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  • Issue with SOAPUI: running test for concurrency

    - by Kangkan
    I am trying to test my web service using SOAPUI (the free version). For testing concurrency, I wished to fire concurrent threads from SOAPUI onto the service. But with the options, the thread count increases gradually (even in the burst mode). The machine where SOAPUI is installed is a WinXP machine. Can I actually do the concurrency testing? If so how? Please guide me. I am waiting for your answers and help.

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  • High-concurrency counters without sharding

    - by dound
    This question concerns two implementations of counters which are intended to scale without sharding (with a tradeoff that they might under-count in some situations): http://appengine-cookbook.appspot.com/recipe/high-concurrency-counters-without-sharding/ (the code in the comments) http://blog.notdot.net/2010/04/High-concurrency-counters-without-sharding My questions: With respect to #1: Running memcache.decr() in a deferred, transactional task seems like overkill. If memcache.decr() is done outside the transaction, I think the worst-case is the transaction fails and we miss counting whatever we decremented. Am I overlooking some other problem that could occur by doing this? What are the significiant tradeoffs between the two implementations? Here are the tradeoffs I see: #2 does not require datastore transactions. To get the counter's value, #2 requires a datastore fetch while with #1 typically only needs to do a memcache.get() and memcache.add(). When incrementing a counter, both call memcache.incr(). Periodically, #2 adds a task to the task queue while #1 transactionally performs a datastore get and put. #1 also always performs memcache.add() (to test whether it is time to persist the counter to the datastore). Conclusions (without actually running any performance tests): #1 should typically be faster at retrieving a counter (#1 memcache vs #2 datastore). Though #1 has to perform an extra memcache.add() too. However, #2 should be faster when updating counters (#1 datastore get+put vs #2 enqueue a task). On the other hand, with #1 you have to be a bit more careful with the update interval since the task queue quota is almost 100x smaller than either the datastore or memcahce APIs.

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  • Why not Green Threads?

    - by redjamjar
    Whilst I know questions on this have been covered already (e.g. http://stackoverflow.com/questions/5713142/green-threads-vs-non-green-threads), I don't feel like I've got a satisfactory answer. The question is: why don't JVM's support green threads anymore? It says this on the code-style Java FAQ: A green thread refers to a mode of operation for the Java Virtual Machine (JVM) in which all code is executed in a single operating system thread. And this over on java.sun.com: The downside is that using green threads means system threads on Linux are not taken advantage of and so the Java virtual machine is not scalable when additional CPUs are added. It seems to me that the JVM could have a pool of system processes equal to the number of cores, and then run green threads on top of that. This could offer some big advantages when you have a very number large of threads which block often (mostly because current JVM's cap the number of threads). Thoughts?

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  • Can I implement the readers and writers algorithm in OpenMP by replacing counting semaphores with another feature?

    - by DeveloperDon
    After reading about OpenMP and not finding functions to support semaphores, I did an internet search for OpenMP and the readers and writers problem, but found no suitable matches. Is there a general method for replacing counting semaphores in OpenMP with something that it supports? Or is there just a gap in the environment where it does not permit things that are asymmetrical like the third readers and writers problem shown on the following page? http://en.wikipedia.org/wiki/Readers-writers_problem#The_third_readers-writers_problem

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  • What are the consequences of immutable classes with references to mutable classes?

    - by glenviewjeff
    I've recently begun adopting the best practice of designing my classes to be immutable per Effective Java [Bloch2008]. I have a series of interrelated questions about degrees of mutability and their consequences. I have run into situations where a (Java) class I implemented is only "internally immutable" because it uses references to other mutable classes. In this case, the class under development appears from the external environment to have state. Do any of the benefits (see below) of immutable classes hold true even by only "internally immutable" classes? Is there an accepted term for the aforementioned "internal mutability"? Wikipedia's immutable object page uses the unsourced term "deep immutability" to describe an object whose references are also immutable. Is the distinction between mutability and side-effect-ness/state important? Josh Bloch lists the following benefits of immutable classes: are simple to construct, test, and use are automatically thread-safe and have no synchronization issues do not need a copy constructor do not need an implementation of clone allow hashCode to use lazy initialization, and to cache its return value do not need to be copied defensively when used as a field make good Map keys and Set elements (these objects must not change state while in the collection) have their class invariant established once upon construction, and it never needs to be checked again always have "failure atomicity" (a term used by Joshua Bloch) : if an immutable object throws an exception, it's never left in an undesirable or indeterminate state

