Hands on big data streaming with Apache Storm

BY
Udemy

Become proficient in the strategies and methods used by Apache Storm for big data streaming.

Mode

Online

Fees

₹ 799

Quick Facts

particular details
Medium of instructions English
Mode of learning Self study
Mode of Delivery Video and Text Based

Course overview

Big data streaming is a methodology that efficiently processes large amounts of data to produce insightful information. The data in movement is the information that is processed. Big data streaming is preferably a speed-focused technique that processes data in a steady flow. Ganapathi Devappa, a Cloud & Big Data Specialist, created the Hands-on big data streaming with Apache Storm online certification, which is provided through Udemy.

Hands-on big data streaming with Apache Storm online course provides 6 hours of in-depth video lectures that are supplemented by 9 articles and 8 downloadable materials, which is designed for learners who wish to get the knowledge necessary to build stream processing apps using Apache Storm. Hands-on big data streaming with Apache Storm online classes put a strong emphasis on teaching learners how to write Apache Storm programs in Java and interfaces for obtaining data from Twitter and tools such as Kafka, processing it in Storm, and saving it to tables in Cassandra or documents in HDFS.

The highlights

  • Certificate of completion
  • Self-paced course
  • 6 hours of pre-recorded video content
  • 9 articles
  • 8 downloadable resources

Program offerings

  • Online course
  • Learning resources
  • 30-day money-back guarantee
  • Unlimited access
  • Accessible on mobile devices and tv

Course and certificate fees

Fees information
₹ 799
certificate availability

Yes

certificate providing authority

Udemy

What you will learn

Software development skills Knowledge of big data Knowledge of kafka

After completing the Hands-on big data streaming with Apache Storm certification course, learners will acquire the knowledge of the functionalities of big data and Apache storm associated with data streaming and developing applications. Learners will explore the strategies involved with data analytics and data streaming, distributed stream processing, state stream processing, and exactly once processing. Learners will study about functionalities of Twitter, Kafka, HDFS, and Cassandra for real-time data streaming.

The syllabus

Introduction

  • Introduction
  • Course prerequisites
  • Course Structure
  • Data Sizes in Big Data
  • Big Data Problem
  • Traditional Solution
  • Big Data Solution
  • Download the training programs
  • Download the Eclipse projects
  • Demo and practice activity: Install Eclipse
  • Import training projects into Eclipse
  • Demo and practice activity: Create a maven project in Eclipse
  • Demo and practice activity: Add Apache Storm programs to Eclipse project
  • Demo and practice activity: compile the Storm program in Eclipse
  • Demo and practice activity: Run the Apache Storm program
  • Summary

Introduction to Apache Storm

  • Agenda
  • Storm Features
  • Zookeeper
  • Storm Architecture
  • Storm Data Model
  • Storm Topology
  • A simple example of Storm Topology
  • Demo and Practice Activity: Create a simple Apache Storm program
  • Storm Topology: Case Study 1
  • Demo and practice activity: Implement the case study solution
  • Storm Topology: Case Study 2
  • Demo and practice activity: Implement the case study 2 solution
  • Tick Tuples
  • Demo and practice activity: Implement periodic processing using Tick Tuples
  • Summary
  • Practice Activities: Create the programs for five practice activities

Storm Installation and Configuration

  • Agenda
  • Setting up Storm Environment
  • Setting up Zookeeper for Storm
  • Storm Download
  • Starting Storm Servers
  • Demo and practice activity: Start Storm Servers
  • Submitting a job to Storm
  • Demo and practice activity: Create a thin jar in Eclipse
  • Demo and practice activity: Create a fat jar in Eclipse
  • Demo and practice activity: Submit a jar to Storm cluster
  • Storm Topology User Interface
  • Demo and practice activity: Storm UI and kill a Storm Topology
  • Using Eclipse for Storm Programs
  • Setting up Multi-node Storm Cluster
  • Summary
  • Practice Activities: Create the programs for five practice activities

Storm Classes & Groupings

  • Agenda
  • Bolt Parallelism
  • Stream Grouping
  • Tuple Classes
  • Spout Classes & Interfaces
  • IRichSpout Interface
  • NextTuple Method
  • Bolt Interfaces & Classes
  • Topology Classes
  • Declarer Interfaces
  • Demo and practice activity: Shuffle grouping with multiple tasks
  • Demo and practice activity: Fields grouping with multiple bolts
  • Reliable Processing in Storm
  • Demo and practice activity: Implement reliable processing
  • Summary
  • Practice Activity

Storm Trident

  • Agenda
  • Trident Layer
  • Trident Operations
  • Case study: Trident Operations
  • Demo and Practice Activity: Implement Trident Stream Operations
  • Windowing
  • Partition Aggregate
  • General Aggregator
  • Re-partitioning Operations
  • Aggregate Operations
  • Operations on Grouped Streams
  • Trident State
  • Exactly once Processing
  • Case study: Trident State Updates
  • Demo and Practice Activity: Trident State Implementation Part 1
  • Demo and Practice Activity: Trident State Implementation Part 2
  • Demo and Practice Activity: Trident State Implementation Part 3
  • Demo and Practice Activity: Trident State Implementation Part 4
  • Demo and Practice Activity: Trident State Implementation Part 5
  • Summary
  • Practice Activity : Write the programs for the six activities

Storm Scheduling

  • Agenda
  • Storm User Interface
  • Demo: Monitor multiple topologies using user interface
  • Storm Schedulers
  • Isolation Scheduler
  • Resource Aware Scheduler
  • Resource Aware Scheduler Example
  • Default Configurations
  • Metrics Reporting
  • Configuration for Ganglia
  • Summary
  • Practice Activity

Storm External Interfaces

  • Agenda
  • Apache Kafka
  • Storm Kafka Spout Example
  • Compiling for Kafka
  • Demo and Practice Activity: Setup & start Zookeeper and Kafka servers
  • Demo and Practice Activity: Create a new topic in Kafka
  • Demo and Practice Activity: Start Kafka producer
  • Demo and Practice Activity: Storm program for interfacing with Kafka
  • Demo and Practice Activity: Message flow from Kafka to Storm
  • Cassandra
  • Setting properties for Cassandra
  • Writing to Cassandra Table
  • Real-time Data Analytics Platform
  • Demo and Practice Activity: Setup and Start Cassandra Server
  • Demo and Practice Activity: Create Keyspace and Table in Cassandra
  • Demo and Practice Activity: Kafka - Storm - Cassandra Program
  • Demo and Practice Activity: Flow of Data from Kafka to Cassandra
  • Example storing data to Hadoop HDFS
  • Demo and Practice Activity: Program to take data from Kafka and store to HDFS
  • Interfacing with Twitter
  • Setting Authorization
  • Demo and Practice Activity: Create a program for getting tweets from twitter
  • Demo and practice activity: Run the twitter program and look at live tweets
  • Summary
  • Practice Activity: Write programs for the seven activities

Conclusion

  • Conclusion, Summary and Next Steps
  • Any thing not covered
  • Course End Quiz 1
  • Course End Quiz 2
  • Course End Quiz 3
  • Course End Quiz 4

Instructors

Mr Ganapathi Devappa

Mr Ganapathi Devappa
Database Administrator
Freelancer

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