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  • Creating multiple heads in remote repository

    - by Jab
    We are looking to move our team (~10 developers) from SVN to mercurial. We are trying to figure out how to manage our workflow. In particular, we are trying to see if creating remote heads is the right solution. We currently have a very large repository with multiple, related projects. They share a lot of code, but pieces of the project are deployed by different teams (3 teams) independent of other portions of the code-base. So each team is working on concurrent large features. The way we currently handles this in SVN are branches. Team1 has a branch for Feature1, same deal for the other teams. When Team1 finishes their change, it gets merged into the trunk and deployed out. The other teams follow suite when their project is complete, merging of course. So my initial thought are using Named Branches for these situations. Team1 makes a Feature1 branch off of the default branch in Hg. Now, here is the question. Should the team PUSH that branch, in it's current/half-state to the repository. This will create a second head in the core repo. My initial reaction was "NO!" as it seems like a bad idea. Handling multiple heads on our repository just sounds awful, but there are some advantages... First, the teams want to setup Continuous Integration to build this branch during their development cycle(months long). This will only work if the CI can pull this branch from the repo. This is something we do now with SVN, copy a CI build and change the branch. Easy. Second, it makes it easier for any team member to jump onto the branch and start working. Without pushing to the core repo, they would have to receive a push from a developer on that team with the changeset information. It is also possible to lose local commits to hardware failure. The chances increase a lot if it's a branch by a single developer who has followed the "don't push until finished" approach. And lastly is just for ease of use. The developers can easily just commit and push on their branch at any time without consequence(as they do today, in their SVN branches). Is there a better way to handle this scenario that I may be missing? I just want a veteran's opinion before moving forward with the strategy. For bug fixes we like the general workflow of mecurial, anonymous branches that only consist of 1-2 commits. The simplicity is great for those cases. By the way, I've read this , great article which seems to favor Named branches.

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  • How can I most accurately calculate the execution time of an ASP.NET page while also displaying it o

    - by henningst
    I want to calculate the execution time of my ASP.NET pages and display it on the page. Currently I'm calculating the execution time using a System.Diagnostics.Stopwatch and then store the value in a log database. The stopwatch is started in OnInit and stopped in OnPreRenderComplete. This seems to be working quite fine, and it's giving a similar execution time as the one shown in the page trace. The problem now is that I'm not able to display the execution time on the page because the stopwatch is stopped too late in the life cycle. What is the best way to do this?

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  • Has anyone had trouble with Intellisense in Visual Studio when using UltraVNC?

    - by mullala
    Hi, a colleague and I are trying pair programming for the first time. We both remote into a development machine; I'm using RemoteDesktop and my colleague is using UltraVNC. This works great except that he can't see the Intellisense dropdown in Visual Studio 2008. According to online posts, this may be something to do with DirectDraw, but I don't see much by way of a workaround. Has anyone else experienced this? Thanks, Andrew

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  • Which network protocol to use for lightweight notification of remote apps (Delphi 2005)

    - by Chris Thornton
    I have this situation.... Client-initiated SOAP 1.1 communication between one server and let's say, tens of thousands of clients. Clients are external, coming in through our firewall, authenticated by certificate, https, etc.. They can be anywhere, and usually have their own firewalls, NAT routers, etc... They're truely external, not just remote corporate offices. They could be in a corporate/campus network, DSL/Cable, even Dialup. Currently, clients push new data to the server and pull new data from the server on 15-minute polling loop. The server currently does not push data - the client hits the "messagecount" method, to see if there is new data to pull. If 0, it sleeps for another 15 min and checks again. We're trying to get that down to 7 seconds. If this were an internal app, with one or just a few dozen clients, we'd write a cilent "listener" soap service, and would push data to it. But since they're external, sit behind their own firewalls, and sometimes private networks behind NAT routers, this is not practical. So we're left with polling on a much quicker loop. 10K clients, each checking their messagecount every 10 seconds, is going to be 1000/sec messages that will mostly just waste bandwidth, server, firewall, and authenticator resources. So I'm trying to design something better than what would amount to a self-inflicted DoS attack. I don't think it's practical to have the server send soap messages to the client (push) as this would require too much configuration at the client end. But I think there are alternatives that I don't know about. Such as: 1) Is there a way for the client to make a request for GetMessageCount() via Soap 1.1, and get the response, and then perhaps, "stay on the line" for perhaps 5-10 minutes to get additional responses in case new data arrives? i.e the server says "0", then a minute later in response to some SQL trigger (the server is C# on Sql Server, btw), knows that this client is still "on the line" and sends the updated message count of "5"? 2) Is there some other protocol that we could use to "ping" the client, using information gathered from their last GetMessageCount() request? 3) I don't even know. I guess I'm looking for some magic protocol where the client can send a GetMessageCount() request, which would include info for "oh by the way, in case the answer changes in the next hour, ping me at this address...". Also, I'm assuming that any of these "keep the line open" schemes would seriously impact the server sizing, as it would need to keep many thousands of connections open, simultaneously. That would likely impact the firewalls too, I think. Is there anything out there like that? Or am I pretty much stuck with polling? TIA, Chris

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  • Ping remote server and wait to get data

    - by infinity
    Hi I'm building my first application for android and I've reached a point where I can't find a solution even have no idea what to search for in Google. So the problem: I am pinging a remote server with GET request through the application passing some parameters like file_id. Then the server gives back confirmation if the file exists or error otherwise, both in plain text. The error string is $$$ERROR$$$. Actually the confirmation is JSON string that holds the path to the file. If the file doesn't exists on the server it generated the error message and start downloading the file and processing it which normally takes 10-30 seconds. What would be the best way to check if the file is ready for download? I have DownloadFile class that extends AsyncTask but before I reach the point to download the file I need the URL which is dependant on the previous request which is in the main class in the UI thread. Here is some code: public class MainActivity extends Activity { private String getInfo() { // Create a new HttpClient and Post Header HttpClient httpClient = new DefaultHttpClient(); HttpGet httpPost = new HttpGet(infoUrl); StringBuilder sb = null; String data; JSONObject jObject = null; try { HttpResponse response = httpClient.execute(httpPost); // This might be equal "$$$ERROR$$$" if no file exists sb = inputStreamToString(response.getEntity().getContent()); } catch(ClientProtocolException e) { // TODO Auto-generated catch block Log.v("Error: pushItem ClientProtocolException: ", e.toString()); } catch (IOException e) { // TODO Auto-generated catch block Log.v("Error: pushItem IOException: ", e.toString()); } // Clean the data to be complaint JSON format data = sb.toString().replace("info = ", ""); try { jObject = new JSONObject(data); data = jObject.getString("h"); fileTitle = jObject.getString("title"); } catch (JSONException e) { // TODO Auto-generated catch block e.printStackTrace(); } downloadUrl = String.format(downloadUrl, fileId, data); return downloadUrl; } } So my idea was to get the content and if equal to $$$ERROR$$$ go into loop until JSON data is passed but I guess there is better solution. Note: I don't have control over the server output so have to deal with what I have.