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  • What are the relative merits for implementing an Erlang-style "Continuation" pattern in C#

    - by JoeGeeky
    What are the relative merits (or demerits) for implementing an Erlang-style "Continuation" pattern in C#. I'm working on a project that has a large number of Lowest priority threads and I'm wondering if my approach may be all wrong. It would seem there is a reasonable upper limit to the number of long-running threads that any one Process 'should' spawn. With that said, I'm not sure what would signal the tipping-point for too many thread or when alternate patterns such as "Continuation" would be more suitable. In this case, many of the threads do a small amount of work and then sleep until woken to go again (Ex. Heartbeat, purge caches, etc...). This continues for the life of the Process.

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  • UML Diagrams of Multi-Threaded Applications

    - by PersonalNexus
    For single-threaded applications I like to use class diagrams to get an overview of the architecture of that application. This type of diagram, however, hasn’t been very helpful when trying to understand heavily multi-threaded/concurrent applications, for instance because different instances of a class "live" on different threads (meaning accessing an instance is save only from the one thread it lives on). Consequently, associations between classes don’t necessarily mean that I can call methods on those objects, but instead I have to make that call on the target object's thread. Most literature I have dug up on the topic such as Designing Concurrent, Distributed, and Real-Time Applications with UML by Hassan Gomaa had some nice ideas, such as drawing thread boundaries into object diagrams, but overall seemed a bit too academic and wordy to be really useful. I don’t want to use these diagrams as a high-level view of the problem domain, but rather as a detailed description of my classes/objects, their interactions and the limitations due to thread-boundaries I mentioned above. I would therefore like to know: What types of diagrams have you found to be most helpful in understanding multi-threaded applications? Are there any extensions to classic UML that take into account the peculiarities of multi-threaded applications, e.g. through annotations illustrating that some objects might live in a certain thread while others have no thread-affinity; some fields of an object may be read from any thread, but written to only from one; some methods are synchronous and return a result while others are asynchronous that get requests queued up and return results for instance via a callback on a different thread.

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  • Why should most logic be in the monitor objects and not in the thread objects when writing concurrent software in Java?

    - by refuser
    When I took the Realtime and Concurrent programming course our lecturer told us that when writing concurrent programs in Java and using monitors, most of the logic should be in the monitor and as little as possible in the threads that access it. I never really understood why and I really would like to. Let me clarify. In this particular case we had several classes. Lift extends Thread Person extends Thread LiftView Monitor, all methods synchronized. This is nothing we came up with, our task was to implement a lift simulation with persons waiting on different floors, and theses were the class skeletons that were given. Then our lecturer said to implement most of the logic in the monitor (he was talking about class Monitor as THE monitor) and as little as possible in the threads. Why would he make a statement like that?

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  • Discussion of a Distributed Data Storage implementation

    - by fegol
    I want to implement a distributed data storage using a client/server architecture. Each data item will be stored persistently in disk in one of several remote servers. The client uses a library to update and query the data, shielding the client from its actual location. This should allow a client to associate keys (String) to values(byte[]), much as a Map does. The system must ensure that the amount of data stored in each server is approximately the same. The set of servers is known beforehand by other servers and clients. Both the client and the server will be written in Java, using sockets, threads, and files. I open this topic with the objective of discussing the best way to implement this idea, assuming simplicity, what are the issues of this implementation, performance measurements and discussion of the limitations.

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  • Help me understand a part of Java Language Specification

    - by Software Engeneering Learner
    I'm reading part 17.2.1 of Java language specification: http://docs.oracle.com/javase/specs/jls/se7/html/jls-17.html#jls-17.2.1 I won't copy a text, it's too long, but I would like to know, why for third step of sequence they're saying that If thread t was removed from m's wait set in step 2 due to an interrupt Thread couldn't get to step 2 it wasn't removed from wait set, because it written for the step 1: Thread t does not execute any further instructions until it has been removed from m's wait set Thus thread can't be removed from wait set in step 2 whatever it's due to, because it was already removed. Please help me understand this.

