Benchmark: Hashmap vs Array.Filter

Script Preparation code:

const counter = 10000
const map = new Map()
const array = new Array(counter)

window.counter = counter
window.map = map
window.array = array
for (let i = 0; i < counter; i++) {
    map.set(i)
    array[counter] = i
}

​x
 
const counter = 10000const map = new Map()const array = new Array(counter)​window.counter = counterwindow.map = mapwindow.array = arrayfor (let i = 0; i < counter; i++) {    map.set(i)    array[counter] = i}

Tests:

Hashmap

for (let i = 0; i < 20000; i++) {
    window.map.has(500)
}

 
for (let i = 0; i < 20000; i++) {    window.map.has(500)}

Array.filter

for (let i = 0; i < 20000; i++) {
    window.array.filter((value) => value === 500)
}

 
​for (let i = 0; i < 20000; i++) {    window.array.filter((value) => value === 500)}

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Experimental features:

Memory measurements supported only in Chrome.
For precise memory measurements Chrome must be launched with --enable-precise-memory-info flag.
More information: Monitoring JavaScript Memory

Test case name	Result
Hashmap
Array.filter

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: one month ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/132.0.0.0 Safari/537.36 OPR/117.0.0.0

Browser/OS: Opera 117 on Windows

View result in a separate tab

Test name	Executions per second
Hashmap	20446.9 Ops/sec
Array.filter	0.4 Ops/sec

Autogenerated LLM Summary (model llama3.2:3b, generated 7 months ago):

Let's break down the benchmark and explain what's being tested.

Benchmark Definition

The benchmark is designed to compare two approaches:

Hashmap: Using the Map data structure in JavaScript to test its performance for fast lookups.
Array.filter: Using the filter() method on an array to test its performance for filtering elements based on a condition.

Options Compared

In this benchmark, we have two options being compared:

Hashmap (using Map)
Array.filter

These two approaches are being tested for their execution speed and efficiency in performing fast lookups or filtering elements.

Pros and Cons of Each Approach:

Hashmap

Pros:

Hashmaps provide fast lookups with an average time complexity of O(1), making them suitable for applications that require frequent searches.
They can handle a large number of key-value pairs efficiently.

Cons:

Hashmaps are not designed specifically for filtering elements, which can lead to slower performance compared to other data structures like arrays.

Array.filter

Pros:

The filter() method is optimized for filtering elements in an array and has a time complexity of O(n), making it suitable for applications that require element removal.
It's a built-in method, so you don't need to create a custom implementation.

Cons:

The filter() method scans the entire array, which can lead to slower performance compared to other data structures like hashmaps.
It may not be as efficient for large datasets since it requires additional memory allocations and copies of elements.

Library and Purpose

In this benchmark, no specific library is being used. However, it's worth noting that some JavaScript environments might use a Map implementation that's derived from the V8 engine (used in Chrome). This could affect the performance results.

Special JS Feature or Syntax

There are no special JavaScript features or syntax mentioned in this benchmark. The code is straightforward and uses standard JavaScript constructs.

Other Alternatives

Some other data structures you might consider for this type of benchmark include:

Set: Similar to Map, but it's more lightweight and optimized for fast lookups.
Sqrtcache: A custom implementation of a cache that uses a square root table for fast lookups.
Trie (also known as a prefix tree): An efficient data structure for storing and searching key-value pairs, especially when the keys are strings.

Keep in mind that these alternatives might have different performance characteristics depending on your specific use case and requirements.

LLMs can make mistakes. Check important info.

Let's break down the benchmark and explain what's being tested.

**Benchmark Definition**

The benchmark is designed to compare two approaches:

1. **Hashmap**: Using the `Map` data structure in JavaScript to test its performance for fast lookups.
2. **Array.filter**: Using the `filter()` method on an array to test its performance for filtering elements based on a condition.

**Options Compared**

In this benchmark, we have two options being compared:

*   Hashmap (using `Map`)
*   Array.filter

These two approaches are being tested for their execution speed and efficiency in performing fast lookups or filtering elements.

**Pros and Cons of Each Approach:**

### Hashmap

Pros:

*   Hashmaps provide fast lookups with an average time complexity of O(1), making them suitable for applications that require frequent searches.
*   They can handle a large number of key-value pairs efficiently.

Cons:

*   Hashmaps are not designed specifically for filtering elements, which can lead to slower performance compared to other data structures like arrays.

### Array.filter

Pros:

*   The `filter()` method is optimized for filtering elements in an array and has a time complexity of O(n), making it suitable for applications that require element removal.
*   It's a built-in method, so you don't need to create a custom implementation.

Cons:

*   The `filter()` method scans the entire array, which can lead to slower performance compared to other data structures like hashmaps.
*   It may not be as efficient for large datasets since it requires additional memory allocations and copies of elements.

**Library and Purpose**

In this benchmark, no specific library is being used. However, it's worth noting that some JavaScript environments might use a `Map` implementation that's derived from the V8 engine (used in Chrome). This could affect the performance results.

**Special JS Feature or Syntax**

There are no special JavaScript features or syntax mentioned in this benchmark. The code is straightforward and uses standard JavaScript constructs.

**Other Alternatives**

Some other data structures you might consider for this type of benchmark include:

*   **Set**: Similar to `Map`, but it's more lightweight and optimized for fast lookups.
*   **Sqrtcache**: A custom implementation of a cache that uses a square root table for fast lookups.
*   **Trie** (also known as a prefix tree): An efficient data structure for storing and searching key-value pairs, especially when the keys are strings.

Keep in mind that these alternatives might have different performance characteristics depending on your specific use case and requirements.

Related benchmarks:

Hashmap vs Array.Filter (version: 0)

Comparing performance of: Hashmap vs Array.filter

Created: 4 years ago by: Guest

Jump to the latest result

Hashmap

Array.filter

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 7 months ago):

Hashmap

Array.filter