@rudderstack/integrations-lib/build/utils/batch-processing.bench.js

A comprehensive TypeScript library providing shared utilities, SDKs, and tools for RudderStack integrations and destinations.

"use strict";
var __importDefault = (this && this.__importDefault) || function (mod) {
    return (mod && mod.__esModule) ? mod : { "default": mod };
};
Object.defineProperty(exports, "__esModule", { value: true });
/* eslint-disable no-console */
const node_perf_hooks_1 = require("node:perf_hooks");
const lodash_1 = __importDefault(require("lodash"));
const batch_processing_1 = require("./batch-processing");
async function bench(fn, label, iterations = 5) {
    let total = 0;
    for (let i = 0; i < iterations; i += 1) {
        const start = node_perf_hooks_1.performance.now();
        // eslint-disable-next-line no-await-in-loop
        await fn();
        total += node_perf_hooks_1.performance.now() - start;
    }
    const avg = total / iterations;
    console.log(`${label}: avg ${avg.toFixed(2)} ms over ${iterations} runs`);
    return avg;
}
async function section(title, fn) {
    console.log(`\n=== ${title} ===`);
    await fn();
}
async function runBenchmarks() {
    const arr = Array.from({ length: 10_000 }, (_, i) => i);
    console.log(`Running benchmarks on array of length ${arr.length}`);
    await section('map', async () => {
        await bench(() => (0, batch_processing_1.mapInBatches)(arr, (x) => x + 1, { batchSize: 20, yieldThreshold: 10 }), 'mapInBatches { batchSize: 20, yieldThreshold: 10 }');
        await bench(() => (0, batch_processing_1.mapInBatches)(arr, (x) => x + 1, {
            batchSize: 20,
            yieldThreshold: 10,
            sequentialProcessing: false,
        }), 'mapInBatches { batchSize: 20, yieldThreshold: 10, sequentialProcessing: false }');
        await bench(() => Promise.resolve(lodash_1.default.map(arr, (x) => x + 1)), 'lodash.map');
        await bench(() => Promise.resolve(arr.map((x) => x + 1)), 'Array.prototype.map');
    });
    await section('filter', async () => {
        await bench(() => (0, batch_processing_1.filterInBatches)(arr, (x) => x % 2 === 0, { batchSize: 20, yieldThreshold: 10 }), 'filterInBatches { batchSize: 20, yieldThreshold: 10 }');
        await bench(() => (0, batch_processing_1.filterInBatches)(arr, (x) => x % 2 === 0, {
            batchSize: 20,
            yieldThreshold: 10,
            sequentialProcessing: false,
        }), 'filterInBatches { batchSize: 20, yieldThreshold: 10, sequentialProcessing: false }');
        await bench(() => Promise.resolve(lodash_1.default.filter(arr, (x) => x % 2 === 0)), 'lodash.filter');
        await bench(() => Promise.resolve(arr.filter((x) => x % 2 === 0)), 'Array.prototype.filter');
    });
    await section('groupBy', async () => {
        await bench(() => (0, batch_processing_1.groupByInBatches)(arr, (x) => (x % 2 === 0 ? 'even' : 'odd'), {
            batchSize: 20,
            yieldThreshold: 10,
        }), 'groupByInBatches { batchSize: 20, yieldThreshold: 10 }');
        await bench(() => (0, batch_processing_1.groupByInBatches)(arr, (x) => (x % 2 === 0 ? 'even' : 'odd'), {
            batchSize: 20,
            yieldThreshold: 10,
            sequentialProcessing: false,
        }), 'groupByInBatches { batchSize: 20, yieldThreshold: 10, sequentialProcessing: false }');
        await bench(() => Promise.resolve(lodash_1.default.groupBy(arr, (x) => (x % 2 === 0 ? 'even' : 'odd'))), 'lodash.groupBy');
    });
    await section('reduce', async () => {
        await bench(() => (0, batch_processing_1.reduceInBatches)(arr, (acc, x) => acc + x, 0, { batchSize: 20, yieldThreshold: 10 }), 'reduceInBatches { batchSize: 20, yieldThreshold: 10 }');
