// 创建并启动一个线程
val thread = Thread {// 线程执行的代码println("Running in thread ${Thread.currentThread().name}")
}
thread.start()// 使用线程池创建线程
val executorService = Executors.newFixedThreadPool(10)
executorService.submit {// 线程执行的代码println("Running in thread ${Thread.currentThread().name}")
}

// 挂起函数示例
suspend fun fetchData(): String {// 模拟网络请求delay(1000) // delay是一个挂起函数return "Data"
}// 在协程中调用挂起函数
GlobalScope.launch {val data = fetchData()println("Fetched data: $data")
}

// 使用协程作用域创建协程
val scope = CoroutineScope(Dispatchers.Default)
scope.launch {// 协程执行的代码
}// 取消协程作用域中的所有协程
scope.cancel()

interface Continuation<in T> {val context: CoroutineContextfun resumeWith(result: Result<T>)
}

suspend fun fetchData(): String {delay(1000)return "Data"
}

public final class FetchDataKt$fetchData$1 implements Continuation<String> {Object result;  // 保存中间结果int label;      // 状态标签public Object invokeSuspend(Object result) {this.result = result;int label = this.label;switch (label) {case 0:// 初始状态ResultKt.throwOnFailure(result);this.label = 1;return DelayKt.delay(1000L, this);case 1:// delay完成后的状态ResultKt.throwOnFailure(result);return "Data";default:throw new IllegalStateException("Unexpected state: " + label);}}// 实现Continuation接口的其他方法// ...
}

public static final Object fetchData(Continuation<? super String> continuation) {FetchDataKt$fetchData$1 stateMachine;if (continuation instanceof FetchDataKt$fetchData$1) {// 重用已有的状态机stateMachine = (FetchDataKt$fetchData$1) continuation;} else {// 创建新的状态机stateMachine = new FetchDataKt$fetchData$1(continuation);}Object result = stateMachine.invokeSuspend(Unit.INSTANCE);return result == IntrinsicsKt.getCOROUTINE_SUSPENDED() ? result : ResultKt.getOrThrow(result);
}

// DefaultDispatcher的简化实现
object DefaultDispatcher : CoroutineDispatcher() {private val threadPool = Executors.newWorkStealingPool()override fun dispatch(context: CoroutineContext, block: Runnable) {threadPool.submit(block)}// 更多方法...
}

// IODispatcher的简化实现
object IODispatcher : CoroutineDispatcher() {private val threadPool = Executors.newCachedThreadPool()override fun dispatch(context: CoroutineContext, block: Runnable) {threadPool.submit(block)}// 更多方法...
}

// MainDispatcher的简化实现
object MainDispatcher : CoroutineDispatcher() {override fun dispatch(context: CoroutineContext, block: Runnable) {if (isMainThread()) {block.run()} else {postToMainThread(block)}}private fun isMainThread(): Boolean {// 判断是否为主线程// ...}private fun postToMainThread(block: Runnable) {// 将任务发送到主线程执行// ...}// 更多方法...
}

// UnconfinedDispatcher的简化实现
object UnconfinedDispatcher : CoroutineDispatcher() {override fun dispatch(context: CoroutineContext, block: Runnable) {block.run()}// 更多方法...
}

