Apache Hadoop & Big Data Certification Training

Live Online & Classroom Training/Tutorial

Become a master of Big Data and Hadoop by learning HDFS, Hadoop Administration & Maitenance, Job Scheduling, Map Reduce, Into Hive, Hbase, Flume, Sqoop, Oozie & Pig in Big Data Hadoop Tutorial/Training & Certification.

(4.9) 675 Learners
Instructed by Jaymin
INDIA

No Public/Open-house class on the topic scheduled at the moment!

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Course Description

Overview

Apache Hadoop the open source data management software that helps organizations analyze massive volumes of structured and unstructured data is a very hot topic across the tech industry. This course enables you to use this technology and to become industry ready. Out of attending this course a developer\/architect can use Apache Hadoop with full confidence.

Objective

In this course, the partcipants will learn:

  • What is Big Data
  • What is Hadoop and why is it important
  • Hadoop Distributed File System (HDFS)
  • Hadoop Deployment
  • Hadoop Administration and Maintenance
  • Map-Reduce
  • Hive, Hbase, Flume, Sqoop, Oozie and Pig

Suggested Audience:

Developers, Architects, System Engineers

Duration - 3 Days

Prerequisites

Some programing and database experience

Course Curriculum

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  • Which data is called as BigData
  • What are business use cases for BigData
  • BigData requirement for traditional Data warehousing and BI space
  • BigData solutions
  • The amount of data processing in today's life
  • What Hadoop is why it is important
  • Hadoop comparison with traditional systems
  • Hadoop history
  • Hadoop main components and architecture
  • HDFS overview and design
  • HDFS architecture
  • HDFS file storage
  • Component failures and recoveries
  • Block placement
  • Balancing the Hadoop cluster
  • Different Hadoop deployment types
  • Hadoop distribution options
  • Hadoop competitors
  • Hadoop installation procedure
  • Distributed cluster architecture
  • Lab: Hadoop Installation
  • Ways of accessing data in HDFS
  • Common HDFS operations and commands
  • Different HDFS commands
  • Internals of a file read in HDFS
  • Data copying with 'distcp'
  • Lab: Working with HDFS
  • Hadoop configuration overview and important configuration file
  • Configuration parameters and values
  • HDFS parameters
  • MapReduce parameters
  • Hadoop environment setup
  • 'Include' and 'Exclude' configuration files
  • Lab: MapReduce Performance Tuning
  • Namenode/Datanode directory structures and files
  • Filesystem image and Edit log
  • The Checkpoint Procedure
  • Namenode failure and recovery procedure
  • Safe Mode
  • Metadata and Data backup
  • Potential problems and solutions / What to look for
  • Adding and removing nodes
  • Lab: MapReduce Filesystem Recovery
  • How to schedule Hadoop Jobs on the same cluster
  • Default Hadoop FIFO Schedule
  • Fair Scheduler and its configuration
  • What MapReduce is and why it is popular
  • The Big Picture of the MapReduce
  • MapReduce process and terminology
  • MapReduce components failures and recoveries
  • Working with MapReduce
  • Lab: Working with MapReduce
  • Java MapReduce implementation
  • Map() and Reduce() methods
  • Java MapReduce calling code
  • Lab: Programming Word Count
  • Default Input and Output formats
  • Sequence File structure
  • Sequence File Input and Output formats
  • Sequence File access via Java API and HDS
  • MapFile
  • Lab: Input Format
  • Lab: Format Conversion
  • Joining Data Sets in MapReduce Jobs
  • How to write a Map-Side Join
  • How to write a Reduce-Side Join
  • MapReduce Counters
  • Built-in and user-defined counters
  • Retrieving MapReduce counters
  • Lab: Map-Side Join
  • Lab: Reduce-Side Join
  • Hive as a data warehouse infrastructure
  • Hbase as the Hadoop Database
  • Using Pig as a scripting language for Hadoop
  • How different organizations use Hadoop cluster in their infrastructure

Certification

SpringPeople works with top industry experts to identify the leading certification bodies on different technologies - which are well respected in the industry and globally accepted as clear evidence of a professional’s “proven” expertise in the technology. As such, these certification are a high value-add to the CVs and can give a massive boost to professionals in their career/professional growth.

Our certification courses are fully aligned to these high-profile certification exams; at the end of the course, participants will have detailed knowledge, be eligible and be fully ready take up these certification exams and pass with flying colours.

 

Resources

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This class is intended for participants with some prior exposure to the technology and are now looking to build up their expertise on the topic.

On successful completion of the course, participants will be eligible to sit of the related certification exam (see course overview). All participants receive a course completion certificate, demonstrating their expertise on the subject.

Total duration of the online, live instructor led sessions. Sessions are typically delivered as short lectures (2-hrs weekdays/3-hrs weekends) and detailed hands-on guidance.

Expected offline lab work hours that participants will need to complete and submit to the trainer, during and after the instructor-led online sessions.

  1. We are happy to refund full fee paid - no questions asked - should you feel that the training is not up to your expectations.
  2. Our dedicated team of expert training enablement advisors are available on email, phone and chat to assist you with your queries.
  3. All courseware, including session recordings, will always be available to access to you for future reference and rework.

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