Benchmark: flatMap count vs reduce count

Script Preparation code:

var arr = [
  {
    loanId: 1077579,
    missingDocs: [
      { docTypeID: 4, docType: "CEMA" },
      { docTypeID: 14, docType: "Policy" },
    ],
  },
  {
    loanId: 1077579,
    missingDocs: [
      { docTypeID: 4, docType: "CEMA" },
      { docTypeID: 14, docType: "Policy" },
    ],
  },
  {
    loanId: 1077579,
    missingDocs: [
      { docTypeID: 4, docType: "CEMA" },
      { docTypeID: 14, docType: "Policy" },
    ],
  },
  {
    loanId: 1077579,
    missingDocs: [
      { docTypeID: 4, docType: "CEMA" },
      { docTypeID: 14, docType: "Policy" },
    ],
  },
  {
    loanId: 1077579,
    missingDocs: [
      { docTypeID: 4, docType: "CEMA" },
      { docTypeID: 14, docType: "Policy" },
    ],
  },
  {
    loanId: 1077579,
    missingDocs: [
      { docTypeID: 4, docType: "CEMA" },
      { docTypeID: 14, docType: "Policy" },
    ],
  },
  {
    loanId: 1077579,
    missingDocs: [
      { docTypeID: 4, docType: "CEMA" },
      { docTypeID: 14, docType: "Policy" },
    ],
  },
  {
    loanId: 1077579,
    missingDocs: [
      { docTypeID: 4, docType: "CEMA" },
      { docTypeID: 14, docType: "Policy" },
    ],
  },
  {
    loanId: 1077579,
    missingDocs: [
      { docTypeID: 4, docType: "CEMA" },
      { docTypeID: 14, docType: "Policy" },
    ],
  },
  {
    loanId: 1077579,
    missingDocs: [
      { docTypeID: 4, docType: "CEMA" },
      { docTypeID: 14, docType: "Policy" },
    ],
  },
  {
    loanId: 1077579,
    missingDocs: [
      { docTypeID: 4, docType: "CEMA" },
      { docTypeID: 14, docType: "Policy" },
    ],
  },
  {
    loanId: 1077579,
    missingDocs: [
      { docTypeID: 4, docType: "CEMA" },
      { docTypeID: 14, docType: "Policy" },
    ],
  },
];

Tests:

reduce with concat
arr.reduce((acc, loan) => acc + loan.missingDocs.length, 0)
flatMap
arr.flatMap(loan => loan.missingDocs).length

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
reduce with concat
flatMap

Fastest: N/A

Slowest: N/A

Latest run results:

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

LLMs can make mistakes. Check important info.

**Benchmark Explanation**

The provided JSON represents two benchmark tests: "flatMap count vs reduce count". The benchmarks are designed to compare the performance of two different approaches for processing an array of objects.

**Options being compared**

1. **flatMap**: This approach uses the `flatMap()` method, which returns a new array with all sub-array elements concatenated into it recursively up to the specified depth.
2. **reduce**: This approach uses the `reduce()` method, which applies a function against an accumulator and each element in the array (from left-to-right) to reduce it to a single value.

**Pros and Cons of each approach**

* **flatMap**:
	+ Pros: More readable and easier to understand, especially for complex data structures.
	+ Cons: May be less efficient than `reduce` due to the recursive nature of concatenation.
* **reduce**:
	+ Pros: Can be more efficient than `flatMap`, as it avoids unnecessary recursive calls.
	+ Cons: Requires a deeper understanding of the accumulator and callback function.

**Library usage**

In both test cases, no external library is required. The `flatMap()` method is a built-in array method in JavaScript, while the `reduce()` method is also built-in.

**Special JS feature or syntax**

There are no special features or syntax used in these benchmarks. They only utilize standard JavaScript methods and data structures.

**Other alternatives**

If you wanted to compare other approaches for processing arrays, some possible alternatives could include:

* Using a custom loop (e.g., `for` or `while`) instead of `flatMap()` or `reduce()`.
* Utilizing third-party libraries like Lodash or Ramda.
* Implementing a recursive function using recursion instead of `reduce()`.

However, for this specific benchmark, the built-in `flatMap()` and `reduce()` methods are likely to be the most efficient and convenient options.

Related benchmarks:

flatMap count vs reduce count (version: 0)

Comparing performance of: reduce with concat vs flatMap

Created: 4 years ago by: Guest

Jump to the latest result

reduce with concat

flatMap

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):