        await bench(() => Promise.resolve(lodash_1.default.reduce(arr, (acc, x) => acc + x, 0)), 'lodash.reduce');
        await bench(() => Promise.resolve(arr.reduce((acc, x) => acc + x, 0)), 'Array.prototype.reduce');
    });
    await section('flatMap', async () => {
        await bench(() => (0, batch_processing_1.flatMapInBatches)(arr, (x) => [x, x], { batchSize: 20, yieldThreshold: 10 }), 'flatMapInBatches { batchSize: 20, yieldThreshold: 10 }');
        await bench(() => (0, batch_processing_1.flatMapInBatches)(arr, (x) => [x, x], {
            batchSize: 20,
            yieldThreshold: 10,
            sequentialProcessing: false,
        }), 'flatMapInBatches { batchSize: 20, yieldThreshold: 10, sequentialProcessing: false }');
        await bench(() => Promise.resolve(lodash_1.default.flatMap(arr, (x) => [x, x])), 'lodash.flatMap');
        await bench(() => Promise.resolve(arr.flatMap
            ? arr.flatMap((x) => [x, x])
            : [].concat(...arr.map((x) => [x, x]))), 'Array.prototype.flatMap');
    });
    await section('forEach', async () => {
        await bench(() => (0, batch_processing_1.forEachInBatches)(arr, () => { }, { batchSize: 20, yieldThreshold: 10 }), 'forEachInBatches { batchSize: 20, yieldThreshold: 10 }');
        await bench(() => (0, batch_processing_1.forEachInBatches)(arr, () => { }, {
            batchSize: 20,
            yieldThreshold: 10,
            sequentialProcessing: false,
        }), 'forEachInBatches { batchSize: 20, yieldThreshold: 10, sequentialProcessing: false }');
        await bench(() => Promise.resolve(arr.forEach(() => { })), 'Array.prototype.forEach');
        await bench(() => Promise.resolve(lodash_1.default.forEach(arr, () => { })), 'lodash.forEach');
    });
}
// to run benchmarks use: npx ts-node src/utils/batch-processing.bench.ts
if (require.main === module) {
    runBenchmarks().catch((err) => {
        console.error(err);
        process.exit(1);
    });
}
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eslint-disable no-console */\nimport { performance } from 'node:perf_hooks';\nimport lodash from 'lodash';\nimport {\n  mapInBatches,\n  filterInBatches,\n  groupByInBatches,\n  reduceInBatches,\n  flatMapInBatches,\n  forEachInBatches,\n} from './batch-processing';\n\nasync function bench(\n  fn: () => Promise<unknown> | unknown,\n  label: string,\n  iterations = 5,\n): Promise<number> {\n  let total = 0;\n  for (let i = 0; i < iterations; i += 1) {\n    const start = performance.now();\n    // eslint-disable-next-line no-await-in-loop\n    await fn();\n    total += performance.now() - start;\n  }\n  const avg = total / iterations;\n  console.log(`${label}: avg ${avg.toFixed(2)} ms over ${iterations} runs`);\n  return avg;\n}\n\nasync function section(title: string, fn: () => Promise<void>) {\n  console.log(`\\n=== ${title} ===`);\n  await fn();\n}\n\nasync function runBenchmarks() {\n  const arr = Array.from({ length: 10_000 }, (_, i) => i);\n\n  console.log(`Running benchmarks on array of length ${arr.length}`);\n\n  await section('map', async () => {\n    await bench(\n      () => mapInBatches(arr, (x) => x + 1, { batchSize: 20, yieldThreshold: 10 }),\n      'mapInBatches { batchSize: 20, yieldThreshold: 10 }',\n    );\n    await bench(\n      () =>\n        mapInBatches(arr, (x) => x + 1, {\n          batchSize: 20,\n          yieldThreshold: 10,\n          sequentialProcessing: false,\n        }),\n      'mapInBatches { batchSize: 20, yieldThreshold: 10, sequentialProcessing: false }',\n    );\n    await bench(() => Promise.resolve(lodash.map(arr, (x) => x + 1)), 'lodash.map');\n    await bench(() => Promise.resolve(arr.map((x) => x + 1)), 'Array.prototype.map');\n  });\n\n  await section('filter', async () => {\n    await bench(\n      () => filterInBatches(arr, (x) => x % 2 === 0, { batchSize: 20, yieldThreshold: 10 }),\n      'filterInBatches { batchSize: 20, yieldThreshold: 10 }',\n    );\n    await bench(\n      () =>\n        filterInBatches(arr, (x) => x % 2 === 0, {\n          batchSize: 20,\n          yieldThreshold: 10,\n          sequentialProcessing: false,\n        }),\n      'filterInBatches { batchSize: 20, yieldThreshold: 10, sequentialProcessing: false }',\n    );\n    await bench(() => Promise.resolve(lodash.filter(arr, (x) => x % 2 === 0)), 'lodash.filter');\n    await bench(() => Promise.resolve(arr.filter((x) => x % 2 === 0)), 'Array.prototype.filter');\n  });\n\n  await section('groupBy', async () => {\n    await bench(\n      () =>\n        groupByInBatches(arr, (x) => (x % 2 === 0 ? 'even' : 'odd'), {\n          batchSize: 20,\n          yieldThreshold: 10,\n        }),\n      'groupByInBatches { batchSize: 20, yieldThreshold: 10 }',\n    );\n    await bench(\n      () =>\n        groupByInBatches(arr, (x) => (x % 2 === 0 ? 'even' : 'odd'), {\n          batchSize: 20,\n          yieldThreshold: 10,\n          sequentialProcessing: false,\n        }),\n      'groupByInBatches { batchSize: 20, yieldThreshold: 10, sequentialProcessing: false }',\n    );\n    await bench(\n      () => Promise.resolve(lodash.groupBy(arr, (x) => (x % 2 === 0 ? 'even' : 'odd'))),\n      'lodash.groupBy',\n    );\n  });\n\n  await section('reduce', async () => {\n    await bench(\n      () => reduceInBatches(arr, (acc, x) => acc + x, 0, { batchSize: 20, yieldThreshold: 10 }),\n      'reduceInBatches { batchSize: 20, yieldThreshold: 10 }',\n    );\n    await bench(() => Promise.resolve(lodash.reduce(arr, (acc, x) => acc + x, 0)), 'lodash.reduce');\n    await bench(\n      () => Promise.resolve(arr.reduce((acc, x) => acc + x, 0)),\n      'Array.prototype.reduce',\n    );\n  });\n\n  await section('flatMap', async () => {\n    await bench(\n      () => flatMapInBatches(arr, (x) => [x, x], { batchSize: 20, yieldThreshold: 10 }),\n      'flatMapInBatches { batchSize: 20, yieldThreshold: 10 }',\n    );\n    await bench(\n      () =>\n        flatMapInBatches(arr, (x) => [x, x], {\n          batchSize: 20,\n          yieldThreshold: 10,\n          sequentialProcessing: false,\n        }),\n      'flatMapInBatches { batchSize: 20, yieldThreshold: 10, sequentialProcessing: false }',\n    );\n    await bench(() => Promise.resolve(lodash.flatMap(arr, (x) => [x, x])), 'lodash.flatMap');\n    await bench(\n      () =>\n        Promise.resolve(\n          arr.flatMap\n            ? arr.flatMap((x) => [x, x])\n            : ([] as number[]).concat(...arr.map((x) => [x, x])),\n        ),\n      'Array.prototype.flatMap',\n    );\n  });\n\n  await section('forEach', async () => {\n    await bench(\n      () => forEachInBatches(arr, () => {}, { batchSize: 20, yieldThreshold: 10 }),\n      'forEachInBatches { batchSize: 20, yieldThreshold: 10 }',\n    );\n    await bench(\n      () =>\n        forEachInBatches(arr, () => {}, {\n          batchSize: 20,\n          yieldThreshold: 10,\n          sequentialProcessing: false,\n        }),\n      'forEachInBatches { batchSize: 20, yieldThreshold: 10, sequentialProcessing: false }',\n    );\n    await bench(() => Promise.resolve(arr.forEach(() => {})), 'Array.prototype.forEach');\n    await bench(() => Promise.resolve(lodash.forEach(arr, () => {})), 'lodash.forEach');\n  });\n}\n\n// to run benchmarks use: npx ts-node src/utils/batch-processing.bench.ts\nif (require.main === module) {\n  runBenchmarks().catch((err) => {\n    console.error(err);\n    process.exit(1);\n  });\n}\n"]}