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  • Unable to fetch Json data from remote url

    - by user3772611
    I am cracking my head to solve this thing. I am unable to fetch the JSON data from remote REST API. I need to fetch the JSOn data nd display the "html_url" field from the JSON data on my website. I saw that you need the below charset and content type for fetching JSON. <html> <head> <meta charset="utf-8"> <meta http-equiv="content-type" content="application/json"> </head> <body> <p>My Instruments page</p> <ul></ul> <script src="http://ajax.googleapis.com/ajax/libs/jquery/1.3/jquery.min.js"></script> <script src="http://ajax.googleapis.com/ajax/libs/jqueryui/1.10.3/jquery-ui.min.js"></script> <script type="text/javascript" src="http://code.jquery.com/jquery-1.11.0.min.js"></script> <script type="text/javascript"> $(document).ready(function () { alert("Inside the script"); $.getJSON(" https://pki.zendesk.com/api/v2/help_center/sections/200268985/articles.json", function (obj) { alert("Inside the getJSON"); $.each(obj, function (key, value) { $("ul").append("<li>" + value.html_url + "</li>"); }); }); }); </script> </body> </html> I referred to following example on jsfiddle http://jsfiddle.net/2xTjf/29/ The "http://date.jsontest.com" given in this example also doesn't work in my code. The first alert is pops but not the other one. I am a novice at JSON/ Jquery. i used jsonlint.com to find if it has valid JSON, it came out valid. I tested using chrome REST client too. What am I missing here ? Help me please ! Thanks in anticipation.

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  • Can Mac have more than one client using its desktop?

    - by Phil
    I have one Server Mac OSX and have 5 windows PC's in my team. So I have this program on the MAC but I want two users in my team to be able to use this program, is there any way more than one person can VNC or remote desktop or something to the MAC server? Then those two users could both use the program on the mac server. I would need two legal licenses, I guess.

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  • Stumped by "The remote server returned an error: (403) Forbidden" with WCF Service in https

    - by RJ
    I have a WCF Service that I have boiled down to next to nothing because of this error. It is driving me up the wall. Here's what I have now. A very simple WCF service with one method that returns a string with the value, "test". A very simple Web app that uses the service and puts the value of the string into a label. A web server running IIS 6 on Win 2003 with a SSL certificate. Other WCF services on the same server that work. I publish the WCF service to it's https location I run the web app in debug mode in VS and it works perfectly. I publish the web app to it's https location on the same server the WCF service resides under the same SSL certificate I get, "The remote server returned an error: (403) Forbidden" I have changed almost every setting in IIS as well as the WCF and Web apps to no avail. I have compared setting in the WCF services that work and everything is the same. Below are the setting in the web.config for the WCF Service and the WEB app: It appears the problem has to do with the Web app but I am out of ideas. Any ideas: WCF Service: <system.serviceModel> <bindings> <client /> <services> <service behaviorConfiguration="Ucf.Smtp.Wcf.SmtpServiceBehavior" name="Ucf.Smtp.Wcf.SmtpService"> <host> <baseAddresses> <add baseAddress="https://test.net.ucf.edu/webservices/Smtp/" /> </baseAddresses> </host> <endpoint address="" binding="wsHttpBinding" contract="Ucf.Smtp.Wcf.ISmtpService" bindingConfiguration="SSLBinding"> <identity> <dns value="localhost"/> </identity> </endpoint> <endpoint address="mex" binding="mexHttpsBinding" contract="IMetadataExchange"/> </service> </services> <behaviors> <serviceBehaviors> <behavior name="Ucf.Smtp.Wcf.SmtpServiceBehavior"> <serviceMetadata httpsGetEnabled="true" /> <serviceDebug includeExceptionDetailInFaults="true" httpsHelpPageEnabled="True"/> </behavior> </serviceBehaviors> </behaviors> Web App: <system.serviceModel> <bindings><wsHttpBinding> <binding name="WSHttpBinding_ISmtpService" closeTimeout="00:01:00" openTimeout="00:01:00" receiveTimeout="00:10:00" sendTimeout="00:01:00" bypassProxyOnLocal="false" transactionFlow="false" hostNameComparisonMode="StrongWildcard" maxBufferPoolSize="524288" maxReceivedMessageSize="65536" messageEncoding="Text" textEncoding="utf-8" useDefaultWebProxy="true" allowCookies="false"> <readerQuotas maxDepth="32" maxStringContentLength="8192" maxArrayLength="16384" maxBytesPerRead="4096" maxNameTableCharCount="16384" /> <reliableSession ordered="true" inactivityTimeout="00:10:00" enabled="false" /> <security mode="Transport"> <transport clientCredentialType="None" proxyCredentialType="None" realm="" /> <message clientCredentialType="Windows" negotiateServiceCredential="true" establishSecurityContext="true" /> </security> </binding> <client> <endpoint address="https://net228.net.ucf.edu/webservices/smtp/SmtpService.svc" binding="wsHttpBinding" bindingConfiguration="WSHttpBinding_ISmtpService" contract="SmtpService.ISmtpService" name="WSHttpBinding_ISmtpService"> <identity> <dns value="localhost" /> </identity> </client> </system.serviceModel>

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  • How to manipulate data after its retrieved via remote database

