Skup Java niti predstavlja grupu radničkih niti koje čekaju na posao i ponovno se koriste mnogo puta.
U slučaju skupa niti, kreira se grupa niti fiksne veličine. Nit iz skupa niti se izvlači i pružatelj usluge joj dodjeljuje posao. Nakon završetka posla, nit se ponovno nalazi u spremištu niti.
Metode skupa niti
newFixedThreadPool(int s): Metoda stvara skup niti fiksne veličine s.
newCachedThreadPool(): Metoda stvara novi skup niti koji stvara nove niti kada je potrebno, ali će i dalje koristiti prethodno stvorene niti kad god su dostupne za korištenje.
sqrt java matematika
newSingleThreadExecutor(): Metoda stvara novu nit.
Prednost Java Thread Pool-a
Bolja izvedba Štedi vrijeme jer nema potrebe za stvaranjem nove niti.
Korištenje u stvarnom vremenu
Koristi se u Servletu i JSP-u gdje spremnik stvara skup niti za obradu zahtjeva.
Primjer Java skupa niti
Pogledajmo jednostavan primjer skupa Java niti pomoću ExecutorService i Executors.
Datoteka: WorkerThread.java
import java.util.concurrent.ExecutorService; import java.util.concurrent.Executors; class WorkerThread implements Runnable { private String message; public WorkerThread(String s){ this.message=s; } public void run() { System.out.println(Thread.currentThread().getName()+' (Start) message = '+message); processmessage();//call processmessage method that sleeps the thread for 2 seconds System.out.println(Thread.currentThread().getName()+' (End)');//prints thread name } private void processmessage() { try { Thread.sleep(2000); } catch (InterruptedException e) { e.printStackTrace(); } } } Datoteka: TestThreadPool.java
public class TestThreadPool { public static void main(String[] args) { ExecutorService executor = Executors.newFixedThreadPool(5);//creating a pool of 5 threads for (int i = 0; i <10; i++) { runnable worker="new" workerthread('' + i); executor.execute(worker); calling execute method of executorservice } executor.shutdown(); while (!executor.isterminated()) system.out.println('finished all threads'); < pre> <p> <strong>Output:</strong> </p> <pre>pool-1-thread-1 (Start) message = 0 pool-1-thread-2 (Start) message = 1 pool-1-thread-3 (Start) message = 2 pool-1-thread-5 (Start) message = 4 pool-1-thread-4 (Start) message = 3 pool-1-thread-2 (End) pool-1-thread-2 (Start) message = 5 pool-1-thread-1 (End) pool-1-thread-1 (Start) message = 6 pool-1-thread-3 (End) pool-1-thread-3 (Start) message = 7 pool-1-thread-4 (End) pool-1-thread-4 (Start) message = 8 pool-1-thread-5 (End) pool-1-thread-5 (Start) message = 9 pool-1-thread-2 (End) pool-1-thread-1 (End) pool-1-thread-4 (End) pool-1-thread-3 (End) pool-1-thread-5 (End) Finished all threads </pre> download this example <h2>Thread Pool Example: 2</h2> <p>Let's see another example of the thread pool.</p> <p> <strong>FileName:</strong> ThreadPoolExample.java</p> <pre> // important import statements import java.util.Date; import java.util.concurrent.ExecutorService; import java.util.concurrent.Executors; import java.text.SimpleDateFormat; class Tasks implements Runnable { private String taskName; // constructor of the class Tasks public Tasks(String str) { // initializing the field taskName taskName = str; } // Printing the task name and then sleeps for 1 sec // The complete process is getting repeated five times public void run() { try { for (int j = 0; j <= 5; j++) { if (j="=" 0) date dt="new" date(); simpledateformat sdf="new" simpledateformat('hh : mm ss'); prints the initialization time for every task system.out.println('initialization name: '+ taskname + '=" + sdf.format(dt)); } else { Date dt = new Date(); SimpleDateFormat sdf = new SimpleDateFormat(" hh execution system.out.println('time of is complete.'); } catch(interruptedexception ie) ie.printstacktrace(); public class threadpoolexample maximum number threads in thread pool static final int max_th="3;" main method void main(string argvs[]) creating five new tasks runnable rb1="new" tasks('task 1'); rb2="new" 2'); rb3="new" 3'); rb4="new" 4'); rb5="new" 5'); a with size fixed executorservice pl="Executors.newFixedThreadPool(MAX_TH);" passes objects to execute (step 3) pl.execute(rb1); pl.execute(rb2); pl.execute(rb3); pl.execute(rb4); pl.execute(rb5); shutdown pl.shutdown(); < pre> <p> <strong>Output:</strong> </p> <pre> Initialization time for the task name: task 1 = 06 : 13 : 02 Initialization time for the task name: task 2 = 06 : 13 : 02 Initialization time for the task name: task 3 = 06 : 13 : 02 Time of execution for the task name: task 1 = 06 : 13 : 04 Time of execution for the task name: task 2 = 06 : 