承接Spring源码情操陶冶-自定义节点的解析。线程池是jdk的一个很重要的概念，在很多的场景都会应用到，多用于处理多任务的并发处理，此处借由spring整合jdk的cocurrent包的方式来进行深入的分析
spring配置文件样例
配置简单线程池
<task:executor keep-alive="60" queue-capacity="20" pool-size="5" rejection-policy="DISCARD">
</task:executor>
以上属性是spring基于task命令空间提供的对外属性，一般是线程池的基础属性，我们可以剖析下相应的解析类具体了解下spring是如何整合线程池的
ExecutorBeanDefinitionParser-解析task-executor节点
- 我们可以直接看下解析的具体方法
doParse()，代码如下
@Override
protected void doParse(Element element, ParserContext parserContext, BeanDefinitionBuilder builder) {
String keepAliveSeconds = element.getAttribute("keep-alive");
if (StringUtils.hasText(keepAliveSeconds)) {
builder.addPropertyValue("keepAliveSeconds", keepAliveSeconds);
}
String queueCapacity = element.getAttribute("queue-capacity");
if (StringUtils.hasText(queueCapacity)) {
builder.addPropertyValue("queueCapacity", queueCapacity);
}
configureRejectionPolicy(element, builder);
String poolSize = element.getAttribute("pool-size");
if (StringUtils.hasText(poolSize)) {
builder.addPropertyValue("poolSize", poolSize);
}
}
很简单就是读取我们第一部分所罗列的属性值，并塞入至BeanDefinitionBuilder对象的属性集合中。借此
对任务的拒绝策略属性解析方法configureRejectionPolicy()我们也可以简单的看下
private void configureRejectionPolicy(Element element, BeanDefinitionBuilder builder) {
String rejectionPolicy = element.getAttribute("rejection-policy");
if (!StringUtils.hasText(rejectionPolicy)) {
return;
}
String prefix = "java.util.concurrent.ThreadPoolExecutor.";
if (builder.getRawBeanDefinition().getBeanClassName().contains("backport")) {
prefix = "edu.emory.mathcs.backport." + prefix;
}
String policyClassName;
if (rejectionPolicy.equals("ABORT")) {
policyClassName = prefix + "AbortPolicy";
}
else if (rejectionPolicy.equals("CALLER_RUNS")) {
policyClassName = prefix + "CallerRunsPolicy";
}
else if (rejectionPolicy.equals("DISCARD")) {
policyClassName = prefix + "DiscardPolicy";
}
else if (rejectionPolicy.equals("DISCARD_OLDEST")) {
policyClassName = prefix + "DiscardOldestPolicy";
}
else {
policyClassName = rejectionPolicy;
}
builder.addPropertyValue("rejectedExecutionHandler", new RootBeanDefinition(policyClassName));
}
由此可看出拒绝策略采取的基本上是java.util.concurrent.ThreadPoolExecutor工具包下的静态内部类，同时也支持用户自定义的拒绝策略，只需要实现RejectedExecutionHandler接口即可。对拒绝策略此处作下小总结
| rejection-policy(Spring)| jdk对应类 | 含义 |
| :-------- | --------:| :------: |
| ABORT | java.util.concurrent.ThreadPoolExecutor.AbortPolicy | 抛出拒绝的异常信息 |
| CALLER_RUNS | java.util.concurrent.ThreadPoolExecutor.CallerRunsPolicy | 直接执行对应的任务(线程池不关闭) |
| DISCARD | java.util.concurrent.ThreadPoolExecutor.DiscardPolicy | 直接丢弃任务 |
| DISCARD_OLDEST | java.util.concurrent.ThreadPoolExecutor.DiscardOldestPolicy | 直接丢弃队列最老的任务(最靠头部)，塞入此任务到队列尾部 |
- bean实体类
那么我们肯定要知道是spring的哪个bean来实例化我们的线程池配置呢?答案就在getBeanClassName()方法
@Override
protected String getBeanClassName(Element element) {
return "org.springframework.scheduling.config.TaskExecutorFactoryBean";
}
直接通过TaskExecutorFactoryBeanbean工厂来实例化线程池，很有意思，我们也别忘了其获取实例化对象其实是调用了其内部的getObject()方法。我们继续跟踪把
TaskExecutorFactoryBean-线程池bean工厂类
看继承结构，我们细心的发现其实现了InitializingBean接口，那我们直接关注afterPropertiesSet()方法
@Override
public void afterPropertiesSet() throws Exception {
// 实例化的bean类型为ThreadPoolTaskExecutor
BeanWrapper bw = new BeanWrapperImpl(ThreadPoolTaskExecutor.class);
determinePoolSizeRange(bw);
// 基本属性保存
if (this.queueCapacity != null) {
bw.setPropertyValue("queueCapacity", this.queueCapacity);
}
if (this.keepAliveSeconds != null) {
bw.setPropertyValue("keepAliveSeconds", this.keepAliveSeconds);
}
if (this.rejectedExecutionHandler != null) {
bw.setPropertyValue("rejectedExecutionHandler", this.rejectedExecutionHandler);
}
if (this.beanName != null) {
bw.setPropertyValue("threadNamePrefix", this.beanName + "-");
}
// 实例化ThreadPoolTaskExecutor对象
this.target = (TaskExecutor) bw.getWrappedInstance();
// 并执行相应的afterPropertiesSet方法
if (this.target instanceof InitializingBean) {
((InitializingBean) this.target).afterPropertiesSet();
}
}
真正实例化的对象为
