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• Passing a string to a function in C++

  - by Chef Flambe

  I want to pass a string like "Celcius" into a function that I have but I keep getting errors tossed back at me from the Function. System::Console::WriteLine' : none of the 19 overloads could convert all the argument types I figure I just have something simple wrong. Can someone point out my mistake please? Using MS Visual C++ 2010 I've posted the offending code. The other functions (not posted) work fine. void PrintResult( double result, std::string sType ); // Print result and string // to the console //============================================================================================= // start of main //============================================================================================= void main( void ) { ConsoleKeyInfo CFM; // Program Title and Description ProgramDescription(); // Menu Selection and calls to data retrieval/calculation/result Print CFM=ChooseFromMenu(); switch(CFM.KeyChar) // ************************************************************ { //* case '1' : PrintResult(F2C(GetTemperature()),"Celsius"); //* break; //* //* case '2' : PrintResult(C2F(GetTemperature()),"Fahrenheit"); //* break; //* //* default : Console::Write("\n\nSwitch : Case !!!FAILURE!!!"); //* } //************************************************************ system("pause"); return; } //Function void PrintResult( double result, std::string sType ) { Console::WriteLine("\n\nThe converted temperature is {0:F2} degrees {1}\n\n",result,sType); return; }

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• Parallelizing for loop

  - by vman049

  I have MATLAB code which I'm trying to parallelize with a simple change from "for" to "parfor." I'm unable to do so because of an error I'm receiving on the variable "votes" which states: Valid indices for 'votes' are restricted in PARFOR loops. Explanation: For MATLAB to execute parfor loops efficiently, the amount of data sent to the MATLAB workers must be minimal. One of the ways MATLAB achieves this is by restricting the way variables can be indexed in parfor iterations. The indicated variable is indexed in a way that is incompatible with parfor. Suggested Action: Fix the indexing. For a description of the indexing restrictions, see “Sliced Variables” in the Parallel Computing Toolbox documentation. Below is my code: votes = zeros(num_layers, size(spikes, 1), size(SVMs_layer1, 1)); predDir = zeros(size(spikes, 1), 1); chronProb = zeros([num_layers, size(chronDists)]); for i = 1:num_layers switch i case 1 B = B1; k_elem_temp = k_elem1; rest_elem_temp = rest_elem1; case 2 B = B2; k_elem_temp = k_elem2; rest_elem_temp = rest_elem2; case 3 B = B3; k_elem_temp = k_elem3; rest_elem_temp = rest_elem3; end for j = 1:length(chronPred) if chronDists(i, j, :) ~= 0 parfor k = 1:8 chronProb(i, j, k) = logistic(B{k}(1) + chronDists(i, j, k).*(B{k}(2))); votes(i, j, k_elem_temp(k, :)) = votes(i, j, k_elem_temp(k, :)) + chronProb(i, j, k)/num_k(i)/num_layers; votes(i, j, rest_elem_temp(k, :)) = votes(i, j, rest_elem_temp(k, :)) + (1 - chronProb(i, j, k))/num_rest(i)/num_layers; end end end end Do you have any suggestions as to how I could adjust my code so that it runs in parallel? Thank you!

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• Help with enum values in registry c++

  - by vBx

  DWORD type = REG_NONE; int i = 0; size = sizeof(ValueName); size2 = sizeof(ValueData); BOOL bContinue = TRUE; do { lRet = RegEnumValue(Hkey , i , ValueName , &size , 0 , &type , ValueData , &size2); switch(lRet) { case ERROR_SUCCESS: print_values(ValueName , type , ValueData , size2); i++; size = sizeof(ValueName); size2 = sizeof(ValueData); break; case ERROR_MORE_DATA: size2 = sizeof(ValueData); if(NULL != ValueData) delete [] ValueData; ValueData = new BYTE[size2]; break; case ERROR_NO_MORE_ITEMS: bContinue = false; break; default: cout << "Unexpected error: " << GetLastError() << endl; bContinue = false; break; } }while(bContinue); it always goes to ERROR_NO_MORE_DATA ,why is that ? :-/

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• SDK2 query for counting: which is more efficient?

  - by user1195996

  I have an app that is displaying metrics about defects in a project. I have the option of making one query that returns all the defects, and from that I can break out about four different metrics (How many defects escaped QA in 90 days, 180 days, and then the same metrics again but only counting sev1/sev2 defects). I could make four queries and limit the results to one so that I just get a count for each. Or I could make one query that encompass them all (all defects that escaped QA in 180 days) and then count up the difference. I'm figuring worst case, the number of defects that escaped QA in the last six months will generally be less than 100, certainly less 500 worst case. Which would you do-- four queryies with one result each, or one single query that on average might return 50, perhaps worst case 500? And I guess the key question is-- where are the inflections points? Perhaps I have more metrics tomorrow (who knows, 8?) and a different average defect counts. Is there a rule of thumb I could use to help choose which approach?

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• How can I combine a LINQ query with an IQueryable<Guid>

  - by John

  I have a LINQ query that uses 1 table + a large number of views. I'd like to be able to write something like this: IQueryable<Guid> mostViewedWriters; switch (datePicker) { case DatePicker.Last12Hours: mostViewedWriters = from x in context.tempMostViewed12Hours select x.GuidId; break; case DatePicker.Last24Hours: mostViewedWriters = from x in context.tempMostViewed12Hours select x.GuidId; break; case DatePicker.Last36Hours: mostViewedWriters = from x in context.tempMostViewed12Hours select x.GuidId; break; } var query = from x1 in context.Articles join x2 in context.Authors on x1.AuthorId == x2.AuthorId join x3 in mostViewedWriters on x2.AuthorId == x3.Id select new { x2.AuthorName, x1.ArticleId, x1.ArticleTitle }; The above C# is pseudo-code written to protect the innocent (me). The gist of the question is this: I have a query that is related to the results of a view. That view, however, could be one of many different views. All the views return the same data type. I thought that I might be able to create an IQueryable that would contain the Ids that I need and use that query. Alas, that effort has stalled.

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• difficulties in javascript coding [on hold]

  - by user3718986

  Question is, It takes me 3 hours to fly from NY to CA. How much it will take me if I fly directly from NY to Florida. suppose that distance from CA to Flordia is 8 hours by air..Rule is if you suppose to travel from NY to Florida you will have to pass through CA. I did the quesiton in JavaScript below but coding isn't correct. Can someone fixed this issue for me please? var destination = prompt('Please enter your destinations. We are currently flying to NY,CA and FL'); var locatioon = prompt("specify your current location. "); switch (destination) { case 'NY': { distanceTeller(locatioon); break; } break; case 'CA': { distanceTeller(locatioon); break; } break; case 'FL': { alert("11 HR"); } default: alert('dont look at me'); break; } function distanceTeller(locatioon) { if (locatioon == 'CA') { alert('it will take you 3 hours'); } else if (locatioon == 'FL') { alert('it will take you 8 hours'); } else alert('it will take you 11 hours to reach NY'); }

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• Using FiddlerCore to capture HTTP Requests with .NET

