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
