Spark MLlib
It is a scalable machine learning library. It delivers both blazing speed (up to 100x faster than MapReduce) and high-quality algorithms (e.g., multiple iterations to increase accuracy). We can use this library in Java, Scala, and Python as part of Spark applications so that you can include it in complete workflows. There are many tools, which are provided by MLlib. Such as-
1- ML Algorithms:
common learning algorithms such as classification, regression, clustering, and collaborative filtering.
2- Featurization:
feature extraction, transformation, dimensionality reduction, and selection.
3- Pipelines:
tools for constructing, evaluating, and tuning ML Pipelines.
4- Persistence:
saving and load algorithms, models, and Pipelines.
5- Utilities:
linear algebra, statistics, data handling, etc.
For detailed insights, follow link: Apache Spark MLlib (Machine Learning Library)