Benchmark: Test for reduce vs flatmap 2

Script Preparation code:

var metadata = {
  'product:1': 'blah',
  'product:2': 'blah',
  'product:10': 'blah',
};

var hits = [
  {
    id: 1,
    objectID: 1
  },
  {
    id: 2,
    objectID: 2
  },
  {
    id: 3,
    objectID: 3
  },
  {
    id: 3,
    objectID: 3
  },
  {
    id: 4,
    objectID: 4
  },
  {
    id: 5,
    objectID: 5
  },
  {
    id: 6,
    objectID: 6
  },
  {
    id: 7,
    objectID: 7
  },
  {
    id: 8,
    objectID: 8
    },
  {
    id: 9,
    objectID: 9
  },
  {
    id: 10,
    objectID: 10
  }
];

Tests:

flatMap
hits.flatMap((hit)=>{ const image = metadata?.[`product:${hit.id}`]; if (image) { return [ { ...hit, renderType: 'item' }, { ...hit, objectID: `${hit.id}-image`, id: `${hit.id}-image`, image, renderType: 'image' } ]; } return { ...hit, renderType: 'item' }; });
reduce
hits.reduce((list, hit) => { const image = metadata?.[`product:${hit.id}`]; if (image) { return [ ...list, { ...hit, renderType: 'item' }, { ...hit, objectID: `${hit.id}-image`, id: `${hit.id}-image`, image, renderType: 'image' }]; } return [...list, { ...hit, renderType: 'item' }]; }, []);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
flatMap
reduce

Fastest: N/A

Slowest: N/A

Latest run results:

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

LLMs can make mistakes. Check important info.

I'll break down the provided benchmark definition and explain what's being tested, compared, and their pros and cons.

**Benchmark Definition**

The benchmark is testing two approaches: `reduce` and `flatMap`. Both functions are used to transform an array of objects into a new array with additional properties added to each object.

**Functionality Overview**

1. **Reduce**: The `reduce()` method applies a function against an accumulator and each element in the array (from left to right) to reduce it to a single value.
2. **FlatMap**: The `flatMap()` method creates a new array with the results of applying a provided function on every element in the calling array.

**Library and Features**

In this benchmark, no specific JavaScript library is mentioned. However, both functions are part of the ECMAScript standard and are implemented by the browser's JavaScript engine.

No special JavaScript features or syntax are used in these benchmarks.

**Test Cases and Options Compared**

The two test cases:

1. **flatMap**
	* Uses `flatMap()` with a callback function that:
		+ Retrieves an image from metadata based on the hit ID.
		+ Returns an array of transformed objects, including the original object with additional properties (renderType: 'item' and objectID: `${hit.id}-image`).
2. **Reduce**
	* Uses `reduce()` with a callback function that:
		+ Retrieves an image from metadata based on the hit ID.
		+ Returns an array of transformed objects, including the original object with additional properties (renderType: 'item' and objectID: `${hit.id}-image`).

**Pros and Cons**

1. **Reduce**
	* Pros:
		+ Can be more efficient for smaller arrays since it only iterates over each element once.
		+ Might be beneficial when the array is not too large, as it avoids creating a new array with intermediate results.
	* Cons:
		+ Requires manual handling of accumulating values and potentially complex edge cases.
2. **FlatMap**
	* Pros:
		+ Creates a new array with all transformed elements, which can simplify code and make it easier to understand.
		+ Avoids the need for manual accumulation or edge case handling.
	* Cons:
		+ Can be less efficient than `reduce()` for very large arrays due to the creation of an intermediate array.

**Other Alternatives**

Other alternatives to `reduce()` and `flatMap()` include:

1. **Array.prototype.map()**: Creates a new array with transformed elements, but does not accumulate values.
2. **Array.prototype.concat()`: Combines two or more arrays into one, but does not provide any accumulation or transformation capabilities.

Keep in mind that these alternatives may change the behavior and performance characteristics of your code compared to using `reduce()` or `flatMap()`.

Related benchmarks:

Test for reduce vs flatmap 2 (version: 0)

Comparing performance of: flatMap vs reduce

Created: 4 years ago by: Guest

Jump to the latest result

flatMap

reduce

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):