    - by bMon
    So I've used code examples from all over the net and got my app to accurately call a .php file on my server, retrieve the JSON data, then parse the data, and print it. The problem is that its just printing to the screen for sake of the tutorial I was following, but now I need to use that data in other places and need help figuring out that process. The ultimate goal is to return my db query with map coordinates, then plot them on a google map. I have another app in which I manually plot points on a map, so I'll be integrating this app with that once I can get my head around how to correctly manipulate the data returned. public class Remote extends Activity { /** Called when the activity is first created. */ TextView txt; @Override public void onCreate(Bundle savedInstanceState) { super.onCreate(savedInstanceState); setContentView(R.layout.main); // Create a crude view - this should really be set via the layout resources // but since its an example saves declaring them in the XML. LinearLayout rootLayout = new LinearLayout(getApplicationContext()); txt = new TextView(getApplicationContext()); rootLayout.addView(txt); setContentView(rootLayout); // Set the text and call the connect function. txt.setText("Connecting..."); //call the method to run the data retreival txt.setText(getServerData(KEY_121)); } public static final String KEY_121 = "http://example.com/mydbcall.php"; private String getServerData(String returnString) { InputStream is = null; String result = ""; //the year data to send //ArrayList<NameValuePair> nameValuePairs = new ArrayList<NameValuePair>(); //nameValuePairs.add(new BasicNameValuePair("year","1970")); try{ HttpClient httpclient = new DefaultHttpClient(); HttpPost httppost = new HttpPost(KEY_121); HttpResponse response = httpclient.execute(httppost); HttpEntity entity = response.getEntity(); is = entity.getContent(); }catch(Exception e){ Log.e("log_tag", "Error in http connection "+e.toString()); } //convert response to string try{ BufferedReader reader = new BufferedReader(new InputStreamReader(is,"iso-8859-1"),8); StringBuilder sb = new StringBuilder(); String line = null; while ((line = reader.readLine()) != null) { sb.append(line + "\n"); } is.close(); result=sb.toString(); }catch(Exception e){ Log.e("log_tag", "Error converting result "+e.toString()); } //parse json data try{ JSONArray jArray = new JSONArray(result); for(int i=0;i<jArray.length();i++){ JSONObject json_data = jArray.getJSONObject(i); Log.i("log_tag","longitude: "+json_data.getDouble("longitude")+ ", latitude: "+json_data.getDouble("latitude") ); //Get an output to the screen returnString += "\n\t" + jArray.getJSONObject(i); } }catch(JSONException e){ Log.e("log_tag", "Error parsing data "+e.toString()); } return returnString; } } So the code: returnString += "\n\t" + jArray.getJSONObject(i); is what is currently printing to the screen. What I have to figure out is how to get the data into something I can reference in other spots in the program, and access the individual elements ie: double longitude = jArray.getJSONObject(3).longitude; or something to that effect.. I figure the class getServerData will have to return a Array type or something? Any help is appreciated, thanks.

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  • The remote server returned an unexpected response: (400) Bad Request while streaming

    - by phenevo
    Hi, I have problem with streaming. When I send small file like 1kb txt everything is ok, but when I send larger file like 100 kb jpg or 2gb psd I get: The remote server returned an unexpected response: (400) Bad Request. I'm using windows 7, VS 2010 and .net 3.5 and WCF Service library I lost all my weekend on this and I still see this error :/ Please help me Client: var client = new WpfApplication1.ServiceReference1.Service1Client("WSHttpBinding_IService1"); client.GetString("test"); string filename = @"d:\test.jpg"; FileStream fs = new FileStream(filename, FileMode.Open); try { client.ProcessStreamFromClient(fs); } catch (Exception exception) { Console.WriteLine(exception); } app.config: <?xml version="1.0" encoding="utf-8" ?> <configuration> <system.serviceModel> <bindings> <basicHttpBinding> <binding name="StreamedHttp" closeTimeout="10:01:00" openTimeout="10:01:00" receiveTimeout="10:10:00" sendTimeout="10:01:00" allowCookies="false" bypassProxyOnLocal="false" hostNameComparisonMode="StrongWildcard" maxBufferSize="65536000" maxBufferPoolSize="524288000" maxReceivedMessageSize="65536000" messageEncoding="Text" textEncoding="utf-8" transferMode="Streamed" useDefaultWebProxy="true"> <readerQuotas maxDepth="0" maxStringContentLength="0" maxArrayLength="0" maxBytesPerRead="0" maxNameTableCharCount="0" /> <security mode="None"> <transport clientCredentialType="None" proxyCredentialType="None" realm="" /> <message clientCredentialType="UserName" algorithmSuite="Default" /> </security> </binding> </basicHttpBinding> </bindings> <client> <endpoint address="http://localhost:8732/Design_Time_Addresses/WcfServiceLibrary2/Service1/" binding="basicHttpBinding" bindingConfiguration="StreamedHttp" contract="ServiceReference1.IService1" name="WSHttpBinding_IService1" /> </client> </system.serviceModel> </configuration> And Wcf ServiceLibrary: public void ProcessStreamFromClient(Stream str) { using (var outStream = new FileStream(@"e:\test.jpg", FileMode.Create)) { var buffer = new byte[4096]; int count; while ((count = str.Read(buffer, 0, buffer.Length)) > 0) { outStream.Write(buffer, 0, count); } } } App.config <?xml version="1.0" encoding="utf-8" ?> <configuration> <system.web> <compilation debug="true" /> </system.web> <!-- When deploying the service library project, the content of the config file must be added to the host's app.config file. System.Configuration does not support config files for libraries. --> <system.serviceModel> <bindings> <basicHttpBinding> <binding name="Binding1" hostNameComparisonMode="StrongWildcard" maxBufferSize="65536000" transferMode="Streamed" bypassProxyOnLocal="false" closeTimeout="10:01:00" openTimeout="10:01:00" receiveTimeout="10:10:00" sendTimeout="10:01:00" maxBufferPoolSize="524288000" maxReceivedMessageSize="65536000" messageEncoding="Text" textEncoding="utf-8" useDefaultWebProxy="true" allowCookies="false"> <security mode="None" /> </binding> </basicHttpBinding> </bindings> <client /> <services> <service name="WcfServiceLibrary2.Service1"> <host> <baseAddresses> <add baseAddress="http://localhost:8732/Design_Time_Addresses/WcfServiceLibrary2/Service1/" /> </baseAddresses> </host> <!-- Service Endpoints --> <!-- Unless fully qualified, address is relative to base address supplied above --> <endpoint address="" binding="basicHttpBinding" contract="WcfServiceLibrary2.IService1"> <!-- Upon deployment, the following identity element should be removed or replaced to reflect the identity under which the deployed service runs. If removed, WCF will infer an appropriate identity automatically. --> <identity> <dns value="localhost"/> </identity> </endpoint> <!-- Metadata Endpoints --> <!-- The Metadata Exchange endpoint is used by the service to describe itself to clients. --> <!-- This endpoint does not use a secure binding and should be secured or removed before deployment --> <endpoint address="mex" binding="mexHttpBinding" contract="IMetadataExchange"/> </service> </services> <behaviors> <serviceBehaviors> <behavior> <!-- To avoid disclosing metadata information, set the value below to false and remove the metadata endpoint above before deployment --> <serviceMetadata httpGetEnabled="True"/> <!-- To receive exception details in faults for debugging purposes, set the value below to true. Set to false before deployment to avoid disclosing exception information --> <dataContractSerializer maxItemsInObjectGraph="2147483647"/> <!-- To receive exception details in faults for debugging purposes, set the value below to true. Set to false before deployment to avoid disclosing exception information --> <serviceDebug includeExceptionDetailInFaults="false" /> </behavior> </serviceBehaviors> </behaviors> </system.serviceModel> </configuration>

