Apache: Spark Scala Interview Questions- Shyam Mallesh [best]

Spark uses (RDD dependency graph). Each RDD remembers how it was built from other datasets. If a partition is lost, Spark recomputes it using the lineage, not replication. However, you can also cache/persist with replication (e.g., StorageLevel.MEMORY_AND_DISK_2 ).

If you have come across training materials or interview prep guides by , you know that his approach is not about rote memorization—it is about deep, conceptual clarity. This article compiles the most critical, frequently asked Apache Spark Scala Interview Questions , inspired by the rigorous standards of Shyam Mallesh’s teaching methodology. Apache Spark Scala Interview Questions- Shyam Mallesh

import org.apache.spark.sql.SparkSession Spark uses (RDD dependency graph)

A Spark DataFrame is a distributed collection of data organized into named columns, while a Dataset is a distributed collection of data that provides a strongly-typed API. Spark recomputes it using the lineage