public class ThreadPoolExecutor extends AbstractExecutorService {private final int corePoolSize;private final int maximumPoolSize;private final long keepAliveTime;private final BlockingQueue<Runnable> workQueue;private final ThreadFactory threadFactory;private final RejectedExecutionHandler handler;private final HashSet<Worker> workers = new HashSet<>();// 构造函数public ThreadPoolExecutor(int corePoolSize,int maximumPoolSize,long keepAliveTime,TimeUnit unit,BlockingQueue<Runnable> workQueue,ThreadFactory threadFactory,RejectedExecutionHandler handler) {// 初始化参数this.corePoolSize = corePoolSize;this.maximumPoolSize = maximumPoolSize;this.keepAliveTime = unit.toNanos(keepAliveTime);this.workQueue = workQueue;this.threadFactory = threadFactory;this.handler = handler;}// 提交任务public void execute(Runnable command) {if (command == null)throw new NullPointerException();int c = ctl.get();if (workerCountOf(c) < corePoolSize) {if (addWorker(command, true))return;c = ctl.get();}if (isRunning(c) && workQueue.offer(command)) {int recheck = ctl.get();if (! isRunning(recheck) && remove(command))reject(command);else if (workerCountOf(recheck) == 0)addWorker(null, false);}else if (!addWorker(command, false))reject(command);}// 添加工作线程private boolean addWorker(Runnable firstTask, boolean core) {retry:for (;;) {int c = ctl.get();int rs = runStateOf(c);// Check if queue empty only if necessary.if (rs >= SHUTDOWN &&! (rs == SHUTDOWN &&firstTask == null &&! workQueue.isEmpty()))return false;for (;;) {int wc = workerCountOf(c);if (wc >= CAPACITY ||wc >= (core ? corePoolSize : maximumPoolSize))return false;if (compareAndIncrementWorkerCount(c))break retry;c = ctl.get();  // Re-read ctlif (runStateOf(c) != rs)continue retry;// else CAS failed due to workerCount change; retry inner loop}}boolean workerStarted = false;boolean workerAdded = false;Worker w = null;try {w = new Worker(firstTask);final Thread t = w.thread;if (t != null) {final ReentrantLock mainLock = this.mainLock;mainLock.lock();try {// Recheck while holding lock.// Back out on ThreadFactory failure or if// shut down before lock acquired.int rs = runStateOf(ctl.get());if (rs < SHUTDOWN ||(rs == SHUTDOWN && firstTask == null)) {if (t.isAlive()) // precheck that t is startablethrow new IllegalThreadStateException();workers.add(w);int s = workers.size();if (s > largestPoolSize)largestPoolSize = s;workerAdded = true;}} finally {mainLock.unlock();}if (workerAdded) {t.start();workerStarted = true;}}} finally {if (! workerStarted)addWorkerFailed(w);}return workerStarted;}// 工作线程类private final class Workerextends AbstractQueuedSynchronizerimplements Runnable{final Thread thread;Runnable firstTask;volatile long completedTasks;Worker(Runnable firstTask) {setState(-1); // inhibit interrupts until runWorkerthis.firstTask = firstTask;this.thread = getThreadFactory().newThread(this);}public void run() {runWorker(this);}// 更多方法...}// 运行工作线程final void runWorker(Worker w) {Thread wt = Thread.currentThread();Runnable task = w.firstTask;w.firstTask = null;w.unlock(); // allow interruptsboolean completedAbruptly = true;try {while (task != null || (task = getTask()) != null) {w.lock();// If pool is stopping, ensure thread is interrupted;// if not, ensure thread is not interrupted.  This// requires a recheck in second case to deal with// shutdownNow race while clearing interruptif ((runStateAtLeast(ctl.get(), STOP) ||(Thread.interrupted() &&runStateAtLeast(ctl.get(), STOP))) &&!wt.isInterrupted())wt.interrupt();try {beforeExecute(wt, task);Throwable thrown = null;try {task.run();} catch (RuntimeException x) {thrown = x; throw x;} catch (Error x) {thrown = x; throw x;} catch (Throwable x) {thrown = x; throw new Error(x);} finally {afterExecute(task, thrown);}} finally {task = null;w.completedTasks++;w.unlock();}}completedAbruptly = false;} finally {processWorkerExit(w, completedAbruptly);}}// 从队列获取任务private Runnable getTask() {boolean timedOut = false; // Did the last poll() time out?for (;;) {int c = ctl.get();int rs = runStateOf(c);// Check if queue empty only if necessary.if (rs >= SHUTDOWN && (rs >= STOP || workQueue.isEmpty())) {decrementWorkerCount();return null;}int wc = workerCountOf(c);// Are workers subject to culling?boolean timed = allowCoreThreadTimeOut || wc > corePoolSize;if ((wc > maximumPoolSize || (timed && timedOut))&& (wc > 1 || workQueue.isEmpty())) {if (compareAndDecrementWorkerCount(c))return null;continue;}try {Runnable r = timed ?workQueue.poll(keepAliveTime, TimeUnit.NANOSECONDS) :workQueue.take();if (r != null)return r;timedOut = true;} catch (InterruptedException retry) {timedOut = false;}}}// 更多方法...
}

