Hadoop Big data Training course institute in Bangalore

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About Big Data Hadoop Training in Bangalore Marathahalli Rajajinagar BTM

Hadoop is an Apache project to store & process Big Data. Hadoop stores large chunk of data called Big Data in a distributed & fault tolerant manner over commodity hardware. After storing, Hadoop tools are used to perform data processing over HDFS (Hadoop Distributed File System).

As companies over time have realized the benefits of Big Data Analytics, there is a huge demand for Big Data & Hadoop professionals. Companies are in search of Big data & Hadoop professionals with the knowledge of Hadoop Ecosystem and best practices about HDFS, MapReduce, Spark, HBase, Hive, Pig, Oozie, Sqoop& Flume.

What are the course objectives of Big Data Hadoop training in Bangalore?

Big Data Hadoop Training is designed by our industry experts to make you a Certified Big Data Practitioner. The Big Data Hadoop course offers the following:

  • Complete knowledge of Big Data and Hadoop including HDFS (Hadoop Distributed File System), YARN (Yet Another Resource Negotiator) and MapReduce
  • Comprehensive knowledge of various tools that is a part of Hadoop Ecosystem like Pig, Hive, Sqoop, Flume, Oozie, and HBase
  • Capability to ingest data in HDFS using Sqoop and Flume, and analyze those large datasets stored in the HDFS.
  • The exposure to many real world industry-based projects which will be executed in CloudLab
  • Projects which are very diverse i.e. different from each other covering various data sets from multiple domains such as banking, telecommunication, social media, insurance, and e-commerce.

Who should attend Big Data Hadoop training Course?

It is best suited for:

  • Engineering Fresher
  • Software Developers, Project Managers
  • Software Architects
  • ETL and Data Warehousing Professionals
  • Data Engineers
  • Data Analysts & Business Intelligence Professionals
  • DBAs and DB professionals
  • Senior IT Professionals
  • Testing professionals
  • Mainframe professionals
  • Graduates looking to build a career in Big Data domain.

How will Big Data Hadoop Training from Apponix help your career?

These predictions will help you in understanding the growth of Big Data:

  • Hadoop Market is expected to reach $99.31B by 2022 at a CAGR of 43%
  • McKinsey predicts that by 2018 there will be a shortage of 1.6M data experts
  • Average Salary of Big Data Hadoop Developers is $96k
  • All our Big data trainers have min 7 years industry experience
  • Our Big Data training course is designed to meet present & future industry requirements
  • We provide an excellent lab facility with live projects
  • All our Big data trainers have min 7 years industry experience
  • Our Big Data training course is designed to meet present & future industry requirements
  • We provide an excellent lab facility with live projects

What are the skills that you will be learning with our Big Data Hadoop Training?

Big Data Hadoop Training will help you to become a Big Data professional. It will offer you comprehensive knowledge on Hadoop framework, and the required hands-on experience for solving real-time industry-based Big Data projects. During Big Data Hadoop course you will be trained by our trainers to:

  • Understand the concepts of HDFS (Hadoop Distributed File System), YARN (Yet Another Resource Negotiator), & understand to work with Hadoop storage & resource management.
  • Understand MapReduce Framework
  • Implement complex business solution using MapReduce
  • Learn data ingestion techniques using Sqoop and Flume
  • Perform ETL operations and data analytics using Pig and Hive
  • Implementing, partitioning, bucketing and Indexing in Hive
  • Understand HBase, i.e a NoSQL Database in Hadoop, HBase Architecture & Mechanisms
  • Integrate HBase with Hive
  • Schedule jobs using Oozie
  • Implement best practices for Hadoop development
  • Understand Apache Spark and its Ecosystem
  • Learn to work with RDD in Apache Spark
  • Work on real world Big Data Analytics Project
  • Work on a real-time Hadoop cluster

What are the pre-requisites for Hadoop Training Course?

There are no such prerequisites requiredfor Big Data Hadoop Course. Prior knowledge of Core Java and SQL will be helpful but not mandatory. Further, to brush up your skills, we will offer you a complimentary self-paced course on “Java essentials for Hadoop” when you enroll for the Big Data Hadoop Course at Apponix.

