并发集合ConcurrentSkipListMap的性能测试_JAVA_编程开发_程序员俱乐部

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并发集合ConcurrentSkipListMap的性能测试

 2014/12/10 18:26:10  lfl2011  程序员俱乐部  我要评论(0)
  • 摘要:ConcurrentSkipListMap是DougLea在java6中新加入的一个并发集合,下面这个例子主要是测试ConcurrentSkipListMap的插入、读取和并发修改集合元素时的性能特征,代码如下:packagetest.caipiao.log;importjava.io.File;importjava.io.IOException;importjava.nio.charset.Charset;importjava.util.concurrent
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ConcurrentSkipListMap是Doug Lea在java6中新加入的一个并发集合,下面这个例子主要是测试ConcurrentSkipListMap的插入、读取和并发修改集合元素时的性能特征,代码如下:

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class="java">package test.caipiao.log;

import java.io.File;
import java.io.IOException;
import java.nio.charset.Charset;
import java.util.concurrent.ConcurrentNavigableMap;
import java.util.concurrent.ConcurrentSkipListMap;
import java.util.concurrent.atomic.AtomicInteger;
import java.util.ArrayList;
import java.util.Iterator;
import java.util.Map;
import java.util.Set;

import com.caipiao.util.io.FileUtils;

public class ConcurrentSkipListMapTest2 {
    

    public static void main(String[] args) throws InterruptedException, Exception {

        final ConcurrentNavigableMap<Integer, String> cslm = new ConcurrentSkipListMap<Integer, String>();
        final Counter5 counter = new Counter5();

        // create 100 threads
        ArrayList<MyThread5> threads = new ArrayList<MyThread5>();
        for (int x = 0; x < 100; x++) {
            threads.add(new MyThread5(counter, cslm));
        }

        long start1 = System.currentTimeMillis();
        // start all of the threads
        Iterator i1 = threads.iterator();
        while (i1.hasNext()) {
            MyThread5 mt = (MyThread5) i1.next();
            mt.start();
        }

        // wait for all the threads to finish
        Iterator i2 = threads.iterator();
        while (i2.hasNext()) {
            MyThread5 mt = (MyThread5) i2.next();
            mt.join();
        }

        long end1 = System.currentTimeMillis();
        System.out.println("100个线程 每个线程插入100000共1000万条记录,耗时: " + (end1 - start1) + " 毫秒");
        System.out.println("Count: " + counter.getCount());
        System.out.println("original size  = " + cslm.size());
        System.out.println("---------------------以上是测试插入---------------------------------------");
        
        // create 1000 threads
        ArrayList<MyThread7> threads3 = new ArrayList<MyThread7>();
        for (int x = 0; x < 1000; x++) {
            threads3.add(new MyThread7(counter, cslm));
        }

        long start3 = System.currentTimeMillis();
        // start all of the threads
        Iterator i3 = threads3.iterator();
        while (i3.hasNext()) {
            MyThread7 mt = (MyThread7) i3.next();
            mt.start();
        }

        // wait for all the threads to finish
        Iterator i33 = threads3.iterator();
        while (i33.hasNext()) {
            MyThread7 mt = (MyThread7) i33.next();
            mt.join();
        }

        long end3 = System.currentTimeMillis();
        System.out.println("1000个线程 每个线程插入10000共1000万条记录,耗时: " + (end3 - start3) + " 毫秒");
        System.out.println("---------------------以上是测试读取---------------------------------------");
        
        long start2 = System.currentTimeMillis();
        ArrayList<MyThread6> threads2 = new ArrayList<MyThread6>();
        for (int x = 0; x < 5; x++) {
            threads2.add(new MyThread6(counter, cslm));
        }

        // start all of the threads
        Iterator i12 = threads2.iterator(); //并发修改 访问 ConcurrentSkipListMap
        while (i12.hasNext()) {
            MyThread6 mt = (MyThread6) i12.next();
            mt.start();
        }
        
