In this section, we will describe two key concepts introduced by the Spark machine learning libraries (Spark MLlib and Spark ML) and the most widely used implemented algorithms that align with the supervised and unsupervised learning techniques we discussed in the previous sections.
Spark machine learning APIs
Spark machine learning libraries
As already stated, in the pre-Spark era, big data modelers typically used to build their ML models using statistical languages such as R, STATA, and SAS. However, this kind of workflow (that is, the execution flow of these ML algorithms) lacks efficiency, scalability, and throughput, as well as accuracy, with, of course, extended execution times.
Then, data engineers used to reimplement...