What is the significance of Resilient Distributed Dataset (RDD) in Apache Spark?
- Data visualization and analytics
- Fault tolerance and distributed data
- In-memory caching and data storage
- Stream processing and real-time analytics
RDDs in Apache Spark provide fault tolerance and distributed data processing capabilities. They allow for resilient distributed computation by automatically recovering from failures and redistributing data.
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