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• Hibernate Lazy init exception in spring scheduled job

  - by Noam Nevo

  I have a spring scheduled job (@Scheduled) that sends emails from my system according to a list of recipients in the DB. This method is annotated with the @Scheduled annotation and it invokes a method from another interface, the method in the interface is annotated with the @Transactional annotation. Now, when i invoke the scheduled method manually, it works perfectly. But when the method is invoked by spring scheduler i get the LazyInitFailed exception in the method implementing the said interface. What am I doing wrong? code: The scheduled method: @Component public class ScheduledReportsSender { public static final int MAX_RETIRES = 3; public static final long HALF_HOUR = 1000 * 60 * 30; @Autowired IScheduledReportDAO scheduledReportDAO; @Autowired IDataService dataService; @Autowired IErrorService errorService; @Scheduled(cron = "0 0 3 ? * *") // every day at 2:10AM public void runDailyReports() { // get all daily reports List<ScheduledReport> scheduledReports = scheduledReportDAO.getDaily(); sendScheduledReports(scheduledReports); } private void sendScheduledReports(List<ScheduledReport> scheduledReports) { if(scheduledReports.size()<1) { return; } //check if data flow ended its process by checking the report_last_updated table in dwh int reportTimeId = scheduledReportDAO.getReportTimeId(); String todayTimeId = DateUtils.getTimeid(DateUtils.getTodayDate()); int yesterdayTimeId = Integer.parseInt(DateUtils.addDaysSafe(todayTimeId, -1)); int counter = 0; //wait for time id to update from the daily flow while (reportTimeId != yesterdayTimeId && counter < MAX_RETIRES) { errorService.logException("Daily report sender, data not ready. Will try again in one hour.", null, null, null); try { Thread.sleep(HALF_HOUR); } catch (InterruptedException ignore) {} reportTimeId = scheduledReportDAO.getReportTimeId(); counter++; } if (counter == MAX_RETIRES) { MarketplaceServiceException mse = new MarketplaceServiceException(); mse.setMessage("Data flow not done for today, reports are not sent."); throw mse; } // get updated timeid updateTimeId(); for (ScheduledReport scheduledReport : scheduledReports) { dataService.generateScheduledReport(scheduledReport); } } } The Invoked interface: public interface IDataService { @Transactional public void generateScheduledReport(ScheduledReport scheduledReport); } The implementation (up to the line of the exception): @Service public class DataService implements IDataService { public void generateScheduledReport(ScheduledReport scheduledReport) { // if no recipients or no export type - return if(scheduledReport.getRecipients()==null || scheduledReport.getRecipients().size()==0 || scheduledReport.getExportType() == null) { return; } } } Stack trace: ERROR: 2012-09-01 03:30:00,365 [Scheduler-15] LazyInitializationException.<init>(42) | failed to lazily initialize a collection of role: com.x.model.scheduledReports.ScheduledReport.recipients, no session or session was closed org.hibernate.LazyInitializationException: failed to lazily initialize a collection of role: com.x.model.scheduledReports.ScheduledReport.recipients, no session or session was closed at org.hibernate.collection.AbstractPersistentCollection.throwLazyInitializationException(AbstractPersistentCollection.java:383) at org.hibernate.collection.AbstractPersistentCollection.throwLazyInitializationExceptionIfNotConnected(AbstractPersistentCollection.java:375) at org.hibernate.collection.AbstractPersistentCollection.readSize(AbstractPersistentCollection.java:122) at org.hibernate.collection.PersistentBag.size(PersistentBag.java:248) at com.x.service.DataService.generateScheduledReport(DataService.java:219) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.lang.reflect.Method.invoke(Method.java:616) at org.springframework.aop.support.AopUtils.invokeJoinpointUsingReflection(AopUtils.java:309) at org.springframework.aop.framework.ReflectiveMethodInvocation.invokeJoinpoint(ReflectiveMethodInvocation.java:183) at org.springframework.aop.framework.ReflectiveMethodInvocation.proceed(ReflectiveMethodInvocation.java:150) at org.springframework.transaction.interceptor.TransactionInterceptor.invoke(TransactionInterceptor.java:110) at org.springframework.aop.framework.ReflectiveMethodInvocation.proceed(ReflectiveMethodInvocation.java:172) at org.springframework.aop.framework.JdkDynamicAopProxy.invoke(JdkDynamicAopProxy.java:202) at $Proxy208.generateScheduledReport(Unknown Source) at com.x.scheduledJobs.ScheduledReportsSender.sendScheduledReports(ScheduledReportsSender.java:85) at com.x.scheduledJobs.ScheduledReportsSender.runDailyReports(ScheduledReportsSender.java:38) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.lang.reflect.Method.invoke(Method.java:616) at org.springframework.util.MethodInvoker.invoke(MethodInvoker.java:273) at org.springframework.scheduling.support.MethodInvokingRunnable.run(MethodInvokingRunnable.java:65) at org.springframework.scheduling.support.DelegatingErrorHandlingRunnable.run(DelegatingErrorHandlingRunnable.java:51) at org.springframework.scheduling.concurrent.ReschedulingRunnable.run(ReschedulingRunnable.java:81) at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:471) at java.util.concurrent.FutureTask$Sync.innerRun(FutureTask.java:334) at java.util.concurrent.FutureTask.run(FutureTask.java:166) at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$101(ScheduledThreadPoolExecutor.java:165) at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:266) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1110) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:603) at java.lang.Thread.run(Thread.java:636) ERROR: 2012-09-01 03:30:00,366 [Scheduler-15] MethodInvokingRunnable.run(68) | Invocation of method 'runDailyReports' on target class [class com.x.scheduledJobs.ScheduledReportsSender] failed org.hibernate.LazyInitializationException: failed to lazily initialize a collection of role: com.x.model.scheduledReports.ScheduledReport.recipients, no session or session was closed at org.hibernate.collection.AbstractPersistentCollection.throwLazyInitializationException(AbstractPersistentCollection.java:383) at org.hibernate.collection.AbstractPersistentCollection.throwLazyInitializationExceptionIfNotConnected(AbstractPersistentCollection.java:375) at org.hibernate.collection.AbstractPersistentCollection.readSize(AbstractPersistentCollection.java:122) at org.hibernate.collection.PersistentBag.size(PersistentBag.java:248) at com.x.service.DataService.generateScheduledReport(DataService.java:219) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.lang.reflect.Method.invoke(Method.java:616) at org.springframework.aop.support.AopUtils.invokeJoinpointUsingReflection(AopUtils.java:309) at org.springframework.aop.framework.ReflectiveMethodInvocation.invokeJoinpoint(ReflectiveMethodInvocation.java:183) at org.springframework.aop.framework.ReflectiveMethodInvocation.proceed(ReflectiveMethodInvocation.java:150) at org.springframework.transaction.interceptor.TransactionInterceptor.invoke(TransactionInterceptor.java:110) at org.springframework.aop.framework.ReflectiveMethodInvocation.proceed(ReflectiveMethodInvocation.java:172) at org.springframework.aop.framework.JdkDynamicAopProxy.invoke(JdkDynamicAopProxy.java:202) at $Proxy208.generateScheduledReport(Unknown Source) at com.x.scheduledJobs.ScheduledReportsSender.sendScheduledReports(ScheduledReportsSender.java:85) at com.x.scheduledJobs.ScheduledReportsSender.runDailyReports(ScheduledReportsSender.java:38) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.lang.reflect.Method.invoke(Method.java:616) at org.springframework.util.MethodInvoker.invoke(MethodInvoker.java:273) at org.springframework.scheduling.support.MethodInvokingRunnable.run(MethodInvokingRunnable.java:65) at org.springframework.scheduling.support.DelegatingErrorHandlingRunnable.run(DelegatingErrorHandlingRunnable.java:51) at org.springframework.scheduling.concurrent.ReschedulingRunnable.run(ReschedulingRunnable.java:81) at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:471) at java.util.concurrent.FutureTask$Sync.innerRun(FutureTask.java:334) at java.util.concurrent.FutureTask.run(FutureTask.java:166) at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$101(ScheduledThreadPoolExecutor.java:165) at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:266) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1110) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:603) at java.lang.Thread.run(Thread.java:636)

