Apache Spark is primarily used for which purpose?

Apache Spark is primarily recognized as a powerful open-source distributed computing system designed for Big Data processing. It excels in handling large volumes of data across multiple nodes in a cluster, allowing for the execution of data processing tasks efficiently and quickly. Spark's architecture supports in-memory computation, which significantly speeds up data processing compared to traditional disk-based processing systems.

It provides a unified framework suitable for various data processing needs, such as batch processing, real-time analytics, and machine learning, making it a versatile tool in the Big Data ecosystem. This capability to handle diverse data types and processing models is what positions Spark as a core technology for data scientists and analysts dealing with large datasets.

The other options involve areas where Apache Spark is not utilized. Web hosting and static website generation pertain to serving web content, and network security focuses on protecting systems and data from threats, neither of which align with the core capabilities and intended use of Apache Spark.