{"id":3138,"date":"2022-06-15T05:27:58","date_gmt":"2022-06-15T05:27:58","guid":{"rendered":"http:\/\/the-codest.localhost\/blog\/concurrency-in-java-part-1-introduction\/"},"modified":"2026-03-11T05:59:41","modified_gmt":"2026-03-11T05:59:41","slug":"wspolbieznosc-w-java-czesc-1-wprowadzenie","status":"publish","type":"post","link":"https:\/\/thecodest.co\/pl\/blog\/concurrency-in-java-part-1-introduction\/","title":{"rendered":"Wsp\u00f3\u0142bie\u017cno\u015b\u0107 w Javie Cz\u0119\u015b\u0107 1 - Wprowadzenie"},"content":{"rendered":"

Og\u00f3lnie rzecz bior\u0105c, konwencjonalne podej\u015bcie do programowania jest sekwencyjne. Wszystko w programie dzieje si\u0119 krok po kroku.
Ale w rzeczywisto\u015bci r\u00f3wnoleg\u0142o\u015b\u0107 jest sposobem, w jaki dzia\u0142a ca\u0142y \u015bwiat - jest to zdolno\u015b\u0107 do wykonywania wi\u0119cej ni\u017c jednego zadania jednocze\u015bnie.<\/p>\n\n\n\n

W\u0105tek a proces<\/h2>\n\n\n\n

Om\u00f3wienie takich zaawansowanych temat\u00f3w jak wsp\u00f3\u0142bie\u017cno\u015b\u0107 w Java<\/a><\/strong> lub wielow\u0105tkowo\u015b\u0107, musimy ustali\u0107 pewne wsp\u00f3lne definicje, aby mie\u0107 pewno\u015b\u0107, \u017ce jeste\u015bmy po tej samej stronie.<\/p>\n\n\n\n

Zacznijmy od podstaw. W niesekwencyjnym \u015bwiecie, mamy dwa rodzaje reprezentant\u00f3w wsp\u00f3\u0142bie\u017cno\u015bci: procesy oraz
w\u0105tki. Proces to instancja uruchomionego programu. Zazwyczaj jest on odizolowany od innych proces\u00f3w.
System operacyjny jest odpowiedzialny za przypisywanie zasob\u00f3w do ka\u017cdego procesu. Ponadto dzia\u0142a jako przewodnik, kt\u00f3ry
harmonogramy i kontroluje je.<\/p>\n\n\n\n

W\u0105tek jest rodzajem procesu, ale na ni\u017cszym poziomie, dlatego jest r\u00f3wnie\u017c znany jako lekki w\u0105tek. Wiele w\u0105tk\u00f3w mo\u017ce dzia\u0142a\u0107 w jednym
proces. W tym przypadku program dzia\u0142a jako harmonogram i kontroler w\u0105tk\u00f3w. W ten spos\u00f3b poszczeg\u00f3lne programy wydaj\u0105 si\u0119 wykonywa\u0107
wiele zada\u0144 w tym samym czasie.<\/p>\n\n\n\n

Podstawow\u0105 r\u00f3\u017cnic\u0105 mi\u0119dzy w\u0105tkami a procesami jest poziom izolacji. Proces ma sw\u00f3j w\u0142asny zestaw
zasob\u00f3w, podczas gdy w\u0105tek wsp\u00f3\u0142dzieli dane<\/a> z innymi w\u0105tkami. Mo\u017ce si\u0119 to wydawa\u0107 podej\u015bciem podatnym na b\u0142\u0119dy i rzeczywi\u015bcie tak jest. Dla
Nie skupiajmy si\u0119 teraz na tym, poniewa\u017c wykracza to poza zakres tego artyku\u0142u.<\/p>\n\n\n\n

Procesy, w\u0105tki - ok... Ale czym dok\u0142adnie jest wsp\u00f3\u0142bie\u017cno\u015b\u0107? Wsp\u00f3\u0142bie\u017cno\u015b\u0107 oznacza mo\u017cliwo\u015b\u0107 wykonywania wielu zada\u0144 jednocze\u015bnie.
czasu. Nie oznacza to, \u017ce zadania te musz\u0105 by\u0107 wykonywane jednocze\u015bnie - na tym polega r\u00f3wnoleg\u0142o\u015b\u0107. Concurrenc w Javay<\/strong> r\u00f3wnie\u017c nie
wymaga posiadania wielu procesor\u00f3w lub nawet wielu rdzeni. Mo\u017cna to osi\u0105gn\u0105\u0107 w \u015brodowisku jednordzeniowym, wykorzystuj\u0105c
prze\u0142\u0105czanie kontekstu.<\/p>\n\n\n\n

