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在人人网海量存储系统的存储引擎部分，为了提高CPU和网络的使用情况，使用了java多线程管理并行操作的方式。
在java中控制线程是一件很简单的事情，jdk提供了诸多的方法，其中比常用的两个是notify()和wait()，一个是唤醒，一个等待线程，在下面的代码中，将看到一个线程分配器，根据cpu的负载情况，自动完成对应线程的唤醒或者是等待操作。整个过程是一个平滑的过程，不会因为线程的切换而导致机器负载出线锯齿。
先看一个类，读取Linux系统TOP等指令拿到系统当前负载：
import java.io.BufferedReader;
import java.io.InputStreamReader;
/**
* 节点的cpu 内存 磁盘空间 情况
*
* @author zhen.chen
*
*/
public class NodeLoadView {
/**
* 获取cpu使用情况
*
* @return
* @throws Exception
*/
public double getCpuUsage() throws Exception {
double cpuUsed = 0;
Runtime rt = Runtime.getRuntime();
Process p = rt.exec(“/usr/bin/uptime”);// 调用系统的“top”命令
String[] strArray = null;
BufferedReader in = null;
try {
in = new BufferedReader(new InputStreamReader(p.getInputStream()));
String str = null;
while ((str = in.readLine()) != null) {
strArray = str.split(“load average: “);
strArray = strArray[1].split(“,”);
cpuUsed = Double.parseDouble(strArray[0]);
}
} catch (Exception e) {
e.printStackTrace();
} finally {
in.close();
}
return cpuUsed;
}
/**
* 内存监控
*
* @return
* @throws Exception
*/
public double getMemUsage() throws Exception {
double menUsed = 0;
Runtime rt = Runtime.getRuntime();
Process p = rt.exec(“top -b -n 1″);// 调用系统的“top”命令
BufferedReader in = null;
try {
in = new BufferedReader(new InputStreamReader(p.getInputStream()));
String str = null;
String[] strArray = null;
while ((str = in.readLine()) != null) {
int m = 0;
if (str.indexOf(” R “) != -1) {// 只分析正在运行的进程，top进程本身除外 &&
//
// System.out.println(“——————3—————–”);
strArray = str.split(” “);
for (String tmp : strArray) {
if (tmp.trim().length() == 0)
continue;
if (++m == 10) {
// 9)–第10列为mem的使用百分比(RedHat 9)
menUsed += Double.parseDouble(tmp);
}
}
}
}
} catch (Exception e) {
e.printStackTrace();
} finally {
in.close();
}
return menUsed;
}
/**
* 获取磁盘空间大小
*
* @return
* @throws Exception
*/
public double getDeskUsage() throws Exception {
double totalHD = 0;
double usedHD = 0;
Runtime rt = Runtime.getRuntime();
Process p = rt.exec(“df -hl”);// df -hl 查看硬盘空间
BufferedReader in = null;
try {
in = new BufferedReader(new InputStreamReader(p.getInputStream()));
String str = null;
String[] strArray = null;
while ((str = in.readLine()) != null) {
int m = 0;
// if (flag > 0) {
// flag++;
strArray = str.split(” “);
for (String tmp : strArray) {
if (tmp.trim().length() == 0)
continue;
++m;
// System.out.println(“—-tmp—-” + tmp);
if (tmp.indexOf(“G”) != -1) {
if (m == 2) {
// System.out.println(“—G—-” + tmp);
if (!tmp.equals(“”) && !tmp.equals(“0″))
totalHD += Double.parseDouble(tmp.substring(0,
tmp.length() – 1)) * 1024;
}
if (m == 3) {
// System.out.println(“—G—-” + tmp);
if (!tmp.equals(“none”) && !tmp.equals(“0″))
usedHD += Double.parseDouble(tmp.substring(0,
tmp.length() – 1)) * 1024;
}
}
if (tmp.indexOf(“M”) != -1) {
if (m == 2) {
// System.out.println(“—M—” + tmp);
if (!tmp.equals(“”) && !tmp.equals(“0″))
totalHD += Double.parseDouble(tmp.substring(0,
tmp.length() – 1));
}
if (m == 3) {
// System.out.println(“—M—” + tmp);
if (!tmp.equals(“none”) && !tmp.equals(“0″))
usedHD += Double.parseDouble(tmp.substring(0,
tmp.length() – 1));
// System.out.println(“—-3—-” + usedHD);
}
}
}
// }
}
} catch (Exception e) {
e.printStackTrace();
} finally {
in.close();
}
return (usedHD / totalHD) * 100;
}
//
// public static void main(String[] args) throws Exception {
// NodeLoadView cpu = new NodeLoadView();
// System.out
// .println(“—————cpu used:” + cpu.getCpuUsage() + “%”);
// System.out
// .println(“—————mem used:” + cpu.getMemUsage() + “%”);
// System.out
// .println(“—————HD used:” + cpu.getDeskUsage() + “%”);
// System.out.println(“————jvm监控———————-”);
// Runtime lRuntime = Runtime.getRuntime();
// System.out.println(“————–Free Momery:” + lRuntime.freeMemory()
// + “K”);
// System.out.println(“————–Max Momery:” + lRuntime.maxMemory()