  - by Rick Strahl

  Over the last few weeks I’ve been working on my Web load testing utility West Wind WebSurge. One of the key components of a load testing tool is the ability to capture URLs effectively so that you can play them back later under load. One of the options in WebSurge for capturing URLs is to use its built-in capture tool which acts as an HTTP proxy to capture any HTTP and HTTPS traffic from most Windows HTTP clients, including Web Browsers as well as standalone Windows applications and services. To make this happen, I used Eric Lawrence’s awesome FiddlerCore library, which provides most of the functionality of his desktop Fiddler application, all rolled into an easy to use library that you can plug into your own applications. FiddlerCore makes it almost too easy to capture HTTP content! For WebSurge I needed to capture all HTTP traffic in order to capture the full HTTP request – URL, headers and any content posted by the client. The result of what I ended up creating is this semi-generic capture form: In this post I’m going to demonstrate how easy it is to use FiddlerCore to build this HTTP Capture Form.  If you want to jump right in here are the links to get Telerik’s Fiddler Core and the code for the demo provided here. FiddlerCore Download FiddlerCore on NuGet Show me the Code (WebSurge Integration code from GitHub) Download the WinForms Sample Form West Wind Web Surge (example implementation in live app) Note that FiddlerCore is bound by a license for commercial usage – see license.txt in the FiddlerCore distribution for details. Integrating FiddlerCore FiddlerCore is a library that simply plugs into your application. You can download it from the Telerik site and manually add the assemblies to your project, or you can simply install the NuGet package via:       PM> Install-Package FiddlerCore The library consists of the FiddlerCore.dll as well as a couple of support libraries (CertMaker.dll and BCMakeCert.dll) that are used for installing SSL certificates. I’ll have more on SSL captures and certificate installation later in this post. But first let’s see how easy it is to use FiddlerCore to capture HTTP content by looking at how to build the above capture form. Capturing HTTP Content Once the library is installed it’s super easy to hook up Fiddler functionality. Fiddler includes a number of static class methods on the FiddlerApplication object that can be called to hook up callback events as well as actual start monitoring HTTP URLs. In the following code directly lifted from WebSurge, I configure a few filter options on Form level object, from the user inputs shown on the form by assigning it to a capture options object. In the live application these settings are persisted configuration values, but in the demo they are one time values initialized and set on the form. Once these options are set, I hook up the AfterSessionComplete event to capture every URL that passes through the proxy after the request is completed and start up the Proxy service:void Start() { if (tbIgnoreResources.Checked) CaptureConfiguration.IgnoreResources = true; else CaptureConfiguration.IgnoreResources = false; string strProcId = txtProcessId.Text; if (strProcId.Contains('-')) strProcId = strProcId.Substring(strProcId.IndexOf('-') + 1).Trim(); strProcId = strProcId.Trim(); int procId = 0; if (!string.IsNullOrEmpty(strProcId)) { if (!int.TryParse(strProcId, out procId)) procId = 0; } CaptureConfiguration.ProcessId = procId; CaptureConfiguration.CaptureDomain = txtCaptureDomain.Text; FiddlerApplication.AfterSessionComplete += FiddlerApplication_AfterSessionComplete; FiddlerApplication.Startup(8888, true, true, true); } The key lines for FiddlerCore are just the last two lines of code that include the event hookup code as well as the Startup() method call. Here I only hook up to the AfterSessionComplete event but there are a number of other events that hook various stages of the HTTP request cycle you can also hook into. Other events include BeforeRequest, BeforeResponse, RequestHeadersAvailable, ResponseHeadersAvailable and so on. In my case I want to capture the request data and I actually have several options to capture this data. AfterSessionComplete is the last event that fires in the request sequence and it’s the most common choice to capture all request and response data. I could have used several other events, but AfterSessionComplete is one place where you can look both at the request and response data, so this will be the most common place to hook into if you’re capturing content. The implementation of AfterSessionComplete is responsible for capturing all HTTP request headers and it looks something like this:private void FiddlerApplication_AfterSessionComplete(Session sess) { // Ignore HTTPS connect requests if (sess.RequestMethod == "CONNECT") return; if (CaptureConfiguration.ProcessId > 0) { if (sess.LocalProcessID != 0 && sess.LocalProcessID != CaptureConfiguration.ProcessId) return; } if (!string.IsNullOrEmpty(CaptureConfiguration.CaptureDomain)) { if (sess.hostname.ToLower() != CaptureConfiguration.CaptureDomain.Trim().ToLower()) return; } if (CaptureConfiguration.IgnoreResources) { string url = sess.fullUrl.ToLower(); var extensions = CaptureConfiguration.ExtensionFilterExclusions; foreach (var ext in extensions) { if (url.Contains(ext)) return; } var filters = CaptureConfiguration.UrlFilterExclusions; foreach (var urlFilter in filters) { if (url.Contains(urlFilter)) return; } } if (sess == null || sess.oRequest == null || sess.oRequest.headers == null) return; string headers = sess.oRequest.headers.ToString(); var reqBody = sess.GetRequestBodyAsString(); // if you wanted to capture the response //string respHeaders = session.oResponse.headers.ToString(); //var respBody = session.GetResponseBodyAsString(); // replace the HTTP line to inject full URL string firstLine = sess.RequestMethod + " " + sess.fullUrl + " " + sess.oRequest.headers.HTTPVersion; int at = headers.IndexOf("\r\n"); if (at < 0) return; headers = firstLine + "\r\n" + headers.Substring(at + 1); string output = headers + "\r\n" + (!string.IsNullOrEmpty(reqBody) ? reqBody + "\r\n" : string.Empty) + Separator + "\r\n\r\n"; BeginInvoke(new Action<string>((text) => { txtCapture.AppendText(text); UpdateButtonStatus(); }), output); } The code starts by filtering out some requests based on the CaptureOptions I set before the capture is started. These options/filters are applied when requests actually come in. This is very useful to help narrow down the requests that are captured for playback based on options the user picked. I find it useful to limit requests to a certain domain for captures, as well as filtering out some request types like static resources – images, css, scripts etc. This is of course optional, but I think it’s a common scenario and WebSurge makes good use of this feature. AfterSessionComplete like other FiddlerCore events, provides a Session object parameter which contains all the request and response details. There are oRequest and oResponse objects to hold their respective data. In my case I’m interested in the raw request headers and body only, as you can see in the commented code you can also retrieve the response headers and body. Here the code captures the request headers and body and simply appends the output to the textbox on the screen. Note that the Fiddler events are asynchronous, so in order to display the content in the UI they have to be marshaled back the UI thread with BeginInvoke, which here simply takes the generated headers and appends it to the existing textbox test on the form. As each request is processed, the headers are captured and appended to the bottom of the textbox resulting in a Session HTTP capture in the format that Web Surge internally supports, which is basically raw request headers with a customized 1st HTTP Header line that includes the full URL rather than a server relative URL. When the capture is done the user can either copy the raw HTTP session to the clipboard, or directly save it to file. This raw capture format is the same format WebSurge and also Fiddler use to import/export request data. While this code is application specific, it demonstrates the kind of logic that you can easily apply to the request capture process, which is one of the reasonsof why FiddlerCore is so powerful. You get to choose what content you want to look up as part of your own application logic and you can then decide how to capture or use that data as part of your application. The actual captured data in this case is only a string. The user can edit the data by hand or in the the case of WebSurge, save it to disk and automatically open the captured session as a new load test. Stopping the FiddlerCore Proxy Finally to stop capturing requests you simply disconnect the event handler and call the FiddlerApplication.ShutDown() method:void Stop() { FiddlerApplication.AfterSessionComplete -= FiddlerApplication_AfterSessionComplete; if (FiddlerApplication.IsStarted()) FiddlerApplication.Shutdown(); } As you can see, adding HTTP capture functionality to an application is very straight forward. FiddlerCore offers tons of features I’m not even touching on here – I suspect basic captures are the most common scenario, but a lot of different things can be done with FiddlerCore’s simple API interface. Sky’s the limit! The source code for this sample capture form (WinForms) is provided as part of this article. Adding Fiddler Certificates with FiddlerCore One of the sticking points in West Wind WebSurge has been that if you wanted to capture HTTPS/SSL traffic, you needed to have the full version of Fiddler and have HTTPS decryption enabled. Essentially you had to use Fiddler to configure HTTPS decryption and the associated installation of the Fiddler local client certificate that is used for local decryption of incoming SSL traffic. While this works just fine, requiring to have Fiddler installed and then using a separate application to configure the SSL functionality isn’t ideal. Fortunately FiddlerCore actually includes the tools to register the Fiddler Certificate directly using FiddlerCore. Why does Fiddler need a Certificate in the first Place? Fiddler and FiddlerCore are essentially HTTP proxies which means they inject themselves into the HTTP conversation by re-routing HTTP traffic to a special HTTP port (8888 by default for Fiddler) and then forward the HTTP data to the original client. Fiddler injects itself as the system proxy in using the WinInet Windows settings  which are the same settings that Internet Explorer uses and that are configured in the Windows and Internet Explorer Internet Settings dialog. Most HTTP clients running on Windows pick up and apply these system level Proxy settings before establishing new HTTP connections and that’s why most clients automatically work once Fiddler – or FiddlerCore/WebSurge are running. For plain HTTP requests this just works – Fiddler intercepts the HTTP requests on the proxy port and then forwards them to the original port (80 for HTTP and 443 for SSL typically but it could be any port). For SSL however, this is not quite as simple – Fiddler can easily act as an HTTPS/SSL client to capture inbound requests from the server, but when it forwards the request to the client it has to also act as an SSL server and provide a certificate that the client trusts. This won’t be the original certificate from the remote site, but rather a custom local certificate that effectively simulates an SSL connection between the proxy and the client. If there is no custom certificate configured for Fiddler the SSL request fails with a certificate validation error. The key for this to work is that a custom certificate has to be installed that the HTTPS client trusts on the local machine. For a much more detailed description of the process you can check out Eric Lawrence’s blog post on Certificates. If you’re using the desktop version of Fiddler you can install a local certificate into the Windows certificate store. Fiddler proper does this from the Options menu: This operation does several things: It installs the Fiddler Root Certificate It sets trust to this Root Certificate A new client certificate is generated for each HTTPS site monitored Certificate Installation with FiddlerCore You can also provide this same functionality using FiddlerCore which includes a CertMaker class. Using CertMaker is straight forward to use and it provides an easy way to create some simple helpers that can install and uninstall a Fiddler Root certificate:public static bool InstallCertificate() { if (!CertMaker.rootCertExists()) { if (!CertMaker.createRootCert()) return false; if (!CertMaker.trustRootCert()) return false; } return true; } public static bool UninstallCertificate() { if (CertMaker.rootCertExists()) { if (!CertMaker.removeFiddlerGeneratedCerts(true)) return false; } return true; } InstallCertificate() works by first checking whether the root certificate is already installed and if it isn’t goes ahead and creates a new one. The process of creating the certificate is a two step process – first the actual certificate is created and then it’s moved into the certificate store to become trusted. I’m not sure why you’d ever split these operations up since a cert created without trust isn’t going to be of much value, but there are two distinct steps. When you trigger the trustRootCert() method, a message box will pop up on the desktop that lets you know that you’re about to trust a local private certificate. This is a security feature to ensure that you really want to trust the Fiddler root since you are essentially installing a man in the middle certificate. It’s quite safe to use this generated root certificate, because it’s been specifically generated for your machine and thus is not usable from external sources, the only way to use this certificate in a trusted way is from the local machine. IOW, unless somebody has physical access to your machine, there’s no useful way to hijack this certificate and use it for nefarious purposes (see Eric’s post for more details). Once the Root certificate has been installed, FiddlerCore/Fiddler create new certificates for each site that is connected to with HTTPS. You can end up with quite a few temporary certificates in your certificate store. To uninstall you can either use Fiddler and simply uncheck the Decrypt HTTPS traffic option followed by the remove Fiddler certificates button, or you can use FiddlerCore’s CertMaker.removeFiddlerGeneratedCerts() which removes the root cert and any of the intermediary certificates Fiddler created. Keep in mind that when you uninstall you uninstall the certificate for both FiddlerCore and Fiddler, so use UninstallCertificate() with care and realize that you might affect the Fiddler application’s operation by doing so as well. When to check for an installed Certificate Note that the check to see if the root certificate exists is pretty fast, while the actual process of installing the certificate is a relatively slow operation that even on a fast machine takes a few seconds. Further the trust operation pops up a message box so you probably don’t want to install the certificate repeatedly. Since the check for the root certificate is fast, you can easily put a call to InstallCertificate() in any capture startup code – in which case the certificate installation only triggers when a certificate is in fact not installed. Personally I like to make certificate installation explicit – just like Fiddler does, so in WebSurge I use a small drop down option on the menu to install or uninstall the SSL certificate:   This code calls the InstallCertificate and UnInstallCertificate functions respectively – the experience with this is similar to what you get in Fiddler with the extra dialog box popping up to prompt confirmation for installation of the root certificate. Once the cert is installed you can then capture SSL requests. There’s a gotcha however… Gotcha: FiddlerCore Certificates don’t stick by Default When I originally tried to use the Fiddler certificate installation I ran into an odd problem. I was able to install the certificate and immediately after installation was able to capture HTTPS requests. Then I would exit the application and come back in and try the same HTTPS capture again and it would fail due to a missing certificate. CertMaker.rootCertExists() would return false after every restart and if re-installed the certificate a new certificate would get added to the certificate store resulting in a bunch of duplicated root certificates with different keys. What the heck? CertMaker and BcMakeCert create non-sticky CertificatesI turns out that FiddlerCore by default uses different components from what the full version of Fiddler uses. Fiddler uses a Windows utility called MakeCert.exe to create the Fiddler Root certificate. FiddlerCore however installs the CertMaker.dll and BCMakeCert.dll assemblies, which use a different crypto library (Bouncy Castle) for certificate creation than MakeCert.exe which uses the Windows Crypto API. The assemblies provide support for non-windows operation for Fiddler under Mono, as well as support for some non-Windows certificate platforms like iOS and Android for decryption. The bottom line is that the FiddlerCore provided bouncy castle assemblies are not sticky by default as the certificates created with them are not cached as they are in Fiddler proper. To get certificates to ‘stick’ you have to explicitly cache the certificates in Fiddler’s internal preferences. A cache aware version of InstallCertificate looks something like this:public static bool InstallCertificate() { if (!CertMaker.rootCertExists()) { if (!CertMaker.createRootCert()) return false; if (!CertMaker.trustRootCert()) return false; App.Configuration.UrlCapture.Cert = FiddlerApplication.Prefs.GetStringPref("fiddler.certmaker.bc.cert", null); App.Configuration.UrlCapture.Key = FiddlerApplication.Prefs.GetStringPref("fiddler.certmaker.bc.key", null); } return true; } public static bool UninstallCertificate() { if (CertMaker.rootCertExists()) { if (!CertMaker.removeFiddlerGeneratedCerts(true)) return false; } App.Configuration.UrlCapture.Cert = null; App.Configuration.UrlCapture.Key = null; return true; } In this code I store the Fiddler cert and private key in an application configuration settings that’s stored with the application settings (App.Configuration.UrlCapture object). These settings automatically persist when WebSurge is shut down. The values are read out of Fiddler’s internal preferences store which is set after a new certificate has been created. Likewise I clear out the configuration settings when the certificate is uninstalled. In order for these setting to be used you have to also load the configuration settings into the Fiddler preferences *before* a call to rootCertExists() is made. I do this in the capture form’s constructor:public FiddlerCapture(StressTestForm form) { InitializeComponent(); CaptureConfiguration = App.Configuration.UrlCapture; MainForm = form; if (!string.IsNullOrEmpty(App.Configuration.UrlCapture.Cert)) { FiddlerApplication.Prefs.SetStringPref("fiddler.certmaker.bc.key", App.Configuration.UrlCapture.Key); FiddlerApplication.Prefs.SetStringPref("fiddler.certmaker.bc.cert", App.Configuration.UrlCapture.Cert); }} This is kind of a drag to do and not documented anywhere that I could find, so hopefully this will save you some grief if you want to work with the stock certificate logic that installs with FiddlerCore. MakeCert provides sticky Certificates and the same functionality as Fiddler But there’s actually an easier way. If you want to skip the above Fiddler preference configuration code in your application you can choose to distribute MakeCert.exe instead of certmaker.dll and bcmakecert.dll. When you use MakeCert.exe, the certificates settings are stored in Windows so they are available without any custom configuration inside of your application. It’s easier to integrate and as long as you run on Windows and you don’t need to support iOS or Android devices is simply easier to deal with. To integrate into your project, you can remove the reference to CertMaker.dll (and the BcMakeCert.dll assembly) from your project. Instead copy MakeCert.exe into your output folder. To make sure MakeCert.exe gets pushed out, include MakeCert.exe in your project and set the Build Action to None, and Copy to Output Directory to Copy if newer. Note that the CertMaker.dll reference in the project has been removed and on disk the files for Certmaker.dll, as well as the BCMakeCert.dll files on disk. Keep in mind that these DLLs are resources of the FiddlerCore NuGet package, so updating the package may end up pushing those files back into your project. Once MakeCert.exe is distributed FiddlerCore checks for it first before using the assemblies so as long as MakeCert.exe exists it’ll be used for certificate creation (at least on Windows). Summary FiddlerCore is a pretty sweet tool, and it’s absolutely awesome that we get to plug in most of the functionality of Fiddler right into our own applications. A few years back I tried to build this sort of functionality myself for an app and ended up giving up because it’s a big job to get HTTP right – especially if you need to support SSL. FiddlerCore now provides that functionality as a turnkey solution that can be plugged into your own apps easily. The only downside is FiddlerCore’s documentation for more advanced features like certificate installation which is pretty sketchy. While for the most part FiddlerCore’s feature set is easy to work with without any documentation, advanced features are often not intuitive to gleam by just using Intellisense or the FiddlerCore help file reference (which is not terribly useful). While Eric Lawrence is very responsive on his forum and on Twitter, there simply isn’t much useful documentation on Fiddler/FiddlerCore available online. If you run into trouble the forum is probably the first place to look and then ask a question if you can’t find the answer. The best documentation you can find is Eric’s Fiddler Book which covers a ton of functionality of Fiddler and FiddlerCore. The book is a great reference to Fiddler’s feature set as well as providing great insights into the HTTP protocol. The second half of the book that gets into the innards of HTTP is an excellent read for anybody who wants to know more about some of the more arcane aspects and special behaviors of HTTP – it’s well worth the read. While the book has tons of information in a very readable format, it’s unfortunately not a great reference as it’s hard to find things in the book and because it’s not available online you can’t electronically search for the great content in it. But it’s hard to complain about any of this given the obvious effort and love that’s gone into this awesome product for all of these years. A mighty big thanks to Eric Lawrence  for having created this useful tool that so many of us use all the time, and also to Telerik for picking up Fiddler/FiddlerCore and providing Eric the resources to support and improve this wonderful tool full time and keeping it free for all. Kudos! Resources FiddlerCore Download FiddlerCore NuGet Fiddler Capture Sample Form Fiddler Capture Form in West Wind WebSurge (GitHub) Eric Lawrence’s Fiddler Book© Rick Strahl, West Wind Technologies, 2005-2014Posted in .NET  HTTP   Tweet !function(d,s,id){var js,fjs=d.getElementsByTagName(s)[0];if(!d.getElementById(id)){js=d.createElement(s);js.id=id;js.src="//platform.twitter.com/widgets.js";fjs.parentNode.insertBefore(js,fjs);}}(document,"script","twitter-wjs"); (function() { var po = document.createElement('script'); po.type = 'text/javascript'; po.async = true; po.src = 'https://apis.google.com/js/plusone.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(po, s); })();

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• Improving Partitioned Table Join Performance

