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  • Help with java executors: wait for task termination.

    - by Raffo
    I need to submit a number of task and then wait for them until all results are available. Each of them adds a String to a Vector (that is synchronized by default). Then I need to start a new task for each result in the Vector but I need to do this only when all the previous tasks have stopped doing their job. I want to use Java Executor, in particular I tried using Executors.newFixedThreadPool(100) in order to use a fixed number of thread (I have a variable number of task that can be 10 or 500) but I'm new with executors and I don't know how to wait for task termination. This is something like a pseudocode of what my program needs to do: EecutorService e = Executors.newFixedThreadPool(100); while(true){ /*do something*/ for(...){ <start task> } <wait for all task termination> for each String in result{ <start task> } <wait for all task termination> } I can't do a e.shutdown because I'm in a while(true) and I need to reuse the executorService... Can you help me? Can you suggest me a guide/book about java executors??

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  • ConcurrentLinkedQueue$Node remains in heap after remove()

    - by action8
    I have a multithreaded app writing and reading a ConcurrentLinkedQueue, which is conceptually used to back entries in a list/table. I originally used a ConcurrentHashMap for this, which worked well. A new requirement required tracking the order entries came in, so they could be removed in oldest first order, depending on some conditions. ConcurrentLinkedQueue appeared to be a good choice, and functionally it works well. A configurable amount of entries are held in memory, and when a new entry is offered when the limit is reached, the queue is searched in oldest-first order for one that can be removed. Certain entries are not to be removed by the system and wait for client interaction. What appears to be happening is I have an entry at the front of the queue that occurred, say 100K entries ago. The queue appears to have the limited number of configured entries (size() == 100), but when profiling, I found that there were ~100K ConcurrentLinkedQueue$Node objects in memory. This appears to be by design, just glancing at the source for ConcurrentLinkedQueue, a remove merely removes the reference to the object being stored but leaves the linked list in place for iteration. Finally my question: Is there a "better" lazy way to handle a collection of this nature? I love the speed of the ConcurrentLinkedQueue, I just cant afford the unbounded leak that appears to be possible in this case. If not, it seems like I'd have to create a second structure to track order and may have the same issues, plus a synchronization concern.

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  • Am I correct in my assumption about synchronized block?

    - by kunjaan
    I have a method shout() with a synchronized block. private void shout(){ System.out.println("SHOUT " + Thread.currentThread().getName()); synchronized(this){ System.out.println("Synchronized Shout" + Thread.currentThread().getName()); try { Thread.sleep(50); } catch (InterruptedException e) { e.printStackTrace(); } System.out.println("Synchronized Shout" + Thread.currentThread().getName()); } } If I have two Threads that run this method, am I correct in assuming that the two "Synchronized Shout" will always appear one after the other? There can be no other statements in between the "Synchronized Shout"?

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  • Will thread.join() block other clients also?

    - by maxp
    In an asp.net web application, say everytime the user makes the request, and the page loads, a thread is fired off that uses thread.join() to block execution until it's finished. Say this thread takes 10 seconds to complete. Does this mean that if 5 totally seperate users make a request to this page, mere miliseconds after the last, does this mean the last user is going to wait 50 seconds to finish their request? Or is each client request threaded?

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  • Find messages[from-to]

    - by Alfred
    I would like to return all messages from certain key to a certain key. The class should be thread-safe and old keys should be able to be deleted say for example after 30 seconds. I was thinking of using a concurrentskiplistset or concurrentskiplist map. Also I was thinking of deleting the items from inside a newSingleThreadScheduledExecutor. I would like to know how you would implement this or maybe use a library?

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  • Python sock.listen(...)

    - by Ian
    All the examples I've seen of sock.listen(5) in the python documentation suggest I should set the max backlog number to be 5. This is causing a problem for my app since I'm expecting some very high volume (many concurrent connections). I set it to 200 and haven't seen any problems on my system, but was wondering how high I can set it before it causes problems.. Anyone know?

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  • Is there an existing solution to the multithreaded data structure problem?