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• ExecutorService that interrupts tasks after a timeout

  - by scompt.com

  I'm looking for an ExecutorService implementation that can be provided with a timeout. Tasks that are submitted to the ExecutorService are interrupted if they take longer than the timeout to run. Implementing such a beast isn't such a difficult task, but I'm wondering if anybody knows of an existing implementation.

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• Efficient algorithm to distribute work?

  - by Zwei Steinen

  It's a bit complicated to explain but here we go. We have problems like this (code is pseudo-code, and is only for illustrating the problem. Sorry it's in java. If you don't understand, I'd be glad to explain.). class Problem { final Set<Integer> allSectionIds = { 1,2,4,6,7,8,10 }; final Data data = //Some data } And a subproblem is: class SubProblem { final Set<Integer> targetedSectionIds; final Data data; SubProblem(Set<Integer> targetedSectionsIds, Data data){ this.targetedSectionIds = targetedSectionIds; this.data = data; } } Work will look like this, then. class Work implements Runnable { final Set<Section> subSections; final Data data; final Result result; Work(Set<Section> subSections, Data data) { this.sections = SubSections; this.data = data; } @Override public void run(){ for(Section section : subSections){ result.addUp(compute(data, section)); } } } Now we have instances of 'Worker', that have their own state sections I have. class Worker implements ExecutorService { final Map<Integer,Section> sectionsIHave; { sectionsIHave = {1:section1, 5:section5, 8:section8 }; } final ExecutorService executor = //some executor. @Override public void execute(SubProblem problem){ Set<Section> sectionsNeeded = fetchSections(problem.targetedSectionIds); super.execute(new Work(sectionsNeeded, problem.data); } } phew. So, we have a lot of Problems and Workers are constantly asking for more SubProblems. My task is to break up Problems into SubProblem and give it to them. The difficulty is however, that I have to later collect all the results for the SubProblems and merge (reduce) them into a Result for the whole Problem. This is however, costly, so I want to give the workers "chunks" that are as big as possible (has as many targetedSections as possible). It doesn't have to be perfect (mathematically as efficient as possible or something). I mean, I guess that it is impossible to have a perfect solution, because you can't predict how long each computation will take, etc.. But is there a good heuristic solution for this? Or maybe some resources I can read up before I go into designing? Any advice is highly appreciated!

