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Has (Map) vs Has (Set)
(version: 0)
Comparing performance of:
Has (Map) vs Has (Set)
Created:
3 years ago
by:
Registered User
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Script Preparation code:
var a = new Map([[1,1],[2,1],[3,1],[4,1],[5,1],[6,1],[7,1],[8,1],[9,1],[10,1]]) var b = new Set([1,2,3,4,5,6,7,8,9,10])
Tests:
Has (Map)
a.has(10)
Has (Set)
b.has(10)
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (2)
Previous results
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Test case name
Result
Has (Map)
Has (Set)
Fastest:
N/A
Slowest:
N/A
Latest run results:
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Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
I'll break down the explanation into sections to make it easier to understand. **Benchmark Overview** MeasureThat.net is a website where users can create and run JavaScript microbenchmarks. The provided JSON represents a benchmark definition, which includes: * **Script Preparation Code**: A script that creates two data structures: a Map `a` with 10 key-value pairs, and a Set `b` with the same keys. * **Html Preparation Code**: Not specified in this example, but it might be used to set up any HTML elements required for the benchmark. **Options being compared** The benchmark compares two options: 1. Using the `has()` method on a Map (`a.has(10)`) 2. Using the `has()` method on a Set (`b.has(10)`) These methods are part of the JavaScript built-in data structures, specifically designed for efficient lookups. **Pros and Cons** * **Using `has()` on a Map**: Maps use a hash table internally, which allows for fast lookup times (O(1) on average). However, this comes at the cost of memory usage and potentially slower iteration over the keys. * **Using `has()` on a Set**: Sets also use a hash table internally, but with some differences in implementation. They are optimized for fast membership testing, which can be faster than looking up an element in a map (O(1) on average). However, sets might not provide the same level of iteration flexibility as maps. **Other considerations** * The benchmark is likely trying to measure the performance difference between using `has()` on a Map and a Set for small datasets. For larger datasets or more complex operations, other factors like memory usage, cache efficiency, and algorithmic complexity may become more important. * Using a hash table data structure can be beneficial when looking up elements by key, as it allows for fast lookup times. **Library used (if applicable)** In this example, no external library is explicitly mentioned. However, if the benchmark were to use a third-party library like `fast-json-stable-stringify` or `json-stable-stringify`, it would be useful for serialization and deserialization of the data structures. **Special JS feature or syntax** There are no special features or syntax used in this benchmark example. It solely relies on JavaScript's built-in data structures (Maps and Sets) and standard JavaScript methods (`has()`). **Other alternatives** If you wanted to test other options, here are a few examples: * Using `Array.includes()` instead of `has()` * Using a custom implementation for searching in the data structures * Testing with different sizes or distributions of data elements Keep in mind that MeasureThat.net provides a wide range of benchmarking options and scripts, so you can explore other scenarios to suit your needs.
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