Best Hadoop Admin Training in Pune

The best thing about the way we impart Hadoop Admin Training in Pune is that it is in sync with industry standards and needs. To be specific, our offered services include Hadoop Admin Corporate Training services, Hadoop Admin Online Training as well as Hadoop Admin in Classroom training. The designing of our syllabus has been done in such a manner that all real-world requirements are efficiently met. The syllabus we offer is not just suited to advanced level students but also beginners. An important aspect of the training we provide is that it is offered on weekdays as well as weekends for the convenience of students, according to their demands.

Our aim has always been on providing One-to-One Hadoop Admin Training in Pune to make sure the trainees extract as much from the course as possible. And since we offer Hadoop Admin Training in Pune on a fast-track basis, time never surfaces as a problem. The instructors focus on imparting A-class training supported by a lot of practical examples.

Besant Technologies has many branches in Pune. Besant imparts the Best Hadoop Admin Training Courses in Pune’s Aundh and Kharadi. Our past students and those who know about us render us the Best Hadoop Admin Training Institute, which has been making people’s career brighter by imparting Certification-Oriented Hadoop Admin Training in Pune.

The training we offer for Hadoop Admin Certification in Pune is seamless for sure, considering the amount of expertise our faculties hold. With the completion of the course we provide, you will feel knowledgeable and confident to face all sorts of IT interviews. The association between the students and trainers at our coaching centres is worth taking a note of. It’s strong and friendly, and the students can engage in course related discussions as and when they feel the need. The trainees can be sure that they will get future assistance too from their trainers.

Although there are many benefits of enrolling yourself with Besant, the biggest benefit lies in the placement assistance you receive. Our dedicated HR cell helps students find jobs of their dreams. Our aim is to provide quality training at affordable prices, because of which the Hadoop Admin Training in Pune Course Fees we charge is pretty reasonable. We are the sole Hadoop Admin training institute which is capable of providing video reviews of our former students so that you can learn from them about the institute.

You will be surprised to know how many different job-positions you can choose from, after the successful completion of the Hadoop Admin course. Here are the major topics we cover under this Hadoop Admin course Syllabus Linux Basics, Bash, Ansible Git, Maven, Docker, Jenkins, and AWS.

Want to reap all the benefits of enrolling yourself with a good training institute? Join Besant Technologies right away! The Course timings and the date of commencement of the course have been dished out below-

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Hadoop Admin Training Key Features

Besant Technologies offers Hadoop Admin Training in Pune in more than 4+ branches with expert trainers. Here are the key features,

30 Hours Course Duration

100% Job Oriented Training

Industry Expert Faculties

Free Demo Class Available

Completed 500+ Batches

Certification Guidance

Authorised Partners

BDreamz Global Solutions Private Limited (Owner of Besant Technologies® Brand) is the unique Authorised Oracle Partner, Authorised Microsoft Partner, Authorised Pearson Vue Exam Center, Authorised PSI Exam Center.

Hadoop Admin Training Batch Schedule

Here are the Hadoop Admin Training Classes in Pune Schedule in our branches. If this schedule doesn't match please let us know. We will try to arrange appropriate timings based on your interest.

Hadoop Admin Training Syllabus

Module 1
Duration :06:00:00
Introduction to Big Data & Hadoop Fundamentals Goal : In this module, you will understand Big Data, the limitations of the existing solutions for Big Data problem, how Hadoop solves the Big Data problem, the common Hadoop ecosystem components, Hadoop Architecture, HDFS, Anatomy of File Write and Read, how MapReduce Framework works.
Objectives - Upon completing this Module, you should be able to understand Big Data is a term applied to data sets that cannot be captured, managed, and processed within a tolerable elapsed and specified time frame by commonly used software tools.
  • Big Data relies on volume, velocity, and variety with respect to processing.
  • Data can be divided into three types—unstructured data, semi-structured data, and structured data.
  • Big Data technology understands and navigates big data sources, analyzes unstructured data, and ingests data at a high speed.
  • Hadoop is a free, Java-based programming framework that supports the processing of large data sets in a distributed computing environment.
  Topics: Apache Hadoop
  • Introduction to Big Data & Hadoop Fundamentals
  • Dimensions of Big data
  • Type of Data generation
  • Apache ecosystem & its projects
  • Hadoop distributors
  • HDFS core concepts
  • Modes of Hadoop employment
  • HDFS Flow architecture
  • HDFS MrV1 vs. MrV2 architecture
  • Types of Data compression techniques
  • Rack topology
  • HDFS utility commands
  • Min h/w requirements for a cluster & property files changes
Module 2
Duration :03:00:00
MapReduce Framework Goal : In this module, you will understand Hadoop MapReduce framework and the working of MapReduce on data stored in HDFS. You will understand concepts like Input Splits in MapReduce, Combiner & Partitioner and Demos on MapReduce using different data sets.
Objectives - Upon completing this Module, you should be able to understand MapReduce involves processing jobs using the batch processing technique.
  • MapReduce can be done using Java programming.
  • Hadoop provides with Hadoop-examples jar file which is normally used by administrators and programmers to perform testing of the MapReduce applications.
  • MapReduce contains steps like splitting, mapping, combining, reducing, and output.
  Topics: Introduction to MapReduce
  • MapReduce Design flow
  • MapReduce Program (Job) execution
  • Types of Input formats & Output Formats
  • MapReduce Datatypes
  • Performance tuning of MapReduce jobs
  • Counters techniques
 