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  • How can I make a universal construction more efficient?

    - by VF1
    A "universal construction" is a wrapper class for a sequential object that enables it to be linearized (a strong consistency condition for concurrent objects). For instance, here's an adapted wait-free construction, in Java, from [1], which presumes the existence of a wait-free queue that satisfies the interface WFQ (which only requires one-time consensus between threads) and assumes a Sequential interface: public interface WFQ<T> // "FIFO" iteration { int enqueue(T t); // returns the sequence number of t Iterable<T> iterateUntil(int max); // iterates until sequence max } public interface Sequential { // Apply an invocation (method + arguments) // and get a response (return value + state) Response apply(Invocation i); } public interface Factory<T> { T generate(); } // generate new default object public interface Universal extends Sequential {} public class SlowUniversal implements Universal { Factory<? extends Sequential> generator; WFQ<Invocation> wfq = new WFQ<Invocation>(); Universal(Factory<? extends Sequential> g) { generator = g; } public Response apply(Invocation i) { int max = wfq.enqueue(i); Sequential s = generator.generate(); for(Invocation invoc : wfq.iterateUntil(max)) s.apply(invoc); return s.apply(i); } } This implementation isn't very satisfying, however, since it presumes determinism of a Sequential and is really slow. I attempted to add memory recycling: public interface WFQD<T> extends WFQ<T> { T dequeue(int n); } // dequeues only when n is the tail, else assists other threads public interface CopyableSequential extends Sequential { CopyableSequential copy(); } public class RecyclingUniversal implements Universal { WFQD<CopyableSequential> wfqd = new WFQD<CopyableSequential>(); Universal(CopyableSequential init) { wfqd.enqueue(init); } public Response apply(Invocation i) { int max = wfqd.enqueue(i); CopyableSequential cs = null; int ctr = max; for(CopyableSequential csq : wfq.iterateUntil(max)) if(--max == 0) cs = csq.copy(); wfqd.dequeue(max); return cs.apply(i); } } Here are my specific questions regarding the extension: Does my implementation create a linearizable multi-threaded version of a CopyableSequential? Is it possible extend memory recycling without extending the interface (perhaps my new methods trivialize the problem)? My implementation only reduces memory when a thread returns, so can this be strengthened? [1] provided an implementation for WFQ<T>, not WFQD<T> - one does exist, though, correct? [1] Herlihy and Shavit, The Art of Multiprocessor Programming.

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  • Which parallel pattern to use?

    - by Wim Van Houts
    I need to write a server application that fetches mails from different mail servers/mailboxes and then needs to process/analyze these mails. Traditionally, I would do this multi-threaded, launching a thread for fetching mails (or maybe one per mailbox) and then process the mails. We are moving more and more to servers where we have 8+ cores, so I would like to make use of these cores as much as possible (and not use 1 at 100% and leave the seven others untouched). So conceptually, as an example, it would be nice that I could write the application in such a way that two cores are "continuously" fetching emails and four cores are "continuously" processing/analyzing the emails (since processing and analyzing mails is more CPU intensive than fetching mails). This seems like a good concept, but after studying some parallel patterns, I'm not really sure how this is best implemented. None of the patterns really fit. I'm working in VS2012, native C++, but I guess from a design point of view this does not really matter and just some pointers on how to organize this would be great!

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  • How to avoid oscillation by async event based systems?