  - by Paul White

  The query optimizer does not always choose an optimal strategy when joining partitioned tables. This post looks at an example, showing how a manual rewrite of the query can almost double performance, while reducing the memory grant to almost nothing. Test Data The two tables in this example use a common partitioning partition scheme. The partition function uses 41 equal-size partitions: CREATE PARTITION FUNCTION PFT (integer) AS RANGE RIGHT FOR VALUES ( 125000, 250000, 375000, 500000, 625000, 750000, 875000, 1000000, 1125000, 1250000, 1375000, 1500000, 1625000, 1750000, 1875000, 2000000, 2125000, 2250000, 2375000, 2500000, 2625000, 2750000, 2875000, 3000000, 3125000, 3250000, 3375000, 3500000, 3625000, 3750000, 3875000, 4000000, 4125000, 4250000, 4375000, 4500000, 4625000, 4750000, 4875000, 5000000 ); GO CREATE PARTITION SCHEME PST AS PARTITION PFT ALL TO ([PRIMARY]); There two tables are: CREATE TABLE dbo.T1 ( TID integer NOT NULL IDENTITY(0,1), Column1 integer NOT NULL, Padding binary(100) NOT NULL DEFAULT 0x,   CONSTRAINT PK_T1 PRIMARY KEY CLUSTERED (TID) ON PST (TID) );   CREATE TABLE dbo.T2 ( TID integer NOT NULL, Column1 integer NOT NULL, Padding binary(100) NOT NULL DEFAULT 0x,   CONSTRAINT PK_T2 PRIMARY KEY CLUSTERED (TID, Column1) ON PST (TID) ); The next script loads 5 million rows into T1 with a pseudo-random value between 1 and 5 for Column1. The table is partitioned on the IDENTITY column TID: INSERT dbo.T1 WITH (TABLOCKX) (Column1) SELECT (ABS(CHECKSUM(NEWID())) % 5) + 1 FROM dbo.Numbers AS N WHERE n BETWEEN 1 AND 5000000; In case you don’t already have an auxiliary table of numbers lying around, here’s a script to create one with 10 million rows: CREATE TABLE dbo.Numbers (n bigint PRIMARY KEY);   WITH L0 AS(SELECT 1 AS c UNION ALL SELECT 1), L1 AS(SELECT 1 AS c FROM L0 AS A CROSS JOIN L0 AS B), L2 AS(SELECT 1 AS c FROM L1 AS A CROSS JOIN L1 AS B), L3 AS(SELECT 1 AS c FROM L2 AS A CROSS JOIN L2 AS B), L4 AS(SELECT 1 AS c FROM L3 AS A CROSS JOIN L3 AS B), L5 AS(SELECT 1 AS c FROM L4 AS A CROSS JOIN L4 AS B), Nums AS(SELECT ROW_NUMBER() OVER (ORDER BY (SELECT NULL)) AS n FROM L5) INSERT dbo.Numbers WITH (TABLOCKX) SELECT TOP (10000000) n FROM Nums ORDER BY n OPTION (MAXDOP 1); Table T1 contains data like this: Next we load data into table T2. The relationship between the two tables is that table 2 contains ‘n’ rows for each row in table 1, where ‘n’ is determined by the value in Column1 of table T1. There is nothing particularly special about the data or distribution, by the way. INSERT dbo.T2 WITH (TABLOCKX) (TID, Column1) SELECT T.TID, N.n FROM dbo.T1 AS T JOIN dbo.Numbers AS N ON N.n >= 1 AND N.n <= T.Column1; Table T2 ends up containing about 15 million rows: The primary key for table T2 is a combination of TID and Column1. The data is partitioned according to the value in column TID alone. Partition Distribution The following query shows the number of rows in each partition of table T1: SELECT PartitionID = CA1.P, NumRows = COUNT_BIG(*) FROM dbo.T1 AS T CROSS APPLY (VALUES ($PARTITION.PFT(TID))) AS CA1 (P) GROUP BY CA1.P ORDER BY CA1.P; There are 40 partitions containing 125,000 rows (40 * 125k = 5m rows). The rightmost partition remains empty. The next query shows the distribution for table 2: SELECT PartitionID = CA1.P, NumRows = COUNT_BIG(*) FROM dbo.T2 AS T CROSS APPLY (VALUES ($PARTITION.PFT(TID))) AS CA1 (P) GROUP BY CA1.P ORDER BY CA1.P; There are roughly 375,000 rows in each partition (the rightmost partition is also empty): Ok, that’s the test data done. Test Query and Execution Plan The task is to count the rows resulting from joining tables 1 and 2 on the TID column: SET STATISTICS IO ON; DECLARE @s datetime2 = SYSUTCDATETIME();   SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID;   SELECT DATEDIFF(Millisecond, @s, SYSUTCDATETIME()); SET STATISTICS IO OFF; The optimizer chooses a plan using parallel hash join, and partial aggregation: The Plan Explorer plan tree view shows accurate cardinality estimates and an even distribution of rows across threads (click to enlarge the image): With a warm data cache, the STATISTICS IO output shows that no physical I/O was needed, and all 41 partitions were touched: Running the query without actual execution plan or STATISTICS IO information for maximum performance, the query returns in around 2600ms. Execution Plan Analysis The first step toward improving on the execution plan produced by the query optimizer is to understand how it works, at least in outline. The two parallel Clustered Index Scans use multiple threads to read rows from tables T1 and T2. Parallel scan uses a demand-based scheme where threads are given page(s) to scan from the table as needed. This arrangement has certain important advantages, but does result in an unpredictable distribution of rows amongst threads. The point is that multiple threads cooperate to scan the whole table, but it is impossible to predict which rows end up on which threads. For correct results from the parallel hash join, the execution plan has to ensure that rows from T1 and T2 that might join are processed on the same thread. For example, if a row from T1 with join key value ‘1234’ is placed in thread 5’s hash table, the execution plan must guarantee that any rows from T2 that also have join key value ‘1234’ probe thread 5’s hash table for matches. The way this guarantee is enforced in this parallel hash join plan is by repartitioning rows to threads after each parallel scan. The two repartitioning exchanges route rows to threads using a hash function over the hash join keys. The two repartitioning exchanges use the same hash function so rows from T1 and T2 with the same join key must end up on the same hash join thread. Expensive Exchanges This business of repartitioning rows between threads can be very expensive, especially if a large number of rows is involved. The execution plan selected by the optimizer moves 5 million rows through one repartitioning exchange and around 15 million across the other. As a first step toward removing these exchanges, consider the execution plan selected by the optimizer if we join just one partition from each table, disallowing parallelism: SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = 1 AND $PARTITION.PFT(T2.TID) = 1 OPTION (MAXDOP 1); The optimizer has chosen a (one-to-many) merge join instead of a hash join. The single-partition query completes in around 100ms. If everything scaled linearly, we would expect that extending this strategy to all 40 populated partitions would result in an execution time around 4000ms. Using parallelism could reduce that further, perhaps to be competitive with the parallel hash join chosen by the optimizer. This raises a question. If the most efficient way to join one partition from each of the tables is to use a merge join, why does the optimizer not choose a merge join for the full query? Forcing a Merge Join Let’s force the optimizer to use a merge join on the test query using a hint: SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID OPTION (MERGE JOIN); This is the execution plan selected by the optimizer: This plan results in the same number of logical reads reported previously, but instead of 2600ms the query takes 5000ms. The natural explanation for this drop in performance is that the merge join plan is only using a single thread, whereas the parallel hash join plan could use multiple threads. Parallel Merge Join We can get a parallel merge join plan using the same query hint as before, and adding trace flag 8649: SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID OPTION (MERGE JOIN, QUERYTRACEON 8649); The execution plan is: This looks promising. It uses a similar strategy to distribute work across threads as seen for the parallel hash join. In practice though, performance is disappointing. On a typical run, the parallel merge plan runs for around 8400ms; slower than the single-threaded merge join plan (5000ms) and much worse than the 2600ms for the parallel hash join. We seem to be going backwards! The logical reads for the parallel merge are still exactly the same as before, with no physical IOs. The cardinality estimates and thread distribution are also still very good (click to enlarge): A big clue to the reason for the poor performance is shown in the wait statistics (captured by Plan Explorer Pro): CXPACKET waits require careful interpretation, and are most often benign, but in this case excessive waiting occurs at the repartitioning exchanges. Unlike the parallel hash join, the repartitioning exchanges in this plan are order-preserving ‘merging’ exchanges (because merge join requires ordered inputs): Parallelism works best when threads can just grab any available unit of work and get on with processing it. Preserving order introduces inter-thread dependencies that can easily lead to significant waits occurring. In extreme cases, these dependencies can result in an intra-query deadlock, though the details of that will have to wait for another time to explore in detail. The potential for waits and deadlocks leads the query optimizer to cost parallel merge join relatively highly, especially as the degree of parallelism (DOP) increases. This high costing resulted in the optimizer choosing a serial merge join rather than parallel in this case. The test results certainly confirm its reasoning. Collocated Joins In SQL Server 2008 and later, the optimizer has another available strategy when joining tables that share a common partition scheme. This strategy is a collocated join, also known as as a per-partition join. It can be applied in both serial and parallel execution plans, though it is limited to 2-way joins in the current optimizer. Whether the optimizer chooses a collocated join or not depends on cost estimation. The primary benefits of a collocated join are that it eliminates an exchange and requires less memory, as we will see next. Costing and Plan Selection The query optimizer did consider a collocated join for our original query, but it was rejected on cost grounds. The parallel hash join with repartitioning exchanges appeared to be a cheaper option. There is no query hint to force a collocated join, so we have to mess with the costing framework to produce one for our test query. Pretending that IOs cost 50 times more than usual is enough to convince the optimizer to use collocated join with our test query: -- Pretend IOs are 50x cost temporarily DBCC SETIOWEIGHT(50);   -- Co-located hash join SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID OPTION (RECOMPILE);   -- Reset IO costing DBCC SETIOWEIGHT(1); Collocated Join Plan The estimated execution plan for the collocated join is: The Constant Scan contains one row for each partition of the shared partitioning scheme, from 1 to 41. The hash repartitioning exchanges seen previously are replaced by a single Distribute Streams exchange using Demand partitioning. Demand partitioning means that the next partition id is given to the next parallel thread that asks for one. My test machine has eight logical processors, and all are available for SQL Server to use. As a result, there are eight threads in the single parallel branch in this plan, each processing one partition from each table at a time. Once a thread finishes processing a partition, it grabs a new partition number from the Distribute Streams exchange…and so on until all partitions have been processed. It is important to understand that the parallel scans in this plan are different from the parallel hash join plan. Although the scans have the same parallelism icon, tables T1 and T2 are not being co-operatively scanned by multiple threads in the same way. Each thread reads a single partition of T1 and performs a hash match join with the same partition from table T2. The properties of the two Clustered Index Scans show a Seek Predicate (unusual for a scan!) limiting the rows to a single partition: The crucial point is that the join between T1 and T2 is on TID, and TID is the partitioning column for both tables. A thread that processes partition ‘n’ is guaranteed to see all rows that can possibly join on TID for that partition. In addition, no other thread will see rows from that partition, so this removes the need for repartitioning exchanges. CPU and Memory Efficiency Improvements The collocated join has removed two expensive repartitioning exchanges and added a single exchange processing 41 rows (one for each partition id). Remember, the parallel hash join plan exchanges had to process 5 million and 15 million rows. The amount of processor time spent on exchanges will be much lower in the collocated join plan. In addition, the collocated join plan has a maximum of 8 threads processing single partitions at any one time. The 41 partitions will all be processed eventually, but a new partition is not started until a thread asks for it. Threads can reuse hash table memory for the new partition. The parallel hash join plan also had 8 hash tables, but with all 5,000,000 build rows loaded at the same time. The collocated plan needs memory for only 8 * 125,000 = 1,000,000 rows at any one time. Collocated Hash Join Performance The collated join plan has disappointing performance in this case. The query runs for around 25,300ms despite the same IO statistics as usual. This is much the worst result so far, so what went wrong? It turns out that cardinality estimation for the single partition scans of table T1 is slightly low. The properties of the Clustered Index Scan of T1 (graphic immediately above) show the estimation was for 121,951 rows. This is a small shortfall compared with the 125,000 rows actually encountered, but it was enough to cause the hash join to spill to physical tempdb: A level 1 spill doesn’t sound too bad, until you realize that the spill to tempdb probably occurs for each of the 41 partitions. As a side note, the cardinality estimation error is a little surprising because the system tables accurately show there are 125,000 rows in every partition of T1. Unfortunately, the optimizer uses regular column and index statistics to derive cardinality estimates here rather than system table information (e.g. sys.partitions). Collocated Merge Join We will never know how well the collocated parallel hash join plan might have worked without the cardinality estimation error (and the resulting 41 spills to tempdb) but we do know: Merge join does not require a memory grant; and Merge join was the optimizer’s preferred join option for a single partition join Putting this all together, what we would really like to see is the same collocated join strategy, but using merge join instead of hash join. Unfortunately, the current query optimizer cannot produce a collocated merge join; it only knows how to do collocated hash join. So where does this leave us? CROSS APPLY sys.partitions We can try to write our own collocated join query. We can use sys.partitions to find the partition numbers, and CROSS APPLY to get a count per partition, with a final step to sum the partial counts. The following query implements this idea: SELECT row_count = SUM(Subtotals.cnt) FROM ( -- Partition numbers SELECT p.partition_number FROM sys.partitions AS p WHERE p.[object_id] = OBJECT_ID(N'T1', N'U') AND p.index_id = 1 ) AS P CROSS APPLY ( -- Count per collocated join SELECT cnt = COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = p.partition_number AND $PARTITION.PFT(T2.TID) = p.partition_number ) AS SubTotals; The estimated plan is: The cardinality estimates aren’t all that good here, especially the estimate for the scan of the system table underlying the sys.partitions view. Nevertheless, the plan shape is heading toward where we would like to be. Each partition number from the system table results in a per-partition scan of T1 and T2, a one-to-many Merge Join, and a Stream Aggregate to compute the partial counts. The final Stream Aggregate just sums the partial counts. Execution time for this query is around 3,500ms, with the same IO statistics as always. This compares favourably with 5,000ms for the serial plan produced by the optimizer with the OPTION (MERGE JOIN) hint. This is another case of the sum of the parts being less than the whole – summing 41 partial counts from 41 single-partition merge joins is faster than a single merge join and count over all partitions. Even so, this single-threaded collocated merge join is not as quick as the original parallel hash join plan, which executed in 2,600ms. On the positive side, our collocated merge join uses only one logical processor and requires no memory grant. The parallel hash join plan used 16 threads and reserved 569 MB of memory:   Using a Temporary Table Our collocated merge join plan should benefit from parallelism. The reason parallelism is not being used is that the query references a system table. We can work around that by writing the partition numbers to a temporary table (or table variable): SET STATISTICS IO ON; DECLARE @s datetime2 = SYSUTCDATETIME();   CREATE TABLE #P ( partition_number integer PRIMARY KEY);   INSERT #P (partition_number) SELECT p.partition_number FROM sys.partitions AS p WHERE p.[object_id] = OBJECT_ID(N'T1', N'U') AND p.index_id = 1;   SELECT row_count = SUM(Subtotals.cnt) FROM #P AS p CROSS APPLY ( SELECT cnt = COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = p.partition_number AND $PARTITION.PFT(T2.TID) = p.partition_number ) AS SubTotals;   DROP TABLE #P;   SELECT DATEDIFF(Millisecond, @s, SYSUTCDATETIME()); SET STATISTICS IO OFF; Using the temporary table adds a few logical reads, but the overall execution time is still around 3500ms, indistinguishable from the same query without the temporary table. The problem is that the query optimizer still doesn’t choose a parallel plan for this query, though the removal of the system table reference means that it could if it chose to: In fact the optimizer did enter the parallel plan phase of query optimization (running search 1 for a second time): Unfortunately, the parallel plan found seemed to be more expensive than the serial plan. This is a crazy result, caused by the optimizer’s cost model not reducing operator CPU costs on the inner side of a nested loops join. Don’t get me started on that, we’ll be here all night. In this plan, everything expensive happens on the inner side of a nested loops join. Without a CPU cost reduction to compensate for the added cost of exchange operators, candidate parallel plans always look more expensive to the optimizer than the equivalent serial plan. Parallel Collocated Merge Join We can produce the desired parallel plan using trace flag 8649 again: SELECT row_count = SUM(Subtotals.cnt) FROM #P AS p CROSS APPLY ( SELECT cnt = COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = p.partition_number AND $PARTITION.PFT(T2.TID) = p.partition_number ) AS SubTotals OPTION (QUERYTRACEON 8649); The actual execution plan is: One difference between this plan and the collocated hash join plan is that a Repartition Streams exchange operator is used instead of Distribute Streams. The effect is similar, though not quite identical. The Repartition uses round-robin partitioning, meaning the next partition id is pushed to the next thread in sequence. The Distribute Streams exchange seen earlier used Demand partitioning, meaning the next partition id is pulled across the exchange by the next thread that is ready for more work. There are subtle performance implications for each partitioning option, but going into that would again take us too far off the main point of this post. Performance The important thing is the performance of this parallel collocated merge join – just 1350ms on a typical run. The list below shows all the alternatives from this post (all timings include creation, population, and deletion of the temporary table where appropriate) from quickest to slowest: Collocated parallel merge join: 1350ms Parallel hash join: 2600ms Collocated serial merge join: 3500ms Serial merge join: 5000ms Parallel merge join: 8400ms Collated parallel hash join: 25,300ms (hash spill per partition) The parallel collocated merge join requires no memory grant (aside from a paltry 1.2MB used for exchange buffers). This plan uses 16 threads at DOP 8; but 8 of those are (rather pointlessly) allocated to the parallel scan of the temporary table. These are minor concerns, but it turns out there is a way to address them if it bothers you. Parallel Collocated Merge Join with Demand Partitioning This final tweak replaces the temporary table with a hard-coded list of partition ids (dynamic SQL could be used to generate this query from sys.partitions): SELECT row_count = SUM(Subtotals.cnt) FROM ( VALUES (1),(2),(3),(4),(5),(6),(7),(8),(9),(10), (11),(12),(13),(14),(15),(16),(17),(18),(19),(20), (21),(22),(23),(24),(25),(26),(27),(28),(29),(30), (31),(32),(33),(34),(35),(36),(37),(38),(39),(40),(41) ) AS P (partition_number) CROSS APPLY ( SELECT cnt = COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = p.partition_number AND $PARTITION.PFT(T2.TID) = p.partition_number ) AS SubTotals OPTION (QUERYTRACEON 8649); The actual execution plan is: The parallel collocated hash join plan is reproduced below for comparison: The manual rewrite has another advantage that has not been mentioned so far: the partial counts (per partition) can be computed earlier than the partial counts (per thread) in the optimizer’s collocated join plan. The earlier aggregation is performed by the extra Stream Aggregate under the nested loops join. The performance of the parallel collocated merge join is unchanged at around 1350ms. Final Words It is a shame that the current query optimizer does not consider a collocated merge join (Connect item closed as Won’t Fix). The example used in this post showed an improvement in execution time from 2600ms to 1350ms using a modestly-sized data set and limited parallelism. In addition, the memory requirement for the query was almost completely eliminated  – down from 569MB to 1.2MB. The problem with the parallel hash join selected by the optimizer is that it attempts to process the full data set all at once (albeit using eight threads). It requires a large memory grant to hold all 5 million rows from table T1 across the eight hash tables, and does not take advantage of the divide-and-conquer opportunity offered by the common partitioning. The great thing about the collocated join strategies is that each parallel thread works on a single partition from both tables, reading rows, performing the join, and computing a per-partition subtotal, before moving on to a new partition. From a thread’s point of view… If you have trouble visualizing what is happening from just looking at the parallel collocated merge join execution plan, let’s look at it again, but from the point of view of just one thread operating between the two Parallelism (exchange) operators. Our thread picks up a single partition id from the Distribute Streams exchange, and starts a merge join using ordered rows from partition 1 of table T1 and partition 1 of table T2. By definition, this is all happening on a single thread. As rows join, they are added to a (per-partition) count in the Stream Aggregate immediately above the Merge Join. Eventually, either T1 (partition 1) or T2 (partition 1) runs out of rows and the merge join stops. The per-partition count from the aggregate passes on through the Nested Loops join to another Stream Aggregate, which is maintaining a per-thread subtotal. Our same thread now picks up a new partition id from the exchange (say it gets id 9 this time). The count in the per-partition aggregate is reset to zero, and the processing of partition 9 of both tables proceeds just as it did for partition 1, and on the same thread. Each thread picks up a single partition id and processes all the data for that partition, completely independently from other threads working on other partitions. One thread might eventually process partitions (1, 9, 17, 25, 33, 41) while another is concurrently processing partitions (2, 10, 18, 26, 34) and so on for the other six threads at DOP 8. The point is that all 8 threads can execute independently and concurrently, continuing to process new partitions until the wider job (of which the thread has no knowledge!) is done. This divide-and-conquer technique can be much more efficient than simply splitting the entire workload across eight threads all at once. Related Reading Understanding and Using Parallelism in SQL Server Parallel Execution Plans Suck © 2013 Paul White – All Rights Reserved Twitter: @SQL_Kiwi