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• Problem with "write" function in linux

  - by Dumitru Catalin

  I am trying to write 2 server/client programs under Linux, in which they communicate through named pipes. The problem is that sometimes when I try to write from the server into a pipe that doesn't exist anymore (the client has stopped), I get a "Resource temporarily unavailable" error and the server stops completely. I understand that this is caused by using a O_NONBLOCK parameter when opening the fifo chanel, indicating the point where the program would usually wait until it could write again in the file, but is there a way to stop this behavior, and not halt the entire program if a problem occurs (shouldn't the write command return -1 ad the program continue normally)? And another strange thing is that this error only occurs when running the programs outside the ide (eclipse). If I run both programs inside eclipse, on error the write function just returns -1 and the programs continues normally.

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• Java Executor: Small tasks or big ones?

  - by Arash Shahkar

  Consider one big task which could be broken into hundreds of small, independently-runnable tasks. To be more specific, each small task is to send a light network request and decide upon the answer received from the server. These small tasks are not expected to take longer than a second, and involve a few servers in total. I have in mind two approaches to implement this using the Executor framework, and I want to know which one's better and why. Create a few, say 5 to 10 tasks each involving doing a bunch of send and receives. Create a single task (Callable or Runnable) for each send & receive and schedule all of them (hundreds) to be run by the executor. I'm sorry if my question shows that I'm lazy to test these and see for myself what's better (at least performance-wise). My question, while looking after an answer to this specific case, has a more general aspect. In situations like these when you want to use an executor to do all the scheduling and other stuff, is it better to create lots of small tasks or to group those into a less number of bigger tasks?

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• ScheduledThreadPoolExecutor executing a wrong time because of CPU time discrepancy

  - by richs

  I'm scheduling a task using a ScheduledThreadPoolExecutor object. I use the following method: public ScheduledFuture<?> schedule(Runnable command, long delay,TimeUnit unit) and set the delay to 30 seconds (delay = 30,000 and unit=TimeUnit.MILLISECONDS). Sometimes my task occurs immediately and other times it takes 70 seconds. I believe the ScheduledThreadPoolExecutor uses CPU specific clocks. When i run tests comparing System.currentTimeMillis(), System.nanoTime() [which is CPU specific] i see the following schedule: 1272637682651ms, 7858346157228410ns execute: 1272637682667ms, 7858386270968425ns difference is 16ms but 4011374001ns (or 40,113ms) so it looks like there is discrepancy between two CPU clocks of 40 seconds How do i resolve this issue in java code? Unfortunately this is a clients machine and i can't modify their system.

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• Invalid Cross-Thread Operations from BackgroundWorker2_RunWorkerCompleted in C#

  - by Jim Fell

  Hello. I'm getting an error that does not make sense. Cross-thread operation not valid: Control 'buttonOpenFile' accessed from a thread other than the thread it was created on. In my application, the UI thread fires off backgroundWorker1, which when almost complete fires off backgroundWorker2 and waits for it to complete. backgroundWorker1 waits for backgroundWorker2 to complete, before it completes. AutoResetEvent variables are used to flag when each of the workers complete. In backgroundWorker2_RunWorkerComplete a function is called that resets the form controls. It is in this ResetFormControls() function where the exception is thrown. I thought it was safe to modify form controls in the RunWorkerCompleted function. Both background workers are instantiated from the UI thread. Here is a greatly summarized version of what I am doing: AutoResetEvent evtProgrammingComplete_c = new AutoResetEvent(false); AutoResetEvent evtResetComplete_c = new AutoResetEvent(false); private void ResetFormControls() { toolStripProgressBar1.Enabled = false; toolStripProgressBar1.RightToLeftLayout = false; toolStripProgressBar1.Value = 0; buttonInit.Enabled = true; buttonOpenFile.Enabled = true; // Error occurs here. buttonProgram.Enabled = true; buttonAbort.Enabled = false; buttonReset.Enabled = true; checkBoxPeripheryModule.Enabled = true; checkBoxVerbose.Enabled = true; comboBoxComPort.Enabled = true; groupBoxToolSettings.Enabled = true; groupBoxNodeSettings.Enabled = true; } private void buttonProgram_Click(object sender, EventArgs e) { while (backgroundWorkerProgram.IsBusy) backgroundWorkerProgram.CancelAsync(); backgroundWorkerProgram.RunWorkerAsync(); } private void backgroundWorkerProgram_DoWork(object sender, DoWorkEventArgs e) { // Does a bunch of stuff... if (tProgramStat_c == eProgramStat_t.DONE) { tProgramStat_c = eProgramStat_t.RESETTING; while (backgroundWorkerReset.IsBusy) backgroundWorkerReset.CancelAsync(); backgroundWorkerReset.RunWorkerAsync(); evtResetComplete_c.WaitOne(LONG_ACK_WAIT * 2); if (tResetStat_c == eResetStat_t.COMPLETED) tProgramStat_c = eProgramStat_t.DONE; } } private void backgroundWorkerProgram_RunWorkerCompleted(object sender, RunWorkerCompletedEventArgs e) { // Updates form to report complete. No problems here. evtProgrammingComplete_c.Set(); backgroundWorkerProgram.Dispose(); } private void backgroundWorkerReset_DoWork(object sender, DoWorkEventArgs e) { // Does a bunch of stuff... if (tResetStat_c == eResetStat_t.COMPLETED) if (tProgramStat_c == eProgramStat_t.RESETTING) evtProgrammingComplete_c.WaitOne(); } private void backgroundWorkerReset_RunWorkerCompleted(object sender, RunWorkerCompletedEventArgs e) { CloseAllComms(); ResetFormControls(); evtResetComplete_c.Set(); backgroundWorkerReset.Dispose(); } Any thoughts or suggestions you may have would be appreciated. I am using Microsoft Visual C# 2008 Express Edition. Thanks.

