Benchmark: Reduce Object vs Reduce Map

Script Preparation code:

var channelStocks = [
    {
        gateId: "khusus-pi",
        channel: "srcl",
        stock: 1
    },
    {
        gateId: "khusus-pi",
        channel: "tkpd",
        stock: 2
    },
    {
        gateId: "khusus-pi",
        channel: "shpe",
        stock: 3
    },
    {
        gateId: "khusus-pi",
        channel: "lzda",
        stock: 4
    },
    {
        gateId: "khusus-pi-2",
        channel: "srcl",
        stock: 10
    },
    {
        gateId: "khusus-pi-2",
        channel: "tkpd",
        stock: 20
    },
    {
        gateId: "khusus-pi-2",
        channel: "shpe",
        stock: 30
    },
    {
        gateId: "khusus-pi-2",
        channel: "lzda",
        stock: 40
    },
  	{
        gateId: "khusus-pi-3",
        channel: "srcl",
        stock: 100
    },
    {
        gateId: "khusus-pi-3",
        channel: "tkpd",
        stock: 200
    },
    {
        gateId: "khusus-pi-3",
        channel: "shpe",
        stock: 300
    },
    {
        gateId: "khusus-pi-3",
        channel: "lzda",
        stock: 400
    },
];

Tests:

Reduce + Every + Map
var gateStocks = channelStocks.reduce((result, nextChannelStock) => { if ( result.every( gateStock => gateStock.gateId !== nextChannelStock.gateId ) ) { result.push({ gateId: nextChannelStock.gateId, details: [ { stocks: nextChannelStock.stock, channelId: nextChannelStock.channel, }, ], }); return result; } return result.map(gateStock => { if ( gateStock.gateId === nextChannelStock.gateId ) { return { ...gateStock, details: [ ...gateStock.details, { stocks: nextChannelStock.stock, channelId: nextChannelStock.channel, }, ], }; } return gateStock; }); },[]);
Reduce + Object
var gateStocks = channelStocks.reduce((gateStock, channelStock) => { if(gateStock[channelStock.gateId]) { gateStock[channelStock.gateId] = { ...gateStock[channelStock.gateId], details: [ ...gateStock[channelStock.gateId].details, { stock: channelStock.stock, channelId: channelStock.channel, } ] } return gateStock; } gateStock[channelStock.gateId] = { gateId: channelStock.gateId, details: [{ stock: channelStock.stock, channelId: channelStock.channel, }] } return gateStock; }, {}) const result = Object.keys(gateStocks).map(gateId => gateStocks[gateId]);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Reduce + Every + Map
Reduce + Object

Fastest: N/A

Slowest: N/A

Latest run results:

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

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Measuring the performance of JavaScript code is crucial for optimizing applications, and MeasureThat.net provides a valuable platform for benchmarking.

The provided JSON represents two test cases: "Reduce Object" and "Reduce Every + Map". These benchmarks compare different approaches to reduce an array of objects.

**Test Case 1: Reduce Object**

This test case uses the `Array.prototype.reduce()` method with a custom callback function. The callback function checks if every gate stock in the result has a unique gate ID, and if so, pushes a new object with the gate ID and stock details. If not, it updates the existing stock details.

**Test Case 2: Reduce Every + Map**

This test case also uses the `Array.prototype.reduce()` method but with two additional steps:

1. It first reduces the array of channel stocks using the same custom callback function as in Test Case 1.
2. Then, it maps over the resulting object and extracts the key-value pairs.

**Options compared:**

* **Reduce Object**: This approach involves creating a new object and pushing or updating its properties based on the condition.
* **Reduce Every + Map**: This approach first reduces the array to an object and then maps over that object to extract specific key-value pairs.

**Pros and Cons:**

* **Reduce Object**:
	+ Pros:
		- Creates a compact object with only unique gate stocks.
		- Less memory-intensive, especially for large datasets.
	+ Cons:
		- May require more CPU cycles due to the push or update operations.
		- Can lead to slower performance if the resulting object is too large.
* **Reduce Every + Map**:
	+ Pros:
		- Allows for easier filtering and extraction of specific data.
		- Can be faster if the resulting object is smaller.
	+ Cons:
		- Creates a new array with extracted key-value pairs, which can be memory-intensive.
		- May lead to slower performance due to the additional mapping step.

**Other considerations:**

* Both approaches have their trade-offs in terms of performance and memory usage. The choice between them depends on the specific requirements and constraints of the application.
* In general, creating a compact object with unique gate stocks can be beneficial for data processing and filtering.
* Using `Reduce Every + Map` can provide more flexibility when working with large datasets or requiring specific data extraction.

**Alternatives:**

* Other approaches to reduce an array of objects include:
	+ Using the `Array.prototype.every()` method in combination with the spread operator (`...`) to create a new object.
	+ Utilizing libraries like Lodash, which provides optimized functions for working with arrays and objects.
	+ Exploring alternative data structures, such as sets or maps, depending on the specific use case.

In conclusion, the choice between "Reduce Object" and "Reduce Every + Map" depends on the application's requirements and constraints. By understanding the pros and cons of each approach, developers can optimize their code for better performance and memory usage.

Related benchmarks:

Reduce Object vs Reduce Map (version: 0)

Comparing performance of: Reduce + Every + Map vs Reduce + Object

Created: 3 years ago by: Registered User

Jump to the latest result

Reduce + Every + Map

Reduce + Object

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):