Termin zwi\u0105zany ze wsp\u00f3\u0142bie\u017cno\u015bci\u0105 to wielow\u0105tkowo\u015b\u0107. Jest to cecha program\u00f3w, kt\u00f3ra pozwala im wykonywa\u0107 kilka zada\u0144 jednocze\u015bnie. Nie ka\u017cdy program korzysta z tego podej\u015bcia, ale te, kt\u00f3re to robi\u0105, mo\u017cna nazwa\u0107 wielow\u0105tkowymi.<\/p>\n\n\n\n

Jeste\u015bmy prawie gotowi, jeszcze tylko jedna definicja. Asynchronia oznacza, \u017ce program wykonuje operacje bez blokowania.
Inicjuje zadanie, a nast\u0119pnie wykonuje inne czynno\u015bci w oczekiwaniu na odpowied\u017a. Kiedy otrzyma odpowied\u017a, mo\u017ce reagowa\u0107<\/a> do niego.<\/p>\n\n\n\n

Ca\u0142y ten jazz<\/h2>\n\n\n\n

Domy\u015blnie ka\u017cdy Aplikacja Java<\/strong> dzia\u0142a w jednym procesie. W procesie tym istnieje jeden w\u0105tek zwi\u0105zany z aplikacj\u0105 main()<\/code> metoda
aplikacji. Jak jednak wspomniano, mo\u017cliwe jest wykorzystanie mechanizm\u00f3w wielow\u0105tkowo\u015bci w ramach jednej aplikacji.
program.<\/p>\n\n\n\n

Wykonywalny<\/h3>\n\n\n\n

W\u0105tek<\/code> jest Java<\/strong> w kt\u00f3rej dzieje si\u0119 magia. Jest to reprezentacja obiektowa wcze\u015bniej wspomnianego w\u0105tku. Do
utworzy\u0107 w\u0142asny w\u0105tek, mo\u017cna rozszerzy\u0107 W\u0105tek<\/code> klasa. Nie jest to jednak zalecane podej\u015bcie. Nici<\/code> powinien by\u0107 u\u017cywany jako mechanizm uruchamiaj\u0105cy zadanie. Zadania s\u0105 elementami kod<\/a> kt\u00f3re chcemy uruchomi\u0107 w trybie wsp\u00f3\u0142bie\u017cnym. Mo\u017cemy je zdefiniowa\u0107 za pomoc\u0105 funkcji Wykonywalny<\/code> interfejs.<\/p>\n\n\n\n

Ale do\u015b\u0107 teorii, w\u0142\u00f3\u017cmy nasz kod tam, gdzie s\u0105 nasze usta.<\/p>\n\n\n\n

Problem<\/h3>\n\n\n\n

Za\u0142\u00f3\u017cmy, \u017ce mamy kilka tablic liczb. Dla ka\u017cdej tablicy chcemy pozna\u0107 sum\u0119 liczb w tablicy. Za\u0142\u00f3\u017cmy
Za\u0142\u00f3\u017cmy, \u017ce takich tablic jest wiele i ka\u017cda z nich jest stosunkowo du\u017ca. W takich warunkach chcemy wykorzysta\u0107 wsp\u00f3\u0142bie\u017cno\u015b\u0107 i zsumowa\u0107 ka\u017cd\u0105 tablic\u0119 jako osobne zadanie.<\/p>\n\n\n\n

