Benchmark: Text search performance

HTML Preparation code:

<div>Tests</div>
<script src='https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.5/lodash.min.js'></script>

Script Preparation code:

function generateItems() {
    let items = [];

    for (let i = 0; i < 60000; i++) {
        items.push({
            value: 'test' + Math.random()
        });
    }

    return items;
}

Tests:

Includes
let items = generateItems(); let filteredItems = items.filter(item => item.value.includes('test0.5'));
Regex
let items = generateItems(); let filteredItems = items.filter(item => /test0\.5/.test(item.value));
Search
let items = generateItems(); let filteredItems = items.filter(item => item.value.search(/test0\.5/) >= 0);
Match
let items = generateItems(); let filteredItems = items.filter(item => Boolean(item.value.match(/test0\.5/)));
IndexOf
let items = generateItems(); let filteredItems = items.filter(item => item.value.indexOf('test0.5') >= 0);
Lodash Includes
let items = generateItems(); let filteredItems = items.filter(item => _.includes(item.value, 'test0.5'));

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Includes
Regex
Search
Match
IndexOf
Lodash Includes

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

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

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I'll break down the benchmark and its various test cases, explaining what's being tested, the pros and cons of each approach, and any relevant libraries or special features used.

**Benchmark Overview**

The benchmark is designed to compare the performance of different text search methods. The script generates an array of 60,000 objects with a random string value, and then filters the array using various methods. The goal is to find the fastest method for filtering an array of strings that contains a specific pattern or substring.

**Test Cases**

Here's a brief explanation of each test case:

1. **Includes**: Uses the `includes()` method to check if the string contains the specified pattern.
	* Pros: Simple and intuitive, widely supported by modern browsers.
	* Cons: May be slower than other methods for large arrays or complex patterns.
2. **Regex**: Uses a regular expression to search for the pattern in the string.
	* Pros: Highly flexible and powerful, can match complex patterns.
	* Cons: Can be slow for simple searches or large arrays.
3. **Search**: Uses the `search()` method to find the index of the first occurrence of the pattern in the string.
	* Pros: Faster than `includes()` for very long strings or performance-critical applications.
	* Cons: May not work as expected if the pattern is not found, can be slower for small arrays.
4. **Match**: Uses the `match()` method to search for a full match of the pattern in the string.
	* Pros: Similar to `includes()`, but returns an array with the matched string.
	* Cons: May be slower than other methods for large arrays or complex patterns.
5. **IndexOf**: Uses the `indexOf()` method to find the index of the first occurrence of the substring.
	* Pros: Fast and efficient, widely supported by modern browsers.
	* Cons: Only returns the index of the first occurrence, may not work as expected if the pattern is not found.
6. **Lodash Includes**: Uses the `includes()` function from the Lodash library to check if an element is in an array.
	* Pros: Similar to native `includes()`, but provides additional utility functions and better performance for large arrays.
	* Cons: Requires including the Lodash library, which may add overhead.

**Library and Special Features**

The benchmark uses the following libraries:

1. **Lodash**: A popular JavaScript library that provides a wide range of utility functions, including `includes()`. The Lodash library is included in the HTML preparation code.

The benchmark does not use any special JavaScript features or syntax beyond what's supported by modern browsers.

**Other Alternatives**

If you're looking for alternative text search methods or want to explore other approaches, consider the following:

1. **Substring searching**: Use a simple substring search algorithm, such as iterating through the string and checking if the pattern matches at each position.
2. **Bloom filters**: Use a Bloom filter data structure to quickly determine if an element is present in the array without actually filtering it.
3. **Hash-based filtering**: Use a hash function to map the string values to indices in an array, then use a binary search algorithm to find matching elements.

Keep in mind that these alternatives may have different performance characteristics and trade-offs compared to the methods tested in the benchmark.

Related benchmarks:

Text search performance (version: 2)

Comparing various text search methods

Comparing performance of: Includes vs Regex vs Search vs Match vs IndexOf vs Lodash Includes

Created: 5 years ago by: Registered User

Jump to the latest result

Includes

Regex

Search

Match

IndexOf

Lodash Includes

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):