Benchmark Overview

The provided JSON represents a benchmark test case for normalizing live update data, specifically comparing two approaches: object-based and array-based normalization.

Script Preparation Code

The script preparation code generates sample data:

• Array.from(Array(100).keys()).map((i) => ({ id: i+1, name: 'Bar', asd: 123123 }));: Creates an array of 100 objects with unique IDs (2-101), a fixed "name" property, and a random "asd" value.
• Array.from(Array(50).keys()).map((i) => ({ id: i+5, title: 'Bar', age: 12 }));: Creates an array of 50 objects with unique IDs (6-55), a fixed "title" property, and a fixed "age" value.

Individual Test Cases

There are two test cases:

Object-Based Approach

const normalizeLiveUpdateData = (
  newData,
  oldaData
) => {
  // ...
};

This approach iterates over the oldAnnotations array, adding new annotations to an object that maps IDs to annotation objects. Then, it iterates over the newAnnotations array and updates the existing annotation objects in the map.

Pros:

• Easy to understand and maintain
• Does not require explicit loop management

Cons:

• May lead to performance issues due to frequent object lookups
• Can result in slower execution times for large datasets

Array-Based Approach

const normalizeLiveUpdateData = (
  newAnnotations,
  oldAnnotations
) => {
  // ...
};

This approach iterates over the newAnnotations array and updates the existing annotation objects in the oldAnnotations array. If a new annotation has an ID that does not exist in oldAnnotations, it is appended to the end of the array.

Pros:

• Can result in faster execution times due to reduced object lookups
• Does not require explicit loop management

Cons:

• Requires additional memory for storing the updated oldAnnotations array
• May lead to slower initialization times due to array resizing

Library and Special Features

None of the provided code snippet indicates any specific JavaScript libraries or special features, such as async/await, Promises, or ES6+ syntax.

Alternatives

Other approaches for normalizing live update data could include:

1. Using a hybrid approach that combines elements of both object-based and array-based methods.
2. Utilizing a data structure like a hash table or a graph to store annotations, which can provide efficient lookup and insertion operations.
3. Implementing an incremental update mechanism that only updates existing annotations, rather than re-normalizing the entire dataset.

Benchmark Results

The latest benchmark result shows:

• The "Object-Based" approach executing approximately 107.5 million times per second.
• The "Array-Based" approach executing approximately 26.7 million times per second on a Safari 14 browser on a Mac OS X 11.0 system.

Please note that these results are specific to the provided benchmark test case and may not reflect real-world performance differences between these approaches.