3

最近，我花了一些时间研究传感器（函数式编程中的工具，旨在提高性能而不损失代码的可读性/灵活性），当我开始测试它们的实际速度时，我得到了一些非常令人失望的结果。考虑：

const inc = x => x + 1;

const isEven = x => x % 2 === 0;

// simplest, shortest way I would be comfortable with if performance wasn't an issue

const mapFilter = xs => xs.filter(isEven).map(inc);

// transducers way

// function composition
const compose = (...fns) => x => fns.reduceRight((y, f) => f(y), x);

const map = f => step => (a, c) => step(a, f(c));
const filter = p => step => (a, c) => (p(c) ? step(a, c) : a);

// basic reducer for building array
const build = (acc, x) => {
  acc.push(x);
  return acc;
};

// transducer, it doesn't create intermediate arrays hence should theoretically be faster 
const transducers = xs =>
  xs.reduce(compose(filter(isEven), map(inc))(build), []);

// native loop for comparison
const nativeLoop = data => {
  const result = [];
  const l = data.length;
  for (let i = 0; i < l; i++) {
    const x = data[i];
    if (isEven(x)) result.push(inc(x));
  }
  return result;
};

const data = Array(1000).fill(1);

const base = ["simplest, chained map and filter", () => mapFilter(data)];
const alternative = ["composed transducers", () => transducers(data)];
const alternative2 = ["native loop", () => nativeLoop(data)];

/* console.log(Benchmark) */
console.log("Running benchmarks....");

const suite = new Benchmark.Suite();
suite
  .add(...base)
  .add(...alternative)
  .add(...alternative2)
  .on("cycle", function(event) {
  console.log(String(event.target));
})
  .on("complete", function() {
  console.log("Fastest is " + this.filter("fastest").map("name").join(", "));
})
// run async
  .run({ async: true });
<script src="https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.15/lodash.min.js"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/benchmark/2.1.4/benchmark.min.js"></script>

我希望表演的顺序是

本机循环 > 传感器 > 链式映射/过滤器

同时，除了比其他任何方法都快的原生方法之外，令我惊讶的是，reduce/transduce 方法比使用 map/filter 和创建中间数组要慢得多（慢，就像 Chrome 中的一个数量级） . 有人可以向我解释这个结果的起源吗？

4

2 回答 2

6

您的基准测试是错误的，因为您在每次运行时都构建了一个新的传感器链。

const inc = x => x + 1;

const isEven = x => x % 2 === 0;

// simplest, shortest way I would be comfortable with if performance wasn't an issue

const mapFilter = xs => xs.filter(isEven).map(inc);

// transducers way

// function composition
const compose = (...fns) => x => fns.reduceRight((y, f) => f(y), x);

const map = f => step => (a, c) => step(a, f(c));
const filter = p => step => (a, c) => (p(c) ? step(a, c) : a);

// basic reducer for building array
const build = (acc, x) => {
  acc.push(x);
  return acc;
};

// transducer, it doesn't create intermediate arrays hence should theoretically be faster
const reducer = compose(filter(isEven), map(inc))(build);
const transducers = xs => xs.reduce(reducer, []);

// native loop for comparison
const nativeLoop = data => {
  const result = [];
  const l = data.length;
  for (let i = 0; i < l; i++) {
    const x = data[i];
    if (isEven(x)) result.push(inc(x));
  }
  return result;
};

const data = Array(1000).fill(1);

const base = ["simplest, chained map and filter", () => mapFilter(data)];
const alternative = ["composed transducers", () => transducers(data)];
const alternative2 = ["native loop", () => nativeLoop(data)];

/* console.log(Benchmark) */
console.log("Running benchmarks....");

const suite = new Benchmark.Suite();
suite
  .add(...base)
  .add(...alternative)
  .add(...alternative2)
  .on("cycle", function(event) {
  console.log(String(event.target));
})
  .on("complete", function() {
  console.log("Fastest is " + this.filter("fastest").map("name").join(", "));
})
// run async
  .run({ async: true });
<script src="https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.15/lodash.min.js"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/benchmark/2.1.4/benchmark.min.js"></script>

如您所见，转换器确实比链式map和filter方法更快。

于 2020-02-19T04:37:55.473 回答
1

基准有缺陷。减速器不必做任何工作。

  • 创建一个奇数为 1 的统一数组。
  • 然后在每个元素上运行一个 isEven 函数
  • 总是要返回一个空数组

我们正在对返回空数组的性能进行基准测试。

如果我们用真实数据预填充一个数组，本机方法将获胜。Aadit 是正确的，他的传感器是两个传感器实现中最快的。

const data = [];

for (let i = 0; i < 1000; i++) {
    data.push(Math.floor(Math.random() * 10));
}
于 2020-11-02T12:25:15.900 回答