MLlib
MLlib is Spark’s machine learning library designed for scalable and efficient ML applications. It has transitioned to focus on the DataFrame-based API in the spark.ml package, moving the RDD-based APIs to maintenance mode. Leveraging optimized linear algebra libraries, MLlib facilitates advanced numerical processing, enhancing performance in machine learning tasks.
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Top MLlib Features
- DataFrame-based API support
- Scalable machine learning
- Optimized numerical processing
- Linear algebra acceleration
- Native acceleration libraries support
- Compatible with Intel MKL
- OpenBLAS integration
- Python NumPy support
- Enhanced performance features
- Maintenance mode for RDD API
- High-level ML tools
- Migration guide availability
- System optimized natives
- Supported in Spark 3.0
- Easy integration with Spark
- Improved library performance
- Simplified ML workflows
- Advanced machine learning algorithms
- User-friendly API design
- Community-driven enhancements
