Reading Time: 4 minutes Joining multiple sets of data into a singular entity is very often when working with data pipelines. In this blog, We will cover how we can perform Join operations between datasets in Apache Beam. There are different ways to Join PCollections in Apache beam – Extension-based joins Group-by-key-based joins Join using side input Let’s understand the above different way’s to perform Join with examples. We Continue Reading
Reading Time: 3 minutes Apache Flink offers rich sources of API and operators which makes Flink application developers productive in terms of dealing with the multiple data streams. Flink provides many multi streams operations like Union, Join, and so on. In this blog, we will explore the Window Join operator in Flink with an example. It joins two data streams on a given key and a common window. Let say we have one stream which contains salary information of all Continue Reading
Reading Time: 3 minutes Introduction to core concepts: Apache Kafka is a distributed streaming platform which enables you to publish and subscribe to a stream of records also letting you process this stream of records as it occurs. Kafka Streams is a client library used for building applications and microservices, where the input and output data are stored in Kafka clusters. Interface KStream<K, V> is an abstraction of Continue Reading
