Chapter 8. Scala and MongoDB
In Chapter 5, Scala and SQL through JDBC, and Chapter 6, Slick – A Functional Interface for SQL, you learned how to insert, transform, and read data in SQL databases. These databases remain (and are likely to remain) very popular in data science, but NoSQL databases are emerging as strong contenders.
The needs for data storage are growing rapidly. Companies are producing and storing more data points in the hope of acquiring better business intelligence. They are also building increasingly large teams of data scientists, who all need to access the data store. Maintaining constant access time as the data load increases requires taking advantage of parallel architectures: we need to distribute the database across several computers so that, as the load on the server increases, we can just add more machines to improve throughput.
In MySQL databases, the data is naturally split across different tables. Complex queries necessitate joining across several tables. This makes...
