Benchmark: TextEncoder vs String hash v2

Script Preparation code:

iterations = 1000;
function randomStringGen(n) {
    let strings = [];
    for (let i = 0; i < n; i++) {
      let s = Math.random().toString(36).substring(2, 15) + Math.random().toString(36).substring(2, 15);
      strings[i] = s;
    }
    return strings;
}
var randomStrings = randomStringGen(iterations);
var encoder = new TextEncoder();
var arrayBuffer = new ArrayBuffer(iterations*1000);
var buffer = new Uint8Array(arrayBuffer);

AخA
 
iterations = 1000;function randomStringGen(n) {    let strings = [];    for (let i = 0; i < n; i++) {      let s = Math.random().toString(36).substring(2, 15) + Math.random().toString(36).substring(2, 15);      strings[i] = s;    }    return strings;}var randomStrings = randomStringGen(iterations);var encoder = new TextEncoder();var arrayBuffer = new ArrayBuffer(iterations*1000);var buffer = new Uint8Array(arrayBuffer);

Tests:

Baseline encoder

var j = 0;
for (let i = 0; i < iterations; i++) {
  var str = randomStrings[i % iterations];
  buffer[j] = str.length;
  var res = encoder.encodeInto(str, buffer.subarray(j+1));
  j = j + res.written;
}

 
var j = 0;for (let i = 0; i < iterations; i++) {  var str = randomStrings[i % iterations];  buffer[j] = str.length;  var res = encoder.encodeInto(str, buffer.subarray(j+1));  j = j + res.written;}

baseline hash

var stringMap = {};
var counter = 0;
function stringToMap(s) {
   	var i = stringMap[s];
	if (i === undefined) {
      stringMap[s] = counter++;
    } else {
      return i;
    }
}
var j = 0;
for (let i = 0; i < iterations; i++) {
  var str = randomStrings[i % iterations];
  var num = stringToMap(str);
  buffer[j] = num;
  j = j + 8;
}

 
var stringMap = {};var counter = 0;function stringToMap(s) {    var i = stringMap[s];    if (i === undefined) {      stringMap[s] = counter++;    } else {      return i;    }}var j = 0;for (let i = 0; i < iterations; i++) {  var str = randomStrings[i % iterations];  var num = stringToMap(str);  buffer[j] = num;  j = j + 8;}

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
Baseline encoder
baseline hash

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (X11; Linux x86_64; rv:125.0) Gecko/20100101 Firefox/125.0

Browser/OS: Firefox 125 on Linux

View result in a separate tab

Test name	Executions per second
Baseline encoder	8036.6 Ops/sec
baseline hash	11038.6 Ops/sec

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

Benchmark Overview

The provided JSON represents a benchmark test case for comparing the performance of TextEncoder in JavaScript with two alternative approaches: hashing a string using a custom map and simply encoding the string.

Test Case 1: Baseline Encoder

This test case uses the TextEncoder to encode the length of a random string into an array buffer. The encoder is used to encode each character of the string, and the written bytes are stored in the buffer.

Pros:

This approach tests the performance of TextEncoder in encoding strings.
It's a straightforward test case that can be easily implemented.

Cons:

May not accurately represent real-world use cases where strings are encoded for storage or transmission.

Test Case 2: Baseline Hash

This test case uses a custom map to hash the length of a random string. The map is used to store the length of each string, and the hashed value is stored in an array buffer.

Pros:

This approach tests the performance of hashing strings.
It can be useful for benchmarking algorithms that involve string hashing.

Cons:

May not accurately represent real-world use cases where strings are encoded for storage or transmission.
The custom map implementation may introduce additional overhead compared to a simple TextEncoder usage.

Other Considerations

Both test cases use the same array buffer size and random string generation function, which helps ensure that the results are comparable.
However, it's worth noting that using an array buffer for storing the result of encoding or hashing a string may not be the most efficient approach in real-world scenarios. A more common approach would be to store only the encoded or hashed value.

Library: TextEncoder

TextEncoder is a built-in JavaScript function that encodes a string into an array of bytes, suitable for storing in a buffer or transmitting over a network. The encodeInto() method takes two arguments: the string to encode and the buffer to write the encoded data into.

Special JS Feature/ Syntax: None

There are no special JavaScript features or syntax used in this benchmark test case that would require additional explanation.

Alternatives

Other approaches for testing the performance of encoding strings include:

Using a different encoding scheme, such as base64 or URL-safe base64.
Testing the performance of different string encoding algorithms, such as UTF-8 or UTF-16.
Benchmarking the performance of other libraries or frameworks that provide string encoding capabilities.

Overall, this benchmark test case provides a simple and straightforward way to compare the performance of TextEncoder with two alternative approaches. However, it's worth noting that real-world use cases may involve additional considerations such as buffer size, data type, and encoding scheme, which are not addressed in this benchmark.

LLMs can make mistakes. Check important info.

**Benchmark Overview**

The provided JSON represents a benchmark test case for comparing the performance of `TextEncoder` in JavaScript with two alternative approaches: hashing a string using a custom map and simply encoding the string.

**Test Case 1: Baseline Encoder**

This test case uses the `TextEncoder` to encode the length of a random string into an array buffer. The encoder is used to encode each character of the string, and the written bytes are stored in the buffer.

Pros:

* This approach tests the performance of `TextEncoder` in encoding strings.
* It's a straightforward test case that can be easily implemented.

Cons:

* May not accurately represent real-world use cases where strings are encoded for storage or transmission.

**Test Case 2: Baseline Hash**

This test case uses a custom map to hash the length of a random string. The map is used to store the length of each string, and the hashed value is stored in an array buffer.

Pros:

* This approach tests the performance of hashing strings.
* It can be useful for benchmarking algorithms that involve string hashing.

Cons:

* May not accurately represent real-world use cases where strings are encoded for storage or transmission.
* The custom map implementation may introduce additional overhead compared to a simple `TextEncoder` usage.

**Other Considerations**

* Both test cases use the same array buffer size and random string generation function, which helps ensure that the results are comparable.
* However, it's worth noting that using an array buffer for storing the result of encoding or hashing a string may not be the most efficient approach in real-world scenarios. A more common approach would be to store only the encoded or hashed value.

**Library: TextEncoder**

`TextEncoder` is a built-in JavaScript function that encodes a string into an array of bytes, suitable for storing in a buffer or transmitting over a network. The `encodeInto()` method takes two arguments: the string to encode and the buffer to write the encoded data into.

**Special JS Feature/ Syntax: None**

There are no special JavaScript features or syntax used in this benchmark test case that would require additional explanation.

**Alternatives**

Other approaches for testing the performance of encoding strings include:

* Using a different encoding scheme, such as base64 or URL-safe base64.
* Testing the performance of different string encoding algorithms, such as UTF-8 or UTF-16.
* Benchmarking the performance of other libraries or frameworks that provide string encoding capabilities.

Overall, this benchmark test case provides a simple and straightforward way to compare the performance of `TextEncoder` with two alternative approaches. However, it's worth noting that real-world use cases may involve additional considerations such as buffer size, data type, and encoding scheme, which are not addressed in this benchmark.

Related benchmarks:

TextEncoder vs String hash v2 (version: 1)

Test TextEncoder encoding vs simply encoding with a string

Comparing performance of: Baseline encoder vs baseline hash

Created: 4 years ago by: Registered User

Jump to the latest result

Baseline encoder

baseline hash

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):