I get all of the context information that the function requires to execute? For example, if func is defined as follows, import MyModule def func(): result = MyModule.my_func() MyModule will need to be available to func either in the global context or funcs local context on the remote server. In this case that's relatively trivial but it can get so much more complicated depending on when and how import statements are used. Is there an easy and elegant way to do this in Python? The best I've come up with at the moment is using the ast library to pull out all import statements, using the inspect module to get string representations of those modules and then reconstructing the entire context on the remote server. Not particularly elegant and I can see lots of room for error. Thanks for your time

    Read the article

  • Git push current branch to a remote with Heroku

    - by cmaughan
    I'm trying to create a staging branch on Heroku, but there's something I don't quite get. Assuming I've already created a heroku app and setup the remote to point to staging-remote, If I do: git checkout -b staging staging-remote/master I get a local branch called 'staging' which tracks staging-remote/master - or that's what I thought.... But: git remote show staging-remote Gives me this: remote staging Fetch URL: [email protected]:myappname.git Push URL: [email protected]:myappname.git HEAD branch: master Remote branch: master tracked Local branch configured for 'git pull': staging-remote merges with remote master Local ref configured for 'git push': master pushes to master (up to date) As you can see, the pull looks reasonable, but the default push does not. It implies that if I do: git push staging-remote I'm going to push my local master branch up to the staging branch. But that's not what I want.... Basically, I want to merge updates into my staging branch, then easily push it to heroku without having to specify the branch like so: git push staging-remote mybranch:master The above isn't hard to do, but I want to avoid accidentally doing the previous push and pushing the wrong branch... This is doubly important for the production branch I'd like to create! I've tried messing with git config, but haven't figured out how to get this right yet...

    Read the article

  • Why can't I debug my ASP project through a remote desktop connection?

    - by Anthony Benavente
    I just asked this question in Stack Overflow but I figured this stack exchange forum is a better fit. It's been about a month of trying to figure out this problem and we've still not found a solution. We have about seven virtual machines on a server running Windows XP Professional w/ SP 3 all with Visual Studio Interdev and IIS 5.1 installed. Running the programs all work fine, but we just can't debug through remote desktop. When we are logged into the server console (through VM Sphere) and log into one of the virtual machines through there, we are able to debug properly. We figured the issue lies with some kind of permissions for Remote Desktop Users. We've tried nearly every article on the internet (exaggerating of course) and are about to give up hope. One more thing, when we are logged into the virtual machine through the server console and then remote in, the user that was logged into the console is kicked off but debugging works! Does remoting in trick the computer into giving us the correct permissions? I'm really not sure how it works. I know that this technology predates human history, but we are in the process of migrating from ASP Classic to ASP.NET Specs: - Windows XP Professional W/ SP3 - IIS 5.1 - Visual Studio 6 Interdev EDIT: By "debug" I mean running the project with breakpoints. Interdev doesn't stop at breakpoints.

    Read the article

facebook twitter digg google delicious technorati stumbleupon myspace wordpress linkedin gmail igoogle windows live tumblr viadeo yahoo buzz yahoo mail yahoo bookmarks favorites email print

< Previous Page | 28 29 30 31 32 33 34 35 36 37 38 39  | Next Page >