Benchmark: Map vs. DataStore p2

Tests:

Map
const MyMap = new Map(); for (let i = 0; i < 1000000; i++) { MyMap.set(i, {value: i}); } for (let i = 0; i < 5000000; i++) { const Id = Math.round(Math.random() * 1000000); MyMap.set(Id); }
Baseline DataStore
class DataStore extends Map { constructor () { super(); this.LRR = null; } set (Key, Val) { Val._DataStore = Key; return super.set(Key, Val); } resolve (Key) { if (this.LRR && this.LRR._DataStore === Key) return this.LRR; return super.get(Key); } } const MyDS = new DataStore(); for (let i = 0; i < 1000000; i++) { MyDS.set(i, {value: i}); } for (let i = 0; i < 5000000; i++) { const Id = Math.round(Math.random() * 1000000); MyDS.get(Id); }
DataStore
class DataStore extends Map { constructor () { super(); this.LRR = null; } set (Key, Val) { Val._DataStore = Key; return super.set(Key, Val); } resolve (Key) { if (this.LRR && this.LRR._DataStore === Key) return this.LRR; return super.get(Key); } } const MyDS = new DataStore(); for (let i = 0; i < 1000000; i++) { MyDS.set(i, {value: i}); } for (let i = 0; i < 5000000; i++) { const Id = Math.round(Math.random() * 1000000); MyDS.resolve(Id); }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Map
Baseline DataStore
DataStore

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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Let's dive into the benchmark.

The provided JSON represents two JavaScript microbenchmarks, Map and DataStore p2, which test different approaches to storing and retrieving data in JavaScript.

**Benchmark Purpose**

The primary goal of this benchmark is to compare the performance of using a built-in `Map` object versus a custom implementation, DataStore. The tests aim to determine which approach is faster for common use cases, such as setting and getting values with unique keys.

**Options Compared**

There are three test cases:

1. **Map**: This test case uses the built-in JavaScript `Map` object. It sets 1 million key-value pairs with random IDs and then retrieves 5 million values using a random ID.
2. **Baseline DataStore**: This test case extends the `Map` object to create a custom implementation called DataStore. It also sets 1 million key-value pairs but uses the custom implementation for retrieval, where it resolves (gets) values by checking if the retrieved value's `_DataStore` property matches the original ID.
3. **DataStore**: This test case is similar to Baseline DataStore but without the custom implementation's resolution logic.

**Pros and Cons of Each Approach**

*   **Map**:
    *   Pros: Built-in JavaScript object, easy to implement and maintain, and widely supported across browsers.
    *   Cons: May not be optimized for performance, as it's a built-in object that's subject to browser optimizations and may have limitations on large datasets.
*   **Baseline DataStore**:
    *   Pros: Provides additional control over data storage and retrieval using custom logic. This approach can potentially optimize the implementation for specific use cases or performance requirements.
    *   Cons: Requires more code, which may introduce overhead in terms of execution time or resource usage. Additionally, this implementation may not be as efficient as the built-in Map object due to the added logic.
*   **DataStore**:
    *   Pros: A combination of Baseline DataStore's custom logic with the potential for optimization in the Map object. This approach offers a balance between control and performance.
    *   Cons: It lacks the additional control provided by Baseline DataStore, as it relies on the built-in Map object.

**Library Used**

The DataStore implementation uses the `Map` object from JavaScript's standard library. The custom logic is implemented using ES6 classes and methods (e.g., `set`, `get`, and `resolve`). This indicates that the test case leverages standard JavaScript features to create a custom data store.

**Special JS Features/Syntax**

The DataStore implementation uses ES6 class syntax, which allows for defining custom classes. The use of the `_DataStore` property in the custom logic suggests that it's used as an identifier or flag to track additional metadata.

**Alternatives**

Other alternatives to consider when implementing data storage in JavaScript include:

*   Using a library like LRU Cache, Redis, or Memcached, which provide optimized data storage and retrieval mechanisms.
*   Implementing a custom data store using Web Workers or worker threads for parallel processing and potential performance gains.
*   Leveraging browser-specific features, such as WebStorage or IndexedDB, to create a custom data store.

Keep in mind that the choice of implementation depends on specific use cases, requirements, and performance considerations.

Related benchmarks:

Map vs. DataStore p2 (version: 0)

Comparing performance of: Map vs Baseline DataStore vs DataStore

Created: 5 years ago by: Guest

Jump to the latest result

Map

Baseline DataStore

DataStore

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):