int[] a1 = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10};\nint[] a2 = {10, 10, 10, 10, 10, 10, 10, 10};;\nint[] a3 = {3, 4, 3, 4, 3, 4, 2, 1, 3, 7};\n\nRunnable task1 = () -> {\n    int sum = Arrays.stream(a1).sum();\n    System.out.println(\"1. Suma wynosi: \" + sum);\n};\n\nRunnable task2 = () -> {\n    int sum = Arrays.stream(a2).sum();\n    System.out.println(\"2. Suma wynosi: \" + sum);\n};\n\nRunnable task3 = () -> {\n    int sum = Arrays.stream(a3).sum();\n    System.out.println(\"3. Suma wynosi: \" + sum);\n};\n\nnew Thread(task1).start();\nnew Thread(task2).start();\nnew Thread(task3).start();<\/code><\/pre>\n\n\n\n
Jak wida\u0107 z powy\u017cszego kodu Wykonywalny<\/code> jest interfejsem funkcjonalnym. Zawiera jedn\u0105 abstrakcyjn\u0105 metod\u0119 run()<\/code>
bez argument\u00f3w. The Wykonywalny<\/code> Interfejs powinien by\u0107 implementowany przez ka\u017cd\u0105 klas\u0119, kt\u00f3rej instancje maj\u0105 by\u0107
wykonywane przez w\u0105tek.<\/p>\n\n\n\n
Po zdefiniowaniu zadania mo\u017cna utworzy\u0107 w\u0105tek do jego uruchomienia. Mo\u017cna to osi\u0105gn\u0105\u0107 poprzez new Thread()<\/code> konstruktor, kt\u00f3ry
bierze Wykonywalny<\/code> jako argument.<\/p>\n\n\n\n
Ostatnim krokiem jest start()<\/code> nowo utworzony w\u0105tek. W API<\/a> s\u0105 r\u00f3wnie\u017c run()<\/code> metody w Wykonywalny<\/code> oraz w
W\u0105tek<\/code>. Nie jest to jednak spos\u00f3b na wykorzystanie wsp\u00f3\u0142bie\u017cno\u015bci w Javie. Bezpo\u015brednie wywo\u0142anie ka\u017cdej z tych metod skutkuje
wykonanie zadania w tym samym w\u0105tku main()<\/code> metoda dzia\u0142a.<\/p>\n\n\n\n
Pule w\u0105tk\u00f3w i executorzy<\/h3>\n\n\n\n
W przypadku du\u017cej liczby zada\u0144 tworzenie osobnego w\u0105tku dla ka\u017cdego z nich nie jest dobrym pomys\u0142em. Tworzenie w\u0105tku W\u0105tek<\/code> jest
i znacznie lepiej jest ponownie wykorzysta\u0107 istniej\u0105ce w\u0105tki ni\u017c tworzy\u0107 nowe.<\/p>\n\n\n\n
Gdy program tworzy wiele kr\u00f3tkotrwa\u0142ych w\u0105tk\u00f3w, lepiej jest u\u017cy\u0107 puli w\u0105tk\u00f3w. Pula w\u0105tk\u00f3w zawiera pewn\u0105 liczb\u0119
gotowych do uruchomienia, ale obecnie nieaktywnych w\u0105tk\u00f3w. Daj\u0105c Wykonywalny<\/code> do puli powoduje, \u017ce jeden z w\u0105tk\u00f3w wywo\u0142uje funkcj\u0119
run()<\/code> metoda danego Wykonywalny<\/code>. Po zako\u0144czeniu zadania w\u0105tek nadal istnieje i znajduje si\u0119 w stanie bezczynno\u015bci.<\/p>\n\n\n\n
Ok, jasne - wolisz pul\u0119 w\u0105tk\u00f3w zamiast r\u0119cznego tworzenia. Ale jak mo\u017cna wykorzysta\u0107 pule w\u0105tk\u00f3w? The Wykonawcy<\/code>
posiada szereg statycznych metod fabrycznych do konstruowania pul w\u0105tk\u00f3w. Na przyk\u0142ad newCachedThredPool()<\/code> tworzy
pula, w kt\u00f3rej nowe w\u0105tki s\u0105 tworzone w razie potrzeby, a bezczynne w\u0105tki s\u0105 przechowywane przez 60 sekund. W przeciwie\u0144stwie do tego,
newFixedThreadPool()<\/code> zawiera sta\u0142y zestaw w\u0105tk\u00f3w, w kt\u00f3rym bezczynne w\u0105tki s\u0105 przechowywane w niesko\u0144czono\u015b\u0107.<\/p>\n\n\n\n
Zobaczmy, jak to mo\u017ce dzia\u0142a\u0107 w naszym przyk\u0142adzie. Teraz nie musimy tworzy\u0107 w\u0105tk\u00f3w r\u0119cznie. Zamiast tego musimy utworzy\u0107
ExecutorService<\/code> kt\u00f3ra zapewnia pul\u0119 w\u0105tk\u00f3w. Nast\u0119pnie mo\u017cemy przypisa\u0107 do niego zadania. Ostatnim krokiem jest zamkni\u0119cie w\u0105tku