    - by inf3rno
    Imagine a system where there are data sources which need to be kept in sync. A simple example is model - view data binding by MVC. Now I intend to describe these kind of systems with data sources and hubs. Data sources are publishing and subscribing for events and hubs are relaying events to data sources. By handling an event a data source will change it state described in the event. By publishing an event the data source puts its current state to the event, so other data sources can use that information to change their state accordingly. The only problem with this system, that events can be reflected from the hub or from the other data sources, and that can put the system into an infinite oscillation (by async or infinite loop by sync). For example A -- data source B -- data source H -- hub A -> H -> A -- reflection from the hub A -> H -> B -> H -> A -- reflection from another data source By sync it is relatively easy to solve this issue. You can compare the current state with the event, and if they are equal, you don't change the state and raise the same event again. By async I could not find a solution yet. The state comparison does not work by async event handling because there is eventual consistency, and new events can be published in an inconsistent state causing the same oscillation. For example: A(*->x) -> H -> B(y->x) -- can go parallel with B(*->y) -> H -> A(x->y) -- so first A changes to x state while B changes to y state -- then B changes to x state while A changes to y state -- and so on for eternity... What do you think is there an algorithm to solve this problem? If there is a solution, is it possible to extend it to prevent oscillation caused by multiple hubs, multiple different events, etc... ? update: I don't think I can make this work without a lot of effort. I think this problem is just the same as we have by syncing multiple databases in a distributed system. So I think what I really need is constraints if I want to prevent this problem in an automatic way. What constraints do you suggest?

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  • I have data that sends in "bursts" of 100 records with a significant delay. How do I structure my classes for multithreading?

    - by makerofthings7
    My datasource sends information in 100 batches of 100 records with a delay of 1 to 3 seconds between batches. I would like to start processing data as soon as it's received, but I'm not sure how to best approach this. Some ideas I've been playing with include: yield Concurrent Dictionary ConcurrentDictionary with INotifyProperyChanged Events etc. As you can see I'm all over the place, and would appreciate some tested guidance on how to approach this

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  • how to serialize function depending on what instance of object calls it, if same instance call in a thread then do serialize else not

    - by LondonDreams
    I have a function which fetches and updates some record from db and I am trying to make sure each if the function is called by same instance of object(same Or different thread) then function should behave synchronized else its a call from different object instance function need not to be synchronized. I have tried it use a lock per client. That is, instead of synchronizing the method directly using explicit locking through lock objects using Map. function is like :- getAndUpdateMyHitCount(myObjId){ //go to db and get unique record by myObjId //fetch value , increment , save update } And this function may get call is same thread by different Or same object instance But as fetching and matching from Map is slow , Is there other optimized way to do this ? Found similar at this Question but dont feel that is optimized

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  • Ideas for pet concurrent applications [closed]

    - by DJoyce
    As part of research I am doing into functional concurrent programming, I am looking to develop a prototype business application (or otherwise), that requires and supports parallelism. So I will first develop this application in java 7, followed by scala and then clojure while demonstrating the concurrent support in each language. However, I am a little short on suitable ideas and therefore i'm hoping I can get some good, interesting ideas on this thread. Thanks!

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  • 3 threads printing numbers of different range

    - by user875036
    This question was asked in an Electronic Arts interview: There are 3 threads. The first thread prints the numbers 1 to 10. The second thread prints the numbers 11 to 20. The third thread prints the numbers from from 21 to 30. Now, all three threads are running. The numbers are printed in an irregular order like 1, 11, 2, 21, 12 etc. If I want numbers to be printed in sorted order like 1, 2, 3, 4..., what should I do with these threads?

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  • question about book example - Java Concurrency in Practice, Listing 4.12

    - by mike
    Hi, I am working through an example in Java Concurrency in Practice and am not understanding why a concurrent-safe container is necessary in the following code. I'm not seeing how the container "locations" 's state could be modified after construction; so since it is published through an 'unmodifiableMap' wrapper, it appears to me that an ordinary HashMap would suffice. EG, it is accessed concurrently, but the state of the map is only accessed by readers, no writers. The value fields in the map are syncronized via delegation to the 'SafePoint' class, so while the points are mutable, the keys for the hash, and their associated values (references to SafePoint instances) in the map never change. I think my confusion is based on what precisely the state of the collection is in the problem. Thanks!! -Mike Listing 4.12, Java Concurrency in Practice, (this listing available as .java here, and also in chapter form via google) /////////////begin code @ThreadSafe public class PublishingVehicleTracker { private final Map<String, SafePoint> locations; private final Map<String, SafePoint> unmodifiableMap; public PublishingVehicleTracker( Map<String, SafePoint> locations) { this.locations = new ConcurrentHashMap<String, SafePoint>(locations); this.unmodifiableMap = Collections.unmodifiableMap(this.locations); } public Map<String, SafePoint> getLocations() { return unmodifiableMap; } public SafePoint getLocation(String id) { return locations.get(id); } public void setLocation(String id, int x, int y) { if (!locations.containsKey(id)) throw new IllegalArgumentException( "invalid vehicle name: " + id); locations.get(id).set(x, y); } } // monitor protected helper-class @ThreadSafe public class SafePoint { @GuardedBy("this") private int x, y; private SafePoint(int[] a) { this(a[0], a[1]); } public SafePoint(SafePoint p) { this(p.get()); } public SafePoint(int x, int y) { this.x = x; this.y = y; } public synchronized int[] get() { return new int[] { x, y }; } public synchronized void set(int x, int y) { this.x = x; this.y = y; } } ///////////end code

