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ae4da6d46qsd4sd2
(version: 0)
Lookup of map vs object
Comparing performance of:
Map lookup vs Obj lookup
Created:
4 years ago
by:
Guest
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Tests:
Map lookup
const x = new Map() for (i=0; i<200; i++) { const value = x.get(i) x.set(i, value || 1000) }
Obj lookup
const x = {} for (i=0; i<200; i++) { const value = x[i] x[i] = value || 1000 }
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (2)
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Test case name
Result
Map lookup
Obj lookup
Fastest:
N/A
Slowest:
N/A
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Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
**Overview of the Benchmark** The provided benchmark measures the performance difference between two approaches: using a `Map` data structure and an object (`{}`) for storing and retrieving values in JavaScript. **Script Preparation Code** Since both test cases have empty script preparation codes, we can assume that no additional setup is required before running each test case. This means that any overhead associated with setting up the environment, such as creating a new context or importing modules, has been accounted for. **Options Compared** Two options are being compared: 1. **Map Lookup**: Using a `Map` data structure to store and retrieve values. 2. **Object Lookup**: Using an object (`{}`) to store and retrieve values. **Pros and Cons of Each Approach** ### Map Lookup Pros: * Faster lookups: `Map`s use a hash table internally, which provides fast lookups (O(1) on average). * Efficient data storage: `Map`s can efficiently store and retrieve large amounts of data. Cons: * Limited direct indexing: Unlike objects, `Map`s do not support direct indexing using square brackets (`[]`). * More complex usage: `Map`s require more code to use compared to objects (e.g., `get()` instead of `[]` notation). ### Object Lookup Pros: * Simple and intuitive usage: Objects support direct indexing using square brackets (`[]`) and have a familiar syntax. * Wide browser support: Objects are widely supported across different browsers. Cons: * Slower lookups: Objects use a tree data structure internally, which provides slower lookups (O(log n) on average). * Less efficient data storage: Objects can be less efficient for large amounts of data due to the overhead of property names and values. **Library Usage** Neither of the test cases uses any external libraries. Both examples rely solely on built-in JavaScript features (`Map` and object literals). **Special JS Features or Syntax** The `||` operator is used in both examples, which is a feature commonly known as the " nullish coalescing operator" (introduced in ECMAScript 2020). It returns the first operand if it's not null or undefined, otherwise, it returns the second operand. **Other Alternatives** If you're interested in exploring other data structures or approaches for this benchmark, consider using: * Arrays: Using arrays to store and retrieve values can provide a balance between performance and simplicity. * Sets: Using sets to store unique values can be efficient for certain use cases but may have overhead due to duplicate value handling. * WeakMaps: Using `WeakMap`s can be more suitable when working with large amounts of data that needs to be garbage collected. **Benchmark Preparation Code** Since the provided benchmark definition and test cases are already well-structured, there's no need for additional code modifications. However, if you want to modify the script preparation code or add custom logic to each test case, it would be a good idea to do so while maintaining consistency throughout your tests. By understanding the differences between these data structures and their performance characteristics, developers can make informed decisions when choosing the best approach for specific use cases in their applications.
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