import kotlinx.coroutines.*
import java.util.concurrent.*fun main() = runBlocking {val coroutineCount = 100_000val threadCount = 10_000 // 线程数量不能太多，否则会导致系统资源耗尽// 测试协程创建和销毁性能val coroutineTime = measureTimeMillis {runBlocking {repeat(coroutineCount) {launch {// 协程执行的代码yield()}}}}println("创建和销毁 $coroutineCount 个协程耗时: $coroutineTime ms")println("每个协程平均耗时: ${coroutineTime.toDouble() / coroutineCount} ms")// 测试线程创建和销毁性能val threadTime = measureTimeMillis {val executorService = Executors.newFixedThreadPool(100)val futures = mutableListOf<Future<*>>()repeat(threadCount) {futures.add(executorService.submit {// 线程执行的代码Thread.yield()})}// 等待所有任务完成futures.forEach { it.get() }executorService.shutdown()}println("创建和销毁 $threadCount 个线程耗时: $threadTime ms")println("每个线程平均耗时: ${threadTime.toDouble() / threadCount} ms")
}

import kotlinx.coroutines.*
import java.lang.management.ManagementFactoryfun main() = runBlocking {val coroutineCount = 1_000_000val threadCount = 10_000 // 线程数量不能太多，否则会导致系统资源耗尽// 测试协程内存占用val coroutineMemory = measureMemory {runBlocking {val jobs = mutableListOf<Job>()repeat(coroutineCount) {jobs.add(launch {// 协程执行的代码delay(Long.MAX_VALUE) // 保持协程运行})}// 等待一段时间，让内存稳定delay(1000)// 取消所有协程jobs.forEach { it.cancel() }}}println("$coroutineCount 个协程占用内存: $coroutineMemory MB")println("每个协程平均占用内存: ${coroutineMemory.toDouble() / coroutineCount * 1024} KB")// 测试线程内存占用val threadMemory = measureMemory {val threads = mutableListOf<Thread>()repeat(threadCount) {val thread = Thread {try {Thread.sleep(Long.MAX_VALUE) // 保持线程运行} catch (e: InterruptedException) {// 处理中断}}threads.add(thread)thread.start()}// 等待一段时间，让内存稳定Thread.sleep(1000)// 中断所有线程threads.forEach { it.interrupt() }threads.forEach { it.join() }}println("$threadCount 个线程占用内存: $threadMemory MB")println("每个线程平均占用内存: ${threadMemory.toDouble() / threadCount * 1024} KB")
}// 测量内存使用的辅助函数
fun measureMemory(block: () -> Unit): Long {val runtime = Runtime.getRuntime()// 执行垃圾回收以获取更准确的内存使用情况runtime.gc()Thread.sleep(1000)val beforeMemory = runtime.totalMemory() - runtime.freeMemory()block()// 执行垃圾回收以获取更准确的内存使用情况runtime.gc()Thread.sleep(1000)val afterMemory = runtime.totalMemory() - runtime.freeMemory()return (afterMemory - beforeMemory) / (1024 * 1024)
}

