Benchmark: test sort uniq - MeasureThat.net

HTML Preparation code:

<script src="https://cdnjs.cloudflare.com/ajax/libs/ramda/0.27.0/ramda.min.js"></script>

Script Preparation code:

var data = []

function getRandomDate() {
  const startMillis = new Date('2020-06-02T00:00:00.000Z').getTime();
  const endMillis = new Date().getTime();
  const randomMillis = startMillis + Math.random() * (endMillis - startMillis);
  const randomDate = new Date(randomMillis);

  return randomDate;
}

for (var i = 0; i < 14000; i++) {
     data.push({ customerId: `CTM-${i % 10}`, worklistId: `WL-${i % 100}`, createdDateTime: getRandomDate() });
}

Tests:

slow
var result = R.uniqBy( R.props(['worklistId', 'customerId']), [...data].sort( (a, b) => new Date(a.createdDateTime).getTime() - new Date(b.createdDateTime).getTime(), ), )
new
var result = R.uniqWith( (a, b) => a.customerId === b.customerId && a.worklistId === b.worklistId, [...data].sort( (a, b) => new Date(a.createdDateTime).getTime() - new Date(b.createdDateTime).getTime(), ), )
new2
var result = R.uniqWith( (a, b) => a.customerId === b.customerId && a.worklistId === b.worklistId, data.sort( (a, b) => a.createdDateTime - b.createdDateTime, ), )

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
slow
new
new2

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 2 years ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36

Browser/OS: Chrome 120 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
slow	3.1 Ops/sec
new	28.9 Ops/sec
new2	116.1 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's dive into explaining the provided benchmark and its various options.

**Overview of the Benchmark**

The provided JSON represents a JavaScript microbenchmark that measures the performance of three different approaches for removing duplicates from an array while preserving uniqueness. The input data is generated using a custom `getRandomDate` function, which creates 14,000 objects with unique customer IDs and worklist IDs.

**Script Preparation Code**

The script preparation code defines the input data as an empty array `data`. It also defines a utility function `getRandomDate` that generates random dates within a specific time range. This function is used to populate the input data with random created dates.

**Html Preparation Code**

The HTML preparation code includes a link to include the Ramda library, which provides functional programming utilities.

**Benchmark Options**

There are three benchmark options:

### 1. `R.uniqBy` (Slow)

```javascript
var result = R.uniqBy(
  R.props(['worklistId', 'customerId']),
  [...data].sort((a, b) => new Date(a.createdDateTime).getTime() - new Date(b.createdDateTime).getTime()),
)
```

This option uses the `R.uniqBy` function from Ramda to remove duplicates based on a specific set of properties (`worklistId` and `customerId`). The input data is sorted in ascending order using a compare function that extracts the created date from each object.

**Pros:**

* Preserves uniqueness by comparing objects based on a specific set of properties.
* Provides a clear and concise way to remove duplicates.

**Cons:**

* Requires sorting the input data, which can be computationally expensive for large datasets.

### 2. `R.uniqWith` (New)

```javascript
var result = R.uniqWith(
  (a, b) => a.customerId === b.customerId && a.worklistId === b.worklistId,
  [...data].sort((a, b) => new Date(a.createdDateTime).getTime() - new Date(b.createdDateTime).getTime()),
)
```

This option uses the `R.uniqWith` function from Ramda to remove duplicates based on a custom comparison function. The input data is sorted in ascending order using the same compare function as before.

**Pros:**

* Preserves uniqueness by comparing objects based on a custom set of properties.
* Provides more flexibility than `R.uniqBy`.

**Cons:**

* Requires defining a custom comparison function, which can be error-prone and less readable than using a specific set of properties.

### 3. In-place sorting (New2)

```javascript
var result = R.uniqWith(
  (a, b) => a.customerId === b.customerId && a.worklistId === b.worklistId,
  data.sort((a, b) => a.createdDateTime - b.createdDateTime),
)
```

This option uses the `R.uniqWith` function from Ramda to remove duplicates while preserving the original order of objects in the input array. The input array is sorted in-place using a compare function that extracts the created date from each object.

**Pros:**

* Preserves uniqueness and the original order of objects.
* Reduces memory usage by sorting in-place.

**Cons:**

* Requires modifying the original input array, which can be undesirable for some use cases.

**Other Considerations**

The benchmark only considers the performance of removing duplicates while preserving uniqueness. Other factors, such as memory allocation or caching effects, may also impact performance.

In conclusion, each option has its pros and cons. The choice between them depends on the specific requirements and constraints of the application.

Related benchmarks:

test sort uniq (version: 0)

Comparing performance of: slow vs new vs new2

Created: 2 years ago by: Guest

Jump to the latest result

slow

new

new2

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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