Hadoop is 100% open source Java‐based programming framework that supports the processing of large data sets in a distributed computing environment. To process and store the data, It utilises inexpensive, industry‐standard servers. The key features of Hadoop are Cost effective system, Scalability, Parallel processing of distributed data, Data locality optimisation, Automatic failover management and supports large clusters of nodes.
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- Flexible Instalment Plans for all the courses, according to your need. (Click here to contact us and get free quote and consultation about study programs).
- Free Project experience.( Click here for More Information)
- Highly experienced trainers (Get courses from our tutors with years of industry and academic experience, gained at high technical support during and after completion of your training.)
- Free Certification Preparation Material.
- Free Up to Date Courses Material.
- Online/ On-Site/ Class room/ and Customised One to One training
- Full flexibility regarding study timing.
- Full training support from start to finish (CV review according to required industry standards, one to one advice and personal training).
- Guaranteed success.
- Job focused approach.
Hadoop Administration training course from Jenrac technologies provides participants expertise in all the steps necessary to operate and maintain a Hadoop cluster, i.e. From Planning, Installation and Configuration through load balancing, Security and Tuning Jenrac training course will provide hands-on preparation for the real-world challenges faced by Hadoop administrators.The course curriculum follows Apache Hadoop distribution.
During the Hadoop Administration Online training, you'll master:
i) Hadoop Architecture, HDFS, Hadoop Cluster and Hadoop Administrator's role
ii) Plan and Deploy a Hadoop Cluster
iii) Load Data and Run Applications
iv) Configuration and Performance Tuning
v) How to Manage, Maintain, Monitor and Troubleshoot a Hadoop Cluster
vi) Cluster Security, Backup and Recovery
vii) Insights on Hadoop 2.0, Name Node High Availability, HDFS Federation, YARN, MapReduce v2
viii) Oozie, Hcatalog/Hive, and HBase Administration and Hands-On Project
This course requires a basic knowledge in Linux/ Unix Bash commands or any programming languages like Java/ Python. How ever we explain linux basic commands so poeple with nill knowledge in big data can also learn this course with out any hurdles.
Classroom Training: An Instructor led training in our dynamic learning environment based in our office at West London. The classroom is fitted with all the essential amenities needed to ensure a comfortable training experience and with this training you will have an opportunity to build a Networking with other learners, share experiences and develop social interaction.
Online: Unlike most organisations our online based training is a tutor led training system similar to the classroom based training in every given aspect making it more convenient to the students from any location around the world and also cost effective.
Onsite: This training is specifically made for the Corporate clients who wish to train their staff in different technologies. The clients are given an opportunity where they can tailor the duration of course according to their requirements and the training can be delivered in house/ at your location of choice or online.
Customised one to one: A tailored course for students looking for undeterred attention from the tutor at all the times. The duration of course and contents of the course are specifically customised to suite the students requirements. In addition to it the timings of the trainings can also be customised based on the availability of both the tutor as well as the student.
• What is Big data
• How is it Evolved
• Four Dimensions (Four V's of big data)
• Use cases of big data
• Different Tools to process big data
• What is Hadoop ?
• Why learn Hadoop ?
• Relational Databases Versace 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
• What is Map Reduce?
• Map Reduce Use cases?
• Map Reducing Functionalities
• Importance of Map Reduce in Hadoop?
• Processing Daemons of Hadoop
» Job Tracker
» Task Tracker
• Input Split
» Role of Input Split in Map Reduce
» InputSplit Size Vs Block Size
» InputSplit Vs Mappers
• How to write a basic Map Reduce Program
» Driver Code
» Mapper Code
» Reducer Code
• Driver Code
- Importance of Driver Code in a Map Reduce program
- How to Identify the Driver Code in Map Reduce program
- Different sections of Driver code
• Mapper Code
- Importance of Mapper Phase in Map Reduce
- How to Write a Mapper Class?
- Methods in Mapper Class
• Reducer Code
- Importance of Reduce phase in Map Reduce
- How to Write Reducer Class?
- Methods in Reducer Class
•Input and output Format's in Map Reduce
• Map Reduce API(Application Programming Interface)
- New API
- Depreciated API
• Combiner in Map Reduce
- Importance of combiner in Map Reduce
- How to use the combiner class in Map Reduce?
- Performance tradeoffs with respects to Combiner
• Partitioner in Map Reduce
- Importance of Partitioner class in Map Reduce
- How to use the Partitioner class in Map Reduce
- hash Partitioner functionality
- How to write a custom Partitioner
• Joins - in Map Reduce
- Map Side Join
- Reduce Side Join
- Performance Trade Off
• How to debug MapReduce Jobs in Local and Pseudo cluster Mode.
• Introduction to MapReduce Streaming
• Data localization in Map Reduce
• Secondary Sorting Using Map Reduce
• Job Scheduling
• How to install Cluster
• Setting up new clusters
• Single and Multi node cluster configurations
• Checking HDFS Status
• Cluster Breaking
• Copying the Data b/w Clusters
• Adding & Removing Cluster Nodes
• Rebalancing the cluster
• Name Node Metadata Backup
• Cluster Upgrading
• What is a job in Cluster
• Starting and stopping Hadoop jobs
• How to start a job in Cluster
• Monitoring HDFS status
• Adding and removing data nodes
• Managing Jobs
• The FIFO Scheduler
• The Fair Schedule
• How to stop & start jobs running on the cluster
• General System conditions to Monitor
• Name Node & Job Tracker Web Uis
• View & Manage Hadoop’s Log files
• Ganglia Monitoring Tool
• Common cluster issues & their resolutions
• Benchmark your cluster’s performance
• How to use Sqoop to import data from RDBMSs to HDFS
• How to gather logs from multiple systems using Flume
• Features of Hive, Hbase & Pig
• How to populate HDFS from external Sources
Lesson 09 -
We give students our top priority and always ensure that every student is given the best possible training. In order to provide the best training, all our training modes have been made interactive sessions. Out of all the 4 training modes, the students are given an opportunity to choose a mode of training depending on their requirements. Different training methods have been introduced for individuals as well as for corporates. Unlike most of the online trainings today, Our Online trainings are interactive sessions and are similar to our classroom trainings. The student will be connecting to our Live virtual classroom where they will be able interact with the trainer.
We at Jenrac Technologies have a unique methodology & approach for our corporate clients. If you are a corporate & looking to train your team. You can contact us over the phone and talk to one of our expert customer service representative. Our customer service representatives are trained and qualified to answer all of your queries right away. You can also fill the contact us form on the side and we will arrange a meeting for you in your premises with one of our expert. We will visit you in person and can explain you in depth about our training programmes, structure and fees.
We provide one of the best professional trainings within SAP in the industry. The courses are run by experts with ample industry experience on this subject matter. The course run are well up to professional standards with the latest industry updates. Contact our team at Jenrac Technologies for all your queries.