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• Nagging As A Strategy For Better Linking: -z guidance

  - by user9154181

  The link-editor (ld) in Solaris 11 has a new feature that we call guidance that is intended to help you build better objects. The basic idea behind guidance is that if (and only if) you request it, the link-editor will issue messages suggesting better options and other changes you might make to your ld command to get better results. You can choose to take the advice, or you can disable specific types of guidance while acting on others. In some ways, this works like an experienced friend leaning over your shoulder and giving you advice — you're free to take it or leave it as you see fit, but you get nudged to do a better job than you might have otherwise. We use guidance to build the core Solaris OS, and it has proven to be useful, both in improving our objects, and in making sure that regressions don't creep back in later. In this article, I'm going to describe the evolution in thinking and design that led to the implementation of the -z guidance option, as well as give a brief description of how it works. The guidance feature issues non-fatal warnings. However, experience shows that once developers get used to ignoring warnings, it is inevitable that real problems will be lost in the noise and ignored or missed. This is why we have a zero tolerance policy against build noise in the core Solaris OS. In order to get maximum benefit from -z guidance while maintaining this policy, I added the -z fatal-warnings option at the same time. Much of the material presented here is adapted from the arc case: PSARC 2010/312 Link-editor guidance The History Of Unfortunate Link-Editor Defaults The Solaris link-editor is one of the oldest Unix commands. It stands to reason that this would be true — in order to write an operating system, you need the ability to compile and link code. The original link-editor (ld) had defaults that made sense at the time. As new features were needed, command line option switches were added to let the user use them, while maintaining backward compatibility for those who didn't. Backward compatibility is always a concern in system design, but is particularly important in the case of the tool chain (compilers, linker, and related tools), since it is a basic building block for the entire system. Over the years, applications have grown in size and complexity. Important concepts like dynamic linking that didn't exist in the original Unix system were invented. Object file formats changed. In the case of System V Release 4 Unix derivatives like Solaris, the ELF (Extensible Linking Format) was adopted. Since then, the ELF system has evolved to provide tools needed to manage today's larger and more complex environments. Features such as lazy loading, and direct bindings have been added. In an ideal world, many of these options would be defaults, with rarely used options that allow the user to turn them off. However, the reality is exactly the reverse: For backward compatibility, these features are all options that must be explicitly turned on by the user. This has led to a situation in which most applications do not take advantage of the many improvements that have been made in linking over the last 20 years. If their code seems to link and run without issue, what motivation does a developer have to read a complex manpage, absorb the information provided, choose the features that matter for their application, and apply them? Experience shows that only the most motivated and diligent programmers will make that effort. We know that most programs would be improved if we could just get you to use the various whizzy features that we provide, but the defaults conspire against us. We have long wanted to do something to make it easier for our users to use the linkers more effectively. There have been many conversations over the years regarding this issue, and how to address it. They always break down along the following lines: Change ld Defaults Since the world would be a better place the newer ld features were the defaults, why not change things to make it so? This idea is simple, elegant, and impossible. Doing so would break a large number of existing applications, including those of ISVs, big customers, and a plethora of existing open source packages. In each case, the owner of that code may choose to follow our lead and fix their code, or they may view it as an invitation to reconsider their commitment to our platform. Backward compatibility, and our installed base of working software, is one of our greatest assets, and not something to be lightly put at risk. Breaking backward compatibility at this level of the system is likely to do more harm than good. But, it sure is tempting. New Link-Editor One might create a new linker command, not called 'ld', leaving the old command as it is. The new one could use the same code as ld, but would offer only modern options, with the proper defaults for features such as direct binding. The resulting link-editor would be a pleasure to use. However, the approach is doomed to niche status. There is a vast pile of exiting code in the world built around the existing ld command, that reaches back to the 1970's. ld use is embedded in large and unknown numbers of makefiles, and is used by name by compilers that execute it. A Unix link-editor that is not named ld will not find a majority audience no matter how good it might be. Finally, a new linker command will eventually cease to be new, and will accumulate its own burden of backward compatibility issues. An Option To Make ld Do The Right Things Automatically This line of reasoning is best summarized by a CR filed in 2005, entitled 6239804 make it easier for ld(1) to do what's best The idea is to have a '-z best' option that unchains ld from its backward compatibility commitment, and allows it to turn on the "best" set of features, as determined by the authors of ld. The specific set of features enabled by -z best would be subject to change over time, as requirements change. This idea is more realistic than the other two, but was never implemented because it has some important issues that we could never answer to our satisfaction: The -z best proposal assumes that the user can turn it on, and trust it to select good options without the user needing to be aware of the options being applied. This is a fallacy. Features such as direct bindings require the user to do some analysis to ensure that the resulting program will still operate properly. A user who is willing to do the work to verify that what -z best does will be OK for their application is capable of turning on those features directly, and therefore gains little added benefit from -z best. The intent is that when a user opts into -z best, that they understand that z best is subject to sometimes incompatible evolution. Experience teaches us that this won't work. People will use this feature, the meaning of -z best will change, code that used to build will fail, and then there will be complaints and demands to retract the change. When (not if) this occurs, we will of course defend our actions, and point at the disclaimer. We'll win some of those debates, and lose others. Ultimately, we'll end up with -z best2 (-z better), or other compromises, and our goal of simplifying the world will have failed. The -z best idea rolls up a set of features that may or may not be related to each other into a unit that must be taken wholesale, or not at all. It could be that only a subset of what it does is compatible with a given application, in which case the user is expected to abandon -z best and instead set the options that apply to their application directly. In doing so, they lose one of the benefits of -z best, that if you use it, future versions of ld may choose a different set of options, and automatically improve the object through the act of rebuilding it. I drew two conclusions from the above history: For a link-editor, backward compatibility is vital. If a given command line linked your application 10 years ago, you have every reason to expect that it will link today, assuming that the libraries you're linking against are still available and compatible with their previous interfaces. For an application of any size or complexity, there is no substitute for the work involved in examining the code and determining which linker options apply and which do not. These options are largely orthogonal to each other, and it can be reasonable not to use any or all of them, depending on the situation, even in modern applications. It is a mistake to tie them together. The idea for -z guidance came from consideration of these points. By decoupling the advice from the act of taking the advice, we can retain the good aspects of -z best while avoiding its pitfalls: -z guidance gives advice, but the decision to take that advice remains with the user who must evaluate its merit and make a decision to take it or not. As such, we are free to change the specific guidance given in future releases of ld, without breaking existing applications. The only fallout from this will be some new warnings in the build output, which can be ignored or dealt with at the user's convenience. It does not couple the various features given into a single "take it or leave it" option, meaning that there will never be a need to offer "-zguidance2", or other such variants as things change over time. Guidance has the potential to be our final word on this subject. The user is given the flexibility to disable specific categories of guidance without losing the benefit of others, including those that might be added to future versions of the system. Although -z fatal-warnings stands on its own as a useful feature, it is of particular interest in combination with -z guidance. Used together, the guidance turns from advice to hard requirement: The user must either make the suggested change, or explicitly reject the advice by specifying a guidance exception token, in order to get a build. This is valuable in environments with high coding standards. ld Command Line Options The guidance effort resulted in new link-editor options for guidance and for turning warnings into fatal errors. Before I reproduce that text here, I'd like to highlight the strategic decisions embedded in the guidance feature: In order to get guidance, you have to opt in. We hope you will opt in, and believe you'll get better objects if you do, but our default mode of operation will continue as it always has, with full backward compatibility, and without judgement. Guidance suggestions always offers specific advice, and not vague generalizations. You can disable some guidance without turning off the entire feature. When you get guidance warnings, you can choose to take the advice, or you can specify a keyword to disable guidance for just that category. This allows you to get guidance for things that are useful to you, without being bothered about things that you've already considered and dismissed. As the world changes, we will add new guidance to steer you in the right direction. All such new guidance will come with a keyword that let's you turn it off. In order to facilitate building your code on different versions of Solaris, we quietly ignore any guidance keywords we don't recognize, assuming that they are intended for newer versions of the link-editor. If you want to see what guidance tokens ld does and does not recognize on your system, you can use the ld debugging feature as follows: % ld -Dargs -z guidance=foo,nodefs debug: debug: Solaris Linkers: 5.11-1.2275 debug: debug: arg[1] option=-D: option-argument: args debug: arg[2] option=-z: option-argument: guidance=foo,nodefs debug: warning: unrecognized -z guidance item: foo The -z fatal-warning option is straightforward, and generally useful in environments with strict coding standards. Note that the GNU ld already had this feature, and we accept their option names as synonyms: -z fatal-warnings | nofatal-warnings --fatal-warnings | --no-fatal-warnings The -z fatal-warnings and the --fatal-warnings option cause the link-editor to treat warnings as fatal errors. The -z nofatal-warnings and the --no-fatal-warnings option cause the link-editor to treat warnings as non-fatal. This is the default behavior. The -z guidance option is defined as follows: -z guidance[=item1,item2,...] Provide guidance messages to suggest ld options that can improve the quality of the resulting object, or which are otherwise considered to be beneficial. The specific guidance offered is subject to change over time as the system evolves. Obsolete guidance offered by older versions of ld may be dropped in new versions. Similarly, new guidance may be added to new versions of ld. Guidance therefore always represents current best practices. It is possible to enable guidance, while preventing specific guidance messages, by providing a list of item tokens, representing the class of guidance to be suppressed. In this way, unwanted advice can be suppressed without losing the benefit of other guidance. Unrecognized item tokens are quietly ignored by ld, allowing a given ld command line to be executed on a variety of older or newer versions of Solaris. The guidance offered by the current version of ld, and the item tokens used to disable these messages, are as follows. Specify Required Dependencies Dynamic executables and shared objects should explicitly define all of the dependencies they require. Guidance recommends the use of the -z defs option, should any symbol references remain unsatisfied when building dynamic objects. This guidance can be disabled with -z guidance=nodefs. Do Not Specify Non-Required Dependencies Dynamic executables and shared objects should not define any dependencies that do not satisfy the symbol references made by the dynamic object. Guidance recommends that unused dependencies be removed. This guidance can be disabled with -z guidance=nounused. Lazy Loading Dependencies should be identified for lazy loading. Guidance recommends the use of the -z lazyload option should any dependency be processed before either a -z lazyload or -z nolazyload option is encountered. This guidance can be disabled with -z guidance=nolazyload. Direct Bindings Dependencies should be referenced with direct bindings. Guidance recommends the use of the -B direct, or -z direct options should any dependency be processed before either of these options, or the -z nodirect option is encountered. This guidance can be disabled with -z guidance=nodirect. Pure Text Segment Dynamic objects should not contain relocations to non-writable, allocable sections. Guidance recommends compiling objects with Position Independent Code (PIC) should any relocations against the text segment remain, and neither the -z textwarn or -z textoff options are encountered. This guidance can be disabled with -z guidance=notext. Mapfile Syntax All mapfiles should use the version 2 mapfile syntax. Guidance recommends the use of the version 2 syntax should any mapfiles be encountered that use the version 1 syntax. This guidance can be disabled with -z guidance=nomapfile. Library Search Path Inappropriate dependencies that are encountered by ld are quietly ignored. For example, a 32-bit dependency that is encountered when generating a 64-bit object is ignored. These dependencies can result from incorrect search path settings, such as supplying an incorrect -L option. Although benign, this dependency processing is wasteful, and might hide a build problem that should be solved. Guidance recommends the removal of any inappropriate dependencies. This guidance can be disabled with -z guidance=nolibpath. In addition, -z guidance=noall can be used to entirely disable the guidance feature. See Chapter 7, Link-Editor Quick Reference, in the Linker and Libraries Guide for more information on guidance and advice for building better objects. Example The following example demonstrates how the guidance feature is intended to work. We will build a shared object that has a variety of shortcomings: Does not specify all it's dependencies Specifies dependencies it does not use Does not use direct bindings Uses a version 1 mapfile Contains relocations to the readonly allocable text (not PIC) This scenario is sadly very common — many shared objects have one or more of these issues. % cat hello.c #include <stdio.h> #include <unistd.h> void hello(void) { printf("hello user %d\n", getpid()); } % cat mapfile.v1 # This version 1 mapfile will trigger a guidance message % cc hello.c -o hello.so -G -M mapfile.v1 -lelf As you can see, the operation completes without error, resulting in a usable object. However, turning on guidance reveals a number of things that could be better: % cc hello.c -o hello.so -G -M mapfile.v1 -lelf -zguidance ld: guidance: version 2 mapfile syntax recommended: mapfile.v1 ld: guidance: -z lazyload option recommended before first dependency ld: guidance: -B direct or -z direct option recommended before first dependency Undefined first referenced symbol in file getpid hello.o (symbol belongs to implicit dependency /lib/libc.so.1) printf hello.o (symbol belongs to implicit dependency /lib/libc.so.1) ld: warning: symbol referencing errors ld: guidance: -z defs option recommended for shared objects ld: guidance: removal of unused dependency recommended: libelf.so.1 warning: Text relocation remains referenced against symbol offset in file .rodata1 (section) 0xa hello.o getpid 0x4 hello.o printf 0xf hello.o ld: guidance: position independent (PIC) code recommended for shared objects ld: guidance: see ld(1) -z guidance for more information Given the explicit advice in the above guidance messages, it is relatively easy to modify the example to do the right things: % cat mapfile.v2 # This version 2 mapfile will not trigger a guidance message $mapfile_version 2 % cc hello.c -o hello.so -Kpic -G -Bdirect -M mapfile.v2 -lc -zguidance There are situations in which the guidance does not fit the object being built. For instance, you want to build an object without direct bindings: % cc -Kpic hello.c -o hello.so -G -M mapfile.v2 -lc -zguidance ld: guidance: -B direct or -z direct option recommended before first dependency ld: guidance: see ld(1) -z guidance for more information It is easy to disable that specific guidance warning without losing the overall benefit from allowing the remainder of the guidance feature to operate: % cc -Kpic hello.c -o hello.so -G -M mapfile.v2 -lc -zguidance=nodirect Conclusions The linking guidelines enforced by the ld guidance feature correspond rather directly to our standards for building the core Solaris OS. I'm sure that comes as no surprise. It only makes sense that we would want to build our own product as well as we know how. Solaris is usually the first significant test for any new linker feature. We now enable guidance by default for all builds, and the effect has been very positive. Guidance helps us find suboptimal objects more quickly. Programmers get concrete advice for what to change instead of vague generalities. Even in the cases where we override the guidance, the makefile rules to do so serve as documentation of the fact. Deciding to use guidance is likely to cause some up front work for most code, as it forces you to consider using new features such as direct bindings. Such investigation is worthwhile, but does not come for free. However, the guidance suggestions offer a structured and straightforward way to tackle modernizing your objects, and once that work is done, for keeping them that way. The investment is often worth it, and will replay you in terms of better performance and fewer problems. I hope that you find guidance to be as useful as we have.

