Functional programming (FP) is a paradigm widely adopted in data science and big data tools (e.g., Spark with Scala/Python). Its useful features include:
Option A (Higher-Order Functions): Functions can take other functions as arguments or return them, enabling powerful abstractions like map(), reduce(), and filter().
Option B (Immutable Data): Ensures reliability and thread-safety, crucial for distributed computing. Once created, data structures cannot be modified, preventing side effects.
Option C (Lazy Evaluation): Computations are delayed until results are needed, improving performance in large-scale data operations.
Since FP leverages all three features, the correct answer is Option D (All of the above).
[Reference:, DASCA Data Scientist Knowledge Framework (DSKF) – Programming for Data Science: Functional Programming in Data Science Tools., ]
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