Spark Machine Learning
The open-source, cluster-computing framework Apache Spark provides a powerful ecosystem for machine learning and predictive analytics through the popular machine learning library, MLlib. MLlib delivers greater scalability, simplicity, and easy interoperability with Python and other machine learning tools. Spark allows users to solve data problems with the languages and tools they are most comfortable with (e.g. Python with pyspark MLlib, Scala, Java, and R).
Spark machine learning offers data scientists, data engineers and other data professionals an easy-to-use platform that is far faster for high-volume and high-velocity data processing than Hadoop and other alternatives.
Spark Machine Learning and Snowflake
With integration to Spark machine learning, Snowflake provides data pros with an elastic, scalable repository for all data supporting algorithm training and testing. With machine learning, processing capacity needs can fluctuate significantly based on need. Snowflake can easily scale compute capacity to allow Spark to process large data volumes.