Benchmark: transrorm template

HTML Preparation code:

<!--your preparation HTML code goes here-->

AخA
 
<!--your preparation HTML code goes here-->

Tests:

transform1

var transform1 = (rowTemplate) => {
    if (!rowTemplate?.length) {
        return [[]];
    }

    const rows = rowTemplate.length;
    const cols = rowTemplate[0].length;

    const tiles = new Map();

    for (let row = 0; row < rows; row++) {
        for (let col = 0; col < cols; col++) {
            const id = rowTemplate[row][col];

            if (!tiles.has(id)) {
                tiles.set(id, { positions: [] });
            }

            tiles.get(id)?.positions.push({ row, col });
        }
    }

    const tilesByColumn = Array.from(tiles.keys()).sort((idA, idB) => {
        const posA = tiles.get(idA)?.positions[0];
        const posB = tiles.get(idB)?.positions[0];

        return posA.col === posB.col
            ? posA.row - posB.row
            : posA.col - posB.col;
    });

    const tilesByRow = Array.from(tiles.keys()).sort((idA, idB) => {
        const posA = tiles.get(idA)?.positions[0];
        const posB = tiles.get(idB)?.positions[0];

        return posA.row === posB.row
            ? posA.col - posB.col
            : posA.row - posB.row;
    });

    const tileMap = {};

    tilesByRow.forEach((rowId, index) => {
        tileMap[rowId] = tilesByColumn[index];
    });

    const result = Array(rows).fill(null)
        .map(() => Array(cols).fill(null));

    for (let row = 0; row < rows; row++) {
        for (let col = 0; col < cols; col++) {
            const originalId = rowTemplate[row][col];
            result[row][col] = tileMap[originalId];
        }
    }

    return result;
};

var t1 = [
    ["1", "1", "2", "3", "4", "4"],
    ["1", "1", "5", "6", "4", "4"]
];

for (var i=0; i < 10000; i++) {
	transform1(t1);
}

​x
 
var transform1 = (rowTemplate) => {    if (!rowTemplate?.length) {        return [[]];    }​    const rows = rowTemplate.length;    const cols = rowTemplate[0].length;​    const tiles = new Map();​    for (let row = 0; row < rows; row++) {        for (let col = 0; col < cols; col++) {            const id = rowTemplate[row][col];​            if (!tiles.has(id)) {                tiles.set(id, { positions: [] });            }​            tiles.get(id)?.positions.push({ row, col });        }    }​    const tilesByColumn = Array.from(tiles.keys()).sort((idA, idB) => {        const posA = tiles.get(idA)?.positions[0];        const posB = tiles.get(idB)?.positions[0];​        return posA.col === posB.col            ? posA.row - posB.row            : posA.col - posB.col;    });​    const tilesByRow = Array.from(tiles.keys()).sort((idA, idB) => {        const posA = tiles.get(idA)?.positions[0];        const posB = tiles.get(idB)?.positions[0];​        return posA.row === posB.row            ? posA.col - posB.col            : posA.row - posB.row;    });​    const tileMap = {};​    tilesByRow.forEach((rowId, index) => {        tileMap[rowId] = tilesByColumn[index];    });​    const result = Array(rows).fill(null)        .map(() => Array(cols).fill(null));​    for (let row = 0; row < rows; row++) {        for (let col = 0; col < cols; col++) {            const originalId = rowTemplate[row][col];            result[row][col] = tileMap[originalId];        }    }​    return result;};​var t1 = [    ["1", "1", "2", "3", "4", "4"],    ["1", "1", "5", "6", "4", "4"]];​for (var i=0; i < 10000; i++) {    transform1(t1);}

transform2

var transform2 = (rowTemplate) => {
  if (!rowTemplate?.length) return [[]];

  const rows = rowTemplate.length;
  const cols = rowTemplate[0].length;
  
  const firstPositions = {};
  
  for (let row = 0; row < rows; row++) {
    for (let col = 0; col < cols; col++) {
      const id = rowTemplate[row][col];
      if (firstPositions[id] === undefined) {
        firstPositions[id] = {row, col};
      }
    }
  }
  
  const uniqueIds = Object.keys(firstPositions);
  
  const rowIds = [...uniqueIds].sort((a, b) => {
    const posA = firstPositions[a];
    const posB = firstPositions[b];
    return posA.row === posB.row ? posA.col - posB.col : posA.row - posB.row;
  });
  
  const colIds = [...uniqueIds].sort((a, b) => {
    const posA = firstPositions[a];
    const posB = firstPositions[b];
    return posA.col === posB.col ? posA.row - posB.row : posA.col - posB.col;
  });
  
