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Date.now() loop
(version: 1)
Comparing performance of:
Outside loop vs Inside loop
Created:
one year ago
by:
Guest
Jump to the latest result
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Tests:
Outside loop
const now = Date.now(); const res = []; for(i=0; i<10000; i++){ res.push(now); }
Inside loop
const res = []; for(i=0; i<10000; i++){ res.push(Date.now()); }
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (2)
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Test case name
Result
Outside loop
Inside loop
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/136.0.0.0 Safari/537.36
Browser/OS:
Chrome 136 on Windows
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Test name
Executions per second
Outside loop
3575.1 Ops/sec
Inside loop
1539.8 Ops/sec
Autogenerated LLM Summary
(model
gpt-4o-mini
, generated one year ago):
The benchmark "Date.now() loop" tests the performance of two different approaches to collecting timestamps using JavaScript's `Date.now()` method. The aim is to observe the impact on performance when `Date.now()` is invoked once versus multiple times within a loop. ### Options Compared 1. **Outside Loop (Test Name: "Outside loop")** - **Benchmark Definition**: ```javascript const now = Date.now(); const res = []; for(i=0; i<10000; i++){ res.push(now); } ``` - **Description**: Here, `Date.now()` is called once prior to entering the loop, thus capturing the current timestamp. The result is then pushed to an array inside the loop 10,000 times. 2. **Inside Loop (Test Name: "Inside loop")** - **Benchmark Definition**: ```javascript const res = []; for(i=0; i<10000; i++){ res.push(Date.now()); } ``` - **Description**: In this case, `Date.now()` is called on each iteration of the loop, generating a new timestamp for every entry in the resulting array. ### Performance Results Summary Based on the benchmark results: - **Outside loop** yielded approximately **3575.09 executions per second**. - **Inside loop** yielded approximately **1539.84 executions per second**. ### Pros and Cons of Different Approaches #### Outside Loop - **Pros**: - Significantly better performance as it eliminates the overhead of repeatedly calling `Date.now()`. - Efficient for scenarios where a constant timestamp is needed repeatedly (like logging an event that occurs within a short duration). - **Cons**: - If the intention is to collect multiple separate timestamps, this approach won’t suffice, as it only captures one timestamp. #### Inside Loop - **Pros**: - Useful when you need unique timestamps for every iteration (e.g., measuring time differences or logging events at various intervals). - **Cons**: - Substantially slower due to the overhead of repeated function calls within loop iterations—especially when the loop executes many times. - Increased computational cost can lead to performance bottlenecks in code that relies on rapid execution of loops. ### Considerations Choosing between these two approaches often hinges on the specific use case. If you're interested in a single timestamp (like logging), the outside loop method is more optimal. When you need dynamic timestamps (for example, for measuring time-sensitive events across iterations), the inside loop is necessary despite its performance drawbacks. ### Alternatives 1. **Using `performance.now()`**: If higher precision timing is required, `performance.now()` can be used instead of `Date.now()`, which provides timestamp values in milliseconds with sub-millisecond precision. However, similar considerations regarding its invocation frequency will affect performance. 2. **Caching Mechanisms**: In situations where multiple calls to retrieve timestamps with minimal latency are needed, consider implementing a caching strategy to reduce the number of direct calls to these timing functions. 3. **Batch Processing**: If timestamps are used for logging or metrics collection, consider batching the operations where multiple timestamps are needed together to minimize repeated calls. In conclusion, the test highlights the trade-offs of performance and requirement specificity when working with time-tracking APIs in JavaScript. It serves as an essential guideline for developers when optimizing code involving frequent function calls within loops.
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