import kotlinx.coroutines.*
import java.util.concurrent.*fun main() = runBlocking {val switchCount = 1_000_000// 测试协程上下文切换性能val coroutineTime = measureTimeMillis {runBlocking {val channel = Channel<Unit>()// 创建两个协程进行上下文切换val sender = launch {repeat(switchCount) {channel.send(Unit)}}val receiver = launch {repeat(switchCount) {channel.receive()}}// 等待两个协程完成sender.join()receiver.join()channel.close()}}println("$switchCount 次协程上下文切换耗时: $coroutineTime ms")println("每次协程上下文切换平均耗时: ${coroutineTime.toDouble() / switchCount * 1000} μs")// 测试线程上下文切换性能val threadTime = measureTimeMillis {val latch = CountDownLatch(1)val counter = AtomicLong(0)// 创建两个线程进行上下文切换val thread1 = Thread {latch.await()while (counter.get() < switchCount * 2) {if (counter.getAndIncrement() % 2 == 0) {// 线程1的工作}}}val thread2 = Thread {latch.await()while (counter.get() < switchCount * 2) {if (counter.getAndIncrement() % 2 == 1) {// 线程2的工作}}}thread1.start()thread2.start()// 开始计时latch.countDown()// 等待两个线程完成thread1.join()thread2.join()}println("$switchCount 次线程上下文切换耗时: $threadTime ms")println("每次线程上下文切换平均耗时: ${threadTime.toDouble() / switchCount * 1000} μs")
}

import kotlinx.coroutines.*
import java.io.*
import java.net.*
import java.util.concurrent.*fun main() = runBlocking {val taskCount = 10_000// 测试协程处理IO密集型任务的吞吐量val coroutineTime = measureTimeMillis {runBlocking {val jobs = mutableListOf<Job>()repeat(taskCount) {jobs.add(launch(Dispatchers.IO) {// 模拟IO操作withContext(Dispatchers.IO) {val socket = Socket("localhost", 8080)val out = PrintWriter(socket.getOutputStream(), true)val inp = BufferedReader(InputStreamReader(socket.getInputStream()))out.println("GET / HTTP/1.1")out.println("Host: localhost")out.println()inp.readLine() // 读取响应socket.close()}})}// 等待所有协程完成jobs.forEach { it.join() }}}println("协程处理 $taskCount 个IO密集型任务耗时: $coroutineTime ms")println("协程吞吐量: ${taskCount.toDouble() / coroutineTime * 1000} 请求/秒")// 测试线程处理IO密集型任务的吞吐量val threadTime = measureTimeMillis {val executorService = Executors.newFixedThreadPool(1000)val futures = mutableListOf<Future<*>>()repeat(taskCount) {futures.add(executorService.submit {// 模拟IO操作val socket = Socket("localhost", 8080)val out = PrintWriter(socket.getOutputStream(), true)val inp = BufferedReader(InputStreamReader(socket.getInputStream()))out.println("GET / HTTP/1.1")out.println("Host: localhost")out.println()inp.readLine() // 读取响应socket.close()})}// 等待所有任务完成futures.forEach { it.get() }executorService.shutdown()}println("线程处理 $taskCount 个IO密集型任务耗时: $threadTime ms")println("线程吞吐量: ${taskCount.toDouble() / threadTime * 1000} 请求/秒")
}

suspend fun fetchData() = coroutineScope {val data1 = async { fetchFromSource1() }val data2 = async { fetchFromSource2() }data1.await() + data2.await()

}

suspend fun processTasks() = supervisorScope {launch {// 可能失败的任务1throw RuntimeException("任务1失败")}launch {// 不受影响的任务2println("任务2正常执行")}
}

class MyViewModel : ViewModel() {val viewModelJob = Job()val viewModelScope = CoroutineScope(Dispatchers.Default + viewModelJob)init {viewModelScope.launch {// 执行一些异步任务}}override fun onCleared() {super.onCleared()viewModelJob.cancel()}
}