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  • Remote EJB lookup issue with WebSphere 6.1

    - by marc dauncey
    I've seen this question asked before, but I've tried various solutions proposed, to no avail. Essentially, I have two EJB enterprise applications, that need to communicate with one another. The first is a web application, the second is a search server - they are located on different development servers, not in the same node, cell, or JVM, although they are on the same physical box. I'm doing the JNDI lookup via IIOP, and the URL I am using is as follows: iiop://searchserver:2819 In my hosts file, I've set searchserver to 127.0.0.1. The ports for my search server are bound to this hostname too. However, when the web app (that uses Spring btw) attempts to lookup the search EJB, it fails with the following error. This is driving me nuts, surely this kind of comms between the servers should be fairly simple to get working. I've checked the ports and they are correct. I note that the exception says the initial context is H00723Node03Cell/nodes/H00723Node03/servers/server1, name: ejb/com/hmv/dataaccess/ejb/hmvsearch/HMVSearchHome. This is the web apps server NOT the search server. Is this correct? How can I get Spring to use the right context? [08/06/10 17:14:28:655 BST] 00000028 SystemErr R org.springframework.remoting.RemoteLookupFailureException: Failed to locate remote EJB [ejb/com/hmv/dataaccess/ejb/hmvsearch/HMVSearchHome]; nested exception is javax.naming.NameNotFoundException: Context: H00723Node03Cell/nodes/H00723Node03/servers/server1, name: ejb/com/hmv/dataaccess/ejb/hmvsearch/HMVSearchHome: First component in name hmvsearch/HMVSearchHome not found. [Root exception is org.omg.CosNaming.NamingContextPackage.NotFound: IDL:omg.org/CosNaming/NamingContext/NotFound:1.0] at org.springframework.ejb.access.SimpleRemoteSlsbInvokerInterceptor.doInvoke(SimpleRemoteSlsbInvokerInterceptor.java:101) at org.springframework.ejb.access.AbstractRemoteSlsbInvokerInterceptor.invoke(AbstractRemoteSlsbInvokerInterceptor.java:140) at org.springframework.aop.framework.ReflectiveMethodInvocation.proceed(ReflectiveMethodInvocation.java:171) at org.springframework.aop.framework.JdkDynamicAopProxy.invoke(JdkDynamicAopProxy.java:204) at $Proxy7.doSearchByProductKeywordsForKiosk(Unknown Source) at com.hmv.web.usecases.search.SearchUC.execute(SearchUC.java:128) at com.hmv.web.actions.search.SearchAction.executeAction(SearchAction.java:129) at com.hmv.web.actions.search.KioskSearchAction.executeAction(KioskSearchAction.java:37) at com.hmv.web.actions.HMVAbstractAction.execute(HMVAbstractAction.java:123) at org.apache.struts.action.RequestProcessor.processActionPerform(RequestProcessor.java:484) at org.apache.struts.action.RequestProcessor.process(RequestProcessor.java:274) at org.apache.struts.action.ActionServlet.process(ActionServlet.java:1482) at com.hmv.web.controller.HMVActionServlet.process(HMVActionServlet.java:149) at org.apache.struts.action.ActionServlet.doGet(ActionServlet.java:507) at javax.servlet.http.HttpServlet.service(HttpServlet.java:743) at javax.servlet.http.HttpServlet.service(HttpServlet.java:856) at com.ibm.ws.webcontainer.servlet.ServletWrapper.service(ServletWrapper.java:1282) at com.ibm.ws.webcontainer.servlet.ServletWrapper.service(ServletWrapper.java:1239) at com.ibm.ws.webcontainer.filter.WebAppFilterChain.doFilter(WebAppFilterChain.java:136) at com.hmv.web.support.SessionFilter.doFilter(SessionFilter.java:137) at com.ibm.ws.webcontainer.filter.FilterInstanceWrapper.doFilter(FilterInstanceWrapper.java:142) at com.ibm.ws.webcontainer.filter.WebAppFilterChain.doFilter(WebAppFilterChain.java:121) at com.ibm.ws.webcontainer.filter.WebAppFilterChain._doFilter(WebAppFilterChain.java:82) at com.ibm.ws.webcontainer.servlet.ServletWrapper.handleRequest(ServletWrapper.java:670) at com.ibm.ws.webcontainer.webapp.WebApp.handleRequest(WebApp.java:2933) at com.ibm.ws.webcontainer.webapp.WebGroup.handleRequest(WebGroup.java:221) at com.ibm.ws.webcontainer.VirtualHost.handleRequest(VirtualHost.java:210) at com.ibm.ws.webcontainer.WebContainer.handleRequest(WebContainer.java:1912) at com.ibm.ws.webcontainer.channel.WCChannelLink.ready(WCChannelLink.java:84) at com.ibm.ws.http.channel.inbound.impl.HttpInboundLink.handleDiscrimination(HttpInboundLink.java:472) at com.ibm.ws.http.channel.inbound.impl.HttpInboundLink.handleNewInformation(HttpInboundLink.java:411) at com.ibm.ws.http.channel.inbound.impl.HttpICLReadCallback.complete(HttpICLReadCallback.java:101) at com.ibm.ws.tcp.channel.impl.WorkQueueManager.requestComplete(WorkQueueManager.java:566) at com.ibm.ws.tcp.channel.impl.WorkQueueManager.attemptIO(WorkQueueManager.java:619) at com.ibm.ws.tcp.channel.impl.WorkQueueManager.workerRun(WorkQueueManager.java:952) at com.ibm.ws.tcp.channel.impl.WorkQueueManager$Worker.run(WorkQueueManager.java:1039) at com.ibm.ws.util.ThreadPool$Worker.run(ThreadPool.java:1462) Caused by: javax.naming.NameNotFoundException: Context: H00723Node03Cell/nodes/H00723Node03/servers/server1, name: ejb/com/hmv/dataaccess/ejb/hmvsearch/HMVSearchHome: First component in name hmvsearch/HMVSearchHome not found. [Root exception is org.omg.CosNaming.NamingContextPackage.NotFound: IDL:omg.org/CosNaming/NamingContext/NotFound:1.0] at com.ibm.ws.naming.jndicos.CNContextImpl.processNotFoundException(CNContextImpl.java:4392) at com.ibm.ws.naming.jndicos.CNContextImpl.doLookup(CNContextImpl.java:1752) at com.ibm.ws.naming.jndicos.CNContextImpl.doLookup(CNContextImpl.java:1707) at com.ibm.ws.naming.jndicos.CNContextImpl.lookupExt(CNContextImpl.java:1412) at com.ibm.ws.naming.jndicos.CNContextImpl.lookup(CNContextImpl.java:1290) at com.ibm.ws.naming.util.WsnInitCtx.lookup(WsnInitCtx.java:145) at javax.naming.InitialContext.lookup(InitialContext.java:361) at org.springframework.jndi.JndiTemplate$1.doInContext(JndiTemplate.java:132) at org.springframework.jndi.JndiTemplate.execute(JndiTemplate.java:88) at org.springframework.jndi.JndiTemplate.lookup(JndiTemplate.java:130) at org.springframework.jndi.JndiTemplate.lookup(JndiTemplate.java:155) at org.springframework.jndi.JndiLocatorSupport.lookup(JndiLocatorSupport.java:95) at org.springframework.jndi.JndiObjectLocator.lookup(JndiObjectLocator.java:105) at org.springframework.ejb.access.AbstractRemoteSlsbInvokerInterceptor.lookup(AbstractRemoteSlsbInvokerInterceptor.java:98) at org.springframework.ejb.access.AbstractSlsbInvokerInterceptor.getHome(AbstractSlsbInvokerInterceptor.java:143) at org.springframework.ejb.access.AbstractSlsbInvokerInterceptor.create(AbstractSlsbInvokerInterceptor.java:172) at org.springframework.ejb.access.AbstractRemoteSlsbInvokerInterceptor.newSessionBeanInstance(AbstractRemoteSlsbInvokerInterceptor.java:226) at org.springframework.ejb.access.SimpleRemoteSlsbInvokerInterceptor.getSessionBeanInstance(SimpleRemoteSlsbInvokerInterceptor.java:141) at org.springframework.ejb.access.SimpleRemoteSlsbInvokerInterceptor.doInvoke(SimpleRemoteSlsbInvokerInterceptor.java:97) ... 36 more Many thanks for any assistance! Marc

