Learning Apache Storm for Big Data Processing

Video description

Using a free and open source, distributed real-time computation system was never this much fun!

About This Video

Learn the key points of the Lambda Architecture and the role Apache Storm plays in it
Learn programming techniques to create a Storm topology, its patterns, and anti-patterns.
Understanding the core components and Apache Storm daemons
Achieving fault-tolerance in Apache Storm

In Detail

Apache Storm is a distributed real-time …

Learning Apache Storm for Big Data Processing

Video description

Using a free and open source, distributed real-time computation system was never this much fun!

About This Video

Learn the key points of the Lambda Architecture and the role Apache Storm plays in it
Learn programming techniques to create a Storm topology, its patterns, and anti-patterns.
Understanding the core components and Apache Storm daemons
Achieving fault-tolerance in Apache Storm

In Detail

Apache Storm is a distributed real-time processing engine. Created by Nathanmarz for Backtype and later open sourced under Apache License 2, it's a scalable and a fault-tolerant engine used to process a massive number of unbounded streams. In this course you will see how simple yet efficient Apache Storm is when it comes to real-time processing.

In the course, you will learn about data processing types followed by Apache Storm and its features. You'll learn the core concepts of Apache Storm such as spouts, bolts, topology, and stream grouping, and set up Apache Storm in single-node and multi-node configurations. Also you'll explore how fault-tolerant Apache Storm is.

Taking this course will kick-start your experience with Apache Storm; you'll create a scalable, fault-tolerant, real-time processing application while setting a strong base for the fundamentals of the real-time processing paradigm and Apache Storm.

Audience

This course targets data engineers, solution architects, Java developers, technical managers, and programming analysts working in a big data setup or anyone who is keen to learn the ins and outs of big data processing.

The audience is expected to have a working knowledge of programming with Java. A basic knowledge of Apache Maven (and a working knowledge of Eclipse and Linux terminals) will help you understand its concepts a lot more easily.

Publisher resources

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Chapter 1 : Introducing Real-time Processing

The Course Overview

Understanding Lambda Architecture

Big Data Processing Types

What Is Apache Storm?

When to Use Apache Storm?

Chapter 2 : Apache Storm Concepts

Topology

Tuples

Spouts and Bolts

Streams and StreamGrouping

Chapter 3 : Setting Up Your Apache Storm Development Environment

Introduction – Prerequisites and System Requirements

Installing Java and Setting Environment Variables

Installing and Configuring Eclipse

Building Apache Storm Project Using Maven

Building Apache Storm Project Using External JAR Configuration

Chapter 4 : Creating Our First Storm Topology

Understanding the Problem Statement

Developing Spout Class to Emit the Data

Develop a Bolt Class to Perform Calculation

Develop a Bolt Class to Print Result in Console

Developing Topology Class

Executing Our Application in Eclipse

Chapter 5 : Setting Up Apache Storm as a Single-Node Cluster

Understanding Storm Daemons

Prerequisites

Setting Up Zookeeper in Standalone Mode

Install and Configure Apache Storm in Single-Node

Deploy NumSquareTopology in Cluster

Explore Storm UI and Understand Essential Features

Chapter 6 : Setting Up Apache Storm in Multi-Node Cluster

Setting Up Zookeeper in Multi-Node Mode

Setting Up Apache Storm in Multi-Node Cluster

Chapter 7 : Implementing StreamGroupings in Apache Storm

Introduction

Implementing ShuffleGrouping

Implementing FieldGrouping

Implementing AllGrouping

Implementing CustomGrouping

Implementing DirectGrouping

Chapter 8 : Integrating Hadoop with Apache Storm

Introduction

Writing a HDFS Bolt

Chapter 9 : Understanding and Implementing Tridents in Apache Storm

Introduction

Building Topology Using Trident

Understand and Implement Map, Filter, and Aggregate Function

Windowing Operations

Joining Stream Tuples in Storm

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