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• problem with sIFR 3 not displaying in IE just getting XXX

  - by user288306

  I am having a problem with sIFR 3 not displaying in IE. I get 3 larges black XXX in IE yet it displays fine in Firefox. I have checked i do have the most recent version of flash installed correctly. Here is the code on the page <div id="features"> <div id="mainmessage_advertisers"><h2>Advertisers</h2><br /><br /><h3><a href="">Reach your customers where they browse. Buy directly from top web publishers.</a></h3><br /><br /><br /><a href=""><img src="img/buyads.gif" border="0"></a></div> <div id="mainmessage_publishers"><h2>Publishers</h2><br /><br /><h3>Take control of your ad space and start generating more revenue than <u>ever before</u>.</h3><br /><br /><br /><a href=""><img src="img/sellads.gif" border="0"></a></div> </div>` Here is the code from my global.css #mainmessage_advertisers { width: 395px; height: 200px; padding: 90px 50px; border: 1px; float: left; } #mainmessage_publishers { width: 395px; height: 200px; padding: 90px 50px; float: right; } and here is what i have in my sifr.js /*********************************************************************** SIFR 3.0 (BETA 1) FUNCTIONS ************************************************************************/ var parseSelector=(function(){var _1=/\s*,\s*/;var _2=/\s*([\s>+~(),]|^|$)\s*/g;var _3=/([\s>+~,]|[^(]\+|^)([#.:@])/g;var _4=/^[^\s>+~]/;var _5=/[\s#.:>+~()@]|[^\s#.:>+~()@]+/g;function 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":"")+escape(_dd.join(" "))+">");if(_db.hasChildNodes()){_d7.push(i);i=0;_d9=_db.childNodes;continue}else{if(!/^(br|img)$/i.test(_db.nodeName)){_d8.push("</",_db.nodeName.toLowerCase(),">")}}}if(_d7.length>0&&!_db.nextSibling){do{i=_d7.pop();_d9=_db.parentNode.parentNode.childNodes;_db=_d9[i];if(_db){_d8.push("</",_db.nodeName.toLowerCase(),">")}}while(i<_d9.length&&_d7.length>0)}i++}return _d8.join("").replace(/\n|\r/g,"")}}; sIFR.prefetch({ src: 'swf/sifr/helvetica.swf' }); sIFR.activate(); sIFR.replace({ selector: 'h2, h3', src: 'swf/sifr/helvetica.swf', wmode: 'transparent', css: { '.sIFR-root' : { 'color': '#000000', 'font-weight': 'bold', 'letter-spacing': '-1' }, 'a': { 'text-decoration': 'none' }, 'a:link': { 'color': '#000000' }, 'a:hover': { 'color': '#000000' }, '.span': { 'color': '#979797' }, 'label': { 'color': '#E11818' } } }); sIFR.replace({ selector: 'h4', src: 'swf/sifr/helvetica.swf', wmode: 'transparent', css: { '.sIFR-root' : { 'color': '#7E7E7E', 'font-weight': 'bold', 'letter-spacing': '-0.8' }, 'a': { 'text-decoration': 'none' }, 'a:link': { 'color': '#7E7E7E' }, 'a:hover': { 'color': '#7E7E7E' }, 'label': { 'color': '#E11818' } } }); sIFR.replace({ selector: '#cart p', src: 'swf/sifr/helvetica-lt.swf', wmode: 'transparent', css: { '.sIFR-root' : { 'color': '#979797', 'font-weight': 'bold', 'letter-spacing': '-0.8' }, 'a': { 'text-decoration': 'none' }, 'a:link': { 'color': '#979797' }, 'a:hover': { 'color': '#000000' }, 'label': { 'color': '#979797' } } }); Thank you in advance for your help!

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• SQL SERVER – Subquery or Join – Various Options – SQL Server Engine knows the Best

  - by pinaldave

  This is followup post of my earlier article SQL SERVER – Convert IN to EXISTS – Performance Talk, after reading all the comments I have received I felt that I could write more on the same subject to clear few things out. First let us run following four queries, all of them are giving exactly same resultset. USE AdventureWorks GO -- use of = SELECT * FROM HumanResources.Employee E WHERE E.EmployeeID = ( SELECT EA.EmployeeID FROM HumanResources.EmployeeAddress EA WHERE EA.EmployeeID = E.EmployeeID) GO -- use of in SELECT * FROM HumanResources.Employee E WHERE E.EmployeeID IN ( SELECT EA.EmployeeID FROM HumanResources.EmployeeAddress EA WHERE EA.EmployeeID = E.EmployeeID) GO -- use of exists SELECT * FROM HumanResources.Employee E WHERE EXISTS ( SELECT EA.EmployeeID FROM HumanResources.EmployeeAddress EA WHERE EA.EmployeeID = E.EmployeeID) GO -- Use of Join SELECT * FROM HumanResources.Employee E INNER JOIN HumanResources.EmployeeAddress EA ON E.EmployeeID = EA.EmployeeID GO Let us compare the execution plan of the queries listed above. Click on image to see larger image. It is quite clear from the execution plan that in case of IN, EXISTS and JOIN SQL Server Engines is smart enough to figure out what is the best optimal plan of Merge Join for the same query and execute the same. However, in the case of use of Equal (=) Operator, SQL Server is forced to use Nested Loop and test each result of the inner query and compare to outer query, leading to cut the performance. Please note that here I no mean suggesting that Nested Loop is bad or Merge Join is better. This can very well vary on your machine and amount of resources available on your computer. When I see Equal (=) operator used in query like above, I usually recommend to see if user can use IN or EXISTS or JOIN. As I said, this can very much vary on different system. What is your take in above query? I believe SQL Server Engines is usually pretty smart to figure out what is ideal execution plan and use it. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL Joins, SQL Optimization, SQL Performance, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, T SQL, Technology

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• Password Security: Short and Complex versus ‘Short or Lengthy’ and Less Complex

  - by Akemi Iwaya

  Creating secure passwords for our online accounts is a necessary evil due to the huge increase in database and account hacking that occurs these days. The problem though is that no two companies have a similar policy for complex and secure password creation, then factor in the continued creation of insecure passwords or multi-site use of the same password and trouble is just waiting to happen. Ars Technica decided to take a look at multiple password types, how users fared with them, and how well those password types held up to cracking attempts in their latest study. The password types that Ars Technica looked at were comprehensive8, basic8, and basic16. The comprehensive type required a variety of upper-case, lower-case, digits, and symbols with no dictionary words allowed. The only restriction on the two basic types was the number of characters used. Which type do you think was easier for users to adopt and did better in the two password cracking tests? You can learn more about how well users did with the three password types and the results of the tests by visiting the article linked below. What are your thoughts on the matter? Are shorter, more complex passwords better or worse than using short or long, but less complex passwords? What methods do you feel work best since most passwords are limited to approximately 16 characters in length? Perhaps you use a service like LastPass or keep a dedicated list/notebook to manage your passwords. Let us know in the comments!    

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• NSClient++: external script with optional arguments

  - by syneticon-dj

  I am trying to define an external script which would take optional arguments in NSClient++ 0.4.1 on Windows. Following the nsclient-full.ini example code I have defined mycheck=cmd /C echo C:\mydir\myscript.ps1 %ARGS% | powershell.exe -command - which simply yields the string %ARGS% passed as the only argument to myscript.ps1, no matter what I specify in my call through NRPE (using Nagios' check_nrpe if that matters). I then tried to rewrite the definition to mycheck=cmd /C echo C:\mydir\myscript.ps1 $ARG1$ $ARG2$ | powershell.exe -command - (myscript.ps1 would take up to two arguments), which does help a bit. At least, if two arguments are provided, I can fetch them via the args[] array. The trouble starts when the call has less than two arguments - in this case the literal strings $ARG2 and $ARG1$ are passed through as arguments. Handling this case in the code of myscript.ps1 makes the whole argument processing routine ugly at best. Is there a sane way of defining optional parameters to an external script which would not pass NSClient's variable names if no parameter has been specified?

