Functional programming's core operations, Map, Reduce, and Filter, are essential for data manipulation. Map transforms elements, Reduce aggregates them, and Filter selects based on criteria. These higher-order functions contribute to more readable, maintainable, and efficient code, with practical applications across various industries.
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Map is a higher-order function that applies a given operation to each item in a collection, producing a new array with the transformed elements
Map is used for data transformation, modifying each element of an array without altering the original data
Map is widely used in various fields such as database management, social networking, image processing, and e-commerce for efficient data processing
Reduce is a higher-order function that aggregates all elements in a collection into a single output through repeated application of a combining function
Reduce is used for combining elements into a unified result, adhering to the principle of immutability
Reduce is commonly used in databases, social networks, and e-commerce sites for efficient record processing, generating user recommendations, and calculating totals
Filter is a higher-order function that selectively includes elements in a collection that meet a certain criterion, resulting in a new array of elements that pass the test
Filter is used for selecting data subsets based on criteria, providing a systematic approach to data manipulation
Filter is commonly used in databases, social networks, and e-commerce sites for efficient record processing, generating user recommendations, and filtering product selections
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Map function operation
Applies a given operation to each item in a collection, creating a new array with transformed elements.
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Reduce function purpose
Aggregates all elements in a collection into a single output via a repeated combining function.
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Filter function criterion
Includes elements that meet a specific condition, producing a new array of elements that pass this test.
