The second example - a data filtering algorithm
Suppose that you have a lot of data that describes a list of items. For example, say that you have a lot of attributes (name, surname, address, phone number, and so on) of a lot of people. It's a common need to obtain the data that meets certain criteria. For example, you might want to obtain the details of people who live in a certain street or with a certain name.
In this section, you will implement one of those filtering programs. We have used the Census-Income KDD dataset from the UCI (you can download it from https://archive.ics.uci.edu/ml/datasets/Census-Income+%28KDD%29), which contains weighted census data extracted from the 1994 and 1995 current population surveys conducted by the U.S. Census Bureau.
In the concurrent version of this example, you will learn how to cancel tasks that are running in the fork/join pool and how to manage unchecked exceptions that can be thrown in a task.
Common features
We have implemented some classes to read...