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  • Where can I go to learn how to read a sql server execution plan?

    - by Chris Lively
    I'm looking for resources that can teach me how to properly read a sql server execution plan. I'm a long time developer, with tons of sql server experience, but I've never really learned how to really understand what an execution plan is saying to me. I guess I'm looking for links, books, anything that can describe things like whether a clustered index scan is good or bad along with examples on how to fix issues.

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  • Trouble with site-to-site OpenVPN & pfSense not passing traffic

    - by JohnCC
    I'm trying to get an OpenVPN tunnel going on pfSense 1.2.3-RELEASE running on embedded routers. I have a local LAN 10.34.43.0/254. The remote LAN is 10.200.1.0/24. The local pfSense is configured as the client, and the remote is configured as the server. My OpenVPN tunnel is using the IP range 10.99.89.0/24 internally. There are also some additional LANs on the remote side routed through the tunnel, but the issue is not with those since my connectivity fails before that point in the chain. The tunnel comes up fine and the logs look healthy. What I find is this:- I can ping and telnet to the remote LAN and the additional remote LANs from the local pfSense box's shell. I cannot ping or telnet to any remote LANs from the local network. I cannot ping or telnet to the local network from the remote LAN or the remote pfSense box's shell. If I tcpdump the tun interfaces on both sides and ping from the local LAN, I see the packets hit the tunnel locally, but they do not appear on the remote side (nor do they appear on the remote LAN interface if I tcpdump that). If I tcpdump the tun interfaces on both sides and ping from the local pfSense shell, I see the packets hit the tunnel locally, and exit the remote side. I can also tcpdump the remote LAN interface and see them pass there too. If I tcpdump the tun interfaces on both sides and ping from the remote pfSense shell, I see the packets hit the remote tun but they do not emerge from the local one. Here is the config file the remote side is using:- #user nobody #group nobody daemon keepalive 10 60 ping-timer-rem persist-tun persist-key dev tun proto udp cipher BF-CBC up /etc/rc.filter_configure down /etc/rc.filter_configure server 10.99.89.0 255.255.255.0 client-config-dir /var/etc/openvpn_csc push "route 10.200.1.0 255.255.255.0" lport <port> route 10.34.43.0 255.255.255.0 ca /var/etc/openvpn_server0.ca cert /var/etc/openvpn_server0.cert key /var/etc/openvpn_server0.key dh /var/etc/openvpn_server0.dh comp-lzo push "route 205.217.5.128 255.255.255.224" push "route 205.217.5.64 255.255.255.224" push "route 165.193.147.128 255.255.255.224" push "route 165.193.147.32 255.255.255.240" push "route 192.168.1.16 255.255.255.240" push "route 192.168.2.16 255.255.255.240" Here is the local config:- writepid /var/run/openvpn_client0.pid #user nobody #group nobody daemon keepalive 10 60 ping-timer-rem persist-tun persist-key dev tun proto udp cipher BF-CBC up /etc/rc.filter_configure down /etc/rc.filter_configure remote <host> <port> client lport 1194 ifconfig 10.99.89.2 10.99.89.1 ca /var/etc/openvpn_client0.ca cert /var/etc/openvpn_client0.cert key /var/etc/openvpn_client0.key comp-lzo You can see the relevant parts of the routing tables extracted from pfSense here http://pastie.org/5365800 The local firewall permits all ICMP from the LAN, and my PC is allowed everything to anywhere. The remote firewall treats its LAN as trusted and permits all traffic on that interface. Can anyone suggest why this is not working, and what I could try next?

