Benchmark: Lodash.isEqual vs object-hash duplicate data detection for array of objects with nested properties and lots of records 13

HTML Preparation code:

<script src="https://cdn.jsdelivr.net/npm/object-hash@2.0.3/dist/object_hash.min.js"></script>
<script src="https://cdn.jsdelivr.net/npm/lodash@4.17.4/lodash.min.js"></script>

AخA
 
<script src="https://cdn.jsdelivr.net/npm/object-hash@2.0.3/dist/object_hash.min.js"></script>
<script src="https://cdn.jsdelivr.net/npm/lodash@4.17.4/lodash.min.js"></script>

Script Preparation code:

window.NUM_ITEMS = 1000;
window.NUM_TAKE = 20;
window.input = [];
window.data = [];
window.check = [];
window.indices = [...Array(window.NUM_ITEMS).keys()];

// Populate data: entries with a nested array of 50 random entries
for (const i of window.indices) {
  window.data[i] = {
    ids: window.indices.slice(0, 50).map((x) => Math.floor(Math.random() * window.NUM_ITEMS * 10)),
    counter: i,
    counter2: Math.floor(Math.random() * i),
  };
  window.check[i] = false;
}

// calculate hashes for each data object
window.hashes = new Set(window.data.map((obj) => objectHash(obj)));
window.strings = new Set(window.data.map(JSON.stringify));

window.TAKE_IDX = window.indices.reverse().slice(0, window.NUM_TAKE);
// Uncomment to choose random indices
//window.TAKE_IDX = window.TAKE_IDX.map((x) => Math.floor(Math.random() * window.NUM_ITEMS));

// Populate input: copies of the data
for (const i of window.TAKE_IDX) {
  window.input[i] = { ids: [...window.data[i].ids], counter: window.data[i].counter, counter2: window.data[i].counter2 };
}

​x
 
window.NUM_ITEMS = 1000;window.NUM_TAKE = 20;window.input = [];window.data = [];window.check = [];window.indices = [...Array(window.NUM_ITEMS).keys()];​// Populate data: entries with a nested array of 50 random entriesfor (const i of window.indices) {  window.data[i] = {    ids: window.indices.slice(0, 50).map((x) => Math.floor(Math.random() * window.NUM_ITEMS * 10)),    counter: i,    counter2: Math.floor(Math.random() * i),  };  window.check[i] = false;}​// calculate hashes for each data objectwindow.hashes = new Set(window.data.map((obj) => objectHash(obj)));window.strings = new Set(window.data.map(JSON.stringify));​window.TAKE_IDX = window.indices.reverse().slice(0, window.NUM_TAKE);// Uncomment to choose random indices//window.TAKE_IDX = window.TAKE_IDX.map((x) => Math.floor(Math.random() * window.NUM_ITEMS));​// Populate input: copies of the datafor (const i of window.TAKE_IDX) {  window.input[i] = { ids: [...window.data[i].ids], counter: window.data[i].counter, counter2: window.data[i].counter2 };}

Tests:

_.isEqual

for (const i of window.TAKE_IDX) {
  window.check[i] = window.data.some((item) => _.isEqual(item, window.input[i]));
}

 
for (const i of window.TAKE_IDX) {  window.check[i] = window.data.some((item) => _.isEqual(item, window.input[i]));}

JSON.stringify
for (const i of window.TAKE_IDX) { window.check[i] = window.strings.has(JSON.stringify(window.input[i])); }
for (const i of window.TAKE_IDX) {
window.check[i] = window.strings.has(JSON.stringify(window.input[i]));
}
objectHash
for (const i of window.TAKE_IDX) { window.check[i] = window.hashes.has(objectHash(window.input[i])); }
for (const i of window.TAKE_IDX) {
window.check[i] = window.hashes.has(objectHash(window.input[i]));
}

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Experimental features:

Memory measurements supported only in Chrome.
For precise memory measurements Chrome must be launched with --enable-precise-memory-info flag.
More information: Monitoring JavaScript Memory

Test case name	Result
_.isEqual
JSON.stringify
objectHash

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: one year ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/119.0.0.0 Safari/537.36

Browser/OS: Chrome 119 on Windows

View result in a separate tab

Test name	Executions per second
_.isEqual	47.6 Ops/sec
JSON.stringify	24354.5 Ops/sec
objectHash	257.5 Ops/sec

Autogenerated LLM Summary (model llama3.2:3b, generated 7 months ago):

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

Benchmark Overview

The benchmark compares three approaches to detect duplicate data in an array of objects with nested properties:

_.isEqual (Lodash)
JSON.stringify
objectHash

The test case uses a large dataset (window.NUM_ITEMS = 1000) and generates random data with nested arrays.

