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Array.prototype.map vs Lodash.map on large data
(version: 0)
Approaches performance
Comparing performance of:
Array.prototype.map vs Lodash.map
Created:
5 years ago
by:
Guest
Jump to the latest result
HTML Preparation code:
<script src="https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.5/lodash.js"></script>
Script Preparation code:
var data = Array(1000000);
Tests:
Array.prototype.map
data.map(function (number) { return number * 2});
Lodash.map
_.map(data, function (number) { return number * 2});
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (2)
Previous results
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Test case name
Result
Array.prototype.map
Lodash.map
Fastest:
N/A
Slowest:
N/A
Latest run results:
Run details:
(Test run date:
4 months ago
)
User agent:
Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/143.0.0.0 Safari/537.36 Edg/143.0.0.0
Browser/OS:
Chrome 143 on Mac OS X 10.15.7
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Embed Benchmark Result
Test name
Executions per second
Array.prototype.map
643.5 Ops/sec
Lodash.map
569.9 Ops/sec
Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
Let's dive into the benchmark test case provided by MeasureThat.net. **What is being tested?** The benchmark tests the performance difference between two approaches: 1. `Array.prototype.map` (native JavaScript method) 2. `_map` function from Lodash library In particular, both methods are applied to an array of 1,000,000 elements and perform a simple transformation on each element: multiplying it by 2. **Options compared** The benchmark compares the performance of two approaches: * `Array.prototype.map`: This is a native JavaScript method that applies a specified function to every element in an array. * `_map` from Lodash library: This is a higher-order function that takes a callback function and applies it to each element in an array. It's essentially a wrapper around the native JavaScript `map` method. **Pros and Cons** Here are some pros and cons of each approach: * `Array.prototype.map`: + Pros: - Native JavaScript, so it should be faster and more efficient. - Less overhead compared to using a library like Lodash. + Cons: - Can be less readable due to the use of `this` context and binding. - May have limitations in terms of functional programming capabilities. * `_map` from Lodash library: + Pros: - Provides a more concise and readable way to perform transformations on arrays. - Offers additional features like memoization, caching, and support for more complex data structures. + Cons: - Introduces an external dependency (Lodash library), which can increase the bundle size and complexity. - May have a slight performance overhead compared to native JavaScript `map`. **Other considerations** In terms of special JavaScript features or syntax, neither approach uses anything that's not standard in modern JavaScript. However, if you're using ES6+ features like `const`, `let`, or `class` declarations, you might want to consider those when writing your own benchmark code. **Alternatives** If you need to compare the performance of other array methods or libraries, here are some alternatives: * For native JavaScript methods: + `Array.prototype.forEach` + `Array.prototype.filter` + `Array.prototype.reduce` * For other library-based approaches: + Use functions like `forEach`, `filter`, and `reduce` from the `array` method in Lodash. + Consider using functional programming libraries like Ramda or Purescript. In terms of other benchmarking frameworks, MeasureThat.net is quite unique because it allows users to create their own microbenchmarks with a simple HTML and JavaScript setup. However, if you're looking for alternative frameworks, you might want to explore options like: * Benchmark.js * JSPerf * Webperf These tools provide more features and flexibility for creating complex benchmarks, but they often require more setup and configuration compared to MeasureThat.net's simple approach.
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