Kaizer India Data Governance Consultant Interview Questions and Answers

Repartition increases or decreases the number of partitions in a DataFrame, while coalesce only decreases the number of partitions.

• Repartition shuffles the data across the network, while coalesce does not.

• Repartition can be used to increase parallelism, while coalesce is used to reduce it.

• Repartition can result in uneven partition sizes, while coalesce always results in equal or smaller partition sizes.

Generator produces values on the fly while iterator returns values from a collection.

• Generators use 'yield' keyword to produce values one at a time.

• Iterators use 'next()' method to return the next value in a collection.

• Generators can be infinite while iterators are finite.

• Generators are memory efficient while iterators may require more memory.

• Example of generator: function* myGenerator() { yield 1; yield 2; }

• Example of...read more