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  • What is Erlang's concurrency model actually ?

    - by arun_suresh
    I was reading a paper recently Why Events are Bad. The paper is a comparative study of Event based and thread based highly concurrent servers and finally concludes stating that Threads are better than events in that scenario. I find that I am not able to classify what sort of concurrency model erlang exposes. Erlang provides Light Weight Processes, but those processes are suspended most of the time until it has received some event/message of some sort. /Arun

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  • How to figure the read/write ratio in Sql Server?

    - by Bill Paetzke
    How can I query the read/write ratio in Sql Server 2005? Are there any caveats I should be aware of? Perhaps it can be found in a DMV query, a standard report, a custom report (i.e the Performance Dashboard), or examining a Sql Profiler trace. I'm not sure exactly. Why do I care? I'm taking time to improve the performance of my web app's data layer. It deals with millions of records and thousands of users. One of the points I'm examining is database concurrency. Sql Server uses pessimistic concurrency by default--good for a write-heavy app. If my app is read-heavy, I might switch it to optimistic concurrency (isolation level: read uncommitted snapshot) like Jeff Atwood did with StackOverflow.

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  • How can I find file system concurrency issues ?

    - by krosenvold
    I have an application running on Linux, and I find myself wanting windows (!). The problem is that every 1000 times or so I run into concurrency problems that are consistent with concurrent reading/writing of files. I am fairly sure that this behavior would be prohibited by file locking under Windows, but I don't have any sufficiently fast windows box to check. There is simply too much file access (too much data) to expect strace to work reliably - the sheer volume of output is likely to change the problem too. It also happens on different files every time. Ideally I would like to change/reconfigure the linux file system to be more restrictive (as in fail-fast) wrt concurrent access. Are there any tools/settings I can use to achieve this ?

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  • Are concurrency issues possible when using the WCF Service Behavoir attribute set to ConcurrencyMode

    - by Brandon Linton
    We have a WCF service that makes a good deal of transactional NHibernate calls. Occasionally we were seeing SQL timeouts, even though the calls were updating different rows and the tables were set to row level locking. After digging into the logs, it looks like different threads were entering the same point in the code (our transaction using block), and an update was hanging on commit. It didn't make sense, though, because we believed that the following service class attribute was forcing a unique execution thread per service call: [ServiceBehavior(ConcurrencyMode = ConcurrencyMode.Multiple, InstanceContextMode = InstanceContextMode.PerCall)] We recently changed the concurrency mode to ConcurrencyMode.Single and haven't yet run into any issues, but the bug was very difficult to reproduce (if anyone has any thoughts on flushing a bug like that out, let me know!). Anyway, that all brings me to my question: shouldn't an InstanceContextMode of PerCall enforce thread-safety within the service, even if the ConcurrencyMode is set to multiple? How would it be possible for two calls to be serviced by the same service instance? Thanks!

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  • Concurrency handling

    - by Lijo
    Hi, Suppose, I am about to start a project using ASP.NET and SQL Server 2005. I have to design the concurrency requirement for this application. I am planning to add a TimeStamp column in each table. While updating the tables I will check that the TimeStamp column is same, as it was selected. Will this approach be suffice? Or is there any shortcomings for this approach under any circumstances? Please advice. Thanks Lijo

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