13 : 04 Time of execution for the task name: task 3 = 06 : 13 : 04 Time of execution for the task name: task 1 = 06 : 13 : 05 Time of execution for the task name: task 2 = 06 : 13 : 05 Time of execution for the task name: task 3 = 06 : 13 : 05 Time of execution for the task name: task 1 = 06 : 13 : 06 Time of execution for the task name: task 2 = 06 : 13 : 06 Time of execution for the task name: task 3 = 06 : 13 : 06 Time of execution for the task name: task 1 = 06 : 13 : 07 Time of execution for the task name: task 2 = 06 : 13 : 07 Time of execution for the task name: task 3 = 06 : 13 : 07 Time of execution for the task name: task 1 = 06 : 13 : 08 Time of execution for the task name: task 2 = 06 : 13 : 08 Time of execution for the task name: task 3 = 06 : 13 : 08 task 2 is complete. Initialization time for the task name: task 4 = 06 : 13 : 09 task 1 is complete. Initialization time for the task name: task 5 = 06 : 13 : 09 task 3 is complete. Time of execution for the task name: task 4 = 06 : 13 : 10 Time of execution for the task name: task 5 = 06 : 13 : 10 Time of execution for the task name: task 4 = 06 : 13 : 11 Time of execution for the task name: task 5 = 06 : 13 : 11 Time of execution for the task name: task 4 = 06 : 13 : 12 Time of execution for the task name: task 5 = 06 : 13 : 12 Time of execution for the task name: task 4 = 06 : 13 : 13 Time of execution for the task name: task 5 = 06 : 13 : 13 Time of execution for the task name: task 4 = 06 : 13 : 14 Time of execution for the task name: task 5 = 06 : 13 : 14 task 4 is complete. task 5 is complete. </pre> <p> <strong>Explanation:</strong> It is evident by looking at the output of the program that tasks 4 and 5 are executed only when the thread has an idle thread. Until then, the extra tasks are put in the queue.</p> <p>The takeaway from the above example is when one wants to execute 50 tasks but is not willing to create 50 threads. In such a case, one can create a pool of 10 threads. Thus, 10 out of 50 tasks are assigned, and the rest are put in the queue. Whenever any thread out of 10 threads becomes idle, it picks up the 11<sup>th </sup>task. The other pending tasks are treated the same way.</p> <h2>Risks involved in Thread Pools</h2> <p>The following are the risk involved in the thread pools.</p> <p> <strong>Deadlock:</strong> It is a known fact that deadlock can come in any program that involves multithreading, and a thread pool introduces another scenario of deadlock. Consider a scenario where all the threads that are executing are waiting for the results from the threads that are blocked and waiting in the queue because of the non-availability of threads for the execution.</p> <p> <strong>Thread Leakage:</strong> Leakage of threads occurs when a thread is being removed from the pool to execute a task but is not returning to it after the completion of the task. For example, when a thread throws the exception and the pool class is not able to catch this exception, then the thread exits and reduces the thread pool size by 1. If the same thing repeats a number of times, then there are fair chances that the pool will become empty, and hence, there are no threads available in the pool for executing other requests.</p> <p> <strong>Resource Thrashing:</strong> A lot of time is wasted in context switching among threads when the size of the thread pool is very large. Whenever there are more threads than the optimal number may cause the starvation problem, and it leads to resource thrashing.</p> <h2>Points to Remember</h2> <p>Do not queue the tasks that are concurrently waiting for the results obtained from the other tasks. It may lead to a deadlock situation, as explained above.</p> <p>Care must be taken whenever threads are used for the operation that is long-lived. It may result in the waiting of thread forever and will finally lead to the leakage of the resource.</p> <p>In the end, the thread pool has to be ended explicitly. If it does not happen, then the program continues to execute, and it never ends. Invoke the shutdown() method on the thread pool to terminate the executor. Note that if someone tries to send another task to the executor after shutdown, it will throw a RejectedExecutionException.</p> <p>One needs to understand the tasks to effectively tune the thread pool. If the given tasks are contrasting, then one should look for pools for executing different varieties of tasks so that one can properly tune them.