What is Apache Spark?

It provides a fast, general-purpose engine for big data processing, capable of handling both batch and real-time data processing tasks.

Spark was developed to overcome the limitations of traditional MapReduce frameworks and offers advanced features like in-memory processing, support for complex analytics, and seamless integration with various data sources.

Spark provides high-level APIs in Java, Scala, Python, and R.

Key Features

• In-Memory Computing - processes data in memory rather than on disk, which accelerates performance for iterative algorithms and interactive queries.

• Unified Analytics Engine - supports batch processing, interactive queries, streaming analytics, and machine learning through a single framework.

• Scalability - scales horizontally by adding more nodes to a cluster, making it capable of handling petabytes of data.

Data Structures

The primary abstractions in Spark are:

• Resilient Distributed Dataset(RDD);
• DataFrame;
• Dataset.

We will discuss them in a more detailed way soon.