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• Multiple java versions running concurrently under Windows

  - by Daniel Stanca

  We have a couple of applications running on Java 5 and would like now to bring in an application based on Java 6. Can both java versions live together under Windows? Is there any control panel to set the appropiate java version for different applications?

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• ArrayBlockingQueue exceeds given capacity

  - by Wojciech Reszelewski

  I've written program solving bounded producer & consumer problem. While constructing ArrayBlockingQueue I defined capacity 100. I'm using methods take and put inside threads. And I've noticed that sometimes I see put 102 times with any take's between them. Why does it happen? Producer run method: public void run() { Object e = new Object(); while(true) { try { queue.put(e); } catch (InterruptedException w) { System.out.println("Oj, nie wyszlo, nie bij"); } System.out.println("Element added"); } } Consumer run method: public void run() { while(true) { try { queue.take(); } catch (InterruptedException e) { e.printStackTrace(); } System.out.println("Element removed"); } } Part of uniq -c on file with output: 102 Element removed 102 Element added 102 Element removed 102 Element added 102 Element removed 102 Element added 102 Element removed 102 Element added 102 Element removed 102 Element added 102 Element removed 102 Element added 2 Element removed 2 Element added 102 Element removed 102 Element added

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• Find messages from certain key till certain key while being able to remove stale keys.

  - by Alfred

  My problem Let's say I add messages to some sort of datastructure: 1. "dude" 2. "where" 3. "is" 4. "my" 5. "car" Asking for messages from index[4,5] should return: "my","car". Next let's assume that after a while I would like to purge old messages because they aren't useful anymore and I want to save memory. Let's say at time x messages[1-3] became stale. I assume that it would be most efficient to just do the deletion once every x seconds. Next my datastructure should contain: 4. "my" 5. "car" My solution? I was thinking of using a concurrentskiplistset or concurrentskiplist map. Also I was thinking of deleting the old messages from inside a newSingleThreadScheduledExecutor. I would like to know how you would implement(efficiently/thread-safe) this or maybe use a library?

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• Long primitive or AtomicLong for a counter?

  - by Rich

  Hi I have a need for a counter of type long with the following requirements/facts: Incrementing the counter should take as little time as possible. The counter will only be written to by one thread. Reading from the counter will be done in another thread. The counter will be incremented regularly (as much as a few thousand times per second), but will only be read once every five seconds. Precise accuracy isn't essential, only a rough idea of the size of the counter is good enough. The counter is never cleared, decremented. Based upon these requirements, how would you choose to implement your counter? As a simple long, as a volatile long or using an AtomicLong? Why? At the moment I have a volatile long but was wondering whether another approach would be better. I am also incrementing my long by doing ++counter as opposed to counter++. Is this really any more efficient (as I have been led to believe elsewhere) because there is no assignment being done? Thanks in advance Rich

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• Benchmarks for Single and MultiThreaded programs

  - by user280848

  Hi I am trying to compare the performance of Single and Multithreaded Java programs. Are there any single thread benchmarks which are available which I could then use and convert to their multithreaded version and compare the performance. Could anybody guide me as to what kind of programs(not very small) are suitable for this empirical comparison. Thanks in advance

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• Why thread started by ScheduledExecutorService.schedule() never quits?

  - by moonese

  If I create a scheduled task by calling ScheduledExecutorService.schedule(), it never quits after execution, is it a JDK bug, or I just miss something? note: doSomething() is empty method below. public static void doSomething() { } public static void main(String[] args) { ScheduledFuture scheduleFuture = Executors.newSingleThreadScheduledExecutor().schedule(new Callable() { public Void call() { try { doSomething(); } catch (Exception e) { e.printStackTrace(); } return null; } }, 1, TimeUnit.SECONDS); }

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• Java Thread wait() => blocked?

  - by Chris

  According to http://java.sun.com/j2se/1.5.0/docs/api/java/lang/Thread.State.html calling wait() will result a thread to go in BLOCKED state. However this piece of code will result (after being called) in a Thread in WAITING State. class bThread extends Thread { public synchronized void run() { try { wait(); } catch (InterruptedException e) { e.printStackTrace(); } } } Have I got something wrong? Can anybody explain this behaviour to me? Any help would be appreciated!

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• Box.com file sharing - How are you managing concurrent document access and file locks? [closed]

  - by Matt

  My company is evaluating Box.com as a file server replacement. It's file locking behavior for concurrent access to files seems incomplete. Specifically, files are not locked* (either exclusive or read-only) when they are being edited by Office or similar programs. This inevitably results in multiple versions of documents as concurrent access results in change conflicts. *The exception is when the file is edited using Zoho Docs - perhaps other web-based office suites as well. Box provides multiple options for editing documents, including Google Docs, a local copy of Office or similar, Zoho Docs and others. If you are using Box how have you managed or worked around this behavior?

