Java: Data Science Made Easy

Improving application performance using parallel techniques

In Chapter 11, Mathematical and Parallel Techniques for Data Analysis, we consider some of the parallel techniques available for data science applications. Concurrent execution of a program can significantly improve performance. In relation to data science, these techniques range from low-level mathematical calculations to higher-level API-specific options.

This chapter includes a discussion of basic performance enhancement considerations. Algorithms and application architecture matter as much as enhanced code, and this should be considered when attempting to integrate parallel techniques. If an application does not behave in the expected or desired manner, any gains from parallel ...