aby unikn\u0105\u0107 wyciek\u00f3w pami\u0119ci. Reszta poprzedniego kodu pozostaje bez zmian.<\/p>\n\n\n\n
ExecutorService executor = Executors.newCachedThreadPool();\n\nexecutor.submit(task1);\nexecutor.submit(task2);\nexecutor.submit(task3);\n\nexecutor.shutdown();<\/code><\/pre>\n\n\n\n
Na \u017c\u0105danie<\/h3>\n\n\n\n
Wykonywalny<\/code> wydaje si\u0119 fajnym sposobem na tworzenie wsp\u00f3\u0142bie\u017cnych zada\u0144, ale ma jedn\u0105 powa\u017cn\u0105 wad\u0119. Nie mo\u017ce zwr\u00f3ci\u0107 \u017cadnego
warto\u015b\u0107. Co wi\u0119cej, nie mo\u017cemy okre\u015bli\u0107, czy zadanie zosta\u0142o uko\u0144czone, czy nie. Nie wiemy te\u017c, czy zosta\u0142o ono uko\u0144czone
normalnie lub wyj\u0105tkowo. Rozwi\u0105zaniem tych bol\u0105czek jest Na \u017c\u0105danie<\/code>.<\/p>\n\n\n\n
Na \u017c\u0105danie<\/code> jest podobny do Wykonywalny<\/code> w pewnym sensie r\u00f3wnie\u017c opakowuje zadania asynchroniczne. G\u0142\u00f3wn\u0105 r\u00f3\u017cnic\u0105 jest to, \u017ce jest w stanie
zwraca warto\u015b\u0107. Zwracana warto\u015b\u0107 mo\u017ce by\u0107 dowolnego (nieprymitywnego) typu, tak jak funkcja Na \u017c\u0105danie<\/code> jest typem sparametryzowanym.
Na \u017c\u0105danie<\/code> jest funkcjonalnym interfejsem, kt\u00f3ry posiada call()<\/code> kt\u00f3ra mo\u017ce rzuci\u0107 metod\u0119 Wyj\u0105tek<\/code>.<\/p>\n\n\n\n
Zobaczmy teraz, jak mo\u017cemy wykorzysta\u0107 Na \u017c\u0105danie<\/code> w naszym problemie z tablic\u0105.<\/p>\n\n\n\n
int[] a1 = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10};\nint[] a2 = {10, 10, 10, 10, 10, 10, 10, 10};;\nint[] a3 = {3, 4, 3, 4, 3, 4, 2, 1, 3, 7};\n\nCallable task1 = () -> Arrays.stream(a1).sum();\nCallable task2 = () -> Arrays.stream(a2).sum();\nCallable task3 = () -> Arrays.stream(a3).sum();\n\nExecutorService executor = Executors.newCachedThreadPool();\nFuture future1 = executor.submit(task1);\nFuture future2 = executor.submit(task2);\nFuture future3 = executor.submit(task3);\n\nSystem.out.println(\"1. Suma wynosi: \" + future1.get());\nSystem.out.println(\"2. Suma wynosi: \" + future2.get());\nSystem.out.println(\"3. Suma wynosi: \" + future3.get());\n\nexecutor.shutdown();<\/code><\/pre>\n\n\n\n
Ok, mo\u017cemy zobaczy\u0107 jak Na \u017c\u0105danie<\/code> jest tworzony, a nast\u0119pnie przesy\u0142any do ExecutorService<\/code>. Ale czym do cholery jest Przysz\u0142o\u015b\u0107<\/code>?
Przysz\u0142o\u015b\u0107<\/code> dzia\u0142a jako pomost mi\u0119dzy w\u0105tkami. Suma ka\u017cdej tablicy jest tworzona w oddzielnym w\u0105tku i potrzebujemy sposobu na
otrzymanie tych wynik\u00f3w z powrotem do main()<\/code>.<\/p>\n\n\n\n
Aby pobra\u0107 wynik z Przysz\u0142o\u015b\u0107<\/code> musimy zadzwoni\u0107 get()<\/code> metoda. Tutaj mo\u017ce wydarzy\u0107 si\u0119 jedna z dw\u00f3ch rzeczy. Po pierwsze
wynik oblicze\u0144 wykonanych przez Na \u017c\u0105danie<\/code> jest dost\u0119pny. Wtedy otrzymujemy go natychmiast. Po drugie, wynik nie jest
jeszcze gotowy. W takim przypadku get()<\/code> b\u0119dzie blokowana do momentu uzyskania wyniku.<\/p>\n\n\n\n
ComputableFuture<\/h3>\n\n\n\n
Problem z Przysz\u0142o\u015b\u0107<\/code> jest to, \u017ce dzia\u0142a w \"paradygmacie push\". Podczas korzystania z Przysz\u0142o\u015b\u0107<\/code> musisz by\u0107 jak szef, kt\u00f3ry
nieustannie pyta: \"Czy zadanie zosta\u0142o wykonane? Czy jest gotowe?\", dop\u00f3ki nie przyniesie rezultatu. Dzia\u0142anie pod ci\u0105g\u0142\u0105 presj\u0105 to