</p> <p>To reduce the probability of running JVM out of memory, one can control the maximum threads that can run in JVM. The thread pool cannot create new threads after it has reached the maximum limit.</p> <p>A thread pool can use the same used thread if the thread has finished its execution. Thus, the time and resources used for the creation of a new thread are saved.</p> <h2>Tuning the Thread Pool</h2> <p>The accurate size of a thread pool is decided by the number of available processors and the type of tasks the threads have to execute. If a system has the P processors that have only got the computation type processes, then the maximum size of the thread pool of P or P + 1 achieves the maximum efficiency. However, the tasks may have to wait for I/O, and in such a scenario, one has to take into consideration the ratio of the waiting time (W) and the service time (S) for the request; resulting in the maximum size of the pool P * (1 + W / S) for the maximum efficiency.</p> <h2>Conclusion</h2> <p>A thread pool is a very handy tool for organizing applications, especially on the server-side. Concept-wise, a thread pool is very easy to comprehend. However, one may have to look at a lot of issues when dealing with a thread pool. It is because the thread pool comes with some risks involved it (risks are discussed above).</p> <hr></=></pre></10;>preuzmite ovaj primjerPrimjer skupa niti: 2
Pogledajmo još jedan primjer skupa niti.
Naziv datoteke: ThreadPoolExample.java
// important import statements import java.util.Date; import java.util.concurrent.ExecutorService; import java.util.concurrent.Executors; import java.text.SimpleDateFormat; class Tasks implements Runnable { private String taskName; // constructor of the class Tasks public Tasks(String str) { // initializing the field taskName taskName = str; } // Printing the task name and then sleeps for 1 sec // The complete process is getting repeated five times public void run() { try { for (int j = 0; j <= 5; j++) { if (j="=" 0) date dt="new" date(); simpledateformat sdf="new" simpledateformat(\'hh : mm ss\'); prints the initialization time for every task system.out.println(\'initialization name: \'+ taskname + \'=" + sdf.format(dt)); } else { Date dt = new Date(); SimpleDateFormat sdf = new SimpleDateFormat(" hh execution system.out.println(\'time of is complete.\'); } catch(interruptedexception ie) ie.printstacktrace(); public class threadpoolexample maximum number threads in thread pool static final int max_th="3;" main method void main(string argvs[]) creating five new tasks runnable rb1="new" tasks(\'task 1\'); rb2="new" 2\'); rb3="new" 3\'); rb4="new" 4\'); rb5="new" 5\'); a with size fixed executorservice pl="Executors.newFixedThreadPool(MAX_TH);" passes objects to execute (step 3) pl.execute(rb1); pl.execute(rb2); pl.execute(rb3); pl.execute(rb4); pl.execute(rb5); shutdown pl.shutdown(); < pre> <p> <strong>Output:</strong> </p> <pre> Initialization time for the task name: task 1 = 06 : 13 : 02 Initialization time for the task name: task 2 = 06 : 13 : 02 Initialization time for the task name: task 3 = 06 : 13 : 02 Time of execution for the task name: task 1 = 06 : 13 : 04 Time of execution for the task name: task 2 = 06 : 13 : 04 Time of execution for the task name: task 3 = 06 : 13 : 04 Time of execution for the task name: task 1 = 06 : 13 : 05 Time of execution for the task name: task 2 = 06 : 13 : 05 Time of execution for the task name: task 3 = 06 : 13 : 05 Time of execution for the task name: task 1 = 06 : 13 : 06 Time of execution for the task name: task 2 = 06 : 13 : 06 Time of execution for the task name: task 3 = 06 : 13 : 06 Time of execution for the task name: task 1 = 06 : 13 : 07 Time of execution for the task name: task 2 = 06 : 13 : 07 Time of execution for the task name: task 3 = 06 : 13 : 07 Time of execution for the task name: task 1 = 06 : 13 : 08 Time of execution for the task name: task 2 = 06 : 13 : 08 Time of execution for the task name: task 3 = 06 : 13 : 08 task 2 is complete. Initialization time for the task name: task 4 = 06 : 13 : 09 task 1 is complete. Initialization time for the task name: task 5 = 06 : 13 : 09 task 3 is complete. Time of execution for the task name: task 4 = 06 : 13 : 10 Time of execution for the task name: task 5 = 06 : 13 : 10 Time of execution for the task name: task 4 = 06 : 13 : 11 Time of execution for the task name: task 5 = 06 : 13 : 11 Time of execution for the task name: task 4 = 06 : 13 : 12 Time of execution for the task name: task 5 = 06 : 13 : 12 Time of execution for the task name: task 4 = 06 : 13 : 13 Time of execution for the task name: task 5 = 06 : 13 : 13 Time of execution for the task name: task 4 = 06 : 13 : 14 Time of execution for the task name: task 5 = 06 : 13 : 14 task 4 is complete. task 5 is complete. </pre> <p> <strong>Explanation:</strong> It is evident by looking at the output of the program that tasks 4 and 5 are executed only when the thread has an idle thread. Until then, the extra tasks are put in the queue.