Mastering Machine Learning with Spark 2.x

From Hadoop MapReduce to Spark

With a growing amount of data, the single-machine tools were not able to satisfy the industry needs and thereby created a space for new data processing methods and tools, especially Hadoop MapReduce, which is based on an idea originally described in the Google paper, MapReduce: Simplified Data Processing on Large Clusters (https://research.google.com/archive/mapreduce.html). On the other hand, it is a generic framework without any explicit support or libraries to create machine learning workflows. Another limitation of classical MapReduce is that it performs many disk I/O operations during the computation instead of benefiting from machine memory.

As you have seen, there are several existing machine learning ...