Big Data - Hadoop

60 Hours
5/5

Big Data - Hadoop

Through this Hadoop training, you’ll learn to work with the flexibility on versatile frameworks based on the Apache Hadoop ecosystem, including Hadoop installation and configuration, cluster management with in-depth knowledge on Big Data and Hadoop Ecosystem tools such as HDFS, YARN, MapReduce, Hive, Pig, HBase, Spark, Scala, Zookeeper, Oozie, Flume and Sqoop.

Overview

Big data is one of the most electrifying and in-demand skills today, powering large companies such as Google and Facebook. In this course, we learn the Hadoop ecosystem modules such as HDFS, Pig, Map Reduce, yarn, impala, Hbase, Apache spark, Oozie, etc. which helps in Big Data processing. And In this hands-on Big Data training, you will implement real-life, industry-based projects using Integrated Lab.

Hadoop is an open-source software to store & process Big Data. Hadoop stores Big Data in a distributed manner over commodity hardware. After that, Hadoop tools are used to execute parallel data processing over the Hadoop Distributed File System (HDFS).

APACHE Hadoop is the latest version of Hadoop released in 2006. Hadoop market was valued around 1700 million USD in the year 2018 and by the year 2024, it is expected to be growing by 9400 million USD.

Why take Training in Bigdata Hadoop?

Big Data Hadoop training is best suited for IT, data management, and analytics professionals looking to gain expertise in Big Data, including: Software Developers and Data Management Professionals, Business Intelligence Professionals, Architects, Analytics Professionals, Senior IT professionals, testing and Mainframe Professionals, Project Managers, Aspiring Data Scientists, Graduates looking to begin a career in Big Data Analytics. Average Remuneration of Big Data Hadoop Developers is $97k.

Organizations are showing attention in Big Data and are adopting Hadoop to store & analyze it. Hence, the demand for jobs in Big Data and Hadoop is also growing speedily. If you are pursuing a career in this field, now is the right time to get started with Hadoop Training.

Curriculum

  • About BigData
  • Types of BigData
  • Sources of BigData
  • Traditional technique to manage BigData
  • Limitations of existing solutions for BigData
  • About Hadoop
  • History of Hadoop
  • Hadoop architecture
  • Hadoop components
  • Hadoop ecosystems
  • Rack awareness theory
  • Limitations of Hadoop 1.x version
  • Features of Hadoop 2.x version
  • Hadoop high availability and federation
  • Workload and Usage patterns
  • Industry recommendations
  • Hadoop cluster administrator
    • Roles
    • Responsibilities
    • Scope
    • Job Opportunities
  • Hadoop server roles and their usage
  • Hadoop installation with basic configuration
  • Deploying Hadoop in standalone mode with troubleshooting skills
  • Deploying Hadoop in pseudo-distributed mode with troubleshooting skills
  • Deploying Hadoop in multi-node Hadoop cluster with troubleshooting skills
  • Deploying YARN framework with YARN ecosystem
  • Deploying Hadoop Clients with troubleshooting skills
  • Understanding the working of HDFS and MapReduce
  • Resolving simulated problems
  • Awareness of deploying multi-node Hadoop cluster on AWS and RedHat Cloud
  • Understanding of Namenode
  • Understanding of Secondary Namenode
  • Understanding of Datanode
  • Understanding of Hadoop Distributed File System(HDFS)
  • Understanding MapReduce
  • Understanding of YARN framework
  • Working with Hadoop Distributed cluster
  • Decommissioning or Commissioning of nodes
  • Add and Remove new Hadoop clients during running Hadoop Cluster Environment
  • Monitoring of Hadoop clusters with help of Hadoop Web Interface Portal
  • Command to start Hadoop cluster setup
  • Command to stop Hadoop cluster setup
  • Command to start individual component
  • Command to stop individual component
  • Command to put data in HDFS
  • Command to get data from HDFS
  • Command to create and delete file, directory in HDFS and etc.
  • Installation and Configuration of Sqoop
  • Installation and Configuration of Flume
  • Installation and Configuration of Hive
  • Installation and Configuration of Spark
  • Installation and Configuration of Oozie
  • Installation and Configuration of Zoopkeeper
  • Installation and Configuration of Kafka
  • Installation and Configuration of Cassendra
  • About MapReduce
  • Why MapReduce?
  • History of MapReduce
  • MapReduce Use Cases
  • Work Flow of MapReduce
  • Traditional way Vs MapReduce way to analyze BigData
  • Hadoop 2.x MapReduce Architecture
  • Hadoop 2.x MapReduce Components
  • MapReduce components
    • Combiner
    • Partitioner
    • Reducer
  • Work Flow of YARN framework
  • Relation between Input Splits and HDFS Blocks
  • MapReduce Practical and Troubleshooting
  • About Hive
  • History of Hive
  • Use of Hive
  • Hive Use Case
  • Hive Vs Pig
  • Hive Architecture and Components
  • Metastore in Hive
  • Limitations of Hive
  • Traditional Database Vs Hive
  • Hive Data Types and Data Models
  • Hive Management
    • Partitions and Buckets
    • Hive Tables(Managed Tables and External Tables)
    • Importing Data
    • Querying Data
    • Managing Outputs
    • Hive Script
  • HiveQL
    • Joining Tables
    • Dynamic Partitioning
    • Custom Map/Reduce Scripts
    • Hive Indexes and views Hive query optimizers
    • Hive : User Defined Functions
  • Hive Practical and Troubleshooting
  • About Sqoop
  • Hostory of Sqoop
  • Usage and Management of sqoop with RDBMS
  • Sqoop Architecture
  • Sqoop Commands
    • Command to get data from RDBMS form HDFS
    • Command to put data in RDBMS form HDFS
  • Importance of sqoop with HDFS and RDBMS
  • Sqoop Practical and Troubleshooting
  • About Apache Spark
  • History of Spark and Spark Versions/Releases
  • Spark Architecture
  • Spark Components
  • Usage and Management of Spark with HDFS
  • Spark Practical
  • Spark Streaming
  • Spark MLlib
  • About Flume
  • History of Flume
  • Flume Architecture
  • Flume Components
  • Usage and Management of Flume
  • Data Fetching from many resources in HDFS using Flume
  • Flume Practical and Troubleshooting
  • About Oozie
  • History of Oozie
  • Oozie Architecture
  • Oozie Components
  • Oozie Work Flow
  • Scheduling with Oozie
  • Oozie with Hive, HBase, Pig, Sqoop, Flume
  • Oozie Practical and Troubleshooting
  • About Zoopkeeper
  • History of Zoopkeeper
  • Zoopkeeper components
  • Zoopkeeper Architecture
  • Usage and Importance Zoopkeeper with Hadoop
  • Management of Zoopkeeper
  • Zoopkeeper Practical and Troubleshooting
  • About Cloudera Manager
  • History of Cloudera Manager
  • Usage and Management of Cloudera Manager
  • Usage and Management of each ecosystem tool with Cloudera manager.
  • Introduction and Configuration
  • Producer API
  • Consumer API
  • Stream API
  • Connector API
  • Topics and Logs
  • Consumers and Producers
  • Kafka as messaging system
  • Kafka as a storage System
  • Kafka for Stream Processing
  • EC2
  • EMR
  • RDS & Redshift
  • Lambda
  • S3 storage
  • Elastic Search
  • Data Bricks (Azure)
  • Map-Reduce: Scripts for data mining and data transformation according to need of problem statement. Some data sets are h1b1 visa, fire incident, credit card fraud.
  • Flume: Data Streaming and Collection from twitter and various sources in various formats such as json, avro, sequence file
  • Sqoop: Data Injection from various type databases to hdfs storage using Incremental Imports.
  • Hive: Analysis of different datasets using HQL scripts (ETL jobs).Some data sets are h1b1 visa, fire incident, credit card fraud.
  • Spark: sentiment analysis of live twitter data. Data Visualization and Data Analysis on Various Data sets.
  • Data Backup & Reporting : Using oozie Job Scheduling, HQL & Spark Scripting, and sqoop scripts creating a solution for collecting data from various data sources and backing up into hdfs as well as generating and mailing analysis reports on daily basis.
  • Cloudera Hadoop Developer (CDHD)
  • Cloudera Hadoop Admin(CDHA)

