Big Data Hadoop

Course Schedule

Enroll Date Week Timings Mode Cost
Mar 1 2020 Sunday 08:30 PM EDT Live Demo Free
Would you like to make your own schedule? Reschedule

Course Description

Big data Hadoop framework has many applications where the data is analyzed in big volumes. Hadoop is written in Java programming language. As the future scope of Big data Hadoop is high, it is used in social networking platforms like Facebook, Yahoo, Google, Linkedin, Twitter and etc. 

Hachion’s Big Data Hadoop tutorial is well prepared by skilled trainers for the beginners, middle-level, and professionals to expert with in-depth information. Basic and advanced topics are also included in the course syllabus to enhance your professional skills. Our Big Data Hadoop training will give practical knowledge on HDFS, MapReduce, Hbase, Hive, Pig, Yarn, Oozie, Flume and Sqoop concepts using real-time applications like retail, social media, aviation, tourism, finance domain.

Course Content

  • Big Data

  • Limitations and Solutions of existing Data Analytics Architecture

  • Hadoop

  • Hadoop Features

  • Hadoop Ecosystem

  • Hadoop 2.x core components

  • Hadoop Storage: HDFS

  • Hadoop Processing: MapReduce Framework

  • Hadoop Different Distributions

  • Hadoop 2.x Cluster Architecture - Federation and High Availability

  • A Typical Production Hadoop Cluster

  • Hadoop Cluster Modes

  • Common Hadoop Shell Commands

  • Hadoop 2.x Configuration Files

  • Single node cluster and Multi node cluster set up Hadoop Administration

  • MapReduce Use Cases

  • Traditional way Vs MapReduce way

  • Why MapReduce

  • Hadoop 2.x MapReduce Architecture

  • Hadoop 2.x MapReduce Components

  • YARN MR Application Execution Flow

  • YARN Workflow

  • Anatomy of MapReduce Program

  • Demo on MapReduce

  • Input Splits

  • Relation between Input Splits and HDFS Blocks

  • MapReduce: Combiner & Partitioner

  • Demo on de-identifying Health Care Data set

  • Demo on Weather Data set

  • Counters

  • Distributed Cache

  • MRunit

  • Reduce Join

  • Custom Input Format

  • Sequence Input Format

  • Xml file Parsing using MapReduce

  • About Pig

  • MapReduce Vs Pig

  • Pig Use Cases

  • Programming Structure in Pig

  • Pig Running Modes

  • Pig components

  • Pig Execution

  • Pig Latin Program

  • Data Models in Pig

  • Pig Data Types

  • Shell and Utility Commands

  • Pig Latin : Relational Operators

  • File Loaders, Group Operator

  • COGROUP Operator

  • Joins and COGROUP

  • Union

  • Diagnostic Operators

  • Specialized joins in Pig

  • Built In Functions ( Eval Function, Load and Store Functions, Math function, String Function, Date Function, Pig UDF, Piggybank, Parameter Substitution ( PIG macros and Pig Parameter substitution )

  • Pig Streaming

  • Testing Pig scripts with Punit

  • Aviation use case in PIG

  • Pig Demo on Healthcare Data set

  • Hive Background

  • Hive Use Case

  • About Hive

  • Hive Vs Pig

  • Hive Architecture and Components

  • Metastore in Hive

  • Limitations of Hive

  • Comparison with Traditional Database

  • Hive Data Types and Data Models

  • Partitions and Buckets

  • Hive Tables(Managed Tables and External Tables)

