better performance test

gistfile1.txt

export const handler = async (event) => {
  // TODO implement
  //#Source https://bit.ly/2neWfJ2 
  const hz = (fn, iterations = 100) => {
    const before = performance.now();
    for (let i = 0; i < iterations; i++) fn();
    return (1000 * iterations) / (performance.now() - before);
  };
  // 10,000 element array
  const numbers = Array(10000)
    .fill()
    .map((_, i) => i);
  
  // Test functions with the same goal: sum up the elements in the array
  const sumReduce = () => numbers.reduce((acc, n) => acc + n, 0);
  const sumForLoop = () => {
    let sum = 0;
    for (let i = 0; i < numbers.length; i++) sum += numbers[i];
    return sum;
  };
  
  function getStandardDeviation (array) {
    const n = array.length
    const mean = array.reduce((a, b) => a + b) / n
    return Math.sqrt(array.map(x => Math.pow(x - mean, 2)).reduce((a, b) => a + b) / n)
  }
  
  
  
  const getStats = (fn, iterations = 100) => {
    const data = [];
    for (let i = 0; i < iterations; i++) {
      data.push(Math.round(hz(fn)))
    };
    return {
      min: Math.min(...data),
      max: Math.max(...data),
      average: data.reduce((partialSum, a) => partialSum + a, 0)/data.length,
      stDev: getStandardDeviation(data),
    }
  }
  
  
  
  // sumForLoop` is nearly 10 times faster
  const statsReduce = getStats(sumReduce);
  const statsForLoop = getStats(sumForLoop);
  
  
  const response = {
    statusCode: 200,
    body: JSON.stringify({
      memory: process.env.AWS_LAMBDA_FUNCTION_MEMORY_SIZE,
      statsReduce, 
      statsForLoop
    }),
  };
  return response;
};