What is Apache Spark and how does Scala relate to it?

Apache Spark is a distributed data processing framework written in Scala, with APIs for Scala, Python (PySpark), Java, and R. Spark is the industry standard for large-scale data processing. The core abstraction: RDD (Resilient Distributed Dataset): fault-tolerant, parallelized collection. DataFrame/Dataset API (Spark SQL): structured data with schema, optimized by the Catalyst query optimizer. Dataset[T]: type-safe RDD with compile-time type checks — only available in Scala/Java. Transformations (lazy): map, filter, groupBy, join. Actions (triggers execution): count, collect, write. Scala is preferred for Spark development because it offers type-safe Dataset API, better IDE support, and performance advantages over Python for complex transformations. Many Spark internals are more accessible in Scala than through the Python wrapper.