What are the different flattening techniques and their performance comparisons?

What are the different flattening techniques used in data processing?

Flattening techniques include simple flattening, hierarchical flattening, and nested flattening. Each has its own use cases.

How do these techniques compare in terms of performance?

Performance varies based on data size and structure. Simple flattening is usually faster, while hierarchical can be more efficient for complex data.

Can you provide examples of when to use each technique?

Sure! Use simple flattening for straightforward datasets, hierarchical for nested structures, and nested flattening for complex relationships.

What tools can I use to implement these techniques?

You can use tools like Apache Spark, Pandas in Python, or SQL for implementing these flattening techniques.