Module 3
Duration :03:00:00
Apache Hive Goal : This module will help you in understanding Hive concepts, Hive Data types, Loading and Querying Data in Hive, running hive scripts and Hive UDF.
Objectives - Upon completing this Module, you should be able to understand Hive is a system for managing and querying unstructured data into a structured format.
  • The various components of Hive architecture are metastore, driver, execution engine, and so on.
  • Metastore is a component that stores the system catalog and metadata about tables, columns, partitions, and so on.
  • Hive installation starts with locating the latest version of tar file and downloading it in Ubuntu system using the wget command.
  • While programming in Hive, use the show tables command to display the total number of tables.
Topics: Introduction to Hive & features
  • Hive architecture flow
  • Types of hive tables flow
  • DML/DDL commands explanation
  • Partitioning logic
  • Bucketing logic
  • Hive script execution in shell & HUE
 
Module 4
Duration :03:00:00
Apache Pig Goal : In this module, you will learn Pig, types of use case we can use Pig, tight coupling between Pig and MapReduce, and Pig Latin scripting, PIG running modes, PIG UDF, Pig Streaming, Testing PIG Scripts. Demo on healthcare dataset.
Objectives - Upon completing this Module, you should be able to understand Pig is a high-level data flow scripting language and has two major components: Runtime engine and Pig Latin language.
  • Pig runs in two execution modes: Local mode and MapReduce mode. Pig script can be written in two modes: Interactive mode and Batch mode.
  • Pig engine can be installed by downloading the mirror web link from the website: pig.apache.org.
Topics:
  • Introduction to Pig concepts
  • Pig modes of execution/storage concepts
  • Pig program logics explanation
  • Pig basic commands
  • Pig script execution in shell/HUE
Module 5
Duration :03:00:00
Goal : This module will cover Advanced HBase concepts. We will see demos on Bulk Loading, Filters. You will also learn what Zookeeper is all about, how it helps in monitoring a cluster, why HBase uses Zookeeper.
Objectives - Upon completing this Module, you should be able to understand HBasehas two types of Nodes—Master and RegionServer. Only one Master node runs at a time. But there can be multiple RegionServersat a time.
  • The data model of Hbasecomprises tables that are sorted by rows. The column families should be defined at the time of table creation.
  • There are eight steps that should be followed for installation of HBase.
  • Some of the commands related to HBaseshell are create, drop, list, count, get, and scan.
  Topics: Apache Hbase GangBoard.com
  • Introduction to Hbase concepts
  • Introdcution to NoSQL/CAP theorem concepts
  • Hbase design/architecture flow
  • Hbase table commands
  • Hive + Hbase integration module/jars deployment
  • Hbase execution in shell/HUE
 
Module 6
Duration :02:00:00
Goal : Sqoop is an Apache Hadoop Eco-system project whose responsibility is to import or export operations across relational databases. Some reasons to use Sqoop are as follows:
  • SQL servers are deployed worldwide
  • Nightly processing is done on SQL servers
  • Allows to move certain part of data from traditional SQL DB to Hadoop
  • Transferring data using script is inefficient and time-consuming
  • To handle large data through Ecosystem
  • To bring processed data from Hadoop to the applications

Objectives - Upon completing this Module, you should be able to understand Sqoop is a tool designed to transfer data between Hadoop and RDBs including MySQL, MS SQL, Postgre SQL, MongoDB, etc.
  • Sqoop allows the import data from an RDB, such as SQL, MySQL or Oracle into HDFS.
  Topics: Apache Sqoop
  • Introduction to Sqoop concepts
  • Sqoop internal design/architecture
  • Sqoop Import statements concepts
  • Sqoop Export Statements concepts
  • Quest Data connectors flow
  • Incremental updating concepts
  • Creating a database in MySQL for importing to HDFS
  • Sqoop commands execution in shell/HUE
 
