用java并发测试tokyo Cabinet的性能[重大更正篇]

在前面一篇文章 用java并发测试tokyo cabinet的性能[五四陈手记]

提到了测试tc的效率问题,最后的结论是70W/s,由于当时的错误,导致了一些严重影响大家的结论,如今本着认真治学,谨慎小心的态度,重新公布最新的代码和结论,还望受影响的同志们不要发烧。。。

首先,总结上一次为什么会犯错的原因:

1. 测试代码有问题,TDB db = new TDB();不能放在线程中去new,也许是tc实现的问题,详细原因没有去研究。

2.赶着时间测,把写入的时候的结果直接给屏了。

重新公布新的测试代码:

package test;

import java.util.ArrayList;

import java.util.HashMap;

import java.util.List;

import java.util.Map;

import java.util.Random;

import java.util.concurrent.atomic.AtomicLong;

import tokyocabinet.*;

public class BenchMark {

private static List<TDB> dbList = new ArrayList<TDB>();

public static class Stat {

private AtomicLong _count = new AtomicLong(0);

private static Stat _instance = new Stat();

public static Stat getInstance() {

return _instance;

}

private Stat() {

_printer = new RatePrinter(_count);

_printer.setDaemon(true);

_printer.start();

}

public void inc() {

_count.incrementAndGet();

}

private RatePrinter _printer;

private static class RatePrinter extends Thread {

private long _last;

private AtomicLong _c;

public RatePrinter(AtomicLong c) {

_c = c;

}

@Override

public void run() {

while (true) {

try {

long current = _c.get();

System.out.println("Rate: " + (current - _last) + " req/s");

_last = current;

Thread.sleep(1000L);

} catch (Throwable e) {

e.printStackTrace();

}

}

}

}

}

public static class EchoThread extends Thread {

// private TDB tdb;

public EchoThread(String ip, String port, int in, ThreadGroup group) {

super(group, "EchoThread-" + in);

// // create the object

// TDB tdb = new TDB();

//

// // open the database

// if(!tdb.open("casket"+in+".tct", TDB.OWRITER | TDB.OCREAT)){

// int ecode = tdb.ecode();

// System.err.println("open error: " + tdb.errmsg(ecode));

// }

}

@Override

public void run() {

int index = 0;

// create the object

Random r = new Random();

// open the database

// if (!tdb.open("casket" + Thread.currentThread().getId() + ".tct", TDB.OWRITER | TDB.OCREAT)) {

// int ecode = tdb.ecode();

// System.err.println("open error: " + tdb.errmsg(ecode));

// }

while (true) {

try {

TDB tdb = dbList.get(0);

String pkey = index + "asdf";

Map<String, String> cols = new HashMap<String, String>();

cols.put("name", "mikio" + index);

cols.put("age", "30");

cols.put("lang", "ja,en,c");

if (!tdb.put(pkey, cols)) {

int ecode = tdb.ecode();

System.err.println("put error: " + tdb.errmsg(ecode) + " key:" + pkey + "  value:" + cols);

}

// client.insert("Table1", "name"+index, "Standard1:name",

// ("name"+index).getBytes("UTF-8"),

// System.currentTimeMillis(), true);

// client.get_column("Table1", "name0", "Standard1:name");

index++;

Stat.getInstance().inc();

} catch (Throwable e) {

e.printStackTrace();

break;

} finally {

// close the database

//if (!tdb.close()) {

//int ecode = tdb.ecode();

// System.err.println("close error: " +

// tdb.errmsg(ecode));

//}

}

}

}

}

/**

* @param args

* @throws TTransportException

*/

public static void main(String[] args) {

if (args.length != 1) {

System.out.println("Usage: Benchmark <concurrent>");

System.exit(1);

}

String ip = args[0];

String port = args[0];

Integer concurrent = Integer.valueOf(args[0]);

System.out.println("ip = " + ip + ",port = " + port + ",concurrent = " + concurrent);

ThreadGroup group = new ThreadGroup("Benchmark");

List<Thread> threads = new ArrayList<Thread>();

for (int i = 0; i < concurrent; i++) {

TDB db = new TDB();

//db.optimize();

if (!db.open("./test" + i + ".tdb", TDB.OCREAT | TDB.OWRITER)) {

int ecode = db.ecode();

System.err.println("open error: " + TDB.errmsg(ecode));

continue;

}

dbList.add(db);

}

for (int x = 0; x < concurrent; ++x) {

Thread t = new EchoThread(ip, port, x, group);

threads.add(t);

t.start();

}

}

} 对比上一次的代码,能够发现,1.new TDB的过程扔进了Thread.start之前;2.在thread中使用一个全局的变量来获取当前的对象。

启十个进程,全往第一个里写:

concurrent = 10

Rate: 25 req/s

Rate: 119617 req/s

Rate: 130620 req/s

Rate: 144202 req/s

Rate: 120458 req/s

Rate: 112809 req/s

Rate: 120800 req/s

Rate: 122290 req/s

Rate: 119526 req/s

Rate: 111189 req/s

Rate: 112483 req/s

Rate: 109138 req/s

Rate: 115648 req/s

Rate: 119419 req/s

Rate: 105558 req/s

Rate: 110230 req/s

Rate: 116507 req/s

Rate: 105367 req/s

Rate: 103781 req/s

Rate: 106618 req/s

Rate: 107698 req/s

Rate: 116768 req/s

Rate: 107244 req/s

保持在10w/s的写入速度,到达30s左右以后,数据急转直下:

Rate: 48060 req/s

Rate: 6901 req/s

Rate: 4987 req/s

Rate: 46229 req/s

Rate: 46686 req/s

Rate: 45402 req/s

Rate: 6271 req/s

Rate: 810 req/s

Rate: 33895 req/s

Rate: 46548 req/s

Rate: 47025 req/s

Rate: 6995 req/s

Rate: 860 req/s

这,就是tc的table表在写入一个ArrayList的真实速度(4核8G)。

官方发言的100W只需要0.4s,说的是写入的hash表,而且数据是纯线性的数字。

提升速度和稳定的办法,和张宴兄弟商量,b+tree类型的数据稳定一些,设置tctdbsetxmsiz也能解决燃眉之急。


原创文章如转载,请注明:转载自五四陈科学院[http://www.54chen.com]

捐款订阅54chen
捐赠说明

Comments