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  • Getting sync(uploading) multipale data on the remote server from iphone

    - by Ajay
    i am try to sync or upload the data on the remote server from iphone but not getting it.I try this from 1 week but didn't success how can solve this .I am using the NSURLConnection methods or any one give idea on ASIHTTPRequest method but i am new for *ASIHTTPReques*t .I need this method only .For this code like this -(void)sendRequestforContent { //this for finding the date of sync on the server NSDate* date = [NSDate date]; //Create the dateformatter object NSDateFormatter* formatter = [[[NSDateFormatter alloc] init] autorelease]; //Set the required date format [formatter setDateFormat:@"dd-MMM-yyyy"]; //Get the string date NSString* str = [formatter stringFromDate:date]; NSError *error = nil; NSHTTPURLResponse *response = nil; NSMutableData *postBody = [NSMutableData data]; NSURL *url = [NSURL URLWithString:@"http://www.google.com"]; NSMutableURLRequest *request = [NSMutableURLRequest requestWithURL:url]; NSString *boundary = @"-------------------a9d8vyb89089dy70"; NSString *contentType = [NSString stringWithFormat:@"multipart/form-data; boundary=%@", boundary]; [request setHTTPMethod:@"POST"]; [request setValue:contentType forHTTPHeaderField:@"Content-Type"]; [postBody appendData:[[NSString stringWithFormat:@"--%@\r\n", boundary] dataUsingEncoding:NSUTF8StringEncoding]]; //this is for TOKEN_API [postBody appendData:[@"Content-disposition: form-data; name=\"Token\"\r\n\r\n" dataUsingEncoding:NSUTF8StringEncoding]]; [postBody appendData:[tokenapi dataUsingEncoding:NSUTF8StringEncoding]]; [postBody appendData:[[NSString stringWithFormat:@"\r\n--%@\r\n", boundary] dataUsingEncoding:NSUTF8StringEncoding]]; //this for the CONTENT_ID [postBody appendData:[@"Content-disposition: form-data; name=\"contentID\"\r\n\r\n" dataUsingEncoding:NSUTF8StringEncoding]]; [postBody appendData:[content_id dataUsingEncoding:NSUTF8StringEncoding]]; [postBody appendData:[[NSString stringWithFormat:@"\r\n--%@\r\n", boundary] dataUsingEncoding:NSUTF8StringEncoding]]; //this for the CONTENTTYPE_ID [postBody appendData:[@"Content-disposition: form-data; name=\"contentTypeID\"\r\n\r\n" dataUsingEncoding:NSUTF8StringEncoding]]; NSString *ContentTypeString = [NSString stringWithFormat:@"%d",content_type]; [postBody appendData:[ContentTypeString dataUsingEncoding:NSUTF8StringEncoding]]; [postBody appendData:[[NSString stringWithFormat:@"\r\n--%@\r\n", boundary] dataUsingEncoding:NSUTF8StringEncoding]]; //this for the CONTENT_Location_Id [postBody appendData:[@"Content-disposition: form-data; name=\"contentLocationID\"\r\n\r\n" dataUsingEncoding:NSUTF8StringEncoding]]; [postBody appendData:[contenLocation_id dataUsingEncoding:NSUTF8StringEncoding]]; [postBody appendData:[[NSString stringWithFormat:@"\r\n--%@\r\n", boundary] dataUsingEncoding:NSUTF8StringEncoding]]; //this is for the User_Caption [postBody appendData:[@"Content-disposition: form-data; name=\"userCaption\"\r\n\r\n" dataUsingEncoding:NSUTF8StringEncoding]]; [postBody appendData:[user_caption dataUsingEncoding:NSUTF8StringEncoding]]; [postBody appendData:[[NSString stringWithFormat:@"\r\n--%@\r\n", boundary] dataUsingEncoding:NSUTF8StringEncoding]]; //this is for the User_Comment [postBody appendData:[@"Content-disposition: form-data; name=\"userComment\"\r\n\r\n" dataUsingEncoding:NSUTF8StringEncoding]]; [postBody appendData:[user_comment dataUsingEncoding:NSUTF8StringEncoding]]; [postBody appendData:[[NSString stringWithFormat:@"\r\n--%@\r\n", boundary] dataUsingEncoding:NSUTF8StringEncoding]]; //this for the Tags [postBody appendData:[@"Content-disposition: form-data; name=\"tags\"\r\n\r\n" dataUsingEncoding:NSUTF8StringEncoding]]; [postBody appendData:[tag dataUsingEncoding:NSUTF8StringEncoding]]; [postBody appendData:[[NSString stringWithFormat:@"\r\n--%@\r\n", boundary] dataUsingEncoding:NSUTF8StringEncoding]]; //this for the Date_Record [postBody appendData:[@"Content-disposition: form-data; name=\"dateRecorded\"\r\n\r\n" dataUsingEncoding:NSUTF8StringEncoding]]; [postBody appendData:[date_recorded dataUsingEncoding:NSUTF8StringEncoding]]; [postBody appendData:[[NSString stringWithFormat:@"\r\n--%@\r\n", boundary] dataUsingEncoding:NSUTF8StringEncoding]]; //this for the image_data [postBody appendData:[[NSString stringWithFormat:@"Content-disposition: form-data; name=\"image_file\"; filename=\"%@\"\r\n",@"image.jpg"] dataUsingEncoding:NSUTF8StringEncoding]]; [postBody appendData:[@"Content-Type: image/jpg\r\n\r\n" dataUsingEncoding:NSUTF8StringEncoding]]; [postBody appendData:image]; [postBody appendData:[[NSString stringWithFormat:@"\r\n--%@--\r\n",boundary] dataUsingEncoding:NSUTF8StringEncoding]]; //this for the Share_type [postBody appendData:[@"Content-disposition: form-data; name=\"shareType\"\r\n\r\n" dataUsingEncoding:NSUTF8StringEncoding]]; NSString *ShareString = [NSString stringWithFormat:@"%d",share_type]; [postBody appendData:[ShareString dataUsingEncoding:NSUTF8StringEncoding]]; [postBody appendData:[[NSString stringWithFormat:@"\r\n--%@\r\n", boundary] dataUsingEncoding:NSUTF8StringEncoding]]; //this for the Views [postBody appendData:[@"Content-disposition: form-data; name=\"views\"\r\n\r\n" dataUsingEncoding:NSUTF8StringEncoding]]; NSString *ViewsString = [NSString stringWithFormat:@"%d",views]; [postBody appendData:[ViewsString dataUsingEncoding:NSUTF8StringEncoding]]; [postBody appendData:[[NSString stringWithFormat:@"\r\n--%@\r\n", boundary] dataUsingEncoding:NSUTF8StringEncoding]]; //this for the PLAY_time [postBody appendData:[@"Content-disposition: form-data; name=\"playTime\"\r\n\r\n" dataUsingEncoding:NSUTF8StringEncoding]]; NSString *TimeString = [NSString stringWithFormat:@"%d",play_time]; [postBody appendData:[TimeString dataUsingEncoding:NSUTF8StringEncoding]]; [postBody appendData:[[NSString stringWithFormat:@"\r\n--%@\r\n", boundary] dataUsingEncoding:NSUTF8StringEncoding]]; //this for the Posted_By [postBody appendData:[@"Content-disposition: form-data; name=\"postedBy\"\r\n\r\n" dataUsingEncoding:NSUTF8StringEncoding]]; [postBody appendData:[postred_by dataUsingEncoding:NSUTF8StringEncoding]]; //this for the AVG_Rating [postBody appendData:[[NSString stringWithFormat:@"\r\n--%@\r\n", boundary] dataUsingEncoding:NSUTF8StringEncoding]]; [postBody appendData:[@"Content-disposition: form-data; name=\"avgRating\"\r\n\r\n" dataUsingEncoding:NSUTF8StringEncoding]]; NSString *AvgString = [NSString stringWithFormat:@"%d",avg_rating]; [postBody appendData:[AvgString dataUsingEncoding:NSUTF8StringEncoding]]; [postBody appendData:[[NSString stringWithFormat:@"\r\n--%@\r\n", boundary] dataUsingEncoding:NSUTF8StringEncoding]]; [postBody appendData:[@"Content-disposition: form-data; name=\"LastSyncDate\"\r\n\r\n" dataUsingEncoding:NSUTF8StringEncoding]]; [postBody appendData:[str dataUsingEncoding:NSUTF8StringEncoding]]; [postBody appendData:[[NSString stringWithFormat:@"\r\n--%@\r\n", boundary] dataUsingEncoding:NSUTF8StringEncoding]]; [request setHTTPBody:postBody]; NSData *shoutData = [NSURLConnection sendSynchronousRequest:request returningResponse:&response error:&error]; NSString *returnString = [[NSString alloc] initWithData:shoutData encoding:NSUTF8StringEncoding]; NSLog(@"%@",returnString); } it is not going into the this mthods -(void)connectionDidFinishLoading:(NSURLConnection *)connection { loginStatus = [[NSString alloc] initWithBytes: [webData mutableBytes] length:[webData length] encoding:NSUTF8StringEncoding]; NSLog(@"%@",loginStatus); } It show me html page on console I hope people help me to solve it out

