The structured-to-hierarchical transformation pattern deals with transforming the data by generating a hierarchical structure, such as XML or JSON from the structured data.
The structured-to-hierarchical transformation pattern creates a new hierarchical structure, such as JSON or XML out of data that is stored in flat, row-like structures. It is a data transformation pattern that creates new records, which are represented in a different structure when compared to the original records.
Hadoop is good at integrating data from multiple sources, but performing joins for the analytics just in time is always a complex and time-consuming operation.
In order to perform certain types of analytics efficiently (such as logfile analysis), the data is sometimes not required to be stored in a normalized form in Hadoop. Storing the data in the normalized form in multiple tables creates an additional step of joining all the data together...