Benchmark: access test - MeasureThat.net

Script Preparation code:

var data = [
  { key:1, value: 1000},
  { key:2, value: 2000},
  { key:3, value: 3000},
  { key:4, value: 4000},
  { key:5, value: 5000},
  { key:6, value: 6000},
  { key:7, value: 7000},
  { key:8, value: 8000},
  { key:9, value: 9000},
  { key:10, value: 10000}
];

var obj = {
  1: 1000,
  2: 2000,
  3: 3000,
  4: 4000,
  5: 5000,
  6: 6000,
  7: 7000,
  8: 8000,
  9: 9000,
  10: 10000
};

function getRandomInt(min, max) {
  return Math.floor(Math.random() * (max - min + 1)) + min;
}

Tests:

Map
for (var i =0; i < 10000; i++) { var num = getRandomInt(1, 10); data.map(item => item.key === num); }
Object access
for (var i =0; i < 10000; i++) { var num = getRandomInt(1, 10); obj[num]; }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Map
Object access

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

This benchmark does not have any results yet. Be the first one to run it!

Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):

LLMs can make mistakes. Check important info.

I'll break down the provided JSON and explain what's being tested, the options compared, pros and cons of each approach, library usage, and special JavaScript features.

**Benchmark Definition**

The test case uses two different approaches to access data:

1. **`Map()`**: This approach iterates over an array using `map()`, filtering values where `item.key === num`. The test creates a random number between 1 and 10 for each iteration (0-9) of the outer loop.
2. **Object Access (`obj[num]`)**: This approach directly accesses an object property by its numerical key, similar to the `Map()` method.

**Options Compared**

The main difference between these two approaches is:

*   **Array vs. Object**: The first option uses an array (`data`) and the second option uses a simple object (`obj`).
*   **Iteration Style**: Both methods iterate over a set of numbers, but one is more explicit about its intent.

**Pros and Cons**

1.  **`Map()`**
    *   Pros:
        *   More concise and efficient for filtering operations.
        *   Built-in JavaScript method reduces code duplication.
        *   Easy to read and maintain due to its declarative nature.
    *   Cons:
        *   Requires an array as input, which might be less readable in some cases.
    *   **Object Access (`obj[num]`)`
    *   Pros:
        *   Can be more straightforward when working with numerical keys.
        *   No need for an array or any additional data structure.
    *   Cons:
        *   Less efficient than `Map()` due to object property lookup overhead.
        *   Less flexible, as it's limited to numerical key access.

**Library Usage**

There is no explicit library usage in the provided code. However, the `map()` function is a built-in JavaScript method and does not require any external libraries.

**Special JavaScript Features**

The test case uses a special JavaScript feature: **Template Literals (Backticks)**. The use of backticks (`\r\n`) in string literals allows for easier multiline string representation.

Now let's talk about the execution results provided by MeasureThat.net:

**Latest Benchmark Results**

The two benchmark tests produce different performance results:

*   `Object access` yields approximately 149 executions per second (on Chrome 69 and Windows).
*   `Map()` yields approximately 178 executions per second (on Chrome 69 and Windows).

This suggests that the built-in array method (`map()`) is slightly faster than direct object property access for this particular use case. However, please note that these results may vary depending on your specific environment, system resources, and JavaScript engine.

**Other Alternatives**

For benchmarking similar use cases, you might consider alternative approaches:

*   **Using `forEach()` instead of `map()`**: The `forEach()` method can provide a more straightforward way to iterate over an array.
*   **Using `reduce()` for filtering operations**: If you need to accumulate results or process data in a different way, using `reduce()` might be more suitable than `map()`.
*   **Using caching mechanisms (e.g., memoization)**: If the filtering operation is computationally expensive, consider implementing caching to avoid redundant computations.

Keep in mind that these alternatives are not necessarily faster or slower than the provided approaches. The best choice depends on your specific requirements and performance characteristics.

Related benchmarks:

access test (version: 0)

sf

Comparing performance of: Map vs Object access

Created: 7 years ago by: Guest

Jump to the latest result

Map

Object access

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

No previous run results

Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):