Kafka Spark Streaming | Kafka Tutorial

Kafka Spark Streaming | Kafka Tutorial

🔥Intellipaat Kafka training: https://intellipaat.com/kafka-training-online/ 👉In this kafka spark streaming tutorial you will learn what is apache kafka, arch...

In this kafka spark streaming tutorial you will learn what is apache kafka, architecture of apache kafka & how to setup a kafka cluster, what is spark & it's features, components of spark and hands on demo on integrating spark streaming with apache kafka and integrating spark flume with apache kafka.

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Spark Structured Streaming – Stateful Streaming

Spark Structured Streaming – Stateful Streaming. Welcome back folks to this blog series of Spark Structured Streaming. This blog is the continuation of the earlier blog "Internals of Structured Streaming".

Spark Streaming: Adding Spark to Streaming

In today’s world we have a lot of data. And this data will only grow more and more in future. According to a study, in 2020, the data produced is abound 44 zettabytes each day. And by 2025, approximately 463 exabytes would be created every 24 hours worldwide. Do you ever imagine how one can store or process this much data ?A solution to this is Apache Spark and in this blog I’m going to discuss about Spark Streaming here.

Spark Streaming Tutorial | Twitter Real time Streaming | Apache Spark For Beginners

Spark Streaming Tutorial will help you to master all the concepts of Spark Streaming. Spark Streaming is an extension of the core Spark API that allows data engineers and data scientists to process real-time data from various sources including (but not limited to) Kafka, Flume, and Amazon Kinesis.

Creating Data Pipeline with Spark streaming, Kafka and Cassandra

Hi Folks!! In this blog, we are going to learn how we can integrate Spark Structured Streaming with Kafka and Cassandra to build a simple data pipeline.

Structured Streaming in Spark 3.0 Using Kafka

After the previous post wherein we explored Apache Kafka, let us now take a look at Apache Spark. This blog post covers working within Spark’s interactive shell environment, launching applications (including onto a standalone cluster), streaming data and lastly, structured streaming using Kafka. To get started right away, all of the examples will run inside Docker containers.