Course Features

Provide Training Certificates, Internship Letter and Red Hat Participation Certificates.
Support on a daily basis and one to one support with Experienced & Certified Trainers.
 Support on a daily basis and one to one support with Experienced & Certified Trainers.
Students will get placement assistance after the summer training gets completed .
Interview preparation with Mock Interview sessions and HR Round skills will be complimentary for students .
Digital notes,assignments , Soft Copies and PDF's will be provided.
Exam prepration of respective global cetification in the course is included in the training .
Weekly test series will be conducted to enhance competitive environment.
Seminars by professionals and industry experts will be conducted to explain the live working in a company and industry standard working tools.

FAQ

Our Summer Internship modules are designed in such a way that you don’t need to have any specific prior knowledge .Whatever knowledge is required, will be delivered during the training itself. Only your enthusiasm and your will to do is required !
Students (BCA, MCA, B. Tech, M. Tech, MSc-it etc.) who want to make their careers in any IT field , want to do mandatory internship/ training prescribed under the university provisions or the one who has the will to learn and utilise summer time /lockdown time can attend this.
All the Mentors are Certified Industry Experts with vast experience in implementing real-time solutions on different queries related to different topics. They will share their personal industry experience with you while connecting with you .
No doubt , our Online Training Conduction Pattern is same as our Classroom Training pattern. Whether it is the curriculum , way of teaching , way of providing practical exposure ,assignments or projects to the students , we abide by the principle of same teaching pattern in both the training .
For sure , our concern is to pay individual attention and assistance to the students . Hence , you can feel free to ask queries , extra time , doubt solving sessions and assistance in making projects
You just need to have laptop/desktop and proper net connection so that these online training sessions can be conducted without hampering the flow of learning .Proper internet connection speed is required so that disturbance and technical glitches can be avoided during the training .
Candidates need not worry about losing any training session. They will be able to take their missing sessions in extra time by mentor. We also have a technical team to assist the candidates in case they have any query.
Before registering , you can attend one FREE WEBINAR where you can decide to join the course or not. After that, if you are enrolled/ registered in classes and/or have paid fees, but want to cancel the registration due to certain reason, it can be attained within 72 hours of initial registration. Please make a note that refunds will be processed within 30 days of prior request.
Yes, we do provide Placement Assistance with our training courses. You will get assistance in getting job references regarding particular technology and stream of IT . If you’re an undergraduate , then also you can get assistance after you are a graduate by our placement team.

You can enroll to this program following the application process mentioned here:-

Depending upon the area of interest, a candidate can opt the course.

We have limited seats; you can make the payment in the payment link which gets generated to your registered email. 

You will get E-Mail and whole the registration process there.

We do have Cash/ Card/ Paytm/ Google pay etc payment option.

You can pay your fees in installments also.

Reach out to https://grras.com/internship / 9001997178/ 9772165018 in case you do not have a provision to make an online payment or you have any query.

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