Integrating Custom Data Sources Into Spark

Nicolas A Perez builds a custom Spark streaming data source:

We first receive the order ID and the total amount of the order, and then we receive the line items of the order. The first value is the item ID, the second is the order ID, (which matches the order ID value) and then the cost of the item. In this example, we have two orders. The first one has four items and the second one has only one item.

The idea is to hide all of this from our Spark application, so what it receives on the DStream is a complete order defined on a stream as follows:

Check out this practical application of Spark Streaming.

Related Posts

Event Sourcing On Kafka

Adam Warski shows how you can use Apache Kafka as your event sourcing data source: There’s a number of great introductory articles, so this is going to be a very brief introduction. With event sourcing, instead of storing the “current” state of the entities that are used in our system, we store a stream of events that relate to these […]

Read More

The Basics Of Kafka Security

Stephane Maarek has a nice post covering some of the basics of securing an Apache Kafka cluster: Once your Kafka clients are authenticated, Kafka needs to be able to decide what they can and cannot do. This is where Authorization comes in, controlled by Access Control Lists (ACL). ACL are what you expect them to be: […]

Read More


May 2016
« Apr Jun »