
Vor ein paar Tagen habe ich für die Kleinen einen LINQ in JavaScript- Post angelegt . Aber meine Bibliothek war in der Leistung den nativen Methoden und Lodash viel unterlegen . Im Allgemeinen werden wir jetzt die Situation ändern.
Ich werde gleich sagen: Es wird keine Enthüllungen in dem Artikel geben, wir werden keine verrückten Algorithmen bauen usw. Wir werden nur die Leistung verschiedener Sprachkonstrukte vergleichen.
, , . callback, , map, filter reduce , .

:
- for of
- for
- Lodash
- ursus-utilus-collections
!
, , for.
,.
Benchmark.js. 10 10,000,000 .
: Node.js.
, , .
.
: . -.

Filter
:
const filterCondition = (item: number) => !!(item % 2);
array.filter(filterCondition);
Benchmark
native filter x 3.58 ops/sec ±5.48% (13 runs sampled)
For of
const result = [];
for(let item of array) {
if(filterCondition(item)) {
result.push(item)
}
}
Benchmark
for… of x 3.48 ops/sec ±3.46% (14 runs sampled)
, for of , — .
For
filterSuite.add('for', () => {
const result = [];
for(let i = 0; i < array.length; i++) {
const item = array[i]
if(filterCondition(item)) {
result.push(item)
}
}
})
Benchmark
for x 6.92 ops/sec ±5.47% (20 runs sampled)
for filter 2 .
Lodash
:
lodash(array).filter(filterCondition).value();
Benchmark
lodash filter x 3.60 ops/sec ±4.13% (13 runs sampled)
Lodash filter.
ursus(array).where(filterCondition).toArray();
Benchmark
ursus where x 6.87 ops/sec ±4.86% (20 runs sampled)
± for, .
lodash filter x 3.75 ops/sec ±4.09% (13 runs sampled)
native filter x 3.35 ops/sec ±7.99% (13 runs sampled)
for ... of x 3.38 ops/sec ±3.88% (13 runs sampled)
for x 6.04 ops/sec ±3.54% (20 runs sampled)
optimized for x 5.82 ops/sec ±3.05% (20 runs sampled)
ursus where x 5.83 ops/sec ±4.62% (21 runs sampled)
lodash filter x 3.37 ops/sec ±3.40% (13 runs sampled)
native filter x 3.33 ops/sec ±4.76% (13 runs sampled)
for ... of x 3.86 ops/sec ±9.36% (14 runs sampled)
for x 6.92 ops/sec ±5.47% (20 runs sampled)
optimized for x 6.96 ops/sec ±4.22% (20 runs sampled)
ursus where x 6.71 ops/sec ±4.75% (19 runs sampled)
lodash filter x 3.51 ops/sec ±4.94% (13 runs sampled)
native filter x 3.72 ops/sec ±0.74% (13 runs sampled)
for ... of x 3.54 ops/sec ±2.14% (14 runs sampled)
for x 6.84 ops/sec ±4.60% (20 runs sampled)
optimized for x 6.85 ops/sec ±3.58% (19 runs sampled)
ursus where x 6.46 ops/sec ±11.83% (20 runs sampled)
lodash filter x 3.55 ops/sec ±6.26% (13 runs sampled)
native filter x 3.66 ops/sec ±3.06% (13 runs sampled)
for ... of x 3.41 ops/sec ±4.28% (14 runs sampled)
for x 6.95 ops/sec ±3.85% (20 runs sampled)
optimized for x 6.79 ops/sec ±4.33% (20 runs sampled)
ursus where x 7.17 ops/sec ±3.29% (21 runs sampled)
lodash filter x 3.63 ops/sec ±3.38% (13 runs sampled)
native filter x 3.63 ops/sec ±3.35% (13 runs sampled)
for ... of x 3.44 ops/sec ±3.99% (14 runs sampled)
for x 6.89 ops/sec ±4.53% (20 runs sampled)
optimized for x 6.95 ops/sec ±3.17% (20 runs sampled)
ursus where x 6.87 ops/sec ±4.86% (20 runs sampled)
lodash filter x 3.60 ops/sec ±4.13% (13 runs sampled)
native filter x 3.58 ops/sec ±5.48% (13 runs sampled)
