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Obj vs Map_111
(version: 0)
Obj vs Map
Comparing performance of:
Obj vs Map
Created:
5 years ago
by:
Registered User
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Tests:
Obj
const size = 10000 let map = new Map() let obj = {} let data = new Array(size).fill((Math.random() +1) * size) data.forEach((number) => { if(obj[number]) obj[number]+=1 else obj[number] = 1 })
Map
const size = 10000 let map = new Map() let obj = {} let data = new Array(size).fill((Math.random() +1) * size) data.forEach((number) => { if(map.get(number)) map.set(number, map.get(number)+1) else map.set(number, 1) })
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (2)
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Result
Obj
Map
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Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
I'd be happy to explain the JavaScript benchmark and its test cases. **What is being tested?** The benchmark measures the performance of two approaches: Object (Obj) and Map data structures in JavaScript. The tests are designed to count the frequency of random numbers generated within a large array. **Options compared:** Two options are being compared: 1. **Object (Obj)**: In this approach, an object is created to store the counts of each number in the array. For each number, if the key already exists in the object, its value is incremented; otherwise, it's set to 1. 2. **Map (Map)**: This approach uses a Map data structure to achieve the same result as the Object approach but with different methods: - `map.get(number)`: Checks if the number is present in the map and returns its current count. - `map.set(number, ...)` : Sets the value for the given key (number). If the key doesn't exist, it creates a new entry. **Pros and Cons of each approach:** 1. **Object (Obj)**: - Pros: Simpler implementation; faster access to element counts because keys are contiguous in memory. - Cons: Slower performance compared to Map since accessing an object's property is slower than looking up a key-value pair in a map. 2. **Map (Map)**: - Pros: Faster performance due to efficient lookups, especially for large datasets; also more flexible with potential future improvements or extensions like insertion orders. - Cons: Slightly more complex implementation compared to the Object approach; slower initial access because it involves a hash-based lookup algorithm. **Other considerations:** - The choice between using an object and a map should be based on the specific requirements of your application, such as performance needs versus ease of development. - For this benchmark, both approaches are designed for simplicity and to focus on the core aspect being measured (performance), so we choose one implementation style over another. **Library used:** In this case, there is no explicit library mentioned in the provided JSON. The JavaScript standard library (`Map`) and `Object` are used as part of the native features for data structures. **Special JS feature or syntax:** No special JavaScript features or syntax are explicitly utilized beyond the use of the built-in `Map` data structure and object literal syntax to create objects. **Alternative approaches:** For testing different data structures, alternatives might include: - Using arrays (indexing) vs. linked lists vs. trees as an alternative way to count frequencies. - Implementing your own custom data structures with a focus on performance optimization. - Using existing libraries like Lodash or Underscore.js which provide methods to achieve similar operations in a more concise manner. These alternatives would typically depend on the specific requirements of the project and whether any additional features are necessary beyond basic frequency counting.
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