    - by thr
    I've had the need for a multi-threaded data structure that supports these claims: Allows multiple concurrent readers and writers Is sorted Is easy to reason about Fulfilling multiple readers and one writer is a lot easier, but I really would wan't to allow multiple writers. I've been doing research into this area, and I'm aware of ConcurrentSkipList (by Lea based on work by Fraser and Harris) as it's implemented in Java SE 6. I've also implemented my own version of a concurrent Skip List based on A Provably Correct Scalable Concurrent Skip List by Herlihy, Lev, Luchangco and Shavit. These two implementations are developed by people that are light years smarter then me, but I still (somewhat ashamed, because it is amazing work) have to ask the question if these are the two only viable implementations of a concurrent multi reader/writer data structures available today?

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  • App only spawns one thread

    - by tipu
    I have what I thought was a thread-friendly app, and after doing some output I've concluded that of the 15 threads I am attempting to run, only one does. I have if __name__ == "__main__": fhf = FileHandlerFactory() tweet_manager = TweetManager("C:/Documents and Settings/Administrator/My Documents/My Dropbox/workspace/trie/Tweet Search Engine/data/partitioned_raw_tweets/raw_tweets.txt.001") start = time.time() for i in range(15): Indexer(tweet_manager, fhf).start() Then in my thread-entry point, I do def run(self): print(threading.current_thread()) self.index() That results in this: <Indexer(Thread-3, started 1168)> So of 15 threads that I thought were running, I'm only running one. Any idea as to why? Edit: code

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  • SQL Concurrent test update question

    - by ptoinson
    Howdy Folks, I have a SQLServer 2008 database in which I have a table for Tags. A tag is just an id and a name. The definition of the tags table looks like: CREATE TABLE [dbo].[Tag]( [ID] [int] IDENTITY(1,1) NOT NULL, [Name] [varchar](255) NOT NULL CONSTRAINT [PK_Tag] PRIMARY KEY CLUSTERED ( [ID] ASC )WITH (PAD_INDEX = OFF, STATISTICS_NORECOMPUTE = OFF, IGNORE_DUP_KEY = OFF, ALLOW_ROW_LOCKS = ON, ALLOW_PAGE_LOCKS = ON) ) Name is also a unique index. further I have several processes adding data to this table at a pretty rapid rate. These processes use a stored proc that looks like: ALTER PROC [dbo].[lg_Tag_Insert] @Name varchar(255) AS DECLARE @ID int SET @ID = (select ID from Tag where Name=@Name ) if @ID is null begin INSERT Tag(Name) VALUES (@Name) RETURN SCOPE_IDENTITY() end else begin return @ID end My issues is that, other than being a novice at concurrent database design, there seems to be a race condition that is causing me to occasionally get an error that I'm trying to enter duplicate keys (Name) into the DB. The error is: Cannot insert duplicate key row in object 'dbo.Tag' with unique index 'IX_Tag_Name'. This makes sense, I'm just not sure how to fix this. If it where code I would know how to lock the right areas. SQLServer is quite a different beast. First question is what is the proper way to code this 'check, then update pattern'? It seems I need to get an exclusive lock on the row during the check, rather than a shared lock, but it's not clear to me the best way to do that. Any help in the right direction will be greatly appreciated. Thanks in advance.

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  • C# Is it possible to interrupt a specific thread inside a ThreadPool?

    - by Lirik
    Suppose that I've queued a work item in a ThreadPool, but the work item blocks if there is no data to process (reading from a BlockingQueue). If the queue is empty and there will be no more work going into the queue, then I must call the Thread.Interrupt method if I want to interrupt the blocking task, but how does one do the same thing with a ThreadPool? The code might look like this: void Run() { try { while(true) { blockingQueue.Dequeue(); doSomething(); } } finally { countDownLatch.Signal(); } } I'm aware that the best thing to do in this situation is use a regular Thread, but I'm wondering if there is a ThreadPool equivalent way to interrupt a work item.

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  • How can I save an NSDocument concurrently?