for ... of x 3.48 ops/sec ±3.46% (14 runs sampled)
for x 6.95 ops/sec ±3.73% (20 runs sampled)
optimized for x 6.78 ops/sec ±5.62% (20 runs sampled)
ursus where x 7.17 ops/sec ±3.79% (21 runs sampled)
lodash filter x 3.64 ops/sec ±4.11% (13 runs sampled)
native filter x 3.63 ops/sec ±3.35% (13 runs sampled)
for ... of x 3.55 ops/sec ±2.36% (14 runs sampled)
for x 6.91 ops/sec ±4.51% (20 runs sampled)
optimized for x 6.89 ops/sec ±3.76% (20 runs sampled)
ursus where x 7.03 ops/sec ±4.84% (21 runs sampled)
lodash filter x 3.59 ops/sec ±4.17% (13 runs sampled)
native filter x 3.60 ops/sec ±3.14% (13 runs sampled)
for ... of x 3.45 ops/sec ±4.69% (14 runs sampled)
for x 7.09 ops/sec ±2.65% (20 runs sampled)
optimized for x 6.81 ops/sec ±2.90% (20 runs sampled)
ursus where x 7.15 ops/sec ±2.60% (21 runs sampled)
lodash filter x 3.60 ops/sec ±5.57% (13 runs sampled)
native filter x 3.60 ops/sec ±4.55% (13 runs sampled)
for ... of x 3.39 ops/sec ±7.33% (13 runs sampled)
for x 5.71 ops/sec ±2.74% (19 runs sampled)
optimized for x 5.85 ops/sec ±2.70% (20 runs sampled)
ursus where x 6.10 ops/sec ±2.43% (21 runs sampled)
lodash filter x 3.18 ops/sec ±5.88% (13 runs sampled)
native filter x 3.34 ops/sec ±4.43% (13 runs sampled)
for ... of x 3.89 ops/sec ±6.84% (14 runs sampled)
for x 7.09 ops/sec ±2.79% (21 runs sampled)
optimized for x 6.70 ops/sec ±3.32% (20 runs sampled)
ursus where x 7.07 ops/sec ±4.02% (20 runs sampled)| . | ||
|---|---|---|
| filter | 3,57 ops/sec | 3,60 ops/sec |
| for | 3,48 ops/sec | 3,47 ops/sec |
| for of | 6,91 ops/sec | 6,92 ops/sec |
| lodash | 3,58 ops/sec | 3,60 ops/sec |
| ursus | 6,88 ops/sec | 6,95 ops/sec |
:
1) For
2) Ursus
3) Lodash
4) Filter
5) For of
Map
+1
const mapCondition = (item: number) => item + 1;
array.map(mapCondition);
Benchmark
native map x 0.68 ops/sec ±3.60% (6 runs sampled)
For of
const result = [];
for(let item of array) {
result.push(mapCondition(item))
}
Benchmark
for… of x 2.19 ops/sec ±3.47% (10 runs sampled)
for of 3 .
For
const result = [];
for(let i = 0; i < array.length; i++) {
result.push(mapCondition(array[i]))
}
Benchmark
for x 3.49 ops/sec ±6.82% (12 runs sampled)
for 5 .
Lodash
lodash(array).map(mapCondition).value();
Benchmark
lodash map x 5.78 ops/sec ±9.03% (18 runs sampled)
Lodash 9 !
, - , .
ursus(array).select(mapCondition).toArray();
Benchmark
ursus select x 3.54 ops/sec ±5.71% (13 runs sampled)
- for, . ¯_(ツ)_/¯
lodash map x 6.08 ops/sec ±4.84% (19 runs sampled)
native map x 0.57 ops/sec ±17.60% (6 runs sampled)
for ... of x 1.91 ops/sec ±13.65% (9 runs sampled)
for x 3.51 ops/sec ±5.25% (13 runs sampled)
optimized for x 3.62 ops/sec ±7.49% (13 runs sampled)
ursus select x 3.29 ops/sec ±9.24% (13 runs sampled)
lodash map x 5.59 ops/sec ±10.61% (19 runs sampled)
native map x 0.61 ops/sec ±11.70% (6 runs sampled)
for ... of x 2.30 ops/sec ±2.13% (10 runs sampled)
for x 3.72 ops/sec ±4.39% (13 runs sampled)
optimized for x 3.58 ops/sec ±5.24% (13 runs sampled)
ursus select x 3.58 ops/sec ±5.21% (13 runs sampled)