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• What to do for a 1 million concurrent web application? [duplicate]

  - by Amit Singh

  This question already has an answer here: How do you do load testing and capacity planning for web sites? 3 answers There are few things that I would like to know here. What server configuration do I need. And if I am deploying it on EC2 how many VMs do I need and what should be their configuration. What options do I have to do a load testing for 1 million concurrent users. Any pointer to (for php) how to code or what to keep in mind for such application. This is for sure that I don't exactly know what to ask because this is my first application on this scale. But one thing is clear that this application should pass a load test of 1 million concurrent request.

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• What is a fairly accepted endpoints to concurrent calls ratio for a PBX?

  - by Logan Bibby

  Hey guys! Not too positive about the relevance of this question to Server Fault, but I'll let you guys poke around at it anyway. :) I'm trying to figure out what an accepted ratio of endpoints to concurrent calls on the "average" office PBX. I'm defining concurrent calls as any call being placed, including internal calls. I'm not going to be considering call centers into this ratio, I'll be looking at those differently, anyway. To give you guys a little history behind the question: I need this ratio to be able to figure out decent specs for a virtual PBX service I'm going to be rolling out within the upcoming months. The ratio will determine the number of trunks needed per PBX system. -- Logan

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• Is FreeBSD better than CentOS for firing 40k concurrent connections (for Jmeter)?

  - by blacklotus

  Hi, I am trying to run Jmeter to simulate 40k concurrent users and stress test a particular system. Putting aside the possibility that Jmeter may not be able to push such a high number (although I have read that it is at least possible to handle 10k concurrent threads on a very powerful machine), is FreeBSD a better OS as compare to CentOS to be used for my Jmeter machine? Reason for asking this is that, I have found articles on FreeBSD for tuning and optimizing for maximum outbound connections, but seem to have little luck with CentOS. Personally however, I am more familiar with CentOS and would like to stick with it if possible. Any input is greatly appreciated!

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• how many concurrent user can login to silverlight application?

  - by chinnayya

  Hi, I am newbie in silver light. Can any one tell me how many concurrent users can have in silverlight application? ANd also what happes to the aplication if we have more than 500 concurrent users? Regards Chinnayya

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• way to fix number of concurrent sessions allowed at app level. django

  - by laspal

  Hi, How can I fix number of concurrent sessions allowed at app level? Basically I want a limit to how many concurrent requests to this url to keep the server from getting congested. I guess some middleware hack? Thanks.

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• C#/.NET Little Wonders: The ConcurrentDictionary

