Java并发编程 - 线程安全性之原子性（一）

AtomicInteger（Long） 源码分析

• 拿当前对象的值和底层的值进行对比，前对象的值和底层的值一致时执行对应的操作，不一样就不停取最新的值，直到相同的时候才执行操作。
• 所谓CAS（Compare And Swap）即比较（工作内存与主内存）并交换，CAS 演示原子性操作：Atomic 类原码实现的时候用了unsafe 类，unsafe.getAndAddInt(); 核心方法都是compareAndSwapInt，用native标识，说明这是Java底层的方法，值的更新都放在了底层，循环判断，期望值和比较值一致时才会替换。

package com.mmall.concurrency.example.atomic;

import com.mmall.concurrency.annoations.ThreadSafe;
import lombok.extern.slf4j.Slf4j;
import java.util.concurrent.CountDownLatch;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
import java.util.concurrent.Semaphore;
import java.util.concurrent.atomic.AtomicInteger;

@Slf4j
@ThreadSafe
public class AtomicExample1 {

    // 请求总数
    public static int clientTotal = 5000;

    // 同时并发执行的线程数
    public static int threadTotal = 200;

    public static AtomicInteger count = new AtomicInteger(0);

    public static void main(String[] args) throws Exception {
        ExecutorService executorService = Executors.newCachedThreadPool();
        final Semaphore semaphore = new Semaphore(threadTotal);
        final CountDownLatch countDownLatch = new CountDownLatch(clientTotal);
        for (int i = 0; i < clientTotal ; i++) {
            executorService.execute(() -> {
                try {
                    semaphore.acquire();
                    add();
                    semaphore.release();
                } catch (Exception e) {
                    log.error("exception", e);
                }
                countDownLatch.countDown();
            });
        }
        countDownLatch.await();
        executorService.shutdown();
        log.info("count:{}", count.get());
    }

    private static void add() {
        count.incrementAndGet();
        // count.getAndIncrement();
    }
}

LongAddr 源码分析

• JDK8 单独新增一个LongAdder类，和AtomicLong 类似， Atomic 类修改类，在高并发情况下，原子操作修改失败率比较高， LongAddr 核心将热点数据分离，它会将AtomicLong里的合一数据 value 分离成一个数组，每个线程访问通过 hash 等算法映射到数组中的其中的数字进行计数，计数的最终结果是这个数组的求和累加，其中热点数据 value 会分离成多个单元cell，每个cell单独管理，将单点的更新压力分散到其他节点上。LongAdder在高并发竞争锁时，会有数据丢失。在序列号生成，全局唯一的数据还是要用AtomicLong。

package com.mmall.concurrency.example.atomic;

import com.mmall.concurrency.annoations.ThreadSafe;
import lombok.extern.slf4j.Slf4j;
import java.util.concurrent.CountDownLatch;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
import java.util.concurrent.Semaphore;
import java.util.concurrent.atomic.AtomicLong;
import java.util.concurrent.atomic.LongAdder;

@Slf4j
@ThreadSafe
public class AtomicExample3 {

    // 请求总数
    public static int clientTotal = 5000;

    // 同时并发执行的线程数
    public static int threadTotal = 200;

    public static LongAdder count = new LongAdder();

    public static void main(String[] args) throws Exception {
        ExecutorService executorService = Executors.newCachedThreadPool();
        final Semaphore semaphore = new Semaphore(threadTotal);
        final CountDownLatch countDownLatch = new CountDownLatch(clientTotal);
        for (int i = 0; i < clientTotal ; i++) {
            executorService.execute(() -> {
                try {
                    semaphore.acquire();
                    add();
                    semaphore.release();
                } catch (Exception e) {
                    log.error("exception", e);
                }
                countDownLatch.countDown();
            });
        }
        countDownLatch.await();
        executorService.shutdown();
        log.info("count:{}", count);
    }

    private static void add() {
        count.increment();
    }
}

总结

• 高并发下用LongAdder
• 低并发下用AtomicLong
• 对数据准确性要求高用AtomicLong
• LongAdder准确性会有误差