For anyone familiar with SQL, the concept of joining data together is well understood. The ability to join one or more tables together for the purpose of analytics has remained relevant throughout my 20+ year career of working with data and I hope it continues to be relevant.
In prior chapters, we introduced the concept of data models and the need for primary and foreign key fields to define relationships. We will now elaborate on these concepts by explaining joins and the different types of joins that exist in SQL and DataFrames.
Joining, in SQL, simply means merging two or more tables into a single dataset. The resulting size and shape of that single dataset will vary depending on the type of join that is used. Some key concepts you want to remember any time you are creating a join between datasets will be that the common unique key should always be used. Ideally, the key field functions as both the primary and foreign key but...
