What are the key components of Spark?

The core components of Spark include:

  1. Spark Core is the foundational runtime framework of Spark, which offers basic functionalities such as task scheduling, memory management, error recovery, and more.
  2. Spark SQL offers a module for handling structured data, supporting both SQL queries and the DataFrame API.
  3. Spark Streaming is a component designed for real-time data processing, capable of reading data in real-time from multiple sources and processing it through micro-batch processing.
  4. MLlib is Spark’s machine learning library that offers popular machine learning algorithms and tools for handling large-scale datasets.
  5. GraphX is a component designed for graph computations, offering APIs and algorithms for graph processing and supporting the handling of large-scale graph data.
  6. SparkR is the R language interface for Spark, allowing users to perform data processing and analysis with Spark in the R language.
  7. Real-time stream processing using Spark Streaming.
  8. MLlib: Machine Learning Library
  9. GraphX: Graph Computing Engine
  10. Spark SQL: structured data processing.
  11. Real-time stream processing through Spark Streaming.
  12. MLlib: Machine Learning Library
  13. GraphX: Graph computing engine
  14. Structured data processing with Spark SQL
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