lodash map x 6.06 ops/sec ±5.23% (19 runs sampled)
native map x 0.68 ops/sec ±3.60% (6 runs sampled)
for ... of x 2.27 ops/sec ±3.49% (10 runs sampled)
for x 3.45 ops/sec ±10.41% (13 runs sampled)
optimized for x 3.59 ops/sec ±4.29% (13 runs sampled)
ursus select x 3.54 ops/sec ±6.08% (12 runs sampled)
lodash map x 5.81 ops/sec ±7.23% (19 runs sampled)
native map x 0.68 ops/sec ±3.63% (6 runs sampled)
for ... of x 2.31 ops/sec ±7.11% (10 runs sampled)
for x 3.62 ops/sec ±4.74% (13 runs sampled)
optimized for x 3.45 ops/sec ±6.67% (13 runs sampled)
ursus select x 3.64 ops/sec ±4.42% (13 runs sampled)
lodash map x 6.03 ops/sec ±5.26% (20 runs sampled)
native map x 0.69 ops/sec ±6.27% (6 runs sampled)
for ... of x 2.12 ops/sec ±8.87% (10 runs sampled)
for x 3.29 ops/sec ±9.33% (13 runs sampled)
optimized for x 3.53 ops/sec ±5.18% (13 runs sampled)
ursus select x 3.66 ops/sec ±4.03% (13 runs sampled)
lodash map x 5.78 ops/sec ±9.03% (18 runs sampled)
native map x 0.65 ops/sec ±6.52% (6 runs sampled)
for ... of x 2.07 ops/sec ±7.41% (10 runs sampled)
for x 3.49 ops/sec ±6.82% (12 runs sampled)
optimized for x 3.50 ops/sec ±5.93% (13 runs sampled)
ursus select x 3.54 ops/sec ±5.71% (13 runs sampled)
lodash map x 5.68 ops/sec ±8.47% (18 runs sampled)
native map x 0.67 ops/sec ±6.40% (6 runs sampled)
for ... of x 2.11 ops/sec ±5.06% (10 runs sampled)
for x 3.52 ops/sec ±5.58% (13 runs sampled)
optimized for x 3.29 ops/sec ±5.51% (13 runs sampled)
ursus select x 3.38 ops/sec ±5.31% (13 runs sampled)
lodash map x 6.37 ops/sec ±3.10% (19 runs sampled)
native map x 0.67 ops/sec ±2.43% (6 runs sampled)
for ... of x 2.19 ops/sec ±3.47% (10 runs sampled)
for x 3.41 ops/sec ±8.13% (13 runs sampled)
optimized for x 3.54 ops/sec ±5.15% (13 runs sampled)
ursus select x 3.53 ops/sec ±6.28% (13 runs sampled)
lodash map x 5.85 ops/sec ±11.04% (19 runs sampled)
native map x 0.66 ops/sec ±4.30% (6 runs sampled)
for ... of x 2.20 ops/sec ±2.97% (10 runs sampled)
for x 3.45 ops/sec ±8.03% (13 runs sampled)
optimized for x 3.48 ops/sec ±5.13% (13 runs sampled)
ursus select x 3.68 ops/sec ±3.33% (13 runs sampled)
lodash map x 5.31 ops/sec ±12.87% (18 runs sampled)
native map x 0.68 ops/sec ±4.26% (6 runs sampled)
for ... of x 2.11 ops/sec ±6.97% (10 runs sampled)
for x 3.35 ops/sec ±6.12% (13 runs sampled)
optimized for x 3.38 ops/sec ±5.55% (13 runs sampled)
ursus select x 3.54 ops/sec ±6.20% (13 runs sampled)| . | ||
|---|---|---|
| map | 0.67 ops/sec | 0.67 ops/sec |
| for | 2.17 ops/sec | 2.16 ops/sec |
| for of | 3.47 ops/sec | 3.47 ops/sec |
| lodash | 5.79 ops/sec | 5.80 ops/sec |
| ursus | 3.56 ops/sec | 3.54 ops/sec |
:
1) Lodash
2) Ursus
3) For
4) For of
5) Map
Reduce
const sumCondition = (item1: number, item2: number) => item1 + item2;
array.reduce(sumCondition);
Benchmark
native reduce x 6.09 ops/sec ±9.13% (20 runs sampled)
For of
, . .
For
let result = array[0];
for(let i = 1; i < array.length; i++) {
result = sumCondition(result, array[i])
}
Benchmark
for x 57.01 ops/sec ±2.53% (59 runs sampled)
For 10 !