  const tileMap = {};
  
  for (let i = 0; i < rowIds.length; i++) {
    tileMap[rowIds[i]] = colIds[i];
  }
  
  const result = Array(rows);
  for (let row = 0; row < rows; row++) {
    result[row] = new Array(cols);
    for (let col = 0; col < cols; col++) {
      result[row][col] = tileMap[rowTemplate[row][col]];
    }
  }
  
  return result;
};

var t1 = [
    ["1", "1", "2", "3", "4", "4"],
    ["1", "1", "5", "6", "4", "4"]
];


for (var i=0; i < 10000; i++) {
	transform2(t1);
}

 
var transform2 = (rowTemplate) => {  if (!rowTemplate?.length) return [[]];​  const rows = rowTemplate.length;  const cols = rowTemplate[0].length;    const firstPositions = {};    for (let row = 0; row < rows; row++) {    for (let col = 0; col < cols; col++) {      const id = rowTemplate[row][col];      if (firstPositions[id] === undefined) {        firstPositions[id] = {row, col};      }    }  }    const uniqueIds = Object.keys(firstPositions);    const rowIds = [...uniqueIds].sort((a, b) => {    const posA = firstPositions[a];    const posB = firstPositions[b];    return posA.row === posB.row ? posA.col - posB.col : posA.row - posB.row;  });    const colIds = [...uniqueIds].sort((a, b) => {    const posA = firstPositions[a];    const posB = firstPositions[b];    return posA.col === posB.col ? posA.row - posB.row : posA.col - posB.col;  });    const tileMap = {};    for (let i = 0; i < rowIds.length; i++) {    tileMap[rowIds[i]] = colIds[i];  }    const result = Array(rows);  for (let row = 0; row < rows; row++) {    result[row] = new Array(cols);    for (let col = 0; col < cols; col++) {      result[row][col] = tileMap[rowTemplate[row][col]];    }  }    return result;};​var t1 = [    ["1", "1", "2", "3", "4", "4"],    ["1", "1", "5", "6", "4", "4"]];​​for (var i=0; i < 10000; i++) {    transform2(t1);}

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
transform1
transform2

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 28 days ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/133.0.0.0 Safari/537.36

Browser/OS: Chrome 133 on Windows

View result in a separate tab

Test name	Executions per second
transform1	72.9 Ops/sec
transform2	97.4 Ops/sec

Autogenerated LLM Summary (model gpt-4o-mini, generated 27 days ago):

The provided benchmarks outline tests for two different JavaScript implementations aimed at transforming a two-dimensional array, referred to as rowTemplate, into a new format based on certain criteria. Both functions (transform1 and transform2) serve to reorganize the elements of the input array based on the positions of unique identifiers, which are the elements themselves in this context.

Overview of the Transform Functions

transform1:
- Uses a Map to store the positions of each unique identifier in the input array (rowTemplate). It iterates through the entire array and collects positions for each identifier.
- It uses two separate sorting operations to create arrays that maintain the order of identifiers by column and row before mapping them to a new result array.
- The result is constructed by filling a new two-dimensional array according to a mapping established by the order of sorted identifiers.
transform2:
- Utilizes a plain object (firstPositions) to achieve a similar goal but collects just the first occurrence of each identifier's position instead of all positions.
- It also sorts unique identifiers by their positions but does so using arrays derived directly from the collected mapping.
- Builds the result in a manner similar to transform1, but relies on the mapping derived from the first occurrence positions without retaining all positions.

Comparison of the Approaches

Pros and Cons

transform1 Pros:
- Retains all positions of identifiers which can be useful if the transformation logic needs to handle all occurrences robustly.
transform1 Cons:
- More memory-intensive due to the need to store multiple positions in a Map, which could result in higher overhead.
transform2 Pros:
- More memory-efficient as it only stores the first occurrences of identifiers’ positions, leading to potentially faster execution time, especially in cases where there are many duplicates.
- Generally simpler logic due to fewer data structures involved.
transform2 Cons:
- May not support scenarios requiring knowledge of all occurrences of identifiers' positions; it's limited to the first occurrence, which could be an issue in certain use cases.

Performance Considerations

The benchmark results indicate that transform2 performed better, executing approximately 97.4 times per second, while transform1 executed 72.9 times per second. This suggests that the reduced memory overhead and simplified logic of transform2 allow it to execute more efficiently in the given environment, which was Chrome on Windows 10.

JavaScript Features Used

Optional Chaining (?.): This feature is used in both functions to safely access properties of objects. If rowTemplate is undefined or null, the expression will not throw an error; instead, it will simply return undefined.

