In this post, we will implement the third part of our system, which is the Speed Layer of Lambda architecture. We will use Spark Structured Streaming to read data from Kafka’s “TwitterStreaming” topic and analyze this data in real time.
In this tutorial, we will use TwitterStreaming API to get Twitter’s tweets in real time and publish it to a Kafka topic. We then use Spark as a Consumer to read Twitter data from Kafka and analyse that data. To
In the previous tutorial (Integrating Kafka with Spark using DStream), we learned how to integrate Kafka with Spark using an old API of Spark – Spark Streaming (DStream) . In this tutorial, we will use a newer API of Spark,
In this tutorial series, we will learn how to use Structured Streaming – a Spark’s stream processing engine built on Spark SQL. In Structured Streaming, stream data is consider as an unbounded table where arriving data is like a new