What is the main difference between DataFrame and RDD in Apache Spark?
- Immutable vs. mutable data structures
- Lazy evaluation vs. eager evaluation
- Low-level API vs. high-level API
- Structured data processing vs. unstructured data processing
The main difference between DataFrame and RDD in Apache Spark lies in their approach to data processing. DataFrames offer structured data processing capabilities, while RDDs handle unstructured data and provide more low-level control.
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