In which we continue the quest about multi-value handling and try to answer the question: Why are we even doing this?

This is part 2 of a miniseries about multi-value dimensions in Apache Druid. More posts can be found here:

• part 1
• part 3
• part 4
• part 5

In an earlier post I discussed how to enable the alerting capabilities of Imply Pivot and send out alerts via email.

Apache Druid is known for its ability to handle schema changes during data ingestion and query in an extraordinarily flexible way. Normally, you don’t even need to worry because everything is handled automatically for you. However, there are a few edge cases that data engineers and data analysts should be aware of. Let’s have a look.