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Map vs Object (R+W)
(version: 0)
Read/Write of Map vs Object (competition use only, please don't use these in the real world).
Comparing performance of:
Map vs Object
Created:
5 years ago
by:
Guest
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Script Preparation code:
var map = new Map(); var obj = {}; var count = 10000; var i = 0, a;
Tests:
Map
for (i = 0; i < count; i++) { map.set((i * 10000).toString(), i); } for (i = 0; i < count; i++) { a = map.get((i * 10000).toString()); }
Object
for (i = 0; i < count; i++) { obj[(i * 10000).toString()] = i; } for (i = 0; i < count; i++) { a = obj[(i * 10000).toString()]; }
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (2)
Previous results
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Test case name
Result
Map
Object
Fastest:
N/A
Slowest:
N/A
Latest run results:
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Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
Let's dive into the world of JavaScript microbenchmarks and explore what's being tested in this specific benchmark. **What is being tested?** The provided JSON represents two test cases: `Map` and `Object`. Both tests are designed to measure the performance of accessing elements in a data structure. The goal is to compare the read-write performance of `Map` and `Object` in JavaScript. In each test case, a loop is executed `count` times (set to 10,000), where: 1. An element is set using either `map.set()` or `obj[(i * 10000).toString()] = i;`. 2. The same element is retrieved using either `map.get((i * 10000).toString())` or `a = obj[(i * 10000).toString()]`. **Options compared** Two options are being compared: 1. **Map**: A `Map` object, which is a hash table-like data structure that stores key-value pairs. 2. **Object**: An ordinary JavaScript object (using bracket notation). **Pros and cons of each approach:** * **Map**: + Pros: - Fast lookups due to its hash-based indexing. - Efficient insertion and deletion of elements. + Cons: - May require more memory compared to objects, as it needs to store a separate index. - Not all browsers support `Map` natively (e.g., older versions of Internet Explorer). * **Object**: + Pros: - Widely supported across most modern browsers and JavaScript engines. - Low overhead in terms of memory usage. + Cons: - Slower lookups compared to `Map`, as it relies on bracket notation or `in` operator. **Library used** In this benchmark, no external library is being used. Both tests are using native JavaScript features: `Map` and objects. **Special JS feature/syntax** No special JavaScript features or syntax is being used in these test cases. The focus is solely on comparing the performance of accessing elements in different data structures. **Other alternatives** If you wanted to use alternative data structures, such as: 1. **Arrays**: Accessing elements in an array would be similar to using `Map`, but with a fixed-size index. 2. **Set**: A set is an unordered collection of unique values. While it's not suitable for this specific benchmark, it could provide interesting insights into set operations performance. Keep in mind that these alternatives might not directly relate to the original intent of the benchmark, which focuses on comparing `Map` and object-based access patterns. That's a summary of what's being tested in this JavaScript microbenchmark!
Related benchmarks:
Map vs Object read performance for a 1000 key lookup
Map vs object copying
Map vs Object (real-world) Performance - Forked
Map.prototype.forEach vs Array.prototype.forEach
Map.forEach vs Array.forEach vs Array.from(Map.prototype.values()).forEach
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