Benchmark: map vs arr - MeasureThat.net

Script Preparation code:

var a1 = [];
for (var f = 0; f < 20000; f++) {
    var newNo = Math.floor(Math.random()*60000+10000);
    a1.push({id: newNo, name: 'test'});
}

Tests:

map
var unique = {}; a1.filter((row) =>{ var id = row.id; if(!unique[id]){ unique[id] = 1; return true; }else{ return false; } });
arr
var unique1 = []; a1.filter((row) => { var id = row.id; if(unique1.indexOf(id) === -1){ unique1.push(id); return true; }else{ return false; } });

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
map
arr

Fastest: N/A

Slowest: N/A

Latest run results:

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Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):

LLMs can make mistakes. Check important info.

Let's break down what's being tested in the provided JSON benchmark.

**Benchmark Definition**

The benchmark is comparing two approaches: using `Array.prototype.filter()` with an arrow function (Map) and using an array to keep track of unique IDs (Array). The script preparation code generates a large array (`a1`) with 20,000 objects, each containing an ID and a name.

**Options being compared**

Two options are being compared:

1. **Map**: Using `Array.prototype.filter()` with an arrow function to remove duplicates from the array.
2. **Array**: Manually keeping track of unique IDs in an array (`unique1`) to filter out duplicates.

**Pros and Cons**

**Map**

Pros:

* Concise and expressive code
* Leverages the built-in functionality of `filter()`
* Efficient, as it only iterates over the elements that need to be processed

Cons:

* Requires a modern JavaScript engine that supports arrow functions (most do)
* Can be slower than manual implementation due to function call overhead

**Array**

Pros:

* Manually controlling the iteration process can lead to better performance
* No function call overhead, as it's a simple array lookup

Cons:

* More verbose and less expressive code
* Requires additional memory to store the `unique1` array

**Other considerations**

* The benchmark assumes that the `filter()` method is implemented in a way that's optimized for arrow functions. In older JavaScript engines or certain implementations, this might not be the case.
* The use of a random ID generator (`Math.floor(Math.random()*60000+10000)`) ensures that the data is uniformly distributed and doesn't exhibit any biases.

**Library/Language features**

None are explicitly mentioned in the benchmark definition. However, it's worth noting that modern JavaScript engines (e.g., V8 in Chrome) support various language features that might affect performance, such as:

* `const` and `let` declarations for scope control
* `for...of` loops for iterating over arrays
* `Object.prototype.hasOwnProperty.call()` for checking object property existence

**Special JS feature/Syntax**

None are explicitly used in the benchmark definition. However, it's worth noting that some modern JavaScript engines might optimize or compile certain features, such as:

* Template literals (`${}`) for string interpolation
* Arrow functions (`() => { }`) for concise function expressions
* `const` and `let` declarations for scope control

**Alternatives**

Other alternatives to compare in this benchmark could include:

* Using a different data structure, like a Set or a Map, to keep track of unique IDs
* Implementing a custom filtering algorithm using bitwise operations or other low-level techniques
* Comparing the performance of different JavaScript engines or browsers with varying levels of optimization

Related benchmarks:

map vs arr (version: 0)

Comparing performance of: map vs arr

Created: 9 years ago by: Guest

Jump to the latest result

map

arr

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

No previous run results

Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):