</p> <p>The takeaway from the above example is when one wants to execute 50 tasks but is not willing to create 50 threads. In such a case, one can create a pool of 10 threads. Thus, 10 out of 50 tasks are assigned, and the rest are put in the queue. Whenever any thread out of 10 threads becomes idle, it picks up the 11<sup>th </sup>task. The other pending tasks are treated the same way.</p> <h2>Risks involved in Thread Pools</h2> <p>The following are the risk involved in the thread pools.</p> <p> <strong>Deadlock:</strong> It is a known fact that deadlock can come in any program that involves multithreading, and a thread pool introduces another scenario of deadlock. Consider a scenario where all the threads that are executing are waiting for the results from the threads that are blocked and waiting in the queue because of the non-availability of threads for the execution.</p> <p> <strong>Thread Leakage:</strong> Leakage of threads occurs when a thread is being removed from the pool to execute a task but is not returning to it after the completion of the task. For example, when a thread throws the exception and the pool class is not able to catch this exception, then the thread exits and reduces the thread pool size by 1. If the same thing repeats a number of times, then there are fair chances that the pool will become empty, and hence, there are no threads available in the pool for executing other requests.</p> <p> <strong>Resource Thrashing:</strong> A lot of time is wasted in context switching among threads when the size of the thread pool is very large. Whenever there are more threads than the optimal number may cause the starvation problem, and it leads to resource thrashing.</p> <h2>Points to Remember</h2> <p>Do not queue the tasks that are concurrently waiting for the results obtained from the other tasks. It may lead to a deadlock situation, as explained above.</p> <p>Care must be taken whenever threads are used for the operation that is long-lived. It may result in the waiting of thread forever and will finally lead to the leakage of the resource.</p> <p>In the end, the thread pool has to be ended explicitly. If it does not happen, then the program continues to execute, and it never ends. Invoke the shutdown() method on the thread pool to terminate the executor. Note that if someone tries to send another task to the executor after shutdown, it will throw a RejectedExecutionException.</p> <p>One needs to understand the tasks to effectively tune the thread pool. If the given tasks are contrasting, then one should look for pools for executing different varieties of tasks so that one can properly tune them.</p> <p>To reduce the probability of running JVM out of memory, one can control the maximum threads that can run in JVM. The thread pool cannot create new threads after it has reached the maximum limit.</p> <p>A thread pool can use the same used thread if the thread has finished its execution. Thus, the time and resources used for the creation of a new thread are saved.</p> <h2>Tuning the Thread Pool</h2> <p>The accurate size of a thread pool is decided by the number of available processors and the type of tasks the threads have to execute. If a system has the P processors that have only got the computation type processes, then the maximum size of the thread pool of P or P + 1 achieves the maximum efficiency. However, the tasks may have to wait for I/O, and in such a scenario, one has to take into consideration the ratio of the waiting time (W) and the service time (S) for the request; resulting in the maximum size of the pool P * (1 + W / S) for the maximum efficiency.</p> <h2>Conclusion</h2> <p>A thread pool is a very handy tool for organizing applications, especially on the server-side. Concept-wise, a thread pool is very easy to comprehend. However, one may have to look at a lot of issues when dealing with a thread pool. It is because the thread pool comes with some risks involved it (risks are discussed above).</p> <hr></=> Obrazloženje: Gledajući izlaz programa vidljivo je da se zadaci 4 i 5 izvršavaju samo kada nit ima neaktivnu nit. Do tada se dodatni zadaci stavljaju u red čekanja.
