原文：http://www.iteye.com/topic/1118660
整个ThreadPoolExecutor的任务处理有4步操作：
- 第一步，初始的poolSize < corePoolSize，提交的runnable任务，会直接做为new一个Thread的参数，立马执行
- 第二步，当提交的任务数超过了corePoolSize，就进入了第二步操作。会将当前的runable提交到一个block queue中
- 第三步，如果block queue是个有界队列，当队列满了之后就进入了第三步。如果poolSize < maximumPoolsize时，会尝试new 一个Thread的进行救急处理，立马执行对应的runnable任务
- 第四步，如果第三步救急方案也无法处理了，就会走到第四步执行reject操作。
几点说明：(相信这些网上一搜一大把，我这里简单介绍下，为后面做一下铺垫)
- block queue有以下几种实现：
1. ArrayBlockingQueue : 有界的数组队列
2. LinkedBlockingQueue : 可支持有界/无界的队列，使用链表实现
3. PriorityBlockingQueue : 优先队列，可以针对任务排序
4. SynchronousQueue : 队列长度为1的队列，和Array有点区别就是：client thread提交到block queue会是一个阻塞过程，直到有一个worker thread连接上来poll task。 - RejectExecutionHandler是针对任务无法处理时的一些自保护处理：
1. Reject 直接抛出Reject exception
2. Discard 直接忽略该runnable，不可取
3. DiscardOldest 丢弃最早入队列的的任务
4. CallsRun 直接让原先的client thread做为worker线程，进行执行
容易被人忽略的点：
1. pool threads启动后，以后的任务获取都会通过block queue中，获取堆积的runnable task.
所以建议：
block size >= corePoolSize ，不然线程池就没任何意义
2. corePoolSize 和 maximumPoolSize的区别， 和大家正常理解的数据库连接池不太一样。
* 据dbcp pool为例，会有minIdle , maxActive配置。minIdle代表是常驻内存中的threads数量，maxActive代表是工作的最大线程数。
* 这里的corePoolSize就是连接池的maxActive的概念，它没有minIdle的概念(每个线程可以设置keepAliveTime，超过多少时间多有任务后销毁线程，但不会固定保持一定数量的threads)。
* 这里的maximumPoolSize，是一种救急措施的第一层。当threadPoolExecutor的工作threads存在满负荷，并且block queue队列也满了，这时代表接近崩溃边缘。这时允许临时起一批threads，用来处理runnable，处理完后立马退出。
所以建议：
maximumPoolSize >= corePoolSize =期望的最大线程数。 (我曾经配置了corePoolSize=1, maximumPoolSize=20, blockqueue为无界队列，最后就成了单线程工作的pool。典型的配置错误)
3. 善用blockqueue和reject组合. 这里要重点推荐下CallsRun的Rejected Handler，从字面意思就是让调用者自己来运行。
我们经常会在线上使用一些线程池做异步处理，比如我前面做的
(业务层)异步并行加载技术分析和设计, 将原本串行的请求都变为了并行操作，但过多的并行会增加系统的负载(比如软中断，上下文切换)。所以肯定需要对线程池做一个size限制。但是为了引入异步操作后，避免因在block queue的等待时间过长，所以需要在队列满的时，执行一个callsRun的策略，并行的操作又转为一个串行处理，这样就可以保证尽量少的延迟影响。
所以建议：
RejectExecutionHandler = CallsRun , blockqueue size = 2 * poolSize (为啥是2倍poolSize，主要一个考虑就是瞬间高峰处理，允许一个thread等待一个runnable任务)
Btrace容量规划
再提供一个btrace脚本，分析线上的thread pool容量规划是否合理，可以运行时输出poolSize等一些数据。
- import static com.sun.btrace.BTraceUtils.addToAggregation;
- import static com.sun.btrace.BTraceUtils.field;
- import static com.sun.btrace.BTraceUtils.get;
- import static com.sun.btrace.BTraceUtils.newAggregation;
- import static com.sun.btrace.BTraceUtils.newAggregationKey;
- import static com.sun.btrace.BTraceUtils.printAggregation;
- import static com.sun.btrace.BTraceUtils.println;
- import static com.sun.btrace.BTraceUtils.str;
- import static com.sun.btrace.BTraceUtils.strcat;
- import java.lang.reflect.Field;
- import java.util.concurrent.atomic.AtomicInteger;
- import com.sun.btrace.BTraceUtils;
- import com.sun.btrace.aggregation.Aggregation;
- import com.sun.btrace.aggregation.AggregationFunction;
- import com.sun.btrace.aggregation.AggregationKey;
- import com.sun.btrace.annotations.BTrace;
- import com.sun.btrace.annotations.Kind;
- import com.sun.btrace.annotations.Location;
- import com.sun.btrace.annotations.OnEvent;
- import com.sun.btrace.annotations.OnMethod;
- import com.sun.btrace.annotations.OnTimer;
- import com.sun.btrace.annotations.Self;
- /**
- * 并行加载监控
- *
- * @author jianghang 2011-4-7 下午10:59:53
- */
- @BTrace
- public class AsyncLoadTracer {
- private static AtomicInteger rejecctCount = BTraceUtils.newAtomicInteger(0);
- private static Aggregation histogram = newAggregation(AggregationFunction.QUANTIZE);