Module 7
Duration :02:00:00
Goal : Apache Flume is a distributed data collection service that gets the flow of data from their source and aggregates them to where they need to be processed.
Objectives - Upon completing this Module, you should be able to understand Apache Flume is a distributed data collection service that gets the flow of data from their source and aggregates the data to sink.
  • Flume provides a reliable and scalable agent mode to ingest data into HDFS.
Topics: Apache Flume
  • Introduction to Flume & features
  • Flume topology & core concepts
  • Property file parameters logic
Module 8
Duration :02:00:00
Goal : Hue is a web front end offered by the ClouderaVM to Apache Hadoop.
Objectives - Upon completing this Module, you should be able to understand how to use hue for hive,pig,oozie. Topics: Apache HUE
  • Introduction to Hue design
  • Hue architecture flow/UI interface
Module 9
Duration :02:00:00
Goal : Following are the goals of ZooKeeper:
  • Serialization ensures avoidance of delay in reading or write operations.
  • Reliability persists when an update is applied by a user in the cluster.
  • Atomicity does not allow partial results. Any user update can either succeed or fail.
  • Simple Application Programming Interface or API provides an interface for development and implementation.
Objectives - Upon completing this Module, you should be able to understand ZooKeeper provides a simple and high-performance kernel for building more complex clients.
  • ZooKeeper has three basic entities—Leader, Follower, and Observer.
  • Watch is used to get the notification of all followers and observers to the leaders.
Topics: Apache Zookeeper
  • Introduction to zookeeper concepts
  • Zookeeper principles & usage in Hadoop framework
  • Basics of Zookeeper
Module 10
Duration :05:00:00
Goal: Explain different configurations of the Hadoop cluster
  • Identify different parameters for performance monitoring and performance tuning
  • Explain configuration of security parameters in Hadoop.
Objectives - Upon completing this Module, you should be able to understand Hadoop can be optimized based on the infrastructure and available resources.
  • Hadoop is an open-source application and the support provided for complicated optimization is less.
  • Optimization is performed through xml files.
  • Logs are the best medium through which an administrator can understand a problem and troubleshoot it accordingly.
  • Hadoop relies on the Kerberos based security mechanism.
Topics: Administration concepts
  • Principles of Hadoop administration & its importance
  • Hadoop admin commands explanation
  • Balancer concepts
  • Rolling upgrade mechanism explanation

Hadoop Admin Training FAQ

Our Hadoop Admin Trainers
  • More than 10 Years of experience in Hadoop Admin Technologies
  • Has worked on multiple realtime Hadoop Admin projects
  • Working in a top MNC company in Pune
  • Trained 2000+ Students so far
  • Strong Theoretical & Practical Knowledge
  • Certified Professionals
  • More than 2000+ students Trained
  • 92% percent Placement Record
  • 1000+ Interviews Organized
Regular Batch (Morning, Day time & Evening)
  • Seats Available : 8 (maximum)
Weekend Training Batch (Saturday, Sunday & Holidays)
  • Seats Available : 8 (maximum)
Fast Track Batch
  • Seats Available : 5 (maximum)

Hadoop Admin Training Reviews

Our Besant Technologies Pune Reviews are listed here. Reviews of our students who completed their training with us and left their reviews in public portals and our primary website of Besant Technologies & Video Reviews.

Besant Technologies Reviews
K
Kanu rated as 2 days ago

I always knew a good training in Hadoop Admin could boost my career by several notches. But I was not being able to buy the claims IT training institutes were making in the ads. I always felt apprehensive of joining any random IT training centre. But then I had to choose one, so I chose Besant. I won’t say it was a well-thought out decision. I didn’t choose Besant because I knew a lot about it. Things just happened in a flow; I just happened to choose Besant. But I can confidently say now that I made the best decision of my life by joining Besant. My concepts in Hadoop Admin are crystal clear, and now I feel extremely confident to face any interview.

V
Vanca rated as 3 days ago

How many times has it so happened that you just hear something from someone, end up trusting them and regret later? Well, for me, I have always believed in other people, and ended up being taken advantage of. And that is why when my friend suggested me to join the Hadoop Admin course at Besant, I was a little doubtful about how things would turn out to be. But surprisingly, I didn’t face any problem this time. In fact, I am grateful, I listened to my friend. Besant has changed my life. I am working at a reputed MNC today and I think I owe everything to Besant.

R
Ravit rated as 5 days ago

I wanted to take up a Hadoop Admin course because my senior had told me its probable benefits in my career. But because I didn’t know much about the city of Pune, I didn’t know which the best coaching centre for a course in Hadoop Admin was. My senior recommended I joined Besant Technologies, so, I did! I am happy about the growth I have made post this training. And there is nothing about my job that I am unhappy about. I am in a good position and I feel I can go places with my Hadoop Admin certification earned from Besant.

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Besant Technologies Placements in Pune

Besant Technologies offers placement opportunities as add-on to every student / professional who completed our classroom or online training. Some of our students are working in these companies listed below.

Hadoop Admin Training Locations in Pune

Most popular locations where students / professionals are lining up to get trained with us.

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