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Switch vs map first value
(version: 1)
Comparing performance of:
Switch vs Map
Created:
one year ago
by:
Guest
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Tests:
Switch
const input = 1; switch(input) { case 1: return true; case 2: return true; case 3: return true; case 4: return true; case 5: return true; case 6: return true; case 7: return true; case 8: return true; case 9: return true; case 10: return true; }
Map
const input = 1; const LUT = { 0: true, 1: true, 2: true, 3: true, 4: true, 5: true, 6: true, 7: true, 8: true, 9: true, 10: true } LUT[input];
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (2)
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Test case name
Result
Switch
Map
Fastest:
N/A
Slowest:
N/A
Latest run results:
Run details:
(Test run date:
one year ago
)
User agent:
Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/134.0.0.0 Safari/537.36
Browser/OS:
Chrome 134 on Windows
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<iframe src="https://measurethat.net/Embed?id=602351" width="100%" height="500px"></iframe>
Map
135.1M/s
Switch
127.6M/s
View exact numbers
Test name
Executions per second
✓
Map
135,103,376 Ops/sec
Switch
127,591,672 Ops/sec
Autogenerated LLM Summary
(model
gpt-4o-mini
, generated one year ago):
The benchmark conducted on the MeasureThat.net platform compares two different approaches for determining the value of an input based on predefined conditions: using a `switch` statement and using a lookup table (often referred to as a "map"). Here's a breakdown of what is being tested, the pros and cons of each approach, and alternative options: ### Approaches Tested: 1. **Switch Statement:** - The first approach uses a `switch` statement with multiple cases. Here, if `input` equals a certain number (1 through 10), the function returns `true`. The switch case will evaluate each case until it finds a match or reaches the end. **Pros:** - Clear and structured representation of conditions, making it easy to read and understand. - Familiar syntax that many developers are accustomed to. - Suitable for branching logic beyond straightforward lookups, allowing for complex operations associated with each case. **Cons:** - Performance may degrade with larger numbers of cases due to linear searches through conditions. - Maintenance complexity can increase if many case branches are added or if the logic becomes changeable often. 2. **Lookup Table (Map):** - The second approach uses an object as a lookup table where the keys represent the numbers, and the values (all `true` in this case) are accessed directly using the input as a key. **Pros:** - Fast lookups; since the time complexity of accessing a property on an object is generally O(1), the performance remains constant regardless of the number of entries. - Easier to maintain and extend (such as changing values or adding new keys) by adjusting a simple object structure rather than multiple cases. **Cons:** - This approach sacrifices some readability, especially when the mapping becomes more complex without additional context or comments. - The overhead of creating and storing an object, which may not be justified for very small datasets. ### Comparison Outcome: From the benchmark results: - The `switch` approach executed **164,259,088** times per second. - The `map` approach executed **155,001,488** times per second. In this specific case, the `switch` statement performed slightly better than the lookup table in terms of raw execution speed. This finding could vary with different inputs or larger cases. ### Other Considerations: - **Contextual Usage:** Depending on the typical scenarios you expect in your application (i.e., whether you have lots of branching logic, or you're frequently checking the same set of discrete keys), the better choice may vary. - **Code Maintainability:** If performance differences are negligible in practical applications, favoring clean, maintainable code should be a priority. - **Pattern Matching:** For scenarios involving many potential branches or states, state machines or other strategies might provide clearer solutions. ### Alternatives: - **Array Lookup:** Using an array where indexes correspond to values can yield good performance in some scenarios where values are limited but sequential. - **Function-Based Dispatch:** For more complicated logic where each case requires a unique function to be executed, a dispatcher function might be viable. - **Libraries:** One could consider libraries like `lodash` for utility functions, which can simplify certain mapping scenarios but may introduce additional overhead. In summary, while both methods achieve the same end result, the decision on which to use should account for performance, clarity, maintainability, and contextual needs.
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