Explain transformation and action in RDD in Apache Spark?



Explain transformation and action in RDD in Apache Spark?..

Answer / Pratibha Gangwar

In Apache Spark, transformations are operations that create a new RDD from an existing one without executing the computation immediately. Examples of transformations include map(), filter(), reduce(), join(), groupByKey(), and sortBy(). Actions, on the other hand, trigger the execution of previously defined transformations and produce a result in the driver program. Examples of actions are count(), collect(), saveAsTextFile(), and foreach(). Transformations in Spark are lazy evaluations, while actions are eager evaluations.

Is This Answer Correct ?    0 Yes 0 No

Post New Answer

More Apache Spark Interview Questions

Define Partition and Partitioner in Apache Spark?

1 Answers  


What operations does the "RDD" support?

1 Answers  


What languages support spark?

1 Answers  


Explain the default level of parallelism in Apache Spark

1 Answers  


Explain the operations of Apache Spark RDD?

1 Answers  


What is graphx spark?

1 Answers  


Explain the run-time architecture of Spark?

1 Answers  


What does a Spark Engine do?

1 Answers  


Explain SparkContext in Apache Spark?

1 Answers  


Can you explain spark mllib?

1 Answers  


What is executor memory and driver memory in spark?

1 Answers  


Why does the picture of Spark come into existence?

1 Answers  


Categories