Course Description In this ’Apache Storm: Learn by Example’ online course, you will learn how to use Storm to build applications which need you to be highly responsive to the latest data, and react within seconds and minutes, such as finding the latest trending topics on Twitter, or monitoring spikes in payment gateway failures. Supplemental material included!Storm is to real-time stream processing what Hadoop is to batch processing. From simple data transformations to applying machine learning algorithms on the fly, Storm can do it all.What’s covered in this Apache Storm: Learn by Example online training course? Understanding Spouts and Bolts, which are the building blocks of every Storm topology Running a Storm topology in the local mode and in the remote mode Parallelizing data processing within a topology using different grouping strategies: Shuffle grouping, Fields grouping, Direct grouping, All grouping, Custom grouping Managing reliability and fault-tolerance within Spouts and Bolts Performing complex transformations on the fly using the Trident topology: Map, Filter, Windowing, and Partitioning operations Applying ML algorithms on the fly using libraries like Trident-ML and Storm-R What are the requirements? Experience in Java programming and familiarity with using Java frameworks A Java IDE such as IntelliJ Idea should be installed What am I going to get from this course? Build a Storm Topology for processing data Manage reliability and fault tolerance of the topology Control parallelism using different grouping strategies Perform complex transformations using Trident Apply Machine Learning algorithms on the fly in Storm applications What is the target audience? Engineers looking to set up end-to-end data processing pipelines that react to changes in real time Folks familiar with Batch processing technologies like Hadoop who want to learn more about Stream processing Example Video Course Outline Chapter 01: You, This Course, and Us 02:06 Introduction Chapter 02: Stream Processing with Storm 25:29 How does Twitter compute Trends? Improving Performance using Distributed Processing Building blocks of Storm Topologies Adding Parallelism in a Storm Topology Components of a Storm Cluster Chapter 03: Implementing a Hello World Topology 25:20 A Simple Hello World Topology Ex 1: Implementing a Spout Ex 1: Implementing a Bolt Ex 1: Submitting the Topology Chapter 04: Processing Data using Files 34:08 Ex 2: Reading Data from a File Representing Data using Tuples Ex 3: Accessing data from Tuples Ex 4: Writing Data to a File Chapter 05: Running a Topology in the Remote Mode 14:42 Setting up a Storm Cluster Ex 5: Submitting a topology to the Storm Cluster Chapter 06: Adding Parallelism to a Storm Topology 24:36 Ex 6 : Shuffle Grouping Ex 7: Fields Grouping Ex 8: All Grouping Ex 9: Custom Grouping Ex 10: Direct Grouping Chapter 07: Building a Word Count Topology 10:04 Ex 11: Building a Word Count Topology Chapter 08: Remote Procedure Calls Using Storm 12:48 Ex 12: A Storm Topology for DRPC calls Chapter 09: Managing Reliability of Topologies 10:31 Ex 13: Managing Failures in Spouts Chapter 10: Integrating Storm with Different Sources/Sinks 15:33 Ex 14: Implementing a Twitter Spout Ex 15: Using a HDFS Bolt Chapter 11: Using the Storm Multilang Protocol 08:24 Ex 16: Building a Storm Topology using Python Chapter 12: Complex Transformations using Trident 01:00:05 Ex 17: Building a basic Trident Topology rs Classifier Ex 18: Implementing a Map Function Ex 19: Implementing a Filter Function Ex 20: Aggregating data Classifiers Ex 21: Understanding States Ex 21: Understanding States Ex 23: Joining data streams Ex 24: Building a Twitter Hashtag Extractor PACKAGE INCLUDES: Length of Subscription: 12 Months Online On-Demand Access Running Time: 4 hrs 4 min Platform: Windows andamp; MAC OS Level: Beginner to Advanced Project Files: Included Learn anytime, anywhere, at home or on the go. Stream your training via the internet, or download to your computer and supported mobile device, including iPad, iPhone, iPod Touch and most Android devices. Need to train your Team? Contact Us for Discounts on Multiple Subscription Purchases.