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• Image Preview in ASP.NET MVC

  - by imran_ku07

    Introduction :         Previewing an image is a great way to improve the UI of your site. Also it is always best to check the file type, size and see a preview before submitting the whole form. There are some ways to do this using simple JavaScript but not work in all browsers (like FF3).In this Article I will show you how do this using ASP.NET MVC application. You also see how this will work in case of nested form.   Description :          Create a new ASP.NET MVC project and then add a file upload and image control into your View. <form id="form1" method="post" action="NerdDinner/ImagePreview/AjaxSubmit">            <table>                <tr>                    <td>                        <input type="file" name="imageLoad1" id="imageLoad1"  onchange="ChangeImage(this,'#imgThumbnail')" />                    </td>                </tr>                <tr>                    <td align="center">                        <img src="images/TempImage.gif" id="imgThumbnail" height="200px" width="200px">                     </td>                </tr>            </table>        </form>           Note that here NerdDinner is refers to the virtual directory name, ImagePreview is the Controller and ImageLoad is the action name which you will see shortly          I will use the most popular jQuery form plug-in, that turns a form into an AJAX form with very little code. Therefore you must get these from Jquery site and then add these files into your page.          <script src="NerdDinner/Scripts/jquery-1.3.2.js" type="text/javascript"></script>        <script src="NerdDinner/Scripts/jquery.form.js" type="text/javascript"></script>            Then add the javascript function. <script type="text/javascript">function ChangeImage(fileId,imageId){ $("#form1").ajaxSubmit({success: function(responseText){ var d=new Date(); $(imageId)[0].src="NerdDinner/ImagePreview/ImageLoad?a="+d.getTime(); } });}</script>             This function simply submit the form named form1 asynchronously to ImagePreviewController's method AjaxSubmit and after successfully receiving the response, it will set the image src property to the action method ImageLoad. Here I am also adding querystring, preventing the browser to serve the cached image.           Now I will create a new Controller named ImagePreviewController. public class ImagePreviewController : Controller { [AcceptVerbs(HttpVerbs.Post)] public ActionResult AjaxSubmit(int? id) { Session["ContentLength"] = Request.Files[0].ContentLength; Session["ContentType"] = Request.Files[0].ContentType; byte[] b = new byte[Request.Files[0].ContentLength]; Request.Files[0].InputStream.Read(b, 0, Request.Files[0].ContentLength); Session["ContentStream"] = b; return Content( Request.Files[0].ContentType+";"+ Request.Files[0].ContentLength ); } public ActionResult ImageLoad(int? id) { byte[] b = (byte[])Session["ContentStream"]; int length = (int)Session["ContentLength"]; string type = (string)Session["ContentType"]; Response.Buffer = true; Response.Charset = ""; Response.Cache.SetCacheability(HttpCacheability.NoCache); Response.ContentType = type; Response.BinaryWrite(b); Response.Flush(); Session["ContentLength"] = null; Session["ContentType"] = null; Session["ContentStream"] = null; Response.End(); return Content(""); } }             The AjaxSubmit action method will save the image in Session and return content type and content length in response. ImageLoad action method will return the contents of image in response.Then clear these Sessions.           Just run your application and see the effect.   Checking Size and Content Type of File:          You may notice that AjaxSubmit action method is returning both content type and content length. You can check both properties before submitting your complete form.     $(myform).ajaxSubmit({success: function(responseText)            {                                var contentType=responseText.substring(0,responseText.indexOf(';'));                var contentLength=responseText.substring(responseText.indexOf(';')+1);                // Here you can do your validation                var d=new Date();                $(imageId)[0].src="http://weblogs.asp.net/MoneypingAPP/ImagePreview/ImageLoad?a="+d.getTime();            }        });  Handling Nested Form Case:          The above code will work if you have only one form. But this is not the case always.You may have a form control which wraps all the controls and you do not want to submit the whole form, just for getting a preview effect.           In this case you need to create a dynamic form control using JavaScript, and then add file upload control to this form and submit the form asynchronously  function ChangeImage(fileId,imageId)         {            var myform=document.createElement("form");                    myform.action="NerdDinner/ImagePreview/AjaxSubmit";            myform.enctype="multipart/form-data";            myform.method="post";            var imageLoad=document.getElementById(fileId).cloneNode(true);            myform.appendChild(imageLoad);            document.body.appendChild(myform);            $(myform).ajaxSubmit({success: function(responseText)                {                                    var contentType=responseText.substring(0,responseText.indexOf(';'));                    var contentLength=responseText.substring(responseText.indexOf(';')+1);                    var d=new Date();                    $(imageId)[0].src="http://weblogs.asp.net/MoneypingAPP/ImagePreview/ImageLoad?a="+d.getTime();                    document.body.removeChild(myform);                }            });        }            You also need append the child in order to send request and remove them after receiving response.

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• SQL SERVER – Difference Between GRANT and WITH GRANT

  - by pinaldave

  This was very interesting question recently asked me to during my session at TechMela Nepal. The question is what is the difference between GRANT and WITH GRANT when giving permissions to user. Let us first see syntax for the same. GRANT: USE master; GRANT VIEW ANY DATABASE TO username; GO WITH GRANT: USE master; GRANT VIEW ANY DATABASE TO username WITH GRANT OPTION; GO The difference between both of this option is very simple. In case of only GRANT – username can not grant the same permission to other users. In case, of the option of WITH GRANT – username will be able to give the permission it has received to other users. This is very basic definition of the subject. I would like to request my readers to come up with working script to prove this scenario. If can submit your script to me by email (pinal ‘at’ sqlauthority.com) or in comment field. Reference : Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL Query, SQL Scripts, SQL Security, SQL Server, SQL Tips and Tricks, T SQL, Technology Tagged: SQL Permissions

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• If-Modified-Since vs If-None-Match

  - by Roger

  This question is based on this article response header HTTP/1.1 200 OK Last-Modified: Tue, 12 Dec 2006 03:03:59 GMT ETag: "10c24bc-4ab-457e1c1f" Content-Length: 12195 request header GET /i/yahoo.gif HTTP/1.1 Host: us.yimg.com If-Modified-Since: Tue, 12 Dec 2006 03:03:59 GMT If-None-Match: "10c24bc-4ab-457e1c1f" HTTP/1.1 304 Not Modified In this case browser is sending both If-None-Match and If-Modified-Since. My question is on the server side do I need to match BOTH etag and If-Modified-Since before I send 304. Or Should I just look at etag and send 304 if etag is a match. In this case I am ignoring If-Modified-Since .

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• SQL SERVER – GUID vs INT – Your Opinion

  - by pinaldave

  I think the title is clear what I am going to write in your post. This is age old problem and I want to compile the list stating advantages and disadvantages of using GUID and INT as a Primary Key or Clustered Index or Both (the usual case). Let me start a list by suggesting one advantage and one disadvantage in each case. INT Advantage: Numeric values (and specifically integers) are better for performance when used in joins, indexes and conditions. Numeric values are easier to understand for application users if they are displayed. Disadvantage: If your table is large, it is quite possible it will run out of it and after some numeric value there will be no additional identity to use. GUID Advantage: Unique across the server. Disadvantage: String values are not as optimal as integer values for performance when used in joins, indexes and conditions. More storage space is required than INT. Please note that I am looking to create list of all the generic comparisons. There can be special cases where the stated information is incorrect, feel free to comment on the same. Please leave your opinion and advice in comment section. I will combine a final list and update this blog after a week. By listing your name in post, I will also give due credit. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL Constraint and Keys, SQL Data Storage, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, SQLServer, T SQL, Technology

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• Agile PLM on Developing Agile PLM: Software Lifecycle Management

  - by Kerrie Foy

  Change is constant.  That saying couldn’t be truer when applied to software development.   And with all that change comes extensive product complexity.  How do you manage it all?  As software developers ourselves, we can certainly empathize with the challenge. On April 3, 2012 Stephen Van Lare, VP of PLM Product Development, hosted a webcast to share how Oracle uses Agile to develop Agile – a PLM solution for managing a PLM solution!   Stephen passionately shared his unique insight based on 10 years of using Agile PLM to manage the development process, as well as customer use cases.  He shared our time-proven view of the software’s relationship to the product record, while pointing out that PLM is not source control.  He began with the challenges of software development, which boiled down to the deduction that “despite many great tools in the software development industry, it takes a lot more than good source control, more than good bug tracking, to get to an on-time, on-budget and quality release in your marketplace.   It requires defining the right things you want to do, managing the scope, managing your schedule, and, most importantly, managing the change to all those things over the lifecycle of the process. And this is the definition of PLM.”   Stephen then defined the relationship of PLM to the software development process by detailing the two main use cases –  Product Lifecycle and Mechatronics – which can be used simultaneously and in fact are already used in most industries today.  The Product Lifecycle use case is used to manage artifacts and change throughout product development, while the Mechatronics use case involves the software, hardware and electrical design in the BOM.  In essence, PLM is just as relevant to software as the rest of the BOM when trying to maximize profits during any phase of the lifecycle. Please take the opportunity to watch Stephen Van Lare as he details how and why based on his own experience developing Agile with Agile, as well as a lively Q&A session, in the Software PLM Webcast Replay.

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• How can I use GPRename's regex feature to reinsert the matched-group into the 'replace'?

  - by David Thomas

  I've been using GPRename to batch-rename files; this is rather more efficient than individually correcting each file, but still seems to be less efficient than it might be, primarily because either I don't understand the regex syntax used, or because the regex implementation is incomplete1 Given a list of files of the following syntax: (01) - title of file1.avi (02) - title of file2.avi (03) - title of file3.avi I attempted to use the 'replace' (with the regex option selected, the case-sensitive option deselected): (\(\d{2}\)) The preview then shows (given that I've specified no 'replace with' option as yet): title of file1.avi title of file2.avi title of file3.avi Which is great, clearly the regex is identifying the correct group (the (01)). Now, what I was hoping to do (using the JavaScript syntax) in the 'replace with' option is use: $1 (I also tried using '$1', \1 and '\1') This was just to check that I could access the matched group, and it seems I can't, the matched group is, as I suppose might be expected, replaced with the literal replacement string. So, my question: is it possible to match a particular group of characters, in this case the numbers within the brackets, and then insert those into the replacement string? Therefore: (01) title of file1.avi (02) title of file2.avi (03) title of file3.avi Becomes: 01 title of file1.avi 02 title of file2.avi 03 title of file3.avi I absolutely suspect the former, personally.

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• Connecting Linux to WatchGuard Firebox SSL (OpenVPN client)