// + “K”);
// System.out.println(“————–Total Momery:”
// + lRuntime.totalMemory() + “K”);
// System.out.println(“—————Available Processors :”
// + lRuntime.availableProcessors());
// }
}
再来看关键的一个类，THreadScheduler：
import java.util.Map;
import org.apache.log4j.Logger;
import test.NodeLoadView;
public class ThreadScheduler {
private static Logger logger = Logger.getLogger(ThreadScheduler.class.getName());
private Map<String, Thread> runningThreadMap;
private Map<String, Thread> waitingThreadMap;
private boolean isFinished = false;
private int runningSize;
public ThreadScheduler (Map<String, Thread> runningThreadMap, Map<String, Thread> waitingThreadMap) {
this.runningThreadMap = runningThreadMap;
this.waitingThreadMap = waitingThreadMap;
this.runningSize = waitingThreadMap.size();
}
/**
* 开始调度线程
* @author zhen.chen
* @createTime 2010-1-28 上午11:04:52
*/
public void schedule(){
long sleepMilliSecond = 1 * 1000;
int allowRunThreads = 15;
// 一次启动的线程数，cpuLoad变大时以此值为参考递减
int allowRunThreadsRef = 15;
double cpuLoad = 0;// 0-15
NodeLoadView load = new NodeLoadView();
while (true) {
try {
cpuLoad = load.getCpuUsage();
} catch (Exception e1) {
e1.printStackTrace();
}
// cpuLoad低 启动的线程多
allowRunThreads = (int) Math.floor(allowRunThreadsRef – cpuLoad);
// threads不能为0
if (allowRunThreads < 1) {
allowRunThreads = 1;
}
if (allowRunThreads > allowRunThreadsRef) {
allowRunThreads = allowRunThreadsRef;
}
if (logger.isDebugEnabled()) {
logger.debug(“[ThreadScheduler]running Thread:” + runningThreadMap.size() + “; waiting Thread:” + waitingThreadMap.size() + “; cpu:” + cpuLoad + ” allowRunThreads:” + allowRunThreads);
}
// 检查runningSize个线程的情况，满足条件则启动
for (int x = 0; x < runningSize; x++) {
if (waitingThreadMap.get(x+”") != null) {
if (allowRunThreadsRef <= runningThreadMap.size()) {
break;
}
synchronized (waitingThreadMap.get(x+”")) {
if (!waitingThreadMap.get(x+”").isAlive()) {
waitingThreadMap.get(x+”").start();
}else{
waitingThreadMap.get(x+”").notify();
}
}
runningThreadMap.put(x+”", waitingThreadMap.get(x+”"));
waitingThreadMap.remove(x+”");
}
}
// 检查runningSize个线程的情况，满足条件则暂停
for (int x = 0; x < runningSize; x++) {
if (runningThreadMap.size() <= allowRunThreads) {
break;
}
if (runningThreadMap.get(x+”") != null) {
synchronized (runningThreadMap.get(x+”")) {
try {
if (runningThreadMap.get(x+”").isAlive()) {
runningThreadMap.get(x+”").wait();
}else{
continue;
}
} catch (InterruptedException e) {
e.printStackTrace();
}
}
waitingThreadMap.put(x+”", runningThreadMap.get(x));
runningThreadMap.remove(x+”");
}
}
// 全部跑完，返回
if (waitingThreadMap.size() == 0 && runningThreadMap.size() == 0) {
if (logger.isDebugEnabled()) {
logger.debug(“[ThreadScheduler] over.total Threads size:” + runningSize);
}
this.isFinished = true;
return;
}
// 使主while循环慢一点
try {
Thread.sleep(sleepMilliSecond);
} catch (InterruptedException e1) {
e1.printStackTrace();
}
}
}
public boolean isFinished() {
return isFinished;
}
}
这个类的作用：
1.接收runningThreadMap和waitingThreadMap两个map，里面对应存了运行中的线程实例和等待中的线程实例。
2.读cpu情况，自动判断要notify等待中的线程还是wait运行中的线程。
3.两个map都结束，退出。（必须runningThreadMap内部的Thread自己将runningThreadMap对应的Thread remove掉）
如何使用：
public class TestThread {
public static class Runner extends Thread {
public Runner(int j, Map<String, Thread> threadMap) {
}
public void run() {
// TODO 你的逻辑 完成后需要从threadMap中remove掉
}
}
public static void main(String[] args) {
// 运行中的线程
Map<String, Thread> threadMap = new HashMap<String, Thread>();
// 正在等待中的线程
Map<String, Thread> waitThreadMap = new HashMap<String, Thread>();
for (int j = 0; j < args.length; j++) {
Thread t = new Runner(j, threadMap);
waitThreadMap.put(j + “”, t);
}
ThreadScheduler threadScheduler = new ThreadScheduler(threadMap, waitThreadMap);
threadScheduler.schedule();
if (threadScheduler.isFinished() == false) {
//没能正常结束
}
}
}