// 不好的示例：将简单计算封装为挂起函数
suspend fun simpleCalculate(a: Int, b: Int): Int {return a + b
}// 好的示例：使用普通函数
fun simpleCalculate(a: Int, b: Int): Int {return a + b
}

suspend fun fetchMultipleData(): List<Any> {val data1 = withContext(Dispatchers.IO) { fetchData1() }val data2 = withContext(Dispatchers.IO) { fetchData2() }return listOf(data1, data2)
}

suspend fun complexTask() {// 先进行CPU密集型计算val result1 = withContext(Dispatchers.Default) { cpuIntensiveCalculation() }// 再进行IO操作val result2 = withContext(Dispatchers.IO) { ioOperation(result1) }
}

import kotlinx.coroutines.*
import java.util.concurrent.ConcurrentLinkedQueueclass CoroutinePool(private val maxSize: Int,private val dispatcher: CoroutineDispatcher
) : Closeable {private val idleCoroutines = ConcurrentLinkedQueue<Job>()private val activeCoroutines = mutableSetOf<Job>()suspend fun <T> submit(block: suspend CoroutineScope.() -> T): T {val job = idleCoroutines.poll() ?: launchNewCoroutine()val result = runBlocking {job.join()job.get()}return result}private fun launchNewCoroutine(): Job {val job = GlobalScope.launch(dispatcher) {try {yield()} finally {synchronized(this) {activeCoroutines.remove(this)idleCoroutines.add(this)}}}synchronized(this) {activeCoroutines.add(job)if (activeCoroutines.size > maxSize) {throw IllegalStateException("协程池已满")}}return job}override fun close() {activeCoroutines.forEach { it.cancel() }}
}

fun main() = runBlocking {val coroutinePool = CoroutinePool(10, Dispatchers.Default)repeat(20) {val result = coroutinePool.submit {// 协程任务逻辑delay(100)it}println(result)}coroutinePool.close()
}

// 创建处理CPU密集型任务的线程池
ExecutorService cpuThreadPool = new ThreadPoolExecutor(Runtime.getRuntime().availableProcessors() + 1,Runtime.getRuntime().availableProcessors() + 1,0L, TimeUnit.MILLISECONDS,new LinkedBlockingQueue<>()
);// 创建处理IO密集型任务的线程池
ExecutorService ioThreadPool = new ThreadPoolExecutor(Runtime.getRuntime().availableProcessors() * 2,Runtime.getRuntime().availableProcessors() * 2,0L, TimeUnit.MILLISECONDS,new LinkedBlockingQueue<>()
);

// 使用ArrayBlockingQueue的线程池
ExecutorService arrayBlockingThreadPool = new ThreadPoolExecutor(5, 10,60L, TimeUnit.SECONDS,new ArrayBlockingQueue<>(100)
);// 使用LinkedBlockingQueue的线程池
ExecutorService linkedBlockingThreadPool = new ThreadPoolExecutor(5, 10,60L, TimeUnit.SECONDS,new LinkedBlockingQueue<>()
);// 使用SynchronousQueue的线程池
ExecutorService synchronousQueueThreadPool = new ThreadPoolExecutor(5, 10,60L, TimeUnit.SECONDS,new SynchronousQueue<>()
);

ThreadFactory namedThreadFactory = new ThreadFactory() {private final AtomicInteger threadNumber = new AtomicInteger(1);@Overridepublic Thread newThread(Runnable r) {Thread thread = new Thread(r, "MyThreadPool-" + threadNumber.getAndIncrement());thread.setPriority(Thread.NORM_PRIORITY);return thread;}
};ExecutorService namedThreadPool = new ThreadPoolExecutor(5, 10,60L, TimeUnit.SECONDS,new LinkedBlockingQueue<>(),namedThreadFactory
);

// 使用CallerRunsPolicy拒绝策略的线程池
ExecutorService callerRunsThreadPool = new ThreadPoolExecutor(5, 10,60L, TimeUnit.SECONDS,new LinkedBlockingQueue<>(10),new ThreadPoolExecutor.CallerRunsPolicy()
);

class DataContainer {private int data1;private int data2;// 不好的示例：对整个方法加锁public synchronized void updateData(int newData1, int newData2) {data1 = newData1;data2 = newData2;}// 好的示例：减小锁的粒度public void updateDataBetter(int newData1, int newData2) {synchronized (this) {data1 = newData1;}synchronized (this) {data2 = newData2;}}
}

