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Јава Тхреад Поол

Јава Тхреад поол представља групу радничких нити које чекају посао и више пута се користе.

У случају скупа нити, креира се група нити фиксне величине. Провајдер сервиса извлачи нит из скупа нити и додељује јој посао. Након завршетка посла, нит је поново садржана у скупу нити.

Методе скупа нити

невФикедТхреадПоол(инт с): Метод креира скуп нити фиксне величине с.

невЦацхедТхреадПоол(): Метод креира нови скуп нити који креира нове нити када је то потребно, али ће и даље користити претходно креирану нит кад год су доступне за употребу.

невСинглеТхреадЕкецутор(): Метод креира нову нит.

Предност Јава Тхреад Поол-а

Боље перформансе То штеди време јер нема потребе за креирањем нове теме.

јсон пример података

Коришћење у реалном времену

Користи се у Сервлет-у и ЈСП-у где контејнер креира скуп нити за обраду захтева.

Пример Јава Пула нити

Хајде да видимо једноставан пример Јава пула нити користећи ЕкецуторСервице и Екецуторс.

Фајл: ВоркерТхреад.јава

пристрасност и варијанса
 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(); } } } 

Датотека: ТестТхреадПоол.јава

 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;>
преузмите овај пример

Пример скупа нити: 2

Хајде да видимо још један пример скупа нити.

Назив документа: ТхреадПоолЕкампле.јава

 // 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></=>

Објашњење: Очигледно је посматрањем излаза програма да се задаци 4 и 5 извршавају само када нит има неактивну нит. До тада, додатни задаци се стављају у ред.

Закључак из горњег примера је када неко жели да изврши 50 задатака, али није вољан да креира 50 нити. У том случају, може се направити скуп од 10 нити. Тако се додељује 10 од 50 задатака, а остали се стављају у ред. Кад год било која нит од 10 нити постане неактивна, она преузима 11тхзадатак. Остали задаци на чекању се третирају на исти начин.

Ризици укључени у скупове нити

Следећи су ризици укључени у скупове нити.

Застој: Позната је чињеница да застој може доћи у било који програм који укључује вишенитност, а скуп нити уводи још један сценарио застоја. Размислите о сценарију где све нити које се извршавају чекају резултате из нити које су блокиране и чекају у реду због недоступности нити за извршење.

Цурење нити: До цурења нити долази када се нит уклања из скупа ради извршења задатка, али се не враћа у њега након завршетка задатка. На пример, када нит избаци изузетак и класа базена није у стању да ухвати овај изузетак, тада нит излази и смањује величину скупа нити за 1. Ако се иста ствар понови неколико пута, онда постоје праве шансе да базен ће постати празан, па стога нема доступних нити у базену за извршавање других захтева.

Разбијање ресурса: Много времена се губи на пребацивање контекста између нити када је величина скупа нити веома велика. Кад год има више нити од оптималног броја, то може изазвати проблем гладовања и доводи до трошења ресурса.

Тачке које треба запамтити

Немојте стављати у ред задатке који истовремено чекају резултате добијене од других задатака. То може довести до застоја, као што је горе објашњено.

Мора се водити рачуна кад год се конци користе за операцију која је дуготрајна. То може довести до заувек чекања нити и коначно ће довести до цурења ресурса.

поставити делимитер јава

На крају, скуп нити се мора експлицитно окончати. Ако се то не догоди, програм наставља да се извршава и никада се не завршава. Позовите схутдовн() метод на скупу нити да бисте прекинули извршитељ. Имајте на уму да ако неко покуша да пошаље други задатак извршиоцу након искључивања, он ће бацити РејецтедЕкецутионЕкцептион.

Потребно је разумети задатке за ефикасно подешавање скупа нити. Ако су дати задаци супротни, онда треба тражити скупове за извршавање различитих врста задатака како би се могли правилно подесити.

Да би се смањила вероватноћа покретања ЈВМ-а без меморије, може се контролисати максимални број нити које се могу покренути у ЈВМ-у. Група нити не може да креира нове нити након што је достигла максимално ограничење.

Група нити може користити исту коришћену нит ако је нит завршила своје извршавање. Тиме се штеди време и ресурси који се користе за креирање нове нити.

Подешавање групе нити

Тачна величина скупа нити је одређена бројем доступних процесора и типом задатака које нити морају да изврше. Ако систем има П процесоре који имају само процесе типа прорачуна, онда максимална величина скупа нити од П или П + 1 постиже максималну ефикасност. Међутим, задаци ће можда морати да чекају на И/О, а у таквом сценарију треба узети у обзир однос времена чекања (В) и времена сервиса (С) за захтев; што резултира максималном величином базена П* (1 + В/С) за максималну ефикасност.

Закључак

Скуп нити је веома згодан алат за организовање апликација, посебно на страни сервера. Концептуално, скуп нити је веома лако разумети. Међутим, можда ћете морати да размотрите многа питања када се бавите скупом нити. То је зато што скуп нити долази са неким ризицима који су укључени у њега (ризици су размотрени горе).