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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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  • How do I convert some ugly inline javascript into a function?

    - by Taylor
    I've got a form with various inputs that by default have no value. When a user changes one or more of the inputs all values including the blank ones are used in the URL GET string when submitted. So to clean it up I've got some javascript that removes the inputs before submission. It works well enough but I was wondering how to put this in a js function or tidy it up. Seems a bit messy to have it all clumped in to an onclick. Plus i'm going to be adding more so there will be quite a few. Here's the relevant code. There are 3 seperate lines for 3 seperate inputs. The first part of the line has a value that refers to the inputs ID ("mf","cf","bf","pf") and the second part of the line refers to the parent div ("dmf","dcf", etc). The first part is an example of the input structure... echo "<div id='dmf'><select id='mf' name='mFilter'>"; This part is the submit and js... echo "<input type='submit' value='Apply' onclick='javascript: if (document.getElementById(\"mf\").value==\"\") { document.getElementById(\"dmf\").innerHTML=\"\"; } if (document.getElementById(\"cf\").value==\"\") { document.getElementById(\"dcf\").innerHTML=\"\"; } if (document.getElementById(\"bf\").value==\"\") { document.getElementById(\"dbf\").innerHTML=\"\"; } if (document.getElementById(\"pf\").value==\"\") { document.getElementById(\"dpf\").innerHTML=\"\"; } ' />"; I have pretty much zero javascript knowledge so help turning this in to a neater function or similar would be much appreciated.

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  • How do I pass credentials to a machine so I can use Microsoft.Win32.RegistryKey.OpenRemoteBaseKey()

    - by JCCyC
    This .NET API works OK if I'm trying to open the Registry in a machine that's in the same domain as I am (and my logged-on user has admin rights on the target machine). It gets tricky if it's an out-of-domain machine with a different, local administrative user (of whom I do have the password). I tried to use WNetUseConnection() (which has served me well in the past in situations where what I wanted was to read a remote disk file) prior to calling OpenRemoteBaseKey(), but no dice -- I get an access denied exception. Clearly, I must pass credentials some other way, but how?

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  • Why does the interpreted order seem different from what I expect?