  - by James Michael Hare

  Once again we consider some of the lesser known classes and keywords of C#.  In this series of posts, we will discuss how the concurrent collections have been developed to help alleviate these multi-threading concerns.  Last week’s post began with a general introduction and discussed the ConcurrentStack<T> and ConcurrentQueue<T>.  Today's post discusses the ConcurrentDictionary<T> (originally I had intended to discuss ConcurrentBag this week as well, but ConcurrentDictionary had enough information to create a very full post on its own!).  Finally next week, we shall close with a discussion of the ConcurrentBag<T> and BlockingCollection<T>. For more of the "Little Wonders" posts, see the index here. Recap As you'll recall from the previous post, the original collections were object-based containers that accomplished synchronization through a Synchronized member.  While these were convenient because you didn't have to worry about writing your own synchronization logic, they were a bit too finely grained and if you needed to perform multiple operations under one lock, the automatic synchronization didn't buy much. With the advent of .NET 2.0, the original collections were succeeded by the generic collections which are fully type-safe, but eschew automatic synchronization.  This cuts both ways in that you have a lot more control as a developer over when and how fine-grained you want to synchronize, but on the other hand if you just want simple synchronization it creates more work. With .NET 4.0, we get the best of both worlds in generic collections.  A new breed of collections was born called the concurrent collections in the System.Collections.Concurrent namespace.  These amazing collections are fine-tuned to have best overall performance for situations requiring concurrent access.  They are not meant to replace the generic collections, but to simply be an alternative to creating your own locking mechanisms. Among those concurrent collections were the ConcurrentStack<T> and ConcurrentQueue<T> which provide classic LIFO and FIFO collections with a concurrent twist.  As we saw, some of the traditional methods that required calls to be made in a certain order (like checking for not IsEmpty before calling Pop()) were replaced in favor of an umbrella operation that combined both under one lock (like TryPop()). Now, let's take a look at the next in our series of concurrent collections!For some excellent information on the performance of the concurrent collections and how they perform compared to a traditional brute-force locking strategy, see this wonderful whitepaper by the Microsoft Parallel Computing Platform team here. ConcurrentDictionary – the fully thread-safe dictionary The ConcurrentDictionary<TKey,TValue> is the thread-safe counterpart to the generic Dictionary<TKey, TValue> collection.  Obviously, both are designed for quick – O(1) – lookups of data based on a key.  If you think of algorithms where you need lightning fast lookups of data and don’t care whether the data is maintained in any particular ordering or not, the unsorted dictionaries are generally the best way to go. Note: as a side note, there are sorted implementations of IDictionary, namely SortedDictionary and SortedList which are stored as an ordered tree and a ordered list respectively.  While these are not as fast as the non-sorted dictionaries – they are O(log2 n) – they are a great combination of both speed and ordering -- and still greatly outperform a linear search. Now, once again keep in mind that if all you need to do is load a collection once and then allow multi-threaded reading you do not need any locking.  Examples of this tend to be situations where you load a lookup or translation table once at program start, then keep it in memory for read-only reference.  In such cases locking is completely non-productive. However, most of the time when we need a concurrent dictionary we are interleaving both reads and updates.  This is where the ConcurrentDictionary really shines!  It achieves its thread-safety with no common lock to improve efficiency.  It actually uses a series of locks to provide concurrent updates, and has lockless reads!  This means that the ConcurrentDictionary gets even more efficient the higher the ratio of reads-to-writes you have. ConcurrentDictionary and Dictionary differences For the most part, the ConcurrentDictionary<TKey,TValue> behaves like it’s Dictionary<TKey,TValue> counterpart with a few differences.  Some notable examples of which are: Add() does not exist in the concurrent dictionary. This means you must use TryAdd(), AddOrUpdate(), or GetOrAdd().  It also means that you can’t use a collection initializer with the concurrent dictionary. TryAdd() replaced Add() to attempt atomic, safe adds. Because Add() only succeeds if the item doesn’t already exist, we need an atomic operation to check if the item exists, and if not add it while still under an atomic lock. TryUpdate() was added to attempt atomic, safe updates. If we want to update an item, we must make sure it exists first and that the original value is what we expected it to be.  If all these are true, we can update the item under one atomic step. TryRemove() was added to attempt atomic, safe removes. To safely attempt to remove a value we need to see if the key exists first, this checks for existence and removes under an atomic lock. AddOrUpdate() was added to attempt an thread-safe “upsert”. There are many times where you want to insert into a dictionary if the key doesn’t exist, or update the value if it does.  This allows you to make a thread-safe add-or-update. GetOrAdd() was added to attempt an thread-safe query/insert. Sometimes, you want to query for whether an item exists in the cache, and if it doesn’t insert a starting value for it.  This allows you to get the value if it exists and insert if not. Count, Keys, Values properties take a snapshot of the dictionary. Accessing these properties may interfere with add and update performance and should be used with caution. ToArray() returns a static snapshot of the dictionary. That is, the dictionary is locked, and then copied to an array as a O(n) operation.  GetEnumerator() is thread-safe and efficient, but allows dirty reads. Because reads require no locking, you can safely iterate over the contents of the dictionary.  The only downside is that, depending on timing, you may get dirty reads. Dirty reads during iteration The last point on GetEnumerator() bears some explanation.  Picture a scenario in which you call GetEnumerator() (or iterate using a foreach, etc.) and then, during that iteration the dictionary gets updated.  This may not sound like a big deal, but it can lead to inconsistent results if used incorrectly.  The problem is that items you already iterated over that are updated a split second after don’t show the update, but items that you iterate over that were updated a split second before do show the update.  Thus you may get a combination of items that are “stale” because you iterated before the update, and “fresh” because they were updated after GetEnumerator() but before the iteration reached them. Let’s illustrate with an example, let’s say you load up a concurrent dictionary like this: 1: // load up a dictionary. 2: var dictionary = new ConcurrentDictionary<string, int>(); 3:  4: dictionary["A"] = 1; 5: dictionary["B"] = 2; 6: dictionary["C"] = 3; 7: dictionary["D"] = 4; 8: dictionary["E"] = 5; 9: dictionary["F"] = 6; Then you have one task (using the wonderful TPL!) to iterate using dirty reads: 1: // attempt iteration in a separate thread 2: var iterationTask = new Task(() => 3: { 4: // iterates using a dirty read 5: foreach (var pair in dictionary) 6: { 7: Console.WriteLine(pair.Key + ":" + pair.Value); 8: } 9: }); And one task to attempt updates in a separate thread (probably): 1: // attempt updates in a separate thread 2: var updateTask = new Task(() => 3: { 4: // iterates, and updates the value by one 5: foreach (var pair in dictionary) 6: { 7: dictionary[pair.Key] = pair.Value + 1; 8: } 9: }); Now that we’ve done this, we can fire up both tasks and wait for them to complete: 1: // start both tasks 2: updateTask.Start(); 3: iterationTask.Start(); 4:  5: // wait for both to complete. 6: Task.WaitAll(updateTask, iterationTask); Now, if I you didn’t know about the dirty reads, you may have expected to see the iteration before the updates (such as A:1, B:2, C:3, D:4, E:5, F:6).  However, because the reads are dirty, we will quite possibly get a combination of some updated, some original.  My own run netted this result: 1: F:6 2: E:6 3: D:5 4: C:4 5: B:3 6: A:2 Note that, of course, iteration is not in order because ConcurrentDictionary, like Dictionary, is unordered.  Also note that both E and F show the value 6.  