Benchmark: for of filtered reduce spread

Tests:

double for of
const dataList = [ [ ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 10], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 11], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 10], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 20], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 31], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 41] ], [ ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 10], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 11], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 10], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 20], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 31], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 41] ], [ ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 10], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 11], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 10], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 20], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 31], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 41] ], [ ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 10], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 11], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 10], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 20], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 31], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 41] ], [ ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 10], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 11], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 10], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 20], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 31], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 41] ] ] let filtered = []; for (data of dataList){ for (row of data){ if (row[10] ==10){ filtered.push(row); } } }
reduce() filtered()
const dataList = [ [ ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 10], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 11], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 10], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 20], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 31], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 41] ], [ ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 10], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 11], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 10], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 20], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 31], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 41] ], [ ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 10], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 11], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 10], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 20], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 31], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 41] ], [ ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 10], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 11], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 10], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 20], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 31], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 41] ], [ ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 10], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 11], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 10], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 20], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 31], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 41] ] ] const filtered = dataList.reduce((acc, data) => { const filtereded = data.filter((row) => row[10] == 10); acc.push(...filtereded); return acc; }, []);
reduce() filtered+spread
const dataList = [ [ ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 10], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 11], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 10], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 20], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 31], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 41] ], [ ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 10], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 11], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 10], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 20], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 31], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 41] ], [ ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 10], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 11], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 10], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 20], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 31], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 41] ], [ ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 10], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 11], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 10], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 20], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 31], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 41] ], [ ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 10], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 11], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 10], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 20], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 31], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 41] ] ] const filtered = dataList.reduce((acc, data) => { acc.push(...data.filter((row) => row[10] === 10)); return acc; }, []);
no push
const dataList = [ [ ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 10], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 11], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 10], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 20], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 31], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 41] ], [ ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 10], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 11], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 10], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 20], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 31], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 41] ], [ ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 10], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 11], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 10], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 20], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 31], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 41] ], [ ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 10], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 11], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 10], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 20], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 31], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 41] ], [ ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 10], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 11], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 10], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 20], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 31], ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'v', 'w', 'xyz', 41] ] ] const filtered = dataList.reduce((acc, data) => { return [...acc, ...data.filter((row) => row[10] == 10)]; }, []);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
double for of
reduce() filtered()
reduce() filtered+spread
no push

Fastest: N/A

Slowest: N/A

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

LLMs can make mistakes. Check important info.

The code is using the `reduce()` method to filter an array of arrays, where each inner array has a value and a key at index 10.

To answer your question, I would recommend adding a test case for "no push" as you mentioned in the benchmark result. Here's why:

In the benchmark result, it seems that the "no push" variant is skipping the `filter()` method and directly using the `reduce()` method with an empty array as the initial value. This might be a performance optimization technique to avoid creating unnecessary intermediate arrays.

To verify this, you can add a test case for "no push" and compare its execution time with the other variants:
```javascript
const dataList = [...]; // your data list here

const noPushData = dataList.reduce((acc, row) => {
  return [...acc, row[10] == 10 ? row : []];
}, []);

// add a test case for "no push"
const tests = [
  { name: 'reduce()', data: dataList, filter: (row) => row[10] == 10 },
  { name: 'no push', data: noPushData, filter: () => true }, // using a truthy function to always match
];

// run the tests and compare execution times
tests.forEach((test) => {
  console.time(test.name);
  test.data.reduce(test.filter, []);
  console.timeEnd(test.name);
});
```
By adding this test case, you can verify if the "no push" variant is indeed faster than the other variants.

As for the actual performance comparison, it's worth noting that the `reduce()` method has a higher overhead compared to using a simple `filter()` method. The `filter()` method creates an intermediate array with the filtered elements, which can be more efficient than creating multiple intermediate arrays in the `reduce()` method.

However, without running the actual benchmark code, it's difficult to determine which variant is faster in this specific case.

Latest run results:

Run details: (Test run date: 11 months 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
double for of	99788.9 Ops/sec
reduce() filtered()	2703245.8 Ops/sec
reduce() filtered+spread	2457453.0 Ops/sec
no push	1910092.4 Ops/sec

Related benchmarks:

for of filtered reduce spread (version: 0)

Comparing performance of: double for of vs reduce() filtered() vs reduce() filtered+spread vs no push

Created: 11 months ago by: Guest

Jump to the latest result

double for of

reduce() filtered()

reduce() filtered+spread

no push

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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