// 使用ReentrantLock示例
class LockExample {private final ReentrantLock lock = new ReentrantLock();private int sharedData;public void updateData(int newData) {lock.lock();try {sharedData = newData;} finally {lock.unlock();}}
}// 使用ReadWriteLock示例
class ReadWriteLockExample {private final ReadWriteLock readWriteLock = new ReentrantReadWriteLock();private int sharedData;public void readData() {readWriteLock.readLock().lock();try {// 读取操作} finally {readWriteLock.readLock().unlock();}}public void writeData(int newData) {readWriteLock.writeLock().lock();try {sharedData = newData;} finally {readWriteLock.writeLock().unlock();}}
}// 使用StampedLock示例
class StampedLockExample {private final StampedLock stampedLock = new StampedLock();private int sharedData;public void optimisticRead() {long stamp = stampedLock.tryOptimisticRead();int data = sharedData;if (!stampedLock.validate(stamp)) {stamp = stampedLock.readLock();try {data = sharedData;} finally {stampedLock.unlockRead(stamp);}}// 使用data进行操作}public void writeData(int newData) {long stamp = stampedLock.writeLock();try {sharedData = newData;} finally {stampedLock.unlockWrite(stamp);}}
}

// Java NIO示例：非阻塞网络连接
try (Selector selector = Selector.open();SocketChannel socketChannel = SocketChannel.open()) {socketChannel.configureBlocking(false);socketChannel.connect(new InetSocketAddress("localhost", 8080));socketChannel.register(selector, SelectionKey.OP_CONNECT);while (selector.select() > 0) {Set<SelectionKey> selectedKeys = selector.selectedKeys();Iterator<SelectionKey> keyIterator = selectedKeys.iterator();while (keyIterator.hasNext()) {SelectionKey key = keyIterator.next();if (key.isConnectable()) {SocketChannel channel = (SocketChannel) key.channel();if (channel.finishConnect()) {// 连接成功，进行后续操作}}keyIterator.remove();}}
} catch (IOException e) {e.printStackTrace();
}

// Kotlin中使用OkHttp进行异步网络请求示例
import okhttp3.*
import kotlinx.coroutines.*suspend fun fetchData(): String {val client = OkHttpClient()val request = Request.Builder().url("https://example.com/api/data").build()return withContext(Dispatchers.IO)

return withContext(Dispatchers.IO) {client.newCall(request).execute().use { response ->if (!response.isSuccessful) throw IOException("Unexpected code $response")response.body?.string() ?: ""}}
}

// 使用ConcurrentHashMap示例
ConcurrentHashMap<String, Integer> concurrentMap = new ConcurrentHashMap<>();// 线程安全的put操作
concurrentMap.put("key", 1);// 线程安全的computeIfAbsent操作
concurrentMap.computeIfAbsent("key", k -> 0);

// 使用Condition示例
class BoundedBuffer {private final Lock lock = new ReentrantLock();private final Condition notFull = lock.newCondition();private final Condition notEmpty = lock.newCondition();private final Object[] items = new Object[100];private int count, putptr, takeptr;public void put(Object x) throws InterruptedException {lock.lock();try {while (count == items.length)notFull.await();items[putptr] = x;if (++putptr == items.length)putptr = 0;++count;notEmpty.signal();} finally {lock.unlock();}}public Object take() throws InterruptedException {lock.lock();try {while (count == 0)notEmpty.await();Object x = items[takeptr];if (++takeptr == items.length)takeptr = 0;--count;notFull.signal();return x;} finally {lock.unlock();}}
}

