RDD 1)Are know as Resilient Distributed Datasets (RDD) 2) It is an core level API of Spark. 3) When ever you work on any DataFrame or Data sets those are converted to low level API i.e. RDD 4) These are use full whenever the business needs are exceptional and you cannot perform m...
Thefilter()function is a transformation operation that takes a Boolean expression or a function as an input and applies it to each element in the RDD (Resilient Distributed Datasets) or DataFrame, retaining only the elements that satisfy the condition. For example, if you have an RDD containing...
In the above example, persisting dataframe df_transformed with MEMORY_AND_DISK storage level keeps it in memory if possible but can also stored on a disk if memory is full, providing a balance between performance and reliability. Differences Between Cache and Persist Storage Options Cache: Only...
Usingcache()andpersist()methods, Spark provides an optimization mechanism to store the intermediate computation of an RDD, DataFrame, and Dataset so they can be reused in subsequent actions(reusing the RDD, Dataframe, and Dataset computation results). Both caching and persisting are used to save t...