  • Importing Data

  • Querying Data

  • Managing Output

  • Hive Script

  • Hive UDF

  • Retail use case in Hive

  • Hive Demo on Healthcare Data set

  • Chapter 7:Advanced Hive and HBase

  • Hive QL: Joining Tables

  • Dynamic Partitioning

  • Custom Map/Reduce Scripts

  • Hive Indexes and views Hive query optimizers

  • Hive : Thrift Server, User Defined Functions

  • HBase: Introduction to NoSQL Databases and HBase

  • HBase v/s RDBMS

  • HBase Components

  • HBase Architecture

  • Run Modes & Configuration

  • HBase Cluster Deployment

  • Chapter 8:Advanced HBase

  • HBase Data Model

  • HBase Shell

  • HBase Client API

  • Data Loading Techniques

  • ZooKeeper Data Model

  • Zookeeper Service

  • Zookeeper

  • Demos on Bulk Loading

  • Getting and Inserting Data

  • Filters in HBase

  • Spark Introduction   
  • Spark Architecture   
  • Spark RDD’s
  • Spark Components( Streaming and Spark SQL)   
  • Programming in Spark + Spark Streaming
  • Sqoop Installation
  • Import Data.(Full table, Only Subset, Target Directory, protecting Password, file format other than CSV, Compressing, Control Parallelism,  All tables Import)
  • Incremental  Import(Import only New data, Last Imported data, storing Password in Metastore, Sharing Metastore between Sqoop Clients)
  • Free Form Query Import
  • Export data to RDBMS,HIVE and HBASE
  • Hands on Exercises
  • What is Apache Spark

  • Spark Ecosystem

  • Spark Components

  • History of Spark and Spark Versions/Releases

  • Spark a Polyglot

  • What is Scala?

  • Why Scala?

  • SparkContext

  • RDD

  • Flume and Sqoop Demo

  • Oozie

  • Oozie Components

  • Oozie Workflow

  • Scheduling with Oozie

  • Demo on Oozie Workflow

  • Oozie Co-ordinator

  • Oozie Commands

  • Oozie Web Console

  • Oozie for MapReduce

  • PIG

  • Hive, and Sqoop

  • Combine flow of MR

  • PIG

  • Hive in Oozie

  • Hadoop Project Demo

  • Hadoop Integration with Talend

Big Data Hadoop Training FAQs

Big Data Hadoop training is one of the most sought after in the industry and has helped thousands of Big Data professionals around the globe bag top jobs in the industry. Big Data & Hadoop Market is expected to exponential growth by 2022.
Detailed Architecture Discussion of Apache Hadoop and Map Reduce Detailed coverage (Basic + Advanced) of the Hadoop Ecosystem components like Hive, Pig,SQOOP, Flume, HBase,Oozie etc. Provides In-depth Knowledge in Spark and Scala The detailed description of Integration of various Ecosystem components with Hadoop and the integration of components among each other. Description of the Implementation of Hadoop Best Practices Performance Tuning techniques Real-time Design discussions A fully hands-on based training approach
According to The Survey Conducted by PayScale, The average annual pay for a Big Data Hadoop Developer is $122,208 a year.
Qualifying a Hadoop certification makes the professionals represent their expertise and skills to the employers, peers, and customers.We Provide Complete Support In Acquiring Hadoop Certification.However, which one you should choose that solely depends on your personal needs, organizational requirements, Hadoop certification cost, and its validity for a specific vendor: Cloudera Certified Administrator for Hadoop (CCAH) Cloudera Certified Hadoop Developer (CCDH) Hortonworks Certified Apache Hadoop Developer (HCAHD) Hortonworks Certified Apache Hadoop Administrator (HCAHA) MapR Certified Hadoop Developer (MCHD) MapR Certified Hadoop Administrator (MCHA) MapR Certified HBase Developer (MCHBD) IBM Hadoop Certification
As such, there are no pre-requisites for learning Hadoop. Knowledge of Core Java and SQL will be beneficial, but certainly not a mandate.
We Provide 100% Placement Assistance Who completed Course with us.

We offer three modes of Training in Tableau Online Training Program.

  • Self Placed
  • Mentorship
  • Instructor-Led

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Big Data Hadoop Certificate

After completion of the Big Data Hadoop online training program, candidates will get the course completion certification.

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