drogie. O wiele lepszym podej\u015bciem by\u0142oby zam\u00f3wienie Przysz\u0142o\u015b\u0107<\/code> co zrobi\u0107, gdy b\u0119dzie gotowy do wykonania swojego zadania. Niestety,
Przysz\u0142o\u015b\u0107<\/code> nie mo\u017ce tego zrobi\u0107, ale ComputableFuture<\/code> mo\u017ce.<\/p>\n\n\n\n
ComputableFuture<\/code> dzia\u0142a w paradygmacie \"pull\". Mo\u017cemy mu powiedzie\u0107, co ma zrobi\u0107 z wynikiem, gdy wykona swoje zadania. To
jest przyk\u0142adem podej\u015bcia asynchronicznego.<\/p>\n\n\n\n
ComputableFuture<\/code> dzia\u0142a idealnie z Wykonywalny<\/code> ale nie z Na \u017c\u0105danie<\/code>. Zamiast tego mo\u017cliwe jest dostarczenie zadania do
ComputableFuture<\/code> w postaci Dostawca<\/code>.<\/p>\n\n\n\n
Zobaczmy, jak powy\u017csze odnosi si\u0119 do naszego problemu.<\/p>\n\n\n\n
int[] a1 = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10};\nint[] a2 = {10, 10, 10, 10, 10, 10, 10, 10};;\nint[] a3 = {3, 4, 3, 4, 3, 4, 2, 1, 3, 7};\n\nCompletableFuture.supplyAsync(() -> Arrays.stream(a1).sum())\n                .thenAccept(System.out::println);\n\nCompletableFuture.supplyAsync(() -> Arrays.stream(a2).sum())\n                .thenAccept(System.out::println);\n\nCompletableFuture.supplyAsync(() -> Arrays.stream(a3).sum())\n                .thenAccept(System.out::println);<\/code><\/pre>\n\n\n\n
Pierwsz\u0105 rzecz\u0105, kt\u00f3ra rzuca si\u0119 w oczy, jest to, o ile kr\u00f3tsze jest to rozwi\u0105zanie. Poza tym wygl\u0105da schludnie i estetycznie.<\/p>\n\n\n\n
Zadanie do CompletableFuture<\/code> mog\u0105 by\u0107 dostarczane przez supplyAsync()<\/code> metoda, kt\u00f3ra przyjmuje Dostawca<\/code> lub przez runAsync()<\/code> \u017ce
bierze Wykonywalny<\/code>. Wywo\u0142anie zwrotne - fragment kodu, kt\u00f3ry powinien zosta\u0107 uruchomiony po zako\u0144czeniu zadania - jest definiowane przez thenAccept()<\/code>
metoda.<\/p>\n\n\n\n
Wnioski<\/h2>\n\n\n\n
Java<\/strong> zapewnia wiele r\u00f3\u017cnych podej\u015b\u0107 do wsp\u00f3\u0142bie\u017cno\u015bci. W tym artykule ledwie dotkn\u0119li\u015bmy tego tematu.<\/p>\n\n\n\n
Niemniej jednak, om\u00f3wili\u015bmy podstawy W\u0105tek<\/code>, Wykonywalny<\/code>, Na \u017c\u0105danie<\/code>oraz CallableFuture<\/code> co stanowi dobry punkt
do dalszego badania tematu.<\/p>\n\n\n\n
\"\"<\/a><\/figure>","protected":false},"excerpt":{"rendered":"
Przeczytaj pierwsz\u0105 cz\u0119\u015b\u0107 naszej serii blog\u00f3w po\u015bwi\u0119conych wsp\u00f3\u0142bie\u017cno\u015bci w Javie. W kolejnym artykule przyjrzymy si\u0119 bli\u017cej r\u00f3\u017cnicom mi\u0119dzy w\u0105tkami i procesami, pulom w\u0105tk\u00f3w, executorom i wielu innym!<\/p>","protected":false},"author":2,"featured_media":3139,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[8],"tags":[],"class_list":["post-3138","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-software-development"],"acf":[],"yoast_head":"\nConcurrency in Java Part 1 - Introduction - The Codest<\/title>\n<meta name=\"description\" content=\"Read the first part of our blog series devoted to concurrency in Java.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/thecodest.co\/pl\/blog\/wspolbieznosc-w-java-czesc-1-wprowadzenie\/\" \/>\n<meta property=\"og:locale\" content=\"pl_PL\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Concurrency in Java Part 1 - 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