Grup de fils de Java representa un grup de fils de treball que estan esperant la feina i que es reutilitzen moltes vegades.

En el cas d'un grup de fils, es crea un grup de fils de mida fixa. Un fil de l'agrupació de fils s'extreu i el proveïdor de serveis li assigna una feina. Un cop finalitzada la feina, el fil torna a estar contingut al grup de fils.

Mètodes d'agrupació de fils

newFixedThreadPool(int s): El mètode crea un grup de fils de mida fixa s.

newCachedThreadPool(): El mètode crea un grup de fils nou que crea els fils nous quan sigui necessari, però seguirà utilitzant el fil creat anteriorment sempre que estigui disponible.

newSingleThreadExecutor(): El mètode crea un fil nou.

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Avantatge de Java Thread Pool

Millor rendiment Estalvia temps perquè no cal crear un fil nou.

Ús en temps real

S'utilitza en Servlet i JSP on el contenidor crea un grup de fils per processar la sol·licitud.

Exemple de grup de fils de Java

Vegem un exemple senzill de l'agrupació de fils Java utilitzant ExecutorService i Executors.

... en java

Fitxer: 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(); } } } 

Fitxer: 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&apos;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;>

Exemple de grup de fils: 2

Vegem un altre exemple del grup de fils.

matrius bash

Nom de l'arxiu: 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></=>

Explicació: És evident mirant la sortida del programa que les tasques 4 i 5 només s'executen quan el fil té un fil inactiu. Fins aleshores, les tasques addicionals es posen a la cua.

La conclusió de l'exemple anterior és quan un vol executar 50 tasques però no està disposat a crear 50 fils. En aquest cas, es pot crear un grup de 10 fils. Així, s'assignen 10 de les 50 tasques, i la resta es posen a la cua. Sempre que qualsevol fil de 10 fils queda inactiu, agafa l'11^thtasca. Les altres tasques pendents es tracten de la mateixa manera.

Riscos relacionats amb els grups de subprocessats

Els següents són els riscos que comporta els grups de fils.

Bloqueig: És un fet conegut que el bloqueig pot venir en qualsevol programa que impliqui multithreading, i un grup de fils introdueix un altre escenari de bloqueig. Considereu un escenari en què tots els fils que s'estan executant estan esperant els resultats dels fils bloquejats i esperant a la cua a causa de la no disponibilitat de fils per a l'execució.

Fuga de fil: La fuga de fils es produeix quan s'elimina un fil de l'agrupació per executar una tasca, però no hi torna després de completar-la. Per exemple, quan un fil llança l'excepció i la classe del grup no és capaç de captar aquesta excepció, aleshores el fil surt i redueix la mida del grup de fils en 1. Si el mateix es repeteix diverses vegades, hi ha moltes possibilitats que el grup es quedarà buit i, per tant, no hi ha fils disponibles al grup per executar altres peticions.

Trituració de recursos: Es perd molt de temps en canviar de context entre fils quan la mida del grup de fils és molt gran. Sempre que hi hagi més fils que el nombre òptim pot causar el problema de la fam, i condueix a la derrota dels recursos.

Punts a recordar

No poseu a la cua les tasques que estan esperant simultàniament els resultats obtinguts de les altres tasques. Pot conduir a una situació de bloqueig, tal com s'ha explicat anteriorment.

S'ha de tenir cura sempre que s'utilitzin fils per a l'operació de llarga durada. Pot resultar en l'espera del fil per sempre i finalment conduirà a la fuga del recurs.

activa java

Al final, el grup de fils s'ha d'acabar explícitament. Si no passa, el programa continua executant-se i no s'acaba mai. Invoqueu el mètode shutdown() al grup de fils per finalitzar l'executor. Tingueu en compte que si algú intenta enviar una altra tasca a l'executor després de l'apagada, llançarà una excepció RejectedExecutionException.

Cal entendre les tasques per ajustar eficaçment el grup de fils. Si les tasques donades són contrastades, cal buscar grups per executar diferents varietats de tasques per poder ajustar-les correctament.

proves i tipus de proves

Per reduir la probabilitat d'executar JVM sense memòria, es pot controlar el màxim de fils que es poden executar a JVM. El grup de fils no pot crear fils nous després d'haver arribat al límit màxim.

Un grup de fils pot utilitzar el mateix fil utilitzat si el fil ha acabat la seva execució. Així, s'estalvia el temps i els recursos utilitzats per a la creació d'un nou fil.

Ajust del grup de fils

La mida precisa d'un grup de fils es decideix pel nombre de processadors disponibles i el tipus de tasques que han d'executar els fils. Si un sistema té els processadors P que només tenen els processos de tipus de càlcul, aleshores la mida màxima del grup de fils de P o P + 1 aconsegueix la màxima eficiència. Tanmateix, és possible que les tasques hagin d'esperar a l'E/S, i en aquest escenari, cal tenir en compte la relació entre el temps d'espera (W) i el temps de servei (S) per a la sol·licitud; resultant en la mida màxima de la piscina P * (1 + W / S) per a la màxima eficiència.

Conclusió

Un grup de fils és una eina molt útil per organitzar aplicacions, especialment al costat del servidor. Conceptualment, un grup de fils és molt fàcil d'entendre. Tanmateix, és possible que s'hagi de mirar molts problemes quan es tracta d'un grup de fils. És perquè el grup de fils inclou alguns riscos (els riscos es comenten més amunt).