Approaches Comparison

Here's a brief overview of each approach:

_.isEqual (Lodash)

Purpose: Compare two objects for equality using a deep comparison algorithm.
Pros:
- Fast execution speed.
- Easy to implement.
Cons:
- Can be slow for very large datasets due to its recursive nature.
- May not work correctly with certain data structures (e.g., circular references).

JSON.stringify

Purpose: Compare two objects by converting them to a string and checking if the resulting strings are equal.
Pros:
- Fast execution speed, especially for smaller datasets.
- Works well with most data types.
Cons:
- May not work correctly with nested arrays or circular references.
- Can be slower than _.isEqual for very large datasets.

objectHash

Purpose: Generate a unique hash value for each object based on its properties and values.
Pros:
- Fast execution speed, especially for larger datasets.
- Works well with nested arrays and most data types.
Cons:
- Requires an external library (object-hash).
- May produce collisions if not designed correctly.

Other Considerations

Data Structure: The benchmark uses a large array of objects with nested arrays, which can make it challenging to detect duplicates using some approaches.
Platform and Browser: The benchmark results are reported for Chrome 119 on Windows Desktop, but the performance may vary across different browsers and platforms.

Alternatives

If you're interested in exploring alternative approaches, here are a few options:

Array.prototype.indexOf(): This method checks if an element exists in an array using its index value. You can use this approach to detect duplicates by iterating through the array and checking for existing indices.
Set data structure: Using a Set data structure can help efficiently detect duplicate elements, especially when working with arrays of unique values.
Other hash-based approaches: There are other libraries and algorithms available that generate hashes for objects, such as crypto module in Node.js or hash-object library.

Keep in mind that the best approach depends on your specific use case and requirements.

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/cons.

**Benchmark Overview**

The benchmark compares three approaches to detect duplicate data in an array of objects with nested properties:

1. `_.isEqual` (Lodash)
2. `JSON.stringify`
3. `objectHash`

The test case uses a large dataset (`window.NUM_ITEMS = 1000`) and generates random data with nested arrays.

**Approaches Comparison**

Here's a brief overview of each approach:

### _.isEqual (Lodash)

* **Purpose**: Compare two objects for equality using a deep comparison algorithm.
* **Pros**:
	+ Fast execution speed.
	+ Easy to implement.
* **Cons**:
	+ Can be slow for very large datasets due to its recursive nature.
	+ May not work correctly with certain data structures (e.g., circular references).

### JSON.stringify

* **Purpose**: Compare two objects by converting them to a string and checking if the resulting strings are equal.
* **Pros**:
	+ Fast execution speed, especially for smaller datasets.
	+ Works well with most data types.
* **Cons**:
	+ May not work correctly with nested arrays or circular references.
	+ Can be slower than _.isEqual for very large datasets.

### objectHash

* **Purpose**: Generate a unique hash value for each object based on its properties and values.
* **Pros**:
	+ Fast execution speed, especially for larger datasets.
	+ Works well with nested arrays and most data types.
* **Cons**:
	+ Requires an external library (object-hash).
	+ May produce collisions if not designed correctly.

**Other Considerations**

* **Data Structure**: The benchmark uses a large array of objects with nested arrays, which can make it challenging to detect duplicates using some approaches.
* **Platform and Browser**: The benchmark results are reported for Chrome 119 on Windows Desktop, but the performance may vary across different browsers and platforms.

**Alternatives**

If you're interested in exploring alternative approaches, here are a few options:

1. **Array.prototype.indexOf()**: This method checks if an element exists in an array using its index value. You can use this approach to detect duplicates by iterating through the array and checking for existing indices.
2. **Set data structure**: Using a Set data structure can help efficiently detect duplicate elements, especially when working with arrays of unique values.
3. **Other hash-based approaches**: There are other libraries and algorithms available that generate hashes for objects, such as `crypto` module in Node.js or `hash-object` library.

Keep in mind that the best approach depends on your specific use case and requirements.

Related benchmarks:

Lodash.isEqual vs object-hash duplicate data detection for array of objects with nested properties and lots of records 13 (version: 0)

Comparing performance of: _.isEqual vs JSON.stringify vs objectHash

Created: 2 years ago by: Guest

Jump to the latest result

_.isEqual

JSON.stringify

objectHash

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 7 months ago):

_.isEqual (Lodash)

JSON.stringify

objectHash