Zaključak iz gornjeg primjera je kada netko želi izvršiti 50 zadataka, ali nije voljan stvoriti 50 niti. U tom slučaju, može se stvoriti skup od 10 niti. Tako se od 50 zadataka dodjeljuje 10, a ostali se stavljaju u red čekanja. Kad god bilo koja nit od 10 postane neaktivna, preuzima 11thzadatak. Ostali zadaci na čekanju tretiraju se na isti način.
Rizici uključeni u skupove niti
Sljedeći su rizici uključeni u skupove niti.
Zastoj: Poznata je činjenica da zastoj može doći u bilo kojem programu koji uključuje višenitnost, a skup niti uvodi još jedan scenarij zastoja. Razmotrite scenarij u kojem sve niti koje se izvode čekaju rezultate od niti koje su blokirane i čekaju u redu čekanja zbog nedostupnosti niti za izvođenje.
redatelj Karan Johar
Propuštanje niti: Do curenja niti dolazi kada se nit uklanja iz skupa radi izvršenja zadatka, ali se u njega ne vraća nakon završetka zadatka. Na primjer, kada nit izbaci iznimku, a klasa bazena ne može uhvatiti ovu iznimku, tada nit izlazi i smanjuje veličinu skupa niti za 1. Ako se ista stvar ponavlja nekoliko puta, tada postoje dobre šanse da bazen će postati prazan i stoga u skupu nema dostupnih niti za izvršavanje drugih zahtjeva.
Razbijanje resursa: Puno se vremena gubi na prebacivanje konteksta između niti kada je veličina skupa niti vrlo velika. Kad god ima više niti od optimalnog broja, to može uzrokovati problem gladovanja, a to dovodi do gubitka resursa.
Bodovi za pamćenje
Nemojte stavljati u red čekanja zadatke koji istovremeno čekaju rezultate dobivene od drugih zadataka. To može dovesti do zastoja, kao što je gore objašnjeno.
arijski kan
Treba paziti kad god se koriste navoji za operaciju koja je dugotrajna. To može rezultirati vječnim čekanjem niti i konačno će dovesti do curenja resursa.
Na kraju, skup niti se mora eksplicitno završiti. Ako se to ne dogodi, tada se program nastavlja izvršavati i nikada ne završava. Pozovite metodu shutdown() na skupu niti da prekinete izvršitelja. Imajte na umu da ako netko pokuša poslati drugi zadatak izvršitelju nakon isključivanja, izbacit će RejectedExecutionException.
Potrebno je razumjeti zadatke za učinkovito podešavanje skupa niti. Ako su zadani zadaci kontrastni, tada treba potražiti skupove za izvršavanje različitih varijanti zadataka kako bi ih se moglo ispravno podesiti.
Kako bi se smanjila vjerojatnost pokretanja JVM-a bez memorije, može se kontrolirati najveći broj niti koje se mogu izvoditi u JVM-u. Skup niti ne može stvoriti nove niti nakon što dosegne maksimalno ograničenje.
Skup niti može koristiti istu korištenu nit ako je nit završila svoje izvođenje. Time se štedi vrijeme i resursi korišteni za stvaranje nove niti.
Podešavanje skupa niti
O točnoj veličini skupa niti odlučuje broj dostupnih procesora i vrsta zadataka koje niti moraju izvršiti. Ako sustav ima P procesore koji imaju samo procese tipa izračunavanja, tada maksimalna veličina skupa niti od P ili P + 1 postiže maksimalnu učinkovitost. Međutim, zadaci će možda morati čekati I/O, au takvom scenariju treba uzeti u obzir omjer vremena čekanja (W) i vremena usluge (S) za zahtjev; što rezultira maksimalnom veličinom bazena P * (1 + W / S) za maksimalnu učinkovitost.
Zaključak
Skup niti je vrlo zgodan alat za organiziranje aplikacija, posebno na strani poslužitelja. Konceptno gledano, skup niti je vrlo lako razumjeti. Međutim, možda ćete morati razmotriti mnogo problema kada se bavite skupom niti. To je zato što skup niti dolazi s određenim rizicima (rizici su spomenuti gore).