[Javascript] Introducing Reduce: Common Patterns

Learn how two common array functions - map() and filter() - are syntactic sugar for reduce operations. Learn how to use them, how to compose them, and how using reduce can give you a big performance boost over composing filters and maps over a large data set.

var data = [1, 2, 3];
var doubled = data.reduce(function(acc, value) {
  acc.push(value * 2);

  return acc;
}, []);

var doubleMapped = data.map(function(item) {
  return item * 2;
});

var data2 = [1, 2, 3, 4, 5, 6];
var evens = data2.reduce(function(acc, value) {
  if (value % 2 === 0) {
    acc.push(value);
  }

  return acc;
}, []);

var evenFiltered = data2.filter(function(item) {
  return (item % 2 === 0);
});

var filterMapped = data2.filter(function(value) {
  return value % 2 === 0;
}).map(function(value) {
  return value * 2;
});

About big data:

var bigData = [];
for (var i = 0; i < 1000000; i++) {
  bigData[i] = i;
}

 console.time(‘bigData‘);
var filterMappedBigData = bigData.filter(function(value) {
  return value % 2 === 0;
}).map(function(value) {
  return value * 2;
});

console.timeEnd(‘bigData‘);  //79ms

 console.time(‘bigDataReduce‘);
var reducedBigData = bigData.reduce(function(acc, value) {
  if (value % 2 === 0) {
    acc.push(value * 2);
  }
  return acc;
}, []);
 console.timeEnd(‘bigDataReduce‘); //54ms

Because map and filter each will go thought the array, but reduce only go thought once.