Lodash
lodash(array).sum();
Benchmark
lodash sum x 8.30 ops/sec ±7.79% (25 runs sampled)
lodash , , reduce.
ursus(array).sum(sumCondition);
Benchmark
ursus sum x 56.12 ops/sec ±2.38% (58 runs sampled)
lodash sum x 8.60 ops/sec ±4.35% (25 runs sampled)
native reduce x 6.69 ops/sec ±3.73% (21 runs sampled)
for x 68.67 ops/sec ±3.41% (70 runs sampled)
optimized for x 70.75 ops/sec ±2.63% (72 runs sampled)
ursus sum x 67.78 ops/sec ±3.12% (70 runs sampled)
lodash sum x 9.00 ops/sec ±3.93% (26 runs sampled)
native reduce x 5.47 ops/sec ±21.31% (19 runs sampled)
for x 56.61 ops/sec ±2.70% (59 runs sampled)
optimized for x 56.85 ops/sec ±2.27% (59 runs sampled)
ursus sum x 56.08 ops/sec ±2.40% (59 runs sampled)
lodash sum x 8.69 ops/sec ±3.36% (26 runs sampled)
native reduce x 6.09 ops/sec ±9.13% (20 runs sampled)
for x 57.01 ops/sec ±2.53% (59 runs sampled)
optimized for x 57.38 ops/sec ±2.64% (60 runs sampled)
ursus sum x 56.12 ops/sec ±2.38% (58 runs sampled)
lodash sum x 8.68 ops/sec ±4.11% (26 runs sampled)
native reduce x 6.06 ops/sec ±9.39% (19 runs sampled)
for x 69.97 ops/sec ±2.82% (71 runs sampled)
optimized for x 66.55 ops/sec ±4.16% (68 runs sampled)
ursus sum x 69.29 ops/sec ±2.73% (71 runs sampled)
lodash sum x 7.86 ops/sec ±8.39% (24 runs sampled)
native reduce x 6.35 ops/sec ±4.79% (20 runs sampled)
for x 55.91 ops/sec ±5.01% (58 runs sampled)
optimized for x 56.41 ops/sec ±2.70% (59 runs sampled)
ursus sum x 57.11 ops/sec ±2.16% (58 runs sampled)
lodash sum x 8.11 ops/sec ±4.72% (24 runs sampled)
native reduce x 5.97 ops/sec ±7.80% (20 runs sampled)
for x 56.43 ops/sec ±3.62% (59 runs sampled)
optimized for x 56.87 ops/sec ±3.75% (59 runs sampled)
ursus sum x 55.37 ops/sec ±3.60% (58 runs sampled)
lodash sum x 8.52 ops/sec ±6.70% (25 runs sampled)
native reduce x 6.12 ops/sec ±7.39% (20 runs sampled)
for x 57.96 ops/sec ±3.50% (58 runs sampled)
optimized for x 55.19 ops/sec ±5.32% (59 runs sampled)
ursus sum x 56.75 ops/sec ±3.33% (58 runs sampled)
lodash sum x 8.00 ops/sec ±8.94% (25 runs sampled)
native reduce x 5.75 ops/sec ±6.95% (19 runs sampled)
for x 56.78 ops/sec ±4.21% (57 runs sampled)
optimized for x 56.89 ops/sec ±2.32% (60 runs sampled)
ursus sum x 54.61 ops/sec ±7.04% (57 runs sampled)
lodash sum x 8.11 ops/sec ±8.83% (24 runs sampled)
native reduce x 5.97 ops/sec ±7.84% (19 runs sampled)
for x 57.32 ops/sec ±4.17% (59 runs sampled)
optimized for x 55.97 ops/sec ±4.18% (59 runs sampled)
ursus sum x 55.76 ops/sec ±3.90% (58 runs sampled)
lodash sum x 8.30 ops/sec ±7.79% (25 runs sampled)
native reduce x 6.31 ops/sec ±5.42% (20 runs sampled)
for x 55.45 ops/sec ±5.56% (58 runs sampled)
optimized for x 57.54 ops/sec ±3.52% (59 runs sampled)
ursus sum x 55.22 ops/sec ±4.34% (57 runs sampled)| . | ||
|---|---|---|
| reduce | 6.09 ops/sec | 6.08 ops/sec |
| for | 57.02 ops/sec | 56.90 ops/sec |
| lodash | 8.39 ops/sec | 8.41 ops/sec |
| ursus | 56.20 ops/sec | 56.10 ops/sec |
:
1) For
2) Ursus
3) Lodash
4) Reduce
, 10 , for .
-, lodash 50k .
25k for.
Meiner Meinung nach war es im Allgemeinen ein ziemlich merkwürdiges Experiment, aber jetzt, wo ich solche Informationen über eine große Anzahl von Elementen habe, werde ich wahrscheinlich zumindest die Leistung nativer Implementierungen überprüfen.
Vielen Dank für Ihre Aufmerksamkeit!