- private static Aggregation average = newAggregation(AggregationFunction.AVERAGE);
- private static Aggregation max = newAggregation(AggregationFunction.MAXIMUM);
- private static Aggregation min = newAggregation(AggregationFunction.MINIMUM);
- private static Aggregation sum = newAggregation(AggregationFunction.SUM);
- private static Aggregation count = newAggregation(AggregationFunction.COUNT);
- @OnMethod(clazz = "java.util.concurrent.ThreadPoolExecutor", method = "execute", location = @Location(value = Kind.ENTRY))
- public static void executeMonitor(@Self Object self) {
- Field poolSizeField = field("java.util.concurrent.ThreadPoolExecutor", "poolSize");
- Field largestPoolSizeField = field("java.util.concurrent.ThreadPoolExecutor", "largestPoolSize");
- Field workQueueField = field("java.util.concurrent.ThreadPoolExecutor", "workQueue");
- Field countField = field("java.util.concurrent.ArrayBlockingQueue", "count");
- int poolSize = (Integer) get(poolSizeField, self);
- int largestPoolSize = (Integer) get(largestPoolSizeField, self);
- int queueSize = (Integer) get(countField, get(workQueueField, self));
- println(strcat(strcat(strcat(strcat(strcat("poolSize : ", str(poolSize)), " largestPoolSize : "),
- str(largestPoolSize)), " queueSize : "), str(queueSize)));
- }
- @OnMethod(clazz = "java.util.concurrent.ThreadPoolExecutor", method = "reject", location = @Location(value = Kind.ENTRY))
- public static void rejectMonitor(@Self Object self) {
- String name = str(self);
- if (BTraceUtils.startsWith(name, "com.alibaba.pivot.common.asyncload.impl.pool.AsyncLoadThreadPool")) {
- BTraceUtils.incrementAndGet(rejecctCount);
- }
- }
- @OnTimer(1000)
- public static void rejectPrintln() {
- int reject = BTraceUtils.getAndSet(rejecctCount, 0);
- println(strcat("reject count in 1000 msec: ", str(reject)));
- AggregationKey key = newAggregationKey("rejectCount");
- addToAggregation(histogram, key, reject);
- addToAggregation(average, key, reject);
- addToAggregation(max, key, reject);
- addToAggregation(min, key, reject);
- addToAggregation(sum, key, reject);
- addToAggregation(count, key, reject);
- }
- @OnEvent
- public static void onEvent() {
- BTraceUtils.truncateAggregation(histogram, 10);
- println("---------------------------------------------");
- printAggregation("Count", count);
- printAggregation("Min", min);
- printAggregation("Max", max);
- printAggregation("Average", average);
- printAggregation("Sum", sum);
- printAggregation("Histogram", histogram);
- println("---------------------------------------------");
- }
- }
import static com.sun.btrace.BTraceUtils.addToAggregation;
import static com.sun.btrace.BTraceUtils.field;
import static com.sun.btrace.BTraceUtils.get;
import static com.sun.btrace.BTraceUtils.newAggregation;
import static com.sun.btrace.BTraceUtils.newAggregationKey;
import static com.sun.btrace.BTraceUtils.printAggregation;
import static com.sun.btrace.BTraceUtils.println;
import static com.sun.btrace.BTraceUtils.str;
import static com.sun.btrace.BTraceUtils.strcat;
import java.lang.reflect.Field;
import java.util.concurrent.atomic.AtomicInteger;
import com.sun.btrace.BTraceUtils;
import com.sun.btrace.aggregation.Aggregation;
import com.sun.btrace.aggregation.AggregationFunction;
import com.sun.btrace.aggregation.AggregationKey;
import com.sun.btrace.annotations.BTrace;