  Recently, I got a new project assignment that requires to connect permanently to the customer's network through VPN. They are using a so-called SSL VPN. As I am using OpenVPN since more than 5 years within my company's network I was quite curious about their solution and how it would actually be different from OpenVPN. Well, short version: It is a disguised version of OpenVPN. Unfortunately, the company only offers a client for Windows and Mac OS which shouldn't bother any Linux user after all. OpenVPN is part of every recent distribution and can be activated in a couple of minutes - both client as well as server (if necessary). WatchGuard Firebox SSL - About dialog Borrowing some files from a Windows client installation Initially, I didn't know about the product, so therefore I went through the installation on Windows 8. No obstacles (and no restart despite installation of TAP device drivers!) here and the secured VPN channel was up and running in less than 2 minutes or so. Much appreciated from both parties - customer and me. Of course, this whole client package and my long year approved and stable installation ignited my interest to have a closer look at the WatchGuard client. Compared to the original OpenVPN client (okay, I have to admit this is years ago) this commercial product is smarter in terms of file locations during installation. You'll be able to access the configuration and key files below your roaming application data folder. To get there, simply enter '%AppData%\WatchGuard\Mobile VPN' in your Windows/File Explorer and confirm with Enter/Return. This will display the following files: Application folder below user profile with configuration and certificate files From there we are going to borrow four files, namely: ca.crt client.crt client.ovpn client.pem and transfer them to the Linux system. You might also be able to isolate those four files from a Mac OS client. Frankly, I'm just too lazy to run the WatchGuard client installation on a Mac mini only to find the folder location, and I'm going to describe why a little bit further down this article. I know that you can do that! Feedback in the comment section is appreciated. Configuration of OpenVPN (console) Depending on your distribution the following steps might be a little different but in general you should be able to get the important information from it. I'm going to describe the steps in Ubuntu 13.04 (Raring Ringtail). As usual, there are two possibilities to achieve your goal: console and UI. Let's what it is necessary to be done. First of all, you should ensure that you have OpenVPN installed on your system. Open your favourite terminal application and run the following statement: $ sudo apt-get install openvpn network-manager-openvpn network-manager-openvpn-gnome Just to be on the safe side. The four above mentioned files from your Windows machine could be copied anywhere but either you place them below your own user directory or you put them (as root) below the default directory: /etc/openvpn At this stage you would be able to do a test run already. Just in case, run the following command and check the output (it's the similar information you would get from the 'View Logs...' context menu entry in Windows: $ sudo openvpn --config client.ovpn Pay attention to the correct path to your configuration and certificate files. OpenVPN will ask you to enter your Auth Username and Auth Password in order to establish the VPN connection, same as the Windows client. Remote server and user authentication to establish the VPN Please complete the test run and see whether all went well. You can disconnect pressing Ctrl+C. Simplifying your life - authentication file In my case, I actually set up the OpenVPN client on my gateway/router. This establishes a VPN channel between my network and my client's network and allows me to switch machines easily without having the necessity to install the WatchGuard client on each and every machine. That's also very handy for my various virtualised Windows machines. Anyway, as the client configuration, key and certificate files are located on a headless system somewhere under the roof, it is mandatory to have an automatic connection to the remote site. For that you should first change the file extension '.ovpn' to '.conf' which is the default extension on Linux systems for OpenVPN, and then open the client configuration file in order to extend an existing line. $ sudo mv client.ovpn client.conf $ sudo nano client.conf You should have a similar content to this one here: dev tunclientproto tcp-clientca ca.crtcert client.crtkey client.pemtls-remote "/O=WatchGuard_Technologies/OU=Fireware/CN=Fireware_SSLVPN_Server"remote-cert-eku "TLS Web Server Authentication"remote 1.2.3.4 443persist-keypersist-tunverb 3mute 20keepalive 10 60cipher AES-256-CBCauth SHA1float 1reneg-sec 3660nobindmute-replay-warningsauth-user-pass auth.txt Note: I changed the IP address of the remote directive above (which should be obvious, right?). Anyway, the required change is marked in red and we have to create a new authentication file 'auth.txt'. You can give the directive 'auth-user-pass' any file name you'd like to. Due to my existing OpenVPN infrastructure my setup differs completely from the above written content but for sake of simplicity I just keep it 'as-is'. Okay, let's create this file 'auth.txt' $ sudo nano auth.txt and just put two lines of information in it - username on the first, and password on the second line, like so: myvpnusernameverysecretpassword Store the file, change permissions, and call openvpn with your configuration file again: $ sudo chmod 0600 auth.txt $ sudo openvpn --config client.conf This should now work without being prompted to enter username and password. In case that you placed your files below the system-wide location /etc/openvpn you can operate your VPNs also via service command like so: $ sudo service openvpn start client $ sudo service openvpn stop client Using Network Manager For newer Linux users or the ones with 'console-phobia' I'm going to describe now how to use Network Manager to setup the OpenVPN client. For this move your mouse to the systray area and click on Network Connections => VPN Connections => Configure VPNs... which opens your Network Connections dialog. Alternatively, use the HUD and enter 'Network Connections'. Network connections overview in Ubuntu Click on 'Add' button. On the next dialog select 'Import a saved VPN configuration...' from the dropdown list and click on 'Create...' Choose connection type to import VPN configuration Now you navigate to your folder where you put the client files from the Windows system and you open the 'client.ovpn' file. Next, on the tab 'VPN' proceed with the following steps (directives from the configuration file are referred): General Check the IP address of Gateway ('remote' - we used 1.2.3.4 in this setup) Authentication Change Type to 'Password with Certificates (TLS)' ('auth-pass-user') Enter User name to access your client keys (Auth Name: myvpnusername) Enter Password (Auth Password: verysecretpassword) and choose your password handling Browse for your User Certificate ('cert' - should be pre-selected with client.crt) Browse for your CA Certificate ('ca' - should be filled as ca.crt) Specify your Private Key ('key' - here: client.pem) Then click on the 'Advanced...' button and check the following values: Use custom gateway port: 443 (second value of 'remote' directive) Check the selected value of Cipher ('cipher') Check HMAC Authentication ('auth') Enter the Subject Match: /O=WatchGuard_Technologies/OU=Fireware/CN=Fireware_SSLVPN_Server ('tls-remote') Finally, you have to confirm and close all dialogs. You should be able to establish your OpenVPN-WatchGuard connection via Network Manager. For that, click on the 'VPN Connections => client' entry on your Network Manager in the systray. It is advised that you keep an eye on the syslog to see whether there are any problematic issues that would require some additional attention. Advanced topic: routing As stated above, I'm running the 'WatchGuard client for Linux' on my head-less server, and since then I'm actually establishing a secure communication channel between two networks. In order to enable your network clients to get access to machines on the remote side there are two possibilities to enable that: Proper routing on both sides of the connection which enables both-direction access, or Network masquerading on the 'client side' of the connection Following, I'm going to describe the second option a little bit more in detail. The Linux system that I'm using is already configured as a gateway to the internet. I won't explain the necessary steps to do that, and will only focus on the additional tweaks I had to do. You can find tons of very good instructions and tutorials on 'How to setup a Linux gateway/router' - just use Google. OK, back to the actual modifications. First, we need to have some information about the network topology and IP address range used on the 'other' side. We can get this very easily from /var/log/syslog after we established the OpenVPN channel, like so: $ sudo tail -n20 /var/log/syslog Or if your system is quite busy with logging, like so: $ sudo less /var/log/syslog | grep ovpn The output should contain PUSH received message similar to the following one: Jul 23 23:13:28 ios1 ovpn-client[789]: PUSH: Received control message: 'PUSH_REPLY,topology subnet,route 192.168.1.0 255.255.255.0,dhcp-option DOMAIN ,route-gateway 192.168.6.1,topology subnet,ping 10,ping-restart 60,ifconfig 192.168.6.2 255.255.255.0' The interesting part for us is the route command which I highlighted already in the sample PUSH_REPLY. Depending on your remote server there might be multiple networks defined (172.16.x.x and/or 10.x.x.x). Important: The IP address range on both sides of the connection has to be different, otherwise you will have to shuffle IPs or increase your the netmask. {loadposition content_adsense} After the VPN connection is established, we have to extend the rules for iptables in order to route and masquerade IP packets properly. I created a shell script to take care of those steps: #!/bin/sh -eIPTABLES=/sbin/iptablesDEV_LAN=eth0DEV_VPNS=tun+VPN=192.168.1.0/24 $IPTABLES -A FORWARD -i $DEV_LAN -o $DEV_VPNS -d $VPN -j ACCEPT$IPTABLES -A FORWARD -i $DEV_VPNS -o $DEV_LAN -s $VPN -j ACCEPT$IPTABLES -t nat -A POSTROUTING -o $DEV_VPNS -d $VPN -j MASQUERADE I'm using the wildcard interface 'tun+' because I have multiple client configurations for OpenVPN on my server. In your case, it might be sufficient to specify device 'tun0' only. Simplifying your life - automatic connect on boot Now, that the client connection works flawless, configuration of routing and iptables is okay, we might consider to add another 'laziness' factor into our setup. Due to kernel updates or other circumstances it might be necessary to reboot your system. Wouldn't it be nice that the VPN connections are established during the boot procedure? Yes, of course it would be. To achieve this, we have to configure OpenVPN to automatically start our VPNs via init script. Let's have a look at the responsible 'default' file and adjust the settings accordingly. $ sudo nano /etc/default/openvpn Which should have a similar content to this: # This is the configuration file for /etc/init.d/openvpn## Start only these VPNs automatically via init script.# Allowed values are "all", "none" or space separated list of# names of the VPNs. If empty, "all" is assumed.# The VPN name refers to the VPN configutation file name.# i.e. "home" would be /etc/openvpn/home.conf#AUTOSTART="all"#AUTOSTART="none"#AUTOSTART="home office"## ... more information which remains unmodified ... With the OpenVPN client configuration as described above you would either set AUTOSTART to "all" or to "client" to enable automatic start of your VPN(s) during boot. You should also take care that your iptables commands are executed after the link has been established, too. You can easily test this configuration without reboot, like so: $ sudo service openvpn restart Enjoy stable VPN connections between your Linux system(s) and a WatchGuard Firebox SSL remote server. Cheers, JoKi

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• BizTalk 2009 - The Scope of the Table Looping Functoid

  - by StuartBrierley

  When mapping in BizTalk you will find there are times when you need to map from flat and dispersed elemements in your source schema to a repeated record with child elements in your destination schema.  Below is an example of how you can make use of the Table Looping Functoid to bring together these flat elements and create your repeated group.  Although this example is purposely simple, I have previsouly encounted this issue on a much more complex scale when mapping the response from a credit scoring agency where all the applicant details were supplied in separate parts of a very flat schema. Consider the source and destination schemas as follows:   Although the Table Looping Functoid states that the first input must be a scoping element linked from a repeating group, you can actually also make use of a constant value.  In this case I know that the source schema always contains two people, so I set this to two. Then you need to set the number of columns in your table, in this case 2 (name and sex) and link all the required fields from the source schema. Following this you can configure the table. You can then add the Table Extractor functoids and complete the map. If you now validate this map you will see that BizTalk will warn you about the scoping link for the Table Looping Functoid, but this can be safely ignored. C:\Code\Developer Folders\Stuart Brierley\Test Mapping\TableLooping.btm: warning btm1071: A first input of the Table-Looping functoid must be a link from a Source Tree Node which acts as the scoping parameter. Testing the map will produce the following output:

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• ScrollViewer.EnsureVisible for Windows Phone

  - by Daniel Moth

  In my Translator By Moth app, on both the current and saved pivot pages the need arose to programmatically scroll to the bottom. In the former, case it is when a translation takes place (if the text is too long, I want to scroll to the bottom of the translation so the user can focus on that, and not their input text for translation). In the latter case it was when a new translation is saved (it is added to the bottom of the list, so scrolling is required to make it visible). On both pages a ScrollViewer is used. In my exploration of the APIs through intellisense and msdn I could not find a method that auto scrolled to the bottom. So I hacked together a solution where I added a blank textblock to the bottom of each page (within the ScrollViewer, but above the translated textblock and the saved list) and tried to make it scroll it into view from code. After searching the web I found a little algorithm that did most of what I wanted (sorry, I do not have the reference handy, but thank you whoever it was) that after minor tweaking I turned into an extension method for the ScrollViewer that is very easy to use: this.Scroller.EnsureVisible(this.BlankText); The method itself I share with you here: public static void EnsureVisible(this System.Windows.Controls.ScrollViewer scroller, System.Windows.UIElement uiElem) { System.Diagnostics.Debug.Assert(scroller != null); System.Diagnostics.Debug.Assert(uiElem != null); scroller.UpdateLayout(); double maxScrollPos = scroller.ExtentHeight - scroller.ViewportHeight; double scrollPos = scroller.VerticalOffset - scroller.TransformToVisual(uiElem).Transform(new System.Windows.Point(0, 0)).Y; if (scrollPos > maxScrollPos) scrollPos = maxScrollPos; else if (scrollPos < 0) scrollPos = 0; scroller.ScrollToVerticalOffset(scrollPos); } I am sure there are better ways, but this "worked for me" :-) Comments about this post by Daniel Moth welcome at the original blog.

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• Translating with Google Translate without API and C# Code

  - by Rick Strahl

  Some time back I created a data base driven ASP.NET Resource Provider along with some tools that make it easy to edit ASP.NET resources interactively in a Web application. One of the small helper features of the interactive resource admin tool is the ability to do simple translations using both Google Translate and Babelfish. Here's what this looks like in the resource administration form: When a resource is displayed, the user can click a Translate button and it will show the current resource text and then lets you set the source and target languages to translate. The Go button fires the translation for both Google and Babelfish and displays them - pressing use then changes the language of the resource to the target language and sets the resource value to the newly translated value. It's a nice and quick way to get a quick translation going. Ch… Ch… Changes Originally, both implementations basically did some screen scraping of the interactive Web sites and retrieved translated text out of result HTML. Screen scraping is always kind of an iffy proposition as content can be changed easily, but surprisingly that code worked for many years without fail. Recently however, Google at least changed their input pages to use AJAX callbacks and the page updates no longer worked the same way. End result: The Google translate code was broken. Now, Google does have an official API that you can access, but the API is being deprecated and you actually need to have an API key. Since I have public samples that people can download the API key is an issue if I want people to have the samples work out of the box - the only way I could even do this is by sharing my API key (not allowed).   However, after a bit of spelunking and playing around with the public site however I found that Google's interactive translate page actually makes callbacks using plain public access without an API key. By intercepting some of those AJAX calls and calling them directly from code I was able to get translation back up and working with minimal fuss, by parsing out the JSON these AJAX calls return. I don't think this particular Warning: This is hacky code, but after a fair bit of testing I found this to work very well with all sorts of languages and accented and escaped text etc. as long as you stick to small blocks of translated text. I thought I'd share it in case anybody else had been relying on a screen scraping mechanism like I did and needed a non-API based replacement. Here's the code: /// <summary> /// Translates a string into another language using Google's translate API JSON calls. /// <seealso>Class TranslationServices</seealso> /// </summary> /// <param name="Text">Text to translate. Should be a single word or sentence.</param> /// <param name="FromCulture"> /// Two letter culture (en of en-us, fr of fr-ca, de of de-ch) /// </param> /// <param name="ToCulture"> /// Two letter culture (as for FromCulture) /// </param> public string TranslateGoogle(string text, string fromCulture, string toCulture) { fromCulture = fromCulture.ToLower(); toCulture = toCulture.ToLower(); // normalize the culture in case something like en-us was passed // retrieve only en since Google doesn't support sub-locales string[] tokens = fromCulture.Split('-'); if (tokens.Length > 1) fromCulture = tokens[0]; // normalize ToCulture tokens = toCulture.Split('-'); if (tokens.Length > 1) toCulture = tokens[0]; string url = string.Format(@"http://translate.google.com/translate_a/t?client=j&text={0}&hl=en&sl={1}&tl={2}", HttpUtility.UrlEncode(text),fromCulture,toCulture); // Retrieve Translation with HTTP GET call string html = null; try { WebClient web = new WebClient(); // MUST add a known browser user agent or else response encoding doen't return UTF-8 (WTF Google?) web.Headers.Add(HttpRequestHeader.UserAgent, "Mozilla/5.0"); web.Headers.Add(HttpRequestHeader.AcceptCharset, "UTF-8"); // Make sure we have response encoding to UTF-8 web.Encoding = Encoding.UTF8; html = web.DownloadString(url); } catch (Exception ex) { this.ErrorMessage = Westwind.Globalization.Resources.Resources.ConnectionFailed + ": " + ex.GetBaseException().Message; return null; } // Extract out trans":"...[Extracted]...","from the JSON string string result = Regex.Match(html, "trans\":(\".*?\"),\"", RegexOptions.IgnoreCase).Groups[1].Value; if (string.IsNullOrEmpty(result)) { this.ErrorMessage = Westwind.Globalization.Resources.Resources.InvalidSearchResult; return null; } //return WebUtils.DecodeJsString(result); // Result is a JavaScript string so we need to deserialize it properly JavaScriptSerializer ser = new JavaScriptSerializer(); return ser.Deserialize(result, typeof(string)) as string; } To use the code is straightforward enough - simply provide a string to translate and a pair of two letter source and target languages: string result = service.TranslateGoogle("Life is great and one is spoiled when it goes on and on and on", "en", "de"); TestContext.WriteLine(result); How it works The code to translate is fairly straightforward. It basically uses the URL I snagged from the Google Translate Web Page slightly changed to return a JSON result (&client=j) instead of the funky nested PHP style JSON array that the default returns. The JSON result returned looks like this: {"sentences":[{"trans":"Das Leben ist großartig und man wird verwöhnt, wenn es weiter und weiter und weiter geht","orig":"Life is great and one is spoiled when it goes on and on and on","translit":"","src_translit":""}],"src":"en","server_time":24} I use WebClient to make an HTTP GET call to retrieve the JSON data and strip out part of the full JSON response that contains the actual translated text. Since this is a JSON response I need to deserialize the JSON string in case it's encoded (for upper/lower ASCII chars or quotes etc.). Couple of odd things to note in this code: First note that a valid user agent string must be passed (or at least one starting with a common browser identification - I use Mozilla/5.0). Without this Google doesn't encode the result with UTF-8, but instead uses a ISO encoding that .NET can't easily decode. Google seems to ignore the character set header and use the user agent instead which is - odd to say the least. The other is that the code returns a full JSON response. Rather than use the full response and decode it into a custom type that matches Google's result object, I just strip out the translated text. Yeah I know that's hacky but avoids an extra type and firing up the JavaScript deserializer. My internal version uses a small DecodeJsString() method to decode Javascript without the overhead of a full JSON parser. It's obviously not rocket science but as mentioned above what's nice about it is that it works without an Google API key. I can't vouch on how many translates you can do before there are cut offs but in my limited testing running a few stress tests on a Web server under load I didn't run into any problems. Limitations There are some restrictions with this: It only works on single words or single sentences - multiple sentences (delimited by .) are cut off at the ".". There is also a length limitation which appears to happen at around 220 characters or so. While that may not sound  like much for typical word or phrase translations this this is plenty of length. Use with a grain of salt - Google seems to be trying to limit their exposure to usage of the Translate APIs so this code might break in the future, but for now at least it works. FWIW, I also found that Google's translation is not as good as Babelfish, especially for contextual content like sentences. Google is faster, but Babelfish tends to give better translations. This is why in my translation tool I show both Google and Babelfish values retrieved. You can check out the code for this in the West Wind West Wind Web Toolkit's TranslationService.cs file which contains both the Google and Babelfish translation code pieces. Ironically the Babelfish code has been working forever using screen scraping and continues to work just fine today. I think it's a good idea to have multiple translation providers in case one is down or changes its format, hence the dual display in my translation form above. I hope this has been helpful to some of you - I've actually had many small uses for this code in a number of applications and it's sweet to have a simple routine that performs these operations for me easily. Resources Live Localization Sample Localization Resource Provider Administration form that includes options to translate text using Google and Babelfish interactively. TranslationService.cs The full source code in the West Wind West Wind Web Toolkit's Globalization library that contains the translation code. © Rick Strahl, West Wind Technologies, 2005-2011Posted in CSharp  HTTP   Tweet (function() { var po = document.createElement('script'); po.type = 'text/javascript'; po.async = true; po.src = 'https://apis.google.com/js/plusone.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(po, s); })();