Alternatives

Use of Libraries:
- Lodash or similar libraries could streamline such transformations, providing optimized functions like _.map, _.reduce, or specialized functions for array manipulation. However, this might introduce external dependencies and potentially modify the execution speed due to overhead.
Native Array Functions:
- Utilizing methods such as Array.prototype.map, Array.prototype.reduce, or Array.prototype.forEach would provide a functional programming approach to handle the transformation. However, these methods may incur additional overhead, especially if used improperly (e.g., performing multiple passes over the array).
Typed Arrays:
- For specific numeric data types, using Typed Arrays might increase performance; however, the current implementation deals with strings which are less efficient for such arrays.

Conclusion

The benchmarks compare two approaches for transforming an array of identifiers into a new structure based on their positions effectively. The results favor transform2, highlighting its efficiency and memory management strategy. When deciding between the two, software engineers should consider the context of their application, the importance of memory usage, and the need for handling multiple occurrences of identifiers.

LLMs can make mistakes. Check important info.

The provided benchmarks outline tests for two different JavaScript implementations aimed at transforming a two-dimensional array, referred to as `rowTemplate`, into a new format based on certain criteria. Both functions (`transform1` and `transform2`) serve to reorganize the elements of the input array based on the positions of unique identifiers, which are the elements themselves in this context.

### Overview of the Transform Functions

1. **`transform1`**: 
   - Uses a `Map` to store the positions of each unique identifier in the input array (`rowTemplate`). It iterates through the entire array and collects positions for each identifier.
   - It uses two separate sorting operations to create arrays that maintain the order of identifiers by column and row before mapping them to a new result array.
   - The result is constructed by filling a new two-dimensional array according to a mapping established by the order of sorted identifiers.

2. **`transform2`**:
   - Utilizes a plain object (`firstPositions`) to achieve a similar goal but collects just the first occurrence of each identifier's position instead of all positions.
   - It also sorts unique identifiers by their positions but does so using arrays derived directly from the collected mapping.
   - Builds the result in a manner similar to `transform1`, but relies on the mapping derived from the first occurrence positions without retaining all positions.

### Comparison of the Approaches

#### Pros and Cons

- **`transform1` Pros**:
  - Retains all positions of identifiers which can be useful if the transformation logic needs to handle all occurrences robustly.

- **`transform1` Cons**:
  - More memory-intensive due to the need to store multiple positions in a `Map`, which could result in higher overhead.

- **`transform2` Pros**:
  - More memory-efficient as it only stores the first occurrences of identifiers’ positions, leading to potentially faster execution time, especially in cases where there are many duplicates.
  - Generally simpler logic due to fewer data structures involved.

- **`transform2` Cons**:
  - May not support scenarios requiring knowledge of all occurrences of identifiers' positions; it's limited to the first occurrence, which could be an issue in certain use cases.

### Performance Considerations

The benchmark results indicate that `transform2` performed better, executing approximately **97.4** times per second, while `transform1` executed **72.9** times per second. This suggests that the reduced memory overhead and simplified logic of `transform2` allow it to execute more efficiently in the given environment, which was Chrome on Windows 10.

### JavaScript Features Used

- **Optional Chaining (`?.`)**: This feature is used in both functions to safely access properties of objects. If `rowTemplate` is undefined or null, the expression will not throw an error; instead, it will simply return undefined.
  
### Alternatives

1. **Use of Libraries**:
   - **Lodash** or similar libraries could streamline such transformations, providing optimized functions like `_.map`, `_.reduce`, or specialized functions for array manipulation. However, this might introduce external dependencies and potentially modify the execution speed due to overhead.

2. **Native Array Functions**:
   - Utilizing methods such as `Array.prototype.map`, `Array.prototype.reduce`, or `Array.prototype.forEach` would provide a functional programming approach to handle the transformation. However, these methods may incur additional overhead, especially if used improperly (e.g., performing multiple passes over the array).

3. **Typed Arrays**:
   - For specific numeric data types, using Typed Arrays might increase performance; however, the current implementation deals with strings which are less efficient for such arrays.

### Conclusion

The benchmarks compare two approaches for transforming an array of identifiers into a new structure based on their positions effectively. The results favor `transform2`, highlighting its efficiency and memory management strategy. When deciding between the two, software engineers should consider the context of their application, the importance of memory usage, and the need for handling multiple occurrences of identifiers.

Related benchmarks:

transrorm template (version: 1)

Comparing performance of: transform1 vs transform2

Created: 28 days ago by: Guest

Jump to the latest result