What are the key components of Spark?
The core components of Spark include:
- Spark Core is the foundational runtime framework of Spark, which offers basic functionalities such as task scheduling, memory management, error recovery, and more.
- Spark SQL offers a module for handling structured data, supporting both SQL queries and the DataFrame API.
- 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.
- MLlib is Spark’s machine learning library that offers popular machine learning algorithms and tools for handling large-scale datasets.
- GraphX is a component designed for graph computations, offering APIs and algorithms for graph processing and supporting the handling of large-scale graph data.
- SparkR is the R language interface for Spark, allowing users to perform data processing and analysis with Spark in the R language.
- Real-time stream processing using Spark Streaming.
- MLlib: Machine Learning Library
- GraphX: Graph Computing Engine
- Spark SQL: structured data processing.
- Real-time stream processing through Spark Streaming.
- MLlib: Machine Learning Library
- GraphX: Graph computing engine
- Structured data processing with Spark SQL
