A Java geek

This is the 19th post in the Exercises in Programming Style focus series. In the last episode of Exercises in Programming Style, we solved the word frequency problem with the Hazelcast library. This time, we are going to use MapReduce for that. MapReduce is a process consisting of two steps: Map performs transformations, filtering and sorting into different queues. Reduce aggregates the content of the queues into a result.

This is the 18th post in the Exercises in Programming Style focus series. The previous week, we shared data among threads to solve the now well-known word frequencies problem. The very next day, I joined Hazelcast as a Developer Advocate. Therefore, I thought it would be extremely interesting to use Hazelcast In-Memory-Data-Grid to improve on the previous solution.

This is the 17th post in the Exercises in Programming Style focus series. Last week, we solved the word count problem using the Actor model: objects running on different threads and communicating through messages. This week, we will drop objects, and use data structures that are shared among the threads: such a shared structure is called data space in the book. The original Python code uses two dedicated data spaces.

This is the 16th post in the Exercises in Programming Style focus series. In the book, this chapter is called Actors. In software, the actor model is a very specific way to design code: The actor model in computer science is a mathematical model of concurrent computation that treats 'actors' as the universal primitives of concurrent computation.

This is the 15th post in the Exercises in Programming Style focus series. Last week, we solved the top 25 word frequencies problem with the help of the database. This week, we will get back to solve it with code alone. The design is to model the problem as a spreadsheet. The spreadsheet holds a number of cells, each cell having a value and a formula.

This is the 14th post in the Exercises in Programming Style focus series. So far, we solved the word frequencies problem with code alone. This week, we will solve it with the help of infrastructure. And with this specific problem at hand, what better fit than the database? We can approach the problem by loading the data read from the files in the database, and retrieving the top 25 words with the relevant query.