This is because the output task reached F before the update, but the updates for the rest of the items occurred before their output (probably because console output is very slow, comparatively). If we want to always guarantee that we will get a consistent snapshot to iterate over (that is, at the point we ask for it we see precisely what is in the dictionary and no subsequent updates during iteration), we should iterate over a call to ToArray() instead: 1: // attempt iteration in a separate thread 2: var iterationTask = new Task(() => 3: { 4: // iterates using a dirty read 5: foreach (var pair in dictionary.ToArray()) 6: { 7: Console.WriteLine(pair.Key + ":" + pair.Value); 8: } 9: }); The atomic Try…() methods As you can imagine TryAdd() and TryRemove() have few surprises.  Both first check the existence of the item to determine if it can be added or removed based on whether or not the key currently exists in the dictionary: 1: // try add attempts an add and returns false if it already exists 2: if (dictionary.TryAdd("G", 7)) 3: Console.WriteLine("G did not exist, now inserted with 7"); 4: else 5: Console.WriteLine("G already existed, insert failed."); TryRemove() also has the virtue of returning the value portion of the removed entry matching the given key: 1: // attempt to remove the value, if it exists it is removed and the original is returned 2: int removedValue; 3: if (dictionary.TryRemove("C", out removedValue)) 4: Console.WriteLine("Removed C and its value was " + removedValue); 5: else 6: Console.WriteLine("C did not exist, remove failed."); Now TryUpdate() is an interesting creature.  You might think from it’s name that TryUpdate() first checks for an item’s existence, and then updates if the item exists, otherwise it returns false.  Well, note quite... It turns out when you call TryUpdate() on a concurrent dictionary, you pass it not only the new value you want it to have, but also the value you expected it to have before the update.  If the item exists in the dictionary, and it has the value you expected, it will update it to the new value atomically and return true.  If the item is not in the dictionary or does not have the value you expected, it is not modified and false is returned. 1: // attempt to update the value, if it exists and if it has the expected original value 2: if (dictionary.TryUpdate("G", 42, 7)) 3: Console.WriteLine("G existed and was 7, now it's 42."); 4: else 5: Console.WriteLine("G either didn't exist, or wasn't 7."); The composite Add methods The ConcurrentDictionary also has composite add methods that can be used to perform updates and gets, with an add if the item is not existing at the time of the update or get. The first of these, AddOrUpdate(), allows you to add a new item to the dictionary if it doesn’t exist, or update the existing item if it does.  For example, let’s say you are creating a dictionary of counts of stock ticker symbols you’ve subscribed to from a market data feed: 1: public sealed class SubscriptionManager 2: { 3: private readonly ConcurrentDictionary<string, int> _subscriptions = new ConcurrentDictionary<string, int>(); 4:  5: // adds a new subscription, or increments the count of the existing one. 6: public void AddSubscription(string tickerKey) 7: { 8: // add a new subscription with count of 1, or update existing count by 1 if exists 9: var resultCount = _subscriptions.AddOrUpdate(tickerKey, 1, (symbol, count) => count + 1); 10:  11: // now check the result to see if we just incremented the count, or inserted first count 12: if (resultCount == 1) 13: { 14: // subscribe to symbol... 15: } 16: } 17: } Notice the update value factory Func delegate.  If the key does not exist in the dictionary, the add value is used (in this case 1 representing the first subscription for this symbol), but if the key already exists, it passes the key and current value to the update delegate which computes the new value to be stored in the dictionary.  The return result of this operation is the value used (in our case: 1 if added, existing value + 1 if updated). Likewise, the GetOrAdd() allows you to attempt to retrieve a value from the dictionary, and if the value does not currently exist in the dictionary it will insert a value.  This can be handy in cases where perhaps you wish to cache data, and thus you would query the cache to see if the item exists, and if it doesn’t you would put the item into the cache for the first time: 1: public sealed class PriceCache 2: { 3: private readonly ConcurrentDictionary<string, double> _cache = new ConcurrentDictionary<string, double>(); 4:  5: // adds a new subscription, or increments the count of the existing one. 6: public double QueryPrice(string tickerKey) 7: { 8: // check for the price in the cache, if it doesn't exist it will call the delegate to create value. 9: return _cache.GetOrAdd(tickerKey, symbol => GetCurrentPrice(symbol)); 10: } 11:  12: private double GetCurrentPrice(string tickerKey) 13: { 14: // do code to calculate actual true price. 15: } 16: } There are other variations of these two methods which vary whether a value is provided or a factory delegate, but otherwise they work much the same. Oddities with the composite Add methods The AddOrUpdate() and GetOrAdd() methods are totally thread-safe, on this you may rely, but they are not atomic.  It is important to note that the methods that use delegates execute those delegates outside of the lock.  This was done intentionally so that a user delegate (of which the ConcurrentDictionary has no control of course) does not take too long and lock out other threads. This is not necessarily an issue, per se, but it is something you must consider in your design.  The main thing to consider is that your delegate may get called to generate an item, but that item may not be the one returned!  Consider this scenario: A calls GetOrAdd and sees that the key does not currently exist, so it calls the delegate.  Now thread B also calls GetOrAdd and also sees that the key does not currently exist, and for whatever reason in this race condition it’s delegate completes first and it adds its new value to the dictionary.  Now A is done and goes to get the lock, and now sees that the item now exists.  In this case even though it called the delegate to create the item, it will pitch it because an item arrived between the time it attempted to create one and it attempted to add it. Let’s illustrate, assume this totally contrived example program which has a dictionary of char to int.  And in this dictionary we want to store a char and it’s ordinal (that is, A = 1, B = 2, etc).  So for our value generator, we will simply increment the previous value in a thread-safe way (perhaps using Interlocked): 1: public static class Program 2: { 3: private static int _nextNumber = 0; 4:  5: // the holder of the char to ordinal 6: private static ConcurrentDictionary<char, int> _dictionary 7: = new ConcurrentDictionary<char, int>(); 8:  9: // get the next id value 10: public static int NextId 11: { 12: get { return Interlocked.Increment(ref _nextNumber); } 13: } Then, we add a method that will perform our insert: 1: public static void Inserter() 2: { 3: for (int i = 0; i < 26; i++) 4: { 5: _dictionary.GetOrAdd((char)('A' + i), key => NextId); 6: } 7: } Finally, we run our test by starting two tasks to do this work and get the results… 1: public static void Main() 2: { 3: // 3 tasks attempting to get/insert 4: var tasks = new List<Task> 5: { 6: new Task(Inserter), 7: new Task(Inserter) 8: }; 9:  10: tasks.ForEach(t => t.Start()); 11: Task.WaitAll(tasks.ToArray()); 12:  13: foreach (var pair in _dictionary.OrderBy(p => p.Key)) 14: { 15: Console.WriteLine(pair.Key + ":" + pair.Value); 16: } 17: } If you run this with only one task, you get the expected A:1, B:2, ..., Z:26.  But running this in parallel you will get something a bit more complex.  My run netted these results: 1: A:1 2: B:3 3: C:4 4: D:5 5: E:6 6: F:7 7: G:8 8: H:9 9: I:10 10: J:11 11: K:12 12: L:13 13: M:14 14: N:15 15: O:16 16: P:17 17: Q:18 18: R:19 19: S:20 20: T:21 21: U:22 22: V:23 23: W:24 24: X:25 25: Y:26 26: Z:27 Notice that B is 3?  This is most likely because both threads attempted to call GetOrAdd() at roughly the same time and both saw that B did not exist, thus they both called the generator and one thread got back 2 and the other got back 3.  However, only one of those threads can get the lock at a time for the actual insert, and thus the one that generated the 3 won and the 3 was inserted and the 2 got discarded.  This is why on these methods your factory delegates should be careful not to have any logic that would be unsafe if the value they generate will be pitched in favor of another item generated at roughly the same time.  As such, it is probably a good idea to keep those generators as stateless as possible. Summary The ConcurrentDictionary is a very efficient and thread-safe version of the Dictionary generic collection.  It has all the benefits of type-safety that it’s generic collection counterpart does, and in addition is extremely efficient especially when there are more reads than writes concurrently. Tweet Technorati Tags: C#, .NET, Concurrent Collections, Collections, Little Wonders, Black Rabbit Coder,James Michael Hare

