Exam Certified Associate Developer for Apache Spark topic 1 question 8 discussion

The most complete description of lazy evaluation is: B. A process is lazily evaluated if its execution does not start until it is put into action by some type of trigger. Explanation: Lazy evaluation is a programming language feature that delays the evaluation of expressions or computations until the result is actually needed or requested. In a lazily evaluated system, expressions are not immediately executed or evaluated when they are defined or assigned. Instead, the evaluation is deferred until the value is needed by another part of the program or when an action is triggered.

B. A process is lazily evaluated if its execution does not start until it is put into action by some type of trigger. Lazy evaluation is a programming paradigm that defers the evaluation of an expression until its value is needed. In other words, lazy evaluation delays the computation of a value until the value is actually required by the program. This is in contrast to eager evaluation, where expressions are evaluated as soon as they are bound to a variable. In Spark, lazy evaluation is used extensively to optimize the execution of complex data processing pipelines. When a user creates a series of operations to transform a dataset, Spark does not immediately execute those operations. Instead, it builds a logical plan that represents the operations as a set of transformations on the original dataset. The actual execution of the plan is deferred until the user requests the result by triggering an action, such as writing the result to disk or displaying it on the screen. By using lazy evaluation, Spark can optimize the execution plan and avoid unnecessary computations, resulting in faster processing times and more efficient use of cluster resources.