Kafka Streams: Streams and Tables

Neha Bhardwaj explains a couple of the key abstractions in Kafka Streams:

In this blog, we’ll move one step forward to get an understanding of the Dual streaming model to see what abstractions does KSQL use to process the data.

All the data that we are working on with KSQL is produced to Kafka topics by some client. This client can be any Application, Kafka connectors etc., which produces continuous never-ending data to the topics.

KSQL does not directly interact with these topics, it rather introduces a couple of abstractions in between to process the data, which are known as Streams and Tables.

Read on to learn what these are and why it’s useful to think in these terms.

Related Posts

Pivoting Spark DataFrames

Unmesha Sreeveni shows how we can pivot a DataFrame in Apache Spark using one line of code: A pivot can be thought of as translating rows into columns while applying one or more aggregations. Lets see how we can achieve the same using the above dataframe. We will pivot the data based on “Item” column. […]

Read More

Troubleshooting Spark Performance

Bikas Saha and Mridul Murlidharan explain some of the basics of performance tuning with Apache Spark: Our objective was to build a system that would provide an intuitive insight into Spark jobs that not just provides visibility but also codifies the best practices and deep experience we have gained after years of debugging and optimizing […]

Read More

Leave a Reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.

Categories

April 2019
MTWTFSS
« Mar  
1234567
891011121314
15161718192021
22232425262728
2930