    - by inspectorG4dget
    I have a problem that I have not faced before: It seems that the order of interpretation in my program is somehow different from what I expect. I have written a small Twitter client. It takes a few seconds for my program to actually post a tweet after I click the "GO" button (which can also be activated by hitting ENTER on the keyboard). I don't want to click multiple times within this time period thinking that I hadn't clicked it the first time. Therefore, when the button is clicked, I would like the label text to display something that tells me that the button has been clicked. I have implemented this message by altering the label text before I send the tweet across. However, for some reason, the message does not display until the tweet has been attempted. But since I have a confirmation message after the tweet, I never get to see this message and my original problem goes unsolved. I would really appreciate any help. Here is the relevant code: class SimpleTextBoxForm(Form): def __init__(self): # set window properties self.Text = "Tweeter" self.Width = 235 self.Height = 250 #tweet away self.label = Label() self.label.Text = "Tweet Away..." self.label.Location = Point(10, 10) self.label.Height = 25 self.label.Width = 200 #get the tweet self.tweetBox = TextBox() self.tweetBox.Location = Point(10, 45) self.tweetBox.Width = 200 self.tweetBox.Height = 60 self.tweetBox.Multiline = True self.tweetBox.WordWrap = True self.tweetBox.MaxLength = 140; #ask for the login ID self.askLogin = Label() self.askLogin.Text = "Login:" self.askLogin.Location = Point(10, 120) self.askLogin.Height = 20 self.askLogin.Width = 60 self.login = TextBox() self.login.Text= "" self.login.Location = Point(80, 120) self.login.Height = 40 self.login.Width = 100 #ask for the password self.askPass = Label() self.askPass.Text = "Password:" self.askPass.Location = Point(10, 150) self.askPass.Height = 20 self.askPass.Width = 60 # display password box with character hiding self.password = TextBox() self.password.Location = Point(80, 150) self.password.PasswordChar = "x" self.password.Height = 40 self.password.Width = 100 #submit button self.button1 = Button() self.button1.Text = 'Tweet' self.button1.Location = Point(10, 180) self.button1.Click += self.update self.AcceptButton = self.button1 #pack all the elements of the form self.Controls.Add(self.label) self.Controls.Add(self.tweetBox) self.Controls.Add(self.askLogin) self.Controls.Add(self.login) self.Controls.Add(self.askPass) self.Controls.Add(self.password) self.Controls.Add(self.button1) def update(self, sender, event): if not self.password.Text: self.label.Text = "You forgot to enter your password..." else: self.tweet(self.tweetBox.Text, self.login.Text, self.password.Text) def tweet(self, msg, login, password): self.label.Text = "Attempting Tweet..." # this should be executed before sending the tweet is attempted. But this seems to be executed only after the try block try: success = 'Tweet successfully completed... yay!\n' + 'At: ' + time.asctime().split()[3] ServicePointManager.Expect100Continue = False Twitter().UpdateAsXML(login, password, msg) except: error = 'Unhandled Exception. Tweet unsuccessful' self.label.Text = error else: self.label.Text = success self.tweetBox.Text = ""

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  • Why does the interpretted order seem different from what I expect?

    - by inspectorG4dget
    I have a problem that I have not faced before: It seems that the order of interpretation in my program is somehow different from what I expect. I have written a small Twitter client. It takes a few seconds for my program to actually post a tweet after I click the "GO" button (which can also be activated by hitting ENTER on the keyboard). I don't want to click multiple times within this time period thinking that I hadn't clicked it the first time. Therefore, when the button is clicked, I would like the label text to display something that tells me that the button has been clicked. I have implemented this message by altering the label text before I send the tweet across. However, for some reason, the message does not display until the tweet has been attempted. But since I have a confirmation message after the tweet, I never get to see this message and my original problem goes unsolved. I would really appreciate any help. Here is the relevant code: class SimpleTextBoxForm(Form): def init(self): # set window properties self.Text = "Tweeter" self.Width = 235 self.Height = 250 #tweet away self.label = Label() self.label.Text = "Tweet Away..." self.label.Location = Point(10, 10) self.label.Height = 25 self.label.Width = 200 #get the tweet self.tweetBox = TextBox() self.tweetBox.Location = Point(10, 45) self.tweetBox.Width = 200 self.tweetBox.Height = 60 self.tweetBox.Multiline = True self.tweetBox.WordWrap = True self.tweetBox.MaxLength = 140; #ask for the login ID self.askLogin = Label() self.askLogin.Text = "Login:" self.askLogin.Location = Point(10, 120) self.askLogin.Height = 20 self.askLogin.Width = 60 self.login = TextBox() self.login.Text= "" self.login.Location = Point(80, 120) self.login.Height = 40 self.login.Width = 100 #ask for the password self.askPass = Label() self.askPass.Text = "Password:" self.askPass.Location = Point(10, 150) self.askPass.Height = 20 self.askPass.Width = 60 # display password box with character hiding self.password = TextBox() self.password.Location = Point(80, 150) self.password.PasswordChar = "x" self.password.Height = 40 self.password.Width = 100 #submit button self.button1 = Button() self.button1.Text = 'Tweet' self.button1.Location = Point(10, 180) self.button1.Click += self.update self.AcceptButton = self.button1 #pack all the elements of the form self.Controls.Add(self.label) self.Controls.Add(self.tweetBox) self.Controls.Add(self.askLogin) self.Controls.Add(self.login) self.Controls.Add(self.askPass) self.Controls.Add(self.password) self.Controls.Add(self.button1) def update(self, sender, event): if not self.password.Text: self.label.Text = "You forgot to enter your password..." else: self.tweet(self.tweetBox.Text, self.login.Text, self.password.Text) def tweet(self, msg, login, password): self.label.Text = "Attempting Tweet..." # this should be executed before sending the tweet is attempted. But this seems to be executed only after the try block try: success = 'Tweet successfully completed... yay!\n' + 'At: ' + time.asctime().split()[3] ServicePointManager.Expect100Continue = False Twitter().UpdateAsXML(login, password, msg) except: error = 'Unhandled Exception. Tweet unsuccessful' self.label.Text = error else: self.label.Text = success self.tweetBox.Text = ""

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