What will you learn?
When you complete Codeinfin Big Data Hadoop Administrator course this course, you’ll be able to:
- Comprehend Hadoop Architecture Hadoop Administrator’s role
- Understand HDFS, Hadoop Cluster planning and
- Understand how to Load Data and Run various Applications
- Do Configuration and Performance Fine Tuning
- Manage, Uphold and Monitor the Hadoop Cluster
- Understand Security, Backup, and data Recovery modules
- Practice on live Hands-On Project
Administrator word will become synonym for Big Data Administrator.
If you are an IT administrator of any sort be it Linux/Unix, windows, system or database, Codeinfin Big data administrator online course is for you. With the gigantic data growth Big Data Hadoop professionals will be the most sought after in next decade. At it would only be prudence on a learner part to get certified as soon as possible.
Growing demand for Hadoop Administrators:
Data size is growing with the digitalization and so are the jobs. Forbes has predicted a 42.1 CAGR growth of Big data Hadoop market by 2022. As more and more learners are rushing to get the certification still the gap between demand and supply is huge for Big data Administrator both in India and Abroad. In India beginners are paid average 6-7 lacs(Indeed.com) salaries rise exponentially as the experience grows.
Codeinfin Hadoop Administrator Courses:
Codeinfin Hadoop Administrator online course has been hand crafted by industry experts who have more than 10 years of day in day out experience on Hadoop and other technologies. They would take you through the real world challenges faced by Hadoop administrators.
- What is Big Data?
- Big Data Facts
- The Three V’s of Big Data
- What is Hadoop?
- Why learn Hadoop ?
- Relational Databases Vs. Hadoop
- Motivation for Hadoop
- 6 Key Hadoop Data Types
- What is HDFS ?
- HDFS components
- Understanding Block storage
- The Name Node
- The Data Nodes
- Data Node Failures
- HDFS Commands
- HDFS File Permissions
- Populating HDFS from External Sources
- Overview of MapReduce
- Understanding MapReduce
- The Map Phase
- The Reduce Phase
- WordCount in MapReduce
- Running MapReduce Job
- Single Node Cluster Configuration
- Multi-Node Cluster Configuration
- Cluster Maintenance
- Checking HDFS Status
- Breaking the cluster
- Copying Data Between Clusters
- Adding and Removing Cluster Nodes
- Rebalancing the cluster
- Name Node Metadata Backup
- Cluster Upgrading
- Common cluster issues and their resolutions
- Benchmark your cluster’s performance
- Cluster Monitoring, Troubleshooting, and Optimizing
- Managing Jobs
- The FIFO Scheduler
- The Fair Schedule
- How to stop and start jobs running on the cluster
- General System conditions to Monitor
- Name Node and Job Tracker Web Uis
- View and Manage Hadoop’s Log files
- Ganglia Monitoring Tool
- How to use Sqoop to import data from RDBMSs to HDFS
- How to gather logs from multiple systems using Flume
- How to populate HDFS from external Sources