- AddressRavi Nagar Square, Nagpur.
- Emailinfo@grrasnagpur.in
- Contact No.+91 99759 98226
-
What's App No.+91 99759 98226
What's App No.+91 99759 98226
As the world is growing Digital, which leads us to large datasets called Big data and for processing and storing this large datasets is a new challenge. For that, one should have skills to analysis the data so there is growing trend for Big data analytics and Hadoop professional who have a good understanding of structured, unstructured, complex data and have skills to use Hadoop Technology for storing and processing Big Data.
Hadoop is an open source, smooth and easy-to-use Apache tool designed to store data, runs application on clusters and is been written in JAVA. Big Data is collection of voluminous and complex data sets that cannot be processed using traditional computer technologies. In this course we learn the Hadoop ecosystem components such as HDFS, Pig, Map reduce, yarn, impala, Hbase, Apache spark etc. which helps in Big Data processing.
| Tracks | Regular Track | Full day (Fastrack) |
|---|---|---|
| Training Duration | 32 hours | 32 hours |
| Training Days | 16 days | 5 days |
- 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 Cassandra
- Project 1: Deploying Hadoop multi node cluster and deploying application and integrated for managing big data challenge.
Technology used : Redhat Linux, Apache Hadoop, Cluster management with backend storage, python programming, Mysql BackEnd Database.
Project 2: Deployment of Apache hadoop cluster and Managing Distributed application and Jobs scheduling in Automation.
Technology used: Redhat Linux, Apache Hadoop, hive, pig, Sqoop, flume, Python programming, shell script
- This is the best job in Hadoop, big Data Engineer develop, maintain, test and evaluate big data solutions with in organisations. He builds large scale data processing systems.
- Hadoop developers are basically software programmers but working in the Big data Hadoop domain. They are masters of computer procedural languages.
- Technical managers work with the departmental managers to ensure their team’s technological developments align with the company's goals.They are also known as information systems (CIS) managers
- A lead data engineer, will lead a team to architect a big data platform that is real time, stable and scalable to support data analytics, reporting data.
- Hadoop administrator is responsible for ongoing administration of hadoop infrastructure, Aligning with the systems engineering team to propose and deploy new hardware and software environment required for Hadoop and to expand existing environments.
- Placement Assistance
- Live Project Assessment
- Lifetime Career Support
- Lifetime Training Membership (Candidate can join same course again for purpose of revision and update at free of cost at our any center in India or you can solve your query by online help)
- Hadoop Based Exam Scenario Preparation Included IN Training
