📜  完整形式的FPS(1)

📅  最后修改于: 2023-12-03 15:39:07.395000             🧑  作者: Mango

完整形式的FPS介绍

FPS (Frames Per Second),即每秒帧数,是衡量电脑游戏、视频等每秒显示多少帧的一种性能指标。在程序员中,也有完整形式的FPS。

完整形式的FPS定义

在程序员中,完整形式的FPS是指“Fiber Per Second”,即每秒纤程数。在多线程、异步编程中,一个独立子任务的纤程数,也可以称为该任务的一秒内完整形式的FPS。

完整形式的FPS的重要性

完整形式的FPS作为衡量异步编程的性能指标,对于项目的性能优化、代码的优化有着重要作用。一般情况下,完整形式的FPS数值越高,表示该任务的性能越好,可以处理更多的并发请求。

完整形式的FPS的实现

基于不同语言,完整形式的FPS的实现可能有所不同,以下是一些常见的实现方式:

Python

在Python中,可以使用asyncio库来实现异步编程,计算当前每秒纤程数的代码片段如下:

import asyncio

async def task():
    await asyncio.sleep(0)  # 模拟任务执行时间
    return

async def main():
    t1 = asyncio.create_task(task())
    t2 = asyncio.create_task(task())
    t3 = asyncio.create_task(task())
    t4 = asyncio.create_task(task())
    tasks = [t1, t2, t3, t4] # 假设有4个独立子任务
    while True:
        before = asyncio.all_tasks()
        await asyncio.sleep(1)
        after = asyncio.all_tasks()
        fps = len(after) - len(before)  # 计算一秒内新增的纤程数
        print(f'FPS: {fps}')

asyncio.run(main())
Java

在Java中,可以使用Spring框架的Fiber来实现异步编程,计算当前每秒纤程数的代码片段如下:

import java.util.concurrent.CountDownLatch;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
import java.util.concurrent.atomic.AtomicLong;
import org.springframework.scheduling.concurrent.ThreadPoolTaskExecutor;
import org.springframework.stereotype.Service;
import com.alibaba.spring.util.CustomThreadPoolTaskExecutor;
import com.alibaba.spring.util.LogUtil;
import com.alibaba.spring.util.StatisticCountUtil;
import com.alibaba.spring.util.ThreadPoolStatisticCountUtil;
import com.alibaba.spring.util.ThreadPoolTaskExecutorUtil;
import com.alibaba.spring.util.TraceThreadLocalUtil;
import com.alibaba.spring.util.spring.FastBeanFactoryPostProcessor;
import reactor.core.publisher.Flux;
import reactor.core.scheduler.Schedulers;
@Service
public class FPS {

    ExecutorService executor;
    AtomicLong atomicLong = new AtomicLong();
    public FPS() {
        executor = Executors.newFixedThreadPool(10);
    }

    public void run1() {

        System.out.println("FPS starting...");

        static int nThread = 10;
        ThreadPoolTaskExecutor executor = ThreadPoolTaskExecutorUtil
                .getFixedThreadPoolTaskExecutor("111", nThread, nThread, 1);
        StatisticCountUtil countUtil = new ThreadPoolStatisticCountUtil(executor.getThreadPoolExecutor());

        LogUtil.log("test biz threadpool executor tasks");

        CountDownLatch latch = new CountDownLatch(nThread);
        for (int index = 1; index < nThread + 1; index++) {

            executor.execute(new Runnable() {
                @Override
                public void run() {
                    Thread.currentThread().setName(TraceThreadLocalUtil.TRACE_ID + "-" + index);
                    try {
                        System.out.println("currentThread: " + Thread.currentThread());
                        Flux.range(0, Integer.MAX_VALUE).publishOn(Schedulers.single()).doOnNext(i -> {
                            StatisticCountUtil.increment(countUtil.getSubmittedCount());
                            try {
                                atomicLong.incrementAndGet();
                                Thread.sleep(10);
                            } catch (Exception e) {
                            }
                        }).subscribe();
                    } catch (Exception e) {
                    } finally {
                        latch.countDown();
                    }
                }
            });
        }

        try {
            latch.await();
        } catch (InterruptedException e) {
            e.printStackTrace();
        }

        System.out.println("FPS: " + atomicLong.get());

    }

}
Node.js

在Node.js中,可以使用async库来实现异步编程,计算当前每秒纤程数的代码片段如下:

const async = require('async');

const tasks = [
  cb => {
    setTimeout(() => {
      cb();
    }, 500);  // 模拟任务执行时间
  },
  cb => {
    setTimeout(() => {
      cb();
    }, 800);  // 模拟任务执行时间
  },
  cb => {
    setTimeout(() => {
      cb();
    }, 700);  // 模拟任务执行时间
  }
];

let fps = 0;
setInterval(() => {
  const before = async.queue().length();
  async.parallel(tasks, () => {
    const after = async.queue().length();
    fps = after - before;
    console.log(`FPS: ${fps}`);
  });
}, 1000);
总结

完整形式的FPS是异步编程中的一种性能指标,计算每秒纤程数的方法因语言而异。程序员可以根据完整形式的FPS数值,对项目的性能进行评估和优化。