Apache Kafka – Spark – Cassandra Real Time Streaming Project

Apache Kafka – Spark – Cassandra Real Time Streaming Project, available at $39.99, has an average rating of 4.05, with 14 lectures, based on 32 reviews, and has 1097 subscribers.

You will learn about Professionals looking for an end to end kafka, spark and cassandra streaming pipeline. Anyone who wants to understand how to use Apache kafka in their current architecture. Engineers who are looking to design a Kafka Solution Pipeline. A complete case study from start to execution. This course is ideal for individuals who are Engineers looking for a CASE STUDY on Real Time Data Streaming involving KAKFA and SPARK It is particularly useful for Engineers looking for a CASE STUDY on Real Time Data Streaming involving KAKFA and SPARK.

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Summary

Title: Apache Kafka – Spark – Cassandra Real Time Streaming Project

Price: $39.99

Average Rating: 4.05

Number of Lectures: 14

Number of Published Lectures: 14

Number of Curriculum Items: 14

Number of Published Curriculum Objects: 14

Original Price: ₹1,199

Quality Status: approved

Status: Live

What You Will Learn

Professionals looking for an end to end kafka, spark and cassandra streaming pipeline.
Anyone who wants to understand how to use Apache kafka in their current architecture.
Engineers who are looking to design a Kafka Solution Pipeline.
A complete case study from start to execution.

Who Should Attend

Engineers looking for a CASE STUDY on Real Time Data Streaming involving KAKFA and SPARK

Target Audiences

Engineers looking for a CASE STUDY on Real Time Data Streaming involving KAKFA and SPARK

The course is designed to provide a comprehensive understanding of real-time big data processing using Kafka, Spark, and Cassandra. In today’s world, data is produced at an unprecedented rate, and the ability to process and analyze this data in real-time is critical for making informed decisions. This course focuses on the fundamental concepts and architecture of Kafka, Spark, and Cassandra, and how they work together to create a robust big data processing pipeline.

Students will learn how to set up Kafka clusters and work with Kafka producers and consumers. Students will also learn about Kafka Streams, a client library for building real-time streaming applications that process data directly within Kafka.

Throughout the course, students will gain hands-on experience through practical exercises and projects that simulate real-world scenarios. By the end of the course, students will have a understanding of how to use Kafka, Spark, and Cassandra to build real-time big data processing systems.

Course Objectives:

Understand the fundamental concepts of real-time big data processing
Learn the architecture setup of Kafka, Spark, and Cassandra
Understand how Kafka, Spark, and Cassandra work together to create a real-time big data processing pipeline
Gain hands-on experience with Kafka, Spark, and Cassandra through practical exercises and projects
Learn how to build a real-time big data processing pipeline from scratch

This course is intended for software engineers, data engineers, and data analysts who have a basic understanding of programming concepts and are familiar with SQL.

Course Curriculum

Chapter 1: Infrastructure Setup for the Pipeline

Lecture 1: Introduction: Project_Overview

Lecture 2: Documents

Lecture 3: Ubuntu_Machine_Creation

Lecture 4: Putty_Installation

Lecture 5: Java_Installation

Lecture 6: Kafka_Setup

Lecture 7: Hadoop_Installation

Lecture 8: SPARK SCALA Installation

Lecture 9: Cassandra_Installation

Chapter 2: Pipeline Setup For KAKFA SPARK Real Time Streaming

Lecture 1: JSON Data Overview and Cassandra Table Creation

Lecture 2: KAFKA Producer & Consumer Configuration

Lecture 3: Code Overview(Spark Scala)

Chapter 3: FINAL Pipeline Execution End to End(KAFKA + SPARK + CASSANDRA)

Lecture 1: Pipeline Execution

Lecture 2: Destroy Droplet (*Important)

Instructors

Sonal Saxena
Technical Training Academy

Rating Distribution

1 stars: 1 votes
2 stars: 1 votes
3 stars: 1 votes
4 stars: 12 votes
5 stars: 17 votes

Frequently Asked Questions

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