    - by Paperflyer
    I have a document based application. Saving the document can take a few seconds, so I want to enable the user to continue using the program while it saves the document in the background. Due to the document architecture, my application is asked to save to a temporary location and that temporary file is then copied over the old file. However, this means that I can not just run my file saving code in the background and return way before it is done, since the temporary file has to be written completely before it can be copied. Is there a way to disable this temporary-file-behavior or otherwise enable file saving in the background?

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  • How does volatile actually work?

    - by FredOverflow
    Marking a variable as volatile in Java ensures that every thread sees the value that was last written to it instead of some stale value. I was wondering how this is actually achieved. Does the JVM emit special instructions that flush the CPU cashes or something?

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  • Java: Implement own message queue (threadsafe)

    - by derMax
    The task is to implement my own messagequeue that is thread safe. My approach: public class MessageQueue { /** * Number of strings (messages) that can be stored in the queue. */ private int capacity; /** * The queue itself, all incoming messages are stored in here. */ private Vector<String> queue = new Vector<String>(capacity); /** * Constructor, initializes the queue. * * @param capacity The number of messages allowed in the queue. */ public MessageQueue(int capacity) { this.capacity = capacity; } /** * Adds a new message to the queue. If the queue is full, it waits until a message is released. * * @param message */ public synchronized void send(String message) { //TODO check } /** * Receives a new message and removes it from the queue. * * @return */ public synchronized String receive() { //TODO check return "0"; } } If the queue is empty and I call remove(), I want to call wait() so that another thread can use the send() method. Respectively, I have to call notifyAll() after every iteration. Question: Is that possible? I mean does it work that when I say wait() in one method of an object, that I can then execute another method of the same object? And another question: Does that seem to be clever?

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  • Must all Concurrent Data Store (CDB) locks be explicitly released when closing a Berkeley DB?

    - by Steve Emmerson
    I have an application that comprises multiple processes each accessing a single Berkeley DB Concurrent Data Store (CDB) database. Each process is single-threaded and does no explicit locking of the database. When each process terminates normally, it calls DB-close() and DB_ENV-close(). When all processes have terminated, there should be no locks on the database. Episodically, however, the database behaves as if some process was holding a write-lock on it even though all processes have terminated normally. Does each process need to explicitly release all locks before calling DB_ENV-close()? If so, how does the process obtain the "locker" parameter for the call to DB_ENV-loc_vec()?

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  • Scala and the Java Memory Model

    - by Ben Lings
    The Java Memory Model (since 1.5) treats final fields differently to non-final fields. In particular, provided the this reference doesn't escape during construction, writes to final fields in the constructor are guaranteed to be visible on other threads even if the object is made available to the other thread via a data race. (Writes to non-final fields aren't guaranteed to be visible, so if you improperly publish them, another thread could see them in a partially constructed state.) Is there any documentation on how/if the Scala compiler creates final (rather than non-final) backing fields for classes? I've looked through the language specification and searched the web but can't find any definitive answers. (In comparison the @scala.volatile annotation is documented to mark a field as volatile)

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  • Webapp: safetly update a shared List/Map in the AppContext

    - by al nik
    I've Lists and Maps in my WebAppContext. Most of the time these are only read by multiple Threads but sometimes there's the need to update or add some data. I'm wondering what's the best way to do this without incurring in a ConcurrentModificationException. I think that using CopyOnWriteArrayList I can achieve what I want in terms of - I do not have to sync on every read operation- I can safety update the list while other threads are reading it. Is this the best solution? What about Maps?

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  • How do JVM's implicit memory barriers behave when chaining constructors

    - by Joonas Pulakka
    Referring to my earlier question on incompletely constructed objects, I have a second question. As Jon Skeet pointed out, there's an implicit memory barrier in the end of a constructor that makes sure that final fields are visible to all threads. But what if a constructor calls another constructor; is there such a memory barrier in the end of each of them, or only in one being called from outside? That is, when the "wrong" solution is: public class ThisEscape { public ThisEscape(EventSource source) { source.registerListener( new EventListener() { public void onEvent(Event e) { doSomething(e); } }); } } And the correct one would be a factory method version: public class SafeListener { private final EventListener listener; private SafeListener() { listener = new EventListener() { public void onEvent(Event e) { doSomething(e); } } } public static SafeListener newInstance(EventSource source) { SafeListener safe = new SafeListener(); source.registerListener(safe.listener); return safe; } } Would the following work too, or not? public class MyListener { private final EventListener Listener; private MyListener() { listener = new EventListener() { public void onEvent(Event e) { doSomething(e); } } } public MyListener(EventSource source) { this(); source.register(listener); } }

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  • volatile keyword seems to be useless?

