Benchmark: Map lookup - MeasureThat.net

Script Preparation code:

let someMap = {}
for (let i = 0; i < 100; i++) {
    someMap[`${i}-test`] = i * 2
}

let someMapNumber = {}
for (let i = 0; i < 100; i++) {
    someMap[i] = i * 2
}

Tests:

string
let someMap = {} for (let i = 0; i < 100; i++) { someMap[`${i}-test`] = i * 2 } for (let i = 0; i < 100; i++) { console.log(someMap[`${i}-test`]) }
number
let someMapNumber = {} for (let i = 0; i < 100; i++) { someMapNumber[i] = i * 2 } for (let i = 0; i < 100; i++) { console.log(someMapNumber[i]) }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
string
number

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):

LLMs can make mistakes. Check important info.

I'll break down the provided JSON benchmark definition and explain what's being tested, compared options, pros and cons, library usage, special JS features, and other considerations.

**Benchmark Definition**

The provided JSON represents a JavaScript microbenchmark that tests two different approaches to accessing an array (or in this case, an object) using string keys. There are no special JS features or syntax used in the benchmark definition.

**Script Preparation Code**

The script preparation code creates two objects:

1. `someMap`: An object with string keys generated using template literals (`i-test`), where `i` ranges from 0 to 99.
2. `someMapNumber`: An array with integer values, also generated using a loop.

**Html Preparation Code**

There is no HTML preparation code provided, which means the benchmark only runs in a JavaScript context.

**Individual Test Cases**

The benchmark consists of two test cases:

1. **"string"`**: This test case creates `someMap` and then iterates over its keys using string indices (`i-test`) to access the corresponding values.
2. **"number"`**: This test case creates `someMapNumber` and then iterates over its indices using integer indices (`i`) to access the corresponding values.

**Comparison of Options**

The benchmark compares two approaches:

1. **String-based indexing**: Using string keys (`i-test`) to access an object.
2. **Integer-based indexing**: Using array indices (`i`) to access an array.

**Pros and Cons of each approach**

* **String-based indexing**:
	+ Pros: Can be more readable and intuitive, especially for developers familiar with JavaScript's object notation.
	+ Cons: May lead to slower performance due to the overhead of string creation and lookup.
* **Integer-based indexing**:
	+ Pros: Typically faster than string-based indexing since arrays are optimized for integer-based access.
	+ Cons: Requires more effort to maintain readability, especially in complex scenarios.

**Library Usage**

There is no explicit library usage in the benchmark definition. However, it's worth noting that JavaScript's built-in `Object` and `Array` types are being used extensively throughout the script.

**Special JS Features**

None of the special JS features or syntax are explicitly mentioned in the benchmark definition.

**Other Considerations**

* **Cache locality**: The string-based indexing approach may exhibit poor cache locality, which can lead to slower performance.
* **String creation overhead**: Creating strings using template literals can add overhead due to the creation and garbage collection of new strings.

**Alternatives**

If you were to create a similar benchmark, you might consider exploring other approaches, such as:

* Using `Symbol` keys for fast and efficient string-based indexing.
* Utilizing libraries like `fast-stories` or `js-obj-csv` for optimized array indexing and manipulation.
* Implementing custom data structures or caching mechanisms to mitigate the performance implications of string-based indexing.

Related benchmarks:

Map lookup (version: 0)

Comparing performance of: string vs number

Created: 5 years ago by: Guest

Jump to the latest result

string

number

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):