What are the differences between map, reduce, and filter in programming?

Can you explain the differences between map, reduce, and filter in programming?

Sure! Map, reduce, and filter are higher-order functions used in functional programming. Map applies a function to each item in a collection, returning a new collection. Reduce combines all items in a collection into a single value, and filter creates a new collection with only the items that meet a certain condition.

Can you give me an example of each?

Of course! For map, if you have an array of numbers and want to double each number, you'd use map. For reduce, if you want to sum all numbers in an array, you'd use reduce. For filter, if you want to get only even numbers from an array, you'd use filter.

How do they differ in terms of output?

Great question! Map always returns a new array of the same length as the original, reduce returns a single value, and filter returns a new array that can be shorter than the original, depending on the condition.

Are there any performance considerations?

Yes, performance can vary. Map and filter create new arrays, which can use more memory, while reduce can be more efficient since it returns a single value. However, the actual performance depends on the size of the data and the operations performed.