        Thread t = new Thread() {
            public void run() {
                for (int x = 0; x < 100000; x++) {
                    String s = cslm.get(x);
                    if (x % 20 == 0) {
//                        System.out.println("key ---" + x + " s--- " + s);
                    }
                }
            }
        };
        
        t.start();
        
        
        
     // wait for all the threads to finish
        Iterator i22 = threads2.iterator();
        while (i22.hasNext()) {
            MyThread6 mt = (MyThread6) i22.next();
            mt.join();
        }
        
        t.join();
        
        long end2 = System.currentTimeMillis();
        System.out.println(end2 - start2);
        System.out.println("over");
        System.out.println("new size  = " + cslm.size());
        System.out.println("---------------------以上是测试并发的修改ConcurrentSkipListMap里的元素---------------------------------------");
        
    }
}

// thread that increments the counter 100000 times.
class MyThread5 extends Thread {
    Counter5 counter;
    ConcurrentNavigableMap<Integer, String> cslm;

    MyThread5(Counter5 counter, ConcurrentNavigableMap<Integer, String> cslm) {
        this.counter = counter;
        this.cslm = cslm;
    }

    public void run() {
        for (int x = 0; x < 100000; x++) {
            int i = counter.incrementCount();
            
            cslm.put(i, "");
        }
    }
}

// class that uses AtomicInteger for counter
class Counter5 {

    private AtomicInteger count = new AtomicInteger(0);

    public int incrementCount() {
        return count.incrementAndGet();
    }
    
    public int decrementAndGet() {
        return count.decrementAndGet();
    }

    public int getCount() {
        return count.get();
    }
}

//class that uses to delete part data of the cslm
class MyThread6 extends Thread {
    Counter5 counter;
    ConcurrentNavigableMap<Integer, String> cslm;

    MyThread6(Counter5 counter, ConcurrentNavigableMap<Integer, String> cslm) {
        this.counter = counter;
        this.cslm = cslm;
    }

    public void run() {
        for (int x = 0; x < 100000; x++) {
            cslm.remove(x);
            try {
                if (x % 100 == 0) {
                    this.sleep(1);
                }
            } catch (InterruptedException e) {
                e.printStackTrace();
            }
        }
    }
}


//thread that decrements the counter 100000 times.
class MyThread7 extends Thread {
    Counter5 counter;
    ConcurrentNavigableMap<Integer, String> cslm;
    
    MyThread7(Counter5 counter, ConcurrentNavigableMap<Integer, String> cslm) {
        this.counter = counter;
        this.cslm = cslm;
    }
    
    public void run() {
        for (int x = 0; x < 10000; x++) {
            int i = counter.decrementAndGet();
            cslm.get(i);
        }
    }
}

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CPU配置为4核?intel i3-2100 3.1GHz,内存分配1G,多次运行输出大致如下:

100个线程 每个线程插入100000共1000万条记录,耗时: 4719 毫秒

Count: 10000000

original size ?= 10000000

---------------------以上是测试插入---------------------------------------

1000个线程 每个线程插入10000共1000万条记录,耗时: 2684 毫秒

---------------------以上是测试读取---------------------------------------

1025

over

new size ?= 9900001

-------------------以上是测试并发的修改、访问ConcurrentSkipListMap里的元素------------------------------------

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可以看到put操作的并发能达到200万/秒以上,get操作的并发能达到350万/秒以上,

这里的性能损耗有一部分是在AtomicInteger原子的递增和递减上,如果在真实的业务场景中,可以知道key的操作不需要使用AtomicInteger或加锁方式来获取,性能会更高。

通过第三个输出可以知道对ConcurrentSkipListMap访问的同时进行删除不会出现ConcurrentModificationException异常

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此例子可以把ConcurrentSkipListMap换成ConcurrentHashMap等其它集合进行测试。

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