Apache Druid : Complete Guide

What do you learn from this course?

In this course, we learn end-to-end Apache druid salient features and integration with Apache Hive. We start this course by gaining theoretical knowledge on Druid and its key features.

Next, we jump to the practical part, where we install druid locally and walk you through its user portal. We change the druid metadata storage to MySQL and deep storage to S3 to enhance the druid setup.  After that, we write our own Twitter Producer app, which pulls the tweets from Twitter in real time and pushes the tweets to Apache Kafka.

We create a Kafka ingestion task on Druid that pulls tweets from Kafka and stores them in Apache Druid. Also, we learn how to apply the transformation, filter, and schema configuration during the Kafka ingestion process.

Keeping practical knowledge in mind, we jump to the theory part and dig deeper into the druid internal working principle. We learn, how the data is distributed between the data nodes and retrieved in real-time.  Next, we tune our ingestion pipeline to gain a better result. Lastly, we explore salient features like Accessing Druid through JDBC and Schema Evolution.

In the 2nd module, we talk about druid hive integration. At first, we learn what is this integration? Next, we provision a VM from AWS and install Apache Druid on it. After that, we acquire a hive EMR cluster from AWS and configure it such that it can communicate to druid easily. Lastly, we run the same druid queries on hive and learn how the computation is pushed down to druid for better performance.

Overall, this course is a composite of theory and practical sessions. Throughout this course, we use the latest druid and hive versions. At the end of this course, you will excel on Apache Druid.