org.springframework.scheduling.concurrent.ThreadPoolTaskExecutor
task-executor指定的pool-size支持-作为分隔符，比如2-4，表示线程池核心线程数为2个，最大线程数为4；如果没有分隔符，则最大线程数等同于核心线程数
task-executor如果指定pool-size为0-4且queue-capacity为null，则会指定线程池的allowCoreThreadTimeout为true，表明支持核心线程超时释放，默认不支持
ThreadPoolTaskExecutor.class也是InitializingBean的实现类，也会被调用afterPropertiesSet()方法
ThreadPoolTaskExecutor#afterPropertiesSet()-实例化
直接查看initializeExecutor()初始化jdk对应的线程池
// 默认的rejectedExecutionHandler为AbortPolicy策略
@Override
protected ExecutorService initializeExecutor(
ThreadFactory threadFactory, RejectedExecutionHandler rejectedExecutionHandler) {
// 先创建阻塞的队列
BlockingQueue<Runnable> queue = createQueue(this.queueCapacity);
// 创建线程池
ThreadPoolExecutor executor = new ThreadPoolExecutor(
this.corePoolSize, this.maxPoolSize, this.keepAliveSeconds, TimeUnit.SECONDS,
queue, threadFactory, rejectedExecutionHandler);
// 设置是否允许核心线程超时被收回。默认不允许
if (this.allowCoreThreadTimeOut) {
executor.allowCoreThreadTimeOut(true);
}
this.threadPoolExecutor = executor;
return executor;
}
我们按照上述的注释，按照两步走进行解析
- 阻塞队列的创建
protected BlockingQueue<Runnable> createQueue(int queueCapacity) {
if (queueCapacity > 0) {
return new LinkedBlockingQueue<Runnable>(queueCapacity);
}
else {
return new SynchronousQueue<Runnable>();
}
}
默认情况下是创建LinkedBlockingQueue链式队列，因为默认的queueCapacity大小为Integer.MAX_VALUE。而queueCapacity为0的情况下则采取SynchronousQueue同步队列，其约定塞入一个元素必须等待另外的线程消费其内部的一个元素，其内部最多指定一个元素用于被消费
- 线程池创建
用到最基本的构造方法ThreadPoolExecutor()
/**
* Creates a new {@code ThreadPoolExecutor} with the given initial
* parameters.
*
* @param corePoolSize the number of threads to keep in the pool, even
* if they are idle, unless {@code allowCoreThreadTimeOut} is set
* @param maximumPoolSize the maximum number of threads to allow in the
* pool
* @param keepAliveTime when the number of threads is greater than
* the core, this is the maximum time that excess idle threads
* will wait for new tasks before terminating.
* @param unit the time unit for the {@code keepAliveTime} argument
* @param workQueue the queue to use for holding tasks before they are
* executed. This queue will hold only the {@code Runnable}
* tasks submitted by the {@code execute} method.
* @param threadFactory the factory to use when the executor
* creates a new thread
* @param handler the handler to use when execution is blocked
* because the thread bounds and queue capacities are reached
* @throws IllegalArgumentException if one of the following holds:<br>
* {@code corePoolSize < 0}<br>
* {@code keepAliveTime < 0}<br>
* {@code maximumPoolSize <= 0}<br>
* {@code maximumPoolSize < corePoolSize}
* @throws NullPointerException if {@code workQueue}
* or {@code threadFactory} or {@code handler} is null
*/
public ThreadPoolExecutor(int corePoolSize,
int maximumPoolSize,
long keepAliveTime,
TimeUnit unit,
BlockingQueue<Runnable> workQueue,
ThreadFactory threadFactory,
RejectedExecutionHandler handler) {
if (corePoolSize < 0 ||
maximumPoolSize <= 0 ||
maximumPoolSize < corePoolSize ||
keepAliveTime < 0)
throw new IllegalArgumentException();
if (workQueue == null || threadFactory == null || handler == null)
throw new NullPointerException();
this.corePoolSize = corePoolSize;
this.maximumPoolSize = maximumPoolSize;
this.workQueue = workQueue;
this.keepAliveTime = unit.toNanos(keepAliveTime);
this.threadFactory = threadFactory;
this.handler = handler;
}
篇幅限于过长，具体就不解释了直接看注释就明白了
TaskExecutorFactoryBean#getObject()-获取实体类
public TaskExecutor getObject() {
return this.target;
}
由上述可知this.target对应的class类为ThreadPoolTaskExecutor，其内部已实例化了ThreadPoolExecutor线程池对象
小结
Spring创建线程池本质上是通过
ThreadPoolExecutor的构造方法来进行创建的。由此可知jdk的concurrent工具包很有参考价值Spring默认指定的线程池队列为
LinkedBlockingQueue链式队列，默认支持无限的任务添加，用户也可以指定queue-capacity来指定队列接受的最多任务数；并默认采用AbortPolicy策略来拒绝多余的任务Spring指定的
pool-size支持-分隔符，具体解释见上文Spring的
task-executor实例化后，用户可通过下述方式调用获取
java TaskExecutor executor = ((TaskExecutorFactoryBean)applicationContext.getBean(TaskExecutorFactoryBean)).getObject();