    - by Finbarr
    import java.util.concurrent.CountDownLatch; import java.util.concurrent.atomic.AtomicInteger; public class Main implements Runnable { private final CountDownLatch cdl1 = new CountDownLatch(NUM_THREADS); private volatile int bar = 0; private AtomicInteger count = new AtomicInteger(0); private static final int NUM_THREADS = 25; public static void main(String[] args) { Main main = new Main(); for(int i = 0; i < NUM_THREADS; i++) new Thread(main).start(); } public void run() { int i = count.incrementAndGet(); cdl1.countDown(); try { cdl1.await(); } catch (InterruptedException e1) { e1.printStackTrace(); } bar = i; if(bar != i) System.out.println("Bar not equal to i"); else System.out.println("Bar equal to i"); } } Each Thread enters the run method and acquires a unique, thread confined, int variable i by getting a value from the AtomicInteger called count. Each Thread then awaits the CountDownLatch called cdl1 (when the last Thread reaches the latch, all Threads are released). When the latch is released each thread attempts to assign their confined i value to the shared, volatile, int called bar. I would expect every Thread except one to print out "Bar not equal to i", but every Thread prints "Bar equal to i". Eh, wtf does volatile actually do if not this?

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  • Java - when to use notify or notifyAll?

    - by mdma
    Why does java.lang.Object have two notify methods - notify and notifyAll? It seems that notifyAll does at least everything notify does, so why not just use notifyAll all the time? If notifyAll is used instead of notify, is the program still correct, and vice versa? What influences the choice between these two methods?

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  • How this pthread actually works?

    - by user289013
    I am actually on my project on compiler with SMP, and want to code with pthreads and heard about many parallel things open mpi and so on, So to start with how this thread is allocated to core while calling pthread,Is there any way to give threads to different cores by pthreads?

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  • Concurency issues with scheduling app

    - by Sazug
    Our application needs a simple scheduling mechanism - we can schedule only one visit per room for the same time interval (but one visit can be using one or more rooms). Using SQL Server 2005, sample procedure could look like this: CREATE PROCEDURE CreateVisit @start datetime, @end datetime, @roomID int AS BEGIN DECLARE @isFreeRoom INT BEGIN TRANSACTION SELECT @isFreeRoom = COUNT(*) FROM visits V INNER JOIN visits_rooms VR on VR.VisitID = V.ID WHERE @start = start AND @end = [end] AND VR.RoomID = @roomID IF (@isFreeRoom = 0) BEGIN INSERT INTO visits (start, [end]) VALUES (@start, @end) INSERT INTO visits_rooms (visitID, roomID) VALUES (SCOPE_IDENTITY(), @roomID) END COMMIT TRANSACTION END In order to not have the same room scheduled for two visits at the same time, how should we handle this problem in procedure? Should we use SERIALIZABLE transaction isolation level or maybe use table hints (locks)? Which one is better?

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  • Is there an implementation of rapid concurrent syntactical sugar in scala? eg. map-reduce

    - by TiansHUo
    Passing messages around with actors is great. But I would like to have even easier code. Examples (Pseudo-code) val splicedList:List[List[Int]]=biglist.partition(100) val sum:Int=ActorPool.numberOfActors(5).getAllResults(splicedList,foldLeft(_+_)) where spliceIntoParts turns one big list into 100 small lists the numberofactors part, creates a pool which uses 5 actors and receives new jobs after a job is finished and getallresults uses a method on a list. all this done with messages passing in the background. where maybe getFirstResult, calculates the first result, and stops all other threads (like cracking a password)

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