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• Handling EJB/JPA exceptions in a “beautiful” way

  - by Rodrigues, Raphael

  In order to handle JPA exceptions, there are some ways already detailed in lots of blogs. Here, I intend to show one of them, which I consider kind of “beauty”. My use case has a unique constraint, when the User try to create a duplicate value in database. The JPA throws a java.sql.SQLIntegrityConstraintViolationException, and I have to catch it and replace the message. In fact, ADF Business Components framework already has a beautiful solution for this very well documented here . However, for EJB/JPA there's no similar approach. In my case, what I had to do was: 1. Create a custom Error Handler Class in DataBindings file; a. Here is how you accomplish it. 2. Override the reportException method and check if the type of exception exists on property file a. If yes, I change the message and rethrows the exception b. If not, go on the execution The main goal of this approach is whether a new or unhandled Exception was raised, the job is, only create a single entry in bundle property file. Here are pictures step by step: 1. CustomExceptionHandler.java 2. Databindings.cpx 3. Bundle file 4. jspx: 5. Stacktrace: Give your opinion, what did you think about that?

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• Using Oracle Enterprise Manager Ops Center to Update Solaris via Live Upgrade

  - by LeonShaner

  Introduction: This Oracle Enterprise Manager Ops Center blog entry provides tips for using Ops Center to update Solaris using Live Upgrade on Solaris 10 and Boot Environments on Solaris 11. Why use Live Upgrade? Live Upgrade (LU) can significantly reduce downtime associated with patching Live Upgrade avoids dropping to single-user mode for long periods of time during patching Live Upgrade relies on an Alternate Boot Environment (ABE)/(BE), which is patched while in multi-user mode; thereby allowing normal system operations to continue with the active BE, while the alternate BE is being patched Activating an newly patched (A)BE is essentially a reboot; therefore the downtime is ~= reboot Admins can easily revert to the prior Boot Environment (BE) as a safeguard / fallback. Why use Ops Center to patch via Live Upgrade, Alternate Boot Environments, and Solaris 11 equivalents? All the benefits of Ops Center's extensive patch and package knowledge base can be leveraged on top of Live Upgrade Ops Center can orchestrate patching based on Live Upgrade and Solaris 11 features, which all works together to minimize downtime Ops Centers advanced inventory and reporting features assurance that each OS is updated to a verifiable, consistent standard, rather than relying on ad-hoc (error prone) procedures and scripts Ops Center gives admins control over the boot environment specifications or they can let Ops Center decide when a BE is necessary, thereby reducing complexity and lowering the opportunity for user error Preparing to use Live Upgrade-like features in Solaris 11 Requirements and information you should know: Global Zone Root file-systems must be separate from Solaris Container / Zone filesystems Solaris 11 has features which are similar in concept to Live Upgrade on Solaris 10, but differ greatly in implementationImportant distinctions: Solaris 11 assumes ZFS root Solaris 11 adds Boot Environments (BE's) as an integrated feature (see beadm) Solaris 11 BE's avoid single-user patching (vs. Solaris 10 w/ ZFS snapshot=ABE). Solaris 11 Image Packaging System (IPS) has hooks for BE creation, as needed Solaris 11 allows pkgs to be installed + upgraded in alternate BE (e.g. instead of the live system) but it is controlled on a per-pkg basis Boot Environments are activated across a reboot; instead of spending long periods installing + upgrading packages in single user mode. Fallback to a prior BE is a function of the BE infrastructure (a la beadm). (Generally) Reboot + BE activation can be much much faster on Solaris 11 Preparing to use Live Upgrade on Solaris 10 Requirements and information you should know: Global Zone Root file-systems must be separate from Solaris Container / Zone filesystems Live Upgrade Pre-requisite patches must be applied before the first Live Upgrade Alternate Boot Environments are created (see "Pre-requisite Patches" section, below...) Solaris 10 Update 6 or newer on ZFS root is the practical starting point for Live Upgrade Live Upgrade with ZFS root is far more straight-forward than any scheme based on Alternative Boot Environments in slices or temporarily breaking mirrors Use Solaris best practices to upgrade the OS to at least Solaris 10 Update 4 (outside of Ops Center) UFS root can (technically) be used, but it is significantly more involved (e.g. discouraged) -- there are many reasons to move to ZFS while going through the process to update to Solaris 10 Update 6 or newer (out side of Ops Center) Recommendation: Start with Solaris 10 Update 6 or newer on ZFS root Recommendation: Start with Ops Center 12c or newer Ops Center 12c can automatically create your ABE's for you, without the need for custom scripts Ops Center 12c Update 2 avoids kernel panic on unpatched Solaris 10 update 9 (and older) -- unrelated to Live Upgrade, but more on the issue, below. NOTE: There is no magic!  If you have systems running Solaris 10 Update 5 or older on UFS root, and you don't know how to get them updated to Solaris 10 on ZFS root, then there are services available from Oracle Advanced Customer Support (ACS), which specialize in this area. Live Upgrade Pre-requisite Patches (Solaris 10) Certain Live Upgrade related patches must be present before the first Live Upgrade ABE's are created on Solaris 10.Use the following MOS Search String to find the “living document” that outlines the required patch minimums, which are necessary before using any Live Upgrade features: Solaris Live Upgrade Software Patch Requirements(Click above – the link is valid as of this writing, but search in MOS for the same "Solaris Live Upgrade Software Patch Requirements" string if necessary) It is a very good idea to check the document periodically and adapt to its contents, accordingly.IMPORTANT:  In case it wasn't clear in the above document, some direct patching of the active OS, including a reboot, may be required before Live Upgrade can be successfully used the first time.HINT: You can use Ops Center to determine what to expect for a given system, and to schedule the “pre-patching” during a maintenance window if necessary. Preparing to use Ops Center Discover + Manage (Install + Configure the Ops Center agent in) each Global Zone Recommendation:  Begin by using OCDoctor --agent-prereq to determine whether OS meets OC prerequisites (resolve any issues) See prior requirements and recommendations w.r.t. starting with Solaris 10 Update 6 or newer on ZFS (or at least Solaris 10 Update 4 on UFS, with caveats) WARNING: Systems running unpatched Solaris 10 update 9 (or older) should run the Ops Center 12c Update 2 agent to avoid a potential kernel panic The 12c Update 2 agent will check patch minimums and disable certain process accounting features if the kernel is not sufficiently patched to avoid the panic SPARC: 142900-05 Obsoleted by: 142900-06 SunOS 5.10: kernel patch 10 Oracle Solaris on SPARC (32-bit) X64: 142901-05 Obsoleted by: 142901-06 SunOS 5.10_x86: kernel patch 10 Oracle Solaris on x86 (32-bit) OR SPARC: 142909-17 SunOS 5.10: kernel patch 10 Oracle Solaris on SPARC (32-bit) X64: 142910-17 SunOS 5.10_x86: kernel patch 10 Oracle Solaris on x86 (32-bit) Ops Center 12c (initial release) and 12c Update 1 agent can also be safely used with a workaround (to be performed BEFORE installing the agent): # mkdir -p /etc/opt/sun/oc # echo "zstat_exacct_allowed=false" > /etc/opt/sun/oc/zstat.conf # chmod 755 /etc/opt/sun /etc/opt/sun/oc # chmod 644 /etc/opt/sun/oc/zstat.conf # chown -Rh root:sys /etc/opt/sun/oc NOTE: Remove the above after patching the OS sufficiently, or after upgrading to the 12c Update 2 agent Using Ops Center to apply Live Upgrade-related Pre-Patches (Solaris 10)Overview: Create an OS Update Profile containing the minimum LU-related pre-patches, based on the Solaris Live Upgrade Software Patch Requirements, previously mentioned. SIMULATE the deployment of the LU-related pre-patches Observe whether any of the LU-related pre-patches will require a reboot The job details for each Global Zone will advise whether a reboot step will be required ACTUALLY deploy the LU-related pre-patches, according to your change control process (e.g. if no reboot, maybe okay to do now; vs. must do later because of the reboot). You can schedule the job to occur later, during a maintenance window Check the job status for each node, resolving any issues found Once the LU-related pre-patches are applied, you can Ops Center to patch using Live Upgrade on Solaris 10 Using Ops Center to patch Solaris 10 with LU/ABE's -- the GOODS!(this is the heart of the tip): Create an OS Update Profile containing the patches that make up your standard build Use Solaris Baselines when possible Add other individual patches as needed ACTUALLY deploy the OS Update Profile Specify the appropriate Live Upgrade options, e.g. Synchronize the active BE to the alternate BE before patching Do not activate the BE after patching Check the job status for each node, resolving any issues found Activate the newly patched BE according to your change control process Activate = Reboot to the ABE, making the ABE the new active BE Ops Center does not separate LU activate from reboot, so expect a reboot! Check the job status for each node, resolving any issues found Examples (w/Screenshots) Solaris 10 and Live Upgrade: Auto-Create the Alternate Boot Environment (ZFS root only) ABE to be created on ZFS with name S10_12_07REC (Example) Uses built in feature to call “lucreate -n S10_12_07REC” behind scenes if not already present NOTE: Leave “lucreate” params blank (if you do specify options, the will be appended after -n $ABEName) Solaris 10 and Live Upgrade: Alternate Boot Environment Creation via Operational Profile (script) The Alternate Boot Environment is to be created via custom, user-supplied script, which does whatever is needed for the system where Live Upgrade will be used. Operational Profile, which provides the script to create an ABE: Very similar to the automatic case, but with a Script (Operational Profile), which is used to create the ABE Relies on user-supplied script in the form of an Operational Profile Could be used to prepare an ABE based on a UFS root in a slice, or on a separate device (e.g. by breaking a mirror first) – it is up to the script author to do the right thing! EXAMPLE: Same result as the ZFS case, but illustrating the Operational Profile (e.g. script) approach to call: # lucreate -n S10_1207REC NOTE: OC special variable is $ABEName Boot Environment Profile, which references the Operational Profile Script = Operational Profile on this screen Refers to Operational Profile shown in the previous section The user-supplied S10_Create_BE Operational Profile will be run The Operational Profile must send a non-zero exit code if there is a problem (so that the OS Update job will not proceed) Solaris 10 OS Update Profile (to provide the actual patch specifications) Solaris 10 Baseline “Recommended” chosen for “Install” Solaris 10 OS Update Plan (two-steps in this case) “Create a Boot Environment” + “Update OS” are chosen. Using Ops Center to patch Solaris 11 with Boot Environments (as needed) Create a Solaris 11 OS Update Profile containing the packages that make up your standard build ACTUALLY deploy the Solaris 11 OS Update Profile BE will be created if needed (or you can stipulate no BE) BE name will be auto-generated (if needed), or you may specify a BE name Check the job status for each node, resolving any issues found Check if a BE was created; if so, activate the new BE Activate = Reboot to the BE, making the new BE the active BE Ops Center does not separate BE activate from reboot NOTE: Not every Solaris 11 OS Update will require a new BE, so a reboot may not be necessary. Solaris 11: Auto BE Create (as Needed -- let Ops Center decide) BE to be created as needed BE to be named automatically Reboot (if necessary) deferred to separate step Solaris 11: OS Profile Solaris 11 “entire” chosen for a particular SRU Solaris 11: OS Update Plan (w/BE)  “Create a Boot Environment” + “Update OS” are chosen. Summary: Solaris 10 Live Upgrade, Alternate Boot Environments, and their equivalents on Solaris 11 can be very powerful tools to help minimize the downtime associated with updating your servers.  For very old Solaris, there are some important prerequisites to adhere to, but once the initial preparation is complete, Live Upgrade can be used going forward.  For Solaris 11, the built-in Boot Environment handling is leveraged directly by the Image Packaging System, and the result is a much more straight forward way to patch, and far fewer prerequisites to satisfy in getting there.  Ops Center simplifies using either approach, and helps you improve consistency from system to system, which ultimately helps you improve the overall up-time across all the Solaris systems in your environment. Please let us know what you think?  Until next time...\Leon-- Leon Shaner | Senior IT/Product ArchitectSystems Management | Ops Center Engineering @ Oracle The views expressed on this [blog; Web site] are my own and do not necessarily reflect the views of Oracle. For more information, please go to Oracle Enterprise Manager  web page or  follow us at :  Twitter | Facebook | YouTube | Linkedin | Newsletter

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