import com.sun.btrace.annotations.Kind;
import com.sun.btrace.annotations.Location;
import com.sun.btrace.annotations.OnEvent;
import com.sun.btrace.annotations.OnMethod;
import com.sun.btrace.annotations.OnTimer;
import com.sun.btrace.annotations.Self;
/**
* 并行加载监控
*
* @author jianghang 2011-4-7 下午10:59:53
*/
@BTrace
public class AsyncLoadTracer {
private static AtomicInteger rejecctCount = BTraceUtils.newAtomicInteger(0);
private static Aggregation histogram = newAggregation(AggregationFunction.QUANTIZE);
private static Aggregation average = newAggregation(AggregationFunction.AVERAGE);
private static Aggregation max = newAggregation(AggregationFunction.MAXIMUM);
private static Aggregation min = newAggregation(AggregationFunction.MINIMUM);
private static Aggregation sum = newAggregation(AggregationFunction.SUM);
private static Aggregation count = newAggregation(AggregationFunction.COUNT);
@OnMethod(clazz = "java.util.concurrent.ThreadPoolExecutor", method = "execute", location = @Location(value = Kind.ENTRY))
public static void executeMonitor(@Self Object self) {
Field poolSizeField = field("java.util.concurrent.ThreadPoolExecutor", "poolSize");
Field largestPoolSizeField = field("java.util.concurrent.ThreadPoolExecutor", "largestPoolSize");
Field workQueueField = field("java.util.concurrent.ThreadPoolExecutor", "workQueue");
Field countField = field("java.util.concurrent.ArrayBlockingQueue", "count");
int poolSize = (Integer) get(poolSizeField, self);
int largestPoolSize = (Integer) get(largestPoolSizeField, self);
int queueSize = (Integer) get(countField, get(workQueueField, self));
println(strcat(strcat(strcat(strcat(strcat("poolSize : ", str(poolSize)), " largestPoolSize : "),
str(largestPoolSize)), " queueSize : "), str(queueSize)));
}
@OnMethod(clazz = "java.util.concurrent.ThreadPoolExecutor", method = "reject", location = @Location(value = Kind.ENTRY))
public static void rejectMonitor(@Self Object self) {
String name = str(self);
if (BTraceUtils.startsWith(name, "com.alibaba.pivot.common.asyncload.impl.pool.AsyncLoadThreadPool")) {
BTraceUtils.incrementAndGet(rejecctCount);
}
}
@OnTimer(1000)
public static void rejectPrintln() {
int reject = BTraceUtils.getAndSet(rejecctCount, 0);
println(strcat("reject count in 1000 msec: ", str(reject)));
AggregationKey key = newAggregationKey("rejectCount");
addToAggregation(histogram, key, reject);
addToAggregation(average, key, reject);
addToAggregation(max, key, reject);
addToAggregation(min, key, reject);
addToAggregation(sum, key, reject);
addToAggregation(count, key, reject);
}
@OnEvent
public static void onEvent() {
BTraceUtils.truncateAggregation(histogram, 10);
println("---------------------------------------------");
printAggregation("Count", count);
printAggregation("Min", min);
printAggregation("Max", max);
printAggregation("Average", average);
printAggregation("Sum", sum);
printAggregation("Histogram", histogram);
println("---------------------------------------------");
}
}
运行结果：
- poolSize : 1 , largestPoolSize = 10 , queueSize = 10
- reject count in 1000 msec: 0
poolSize : 1 , largestPoolSize = 10 , queueSize = 10 reject count in 1000 msec: 0
说明：
1. poolSize 代表为当前的线程数
2. largestPoolSize 代表为历史最大的线程数
3. queueSize 代表blockqueue的当前堆积的size
4. reject count 代表在1000ms内的被reject的数量
最后
这是我对ThreadPoolExecutor使用过程中的一些经验总结，希望能对大家有所帮助，如有描述不对的地方欢迎拍砖。