import org.openjdk.jmh.annotations.*;
import org.openjdk.jmh.runner.Runner;
import org.openjdk.jmh.runner.RunnerException;
import org.openjdk.jmh.runner.options.Options;
import org.openjdk.jmh.runner.options.OptionsBuilder;import java.util.concurrent.TimeUnit;@BenchmarkMode(Mode.AverageTime)
@OutputTimeUnit(TimeUnit.MILLISECONDS)
@Warmup(iterations = 5, time = 1, timeUnit = TimeUnit.SECONDS)
@Measurement(iterations = 5, time = 1, timeUnit = TimeUnit.SECONDS)
@Fork(1)
@State(Scope.Benchmark)
public class CoroutineVsThreadBenchmark {private int taskCount = 1000;@Benchmarkpublic void testThreads() throws InterruptedException {Thread[] threads = new Thread[taskCount];for (int i = 0; i < taskCount; i++) {threads[i] = new Thread(() -> {// 模拟任务执行try {Thread.sleep(10);} catch (InterruptedException e) {e.printStackTrace();}});threads[i].start();}for (Thread thread : threads) {thread.join();}}public static void main(String[] args) throws RunnerException {Options opt = new OptionsBuilder().include(CoroutineVsThreadBenchmark.class.getSimpleName()).build();new Runner(opt).run();}
}

import kotlinx.coroutines.*
import kotlinx.coroutines.test.*
import org.junit.Test
import java.util.concurrent.CountDownLatch
import kotlin.system.measureTimeMillisclass CoroutinePerformanceTest {@Testfun testCoroutinePerformance() = runBlockingTest {val scope = TestCoroutineScope()val taskCount = 1000val latch = CountDownLatch(taskCount)val time = measureTimeMillis {repeat(taskCount) {scope.launch {// 模拟任务执行delay(10)latch.countDown()}}latch.await()}println("执行 $taskCount 个协程任务耗时: $time ms")}
}

class MainViewModel : ViewModel() {private val viewModelScope = CoroutineScope(Dispatchers.Main + Job())fun fetchData() {viewModelScope.launch {try {// 显示加载状态_isLoading.value = true// 在IO线程执行网络请求val data = withContext(Dispatchers.IO) {repository.fetchData()}// 更新UI_data.value = data} catch (e: Exception) {// 处理异常_error.value = e.message} finally {// 隐藏加载状态_isLoading.value = false}}}override fun onCleared() {super.onCleared()// 取消所有协程viewModelScope.cancel()}
}

fun Application.module() {routing {get("/data") {// 处理HTTP请求的协程val data = withContext(Dispatchers.IO) {// 从数据库或其他数据源获取数据repository.getData()}call.respond(data)}}
}

fun fetchDataFlow(): Flow<Data> = flow {// 在IO线程执行withContext(Dispatchers.IO) {// 模拟分批获取数据repeat(10) {delay(100)emit(Data("Data $it"))}}
}// 在ViewModel中使用
viewModelScope.launch {fetchDataFlow().flowOn(Dispatchers.IO).collect { data ->// 更新UI_dataList.value = _dataList.value + data}
}

public class ImageProcessor {private final int threadCount = Runtime.getRuntime().availableProcessors();public BufferedImage processImage(BufferedImage image) {int width = image.getWidth();int height = image.getHeight();BufferedImage result = new BufferedImage(width, height, image.getType());// 计算每个线程处理的行数int rowsPerThread = height / threadCount;// 创建并启动线程Thread[] threads = new Thread[threadCount];for (int i = 0; i < threadCount; i++) {final int startRow = i * rowsPerThread;final int endRow = (i == threadCount - 1) ? height : (i + 1) * rowsPerThread;threads[i] = new Thread(() -> {for (int y = startRow; y < endRow; y++) {for (int x = 0; x < width; x++) {// 处理像素int pixel = image.getRGB(x, y);int processedPixel = processPixel(pixel);result.setRGB(x, y, processedPixel);}}});threads[i].start();}// 等待所有线程完成for (Thread thread : threads) {try {thread.join();} catch (InterruptedException e) {e.printStackTrace();}}return result;}private int processPixel(int pixel) {// 图像处理逻辑// ...return pixel;}
}