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• How many concurrent RDP Connections on Windows 7 Pro, Enterprise and Ultimate?

  - by Michael Stum

  Windows 7 Professional, Enterprise and Ultimate offer Remote Desktop Server. How many concurrent connections does this allow? Only 1?

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• How to rate-limit concurrent sessions with nginx or haproxy?

  - by bantic

  I'm currently using nginx to reverse-proxy requests from web clients that are doing long-polling to an upstream. Since we're doing long polling (as opposed to websockets), when a client connects it will make multiple http connections to the server in serial, re-establishing a connection every time the server sends it some data (or timing out and re-establishing if the server has nothing to say for 10 seconds). What I'd like to do is limit the number of concurrent web clients. Since the clients are constantly making new HTTP requests instead of keeping a single request open, it's a little tricky to count the total number of web clients (because it's not the same as total number of concurrently connected http clients). The method I've come up with is to track http requests by the originating IP address, and store the IP address somewhere with a TTL of 20 seconds. If a request comes in whose IP isn't recognized, then we check the total number of unexpired stored IP addresses; if that's less than the maximum then we allow this request through. And if a request comes in with an IP address that we can find in the look-up table that hasn't yet expired, then it is allowed through as well. All requests that are allowed through have their IPs added to the table (if not there before) and the TTL refreshed to 20 seconds again. I had actually whipped something together that worked correctly this way using nginx along with the Redis 2.0 Nginx Module (and the nginx lua module to simplify the conditional branching), using redis to store my IP addresses with a TTL (the SETEX command), and checking the table size with the DBSIZE command. This worked but the performance was horrible. nginx and redis ended up using lots of cpu and the machine could only handle a very small number of concurrent requests. The new stick-table and tracking counters that were added to Haproxy in version 1.5 (via a commission from serverfault) seem like they might be ideal to implement exactly this sort of rate limiting, because the stick-table can track IP addresses and automatically expire entries. However, I don't see an easy way to get a total count of the unexpired entries in the stick table, which would be necessary to know the number of connected web clients. I'm curious if anyone has any suggestions, for nginx or haproxy or even for something else not mentioned here that I haven't thought of yet.

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• how do one determine the number of concurrent users that a web application can handle?

  - by lakshmiiyer

  As far as what I know , I think apache web server handles multiple requests through a combination of multi-processing and multi-threading. Want to know for a php application running a webserver is it just the apache which decides the concurrent users it can handle or it also depends on the php application. If yes, then to what extent?

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• Are there any "traps" in cloning a VirtualBox VM for concurrent use on the same Host/LAN?

  - by fred.bear

  With Ubuntu as the Host, I want to run two similar/identical(?) instances of a VirtualBox Guest on the same Host, or perhaps on another Host which is on the same LAN... I have set up a Guest as a "base" for the two clones. I have exported it as an ovf appliance. I've imported this "base" guest OS back into VirtualBox, with a unique name and .vdk ... and I have started them both on the same Host, and all seems okay, but I do wonder if I have missed some significant point. ...eg. Is the virtual NIC the same? this would throw the LAN into confusion (I think)... and what about UUIDs? I haven't actually tried 2 clones together, yet... only the original and one clone, but I haven't gone beyond a simple startup ...

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