Hadoop (1.x / 2.x) Course Content

Module 1: Hadoop Introduction
  1. Introduction to Data and System
  2. Types of Data
  3. Traditional way of dealing large data and its problems
  4. Types of Systems & Scaling
  5. What is Big Data
  6. Challenges in Big Data
  7. Challenges in Traditional Application
  8. New Requirements
  9. What is Hadoop? Why Hadoop?
  10. Brief history of Hadoop
  11. Features of Hadoop
  12. Hadoop and RDBMS
  13. Hadoop Ecosystem’s overview
Module 2: Hadoop Installation
  1. Installation in detail
  2. Creating Ubuntu image in VMware
  3. Downloading Hadoop
  4. Installing SSH
  5. Configuring Hadoop, HDFS & MapReduce
  6. Download, Installation & Configuration Hive
  7. Download, Installation & Configuration Pig
  8. Download, Installation & Configuration Sqoop
  9. Download, Installation & Configuration Hive
  10. Configuring Hadoop in Different Modes
Module 3: Hadoop Distribute File System (HDFS)
  1. File System - Concepts
  2. Blocks
  3. Replication Factor
  4. Version File
  5. Safe mode
  6. Namespace IDs
  7. Purpose of Name Node
  8. Purpose of Data Node
  9. Purpose of Secondary Name Node
  10. Purpose of Job Tracker
  11. Purpose of Task Tracker
  12. HDFS Shell Commands – copy, delete, create directories etc.
  13. Reading and Writing in HDFS
  14. Difference of Unix Commands and HDFS commands
  15. Hadoop Admin Commands
  16. Hands on exercise with Unix and HDFS commands
  17. Read / Write in HDFS – Internal Process between Client, NameNode & DataNodes
  18. Accessing HDFS using Java API
  19. Various Ways of Accessing HDFS
  20. Understanding HDFS Java classes and methods
  21. Commissioning / DeCommissioning DataNode
  22. Balancer
  23. Replication Policy
  24. Network Distance / Topology Script
Module 4: Map Reduce Programming
  1. About MapReduce
  2. Understanding block and input splits
  3. MapReduce Data types
  4. Understanding Writable
  5. Data Flow in MapReduce Application
  6. Understanding MapReduce problem on datasets
  7. MapReduce and Functional Programming
  8. Writing MapReduce Application
  9. Understanding Mapper function
  10. Understanding Reducer Function
  11. Understanding Driver
  12. Usage of Combiner
  13. Usage of Distributed Cache
  14. Passing the parameters to mapper and reducer
  15. Analysing the Results
  16. Log files
  17. Input Formats and Output Formats
  18. Counters, Skipping Bad and unwanted Records
  19. Writing Join’s in MapReduce with 2 Input files. Join Types
  20. Execute MapReduce Job - Insights
  21. Exercise’s on MapReduce
Module 5: Hive
  1. Hive concepts
  2. Hive architecture
  3. Install and configure hive on cluster
  4. Different type of tables in hive
  5. Hive library functions
  6. Buckets
  7. Partitions
  8. Joins in hive
  9. Inner joins
  10. Outer Joins
  11. Hive UDF
  12. Hive Query Language
Module 6: PIG
  1. Pig basics
  2. Install and configure PIG on a cluster
  3. PIG Library functions
  4. Pig Vs Hive
  5. Write sample Pig Latin scripts
  6. Modes of running PIG
  7. Running in Grunt shell
  8. Running as Java program
  9. PIG UDFs
Module 7: Sqoop
  1. Install and configure Sqoop on cluster
  2. Connecting to RDBMS
  3. Installing Mysql
  4. Import data from Mysql to hive
  5. Export data to Mysql
  6. Internal mechanism of import/export
Module 8: HBase
  1. HBase concepts
  2. HBase architecture
  3. Region server architecture
  4. File storage architecture
  5. HBase basics
  6. Column access
  7. Scans
  8. HBase use cases
  9. Install and configure HBase on a multi node cluster
  10. Create database, Develop and run sample applications
  11. Access data stored in HBase using Java API
  12. Map Reduce client to access the HBase data
Module 9: YARN
  1. Resource Manager (RM)
  2. Node Manager (NM)
  3. Application Master (AM)

Apponix Hadoop Big data Training locations in Bangalore

  • Hadoop Big data Training in Vijay Nagar
  • Hadoop Big data Training in Malleshwaram
  • Hadoop Big data Training in Mattikere
  • Hadoop Big data Training in BTM Layout
  • Hadoop Big data Training in Jayanagar
  • Hadoop Big data Training in M G Road
  • Hadoop Big data Training in Marathahalli
  • Hadoop Big data Training in Jayanagar
  • Hadoop Big data Training in Rajaji Nagar
  • Hadoop Big data Training in Indira Nagar
  • Hadoop Big data Training in Koramangala
  • Hadoop Big data Training in Hebbal
  • Hadoop Big data Training in Banashankari
  • Hadoop Big data Training in Ulsoor
  • Hadoop Big data Training in Basavanagudi