Real Time Experts
4.9 out of 5 based on 448 Reviews
Enrolled my self to join in hadoop Training in this institute. It is 1 month training. They provided some software materials to learn the course. Their teaching is so professional. I am fulfilled with their coaching.
Ravishankar1 days ago
I am fresher i did hadoop and in TIB Academy Bangalore. Training was ultimate. Got offer in Istudio Bangalore.
ramya1 days ago
Thanks to RTE for providing excellent training on Hadoop course . I would to like to say thanks to support Management team for there advise and help when ever I faced any issues.Even though they changed trainer once for our batch,they gave the Best Hadoop Trainer.Thanks for Comittment.
Sanjay1 days ago
The classes were very informative and fully practical and the faculty was much friendly. I could learn the topics in Hadoop very clearly and it is Very useful to my career. Thanks to Real Time Experts for the useful guidance and the learning experience.
Navadeep4 days ago
Prabu1 days ago
My Hadoop Trainer has a very good skill to explain technology with his best knowledge of it. He always looks forward to resolve queries which ever students ask. Provided good amount of data along with use cases which will very helpful to practice offline. I was thinking for me BIG Data HADOOP will be quite difficult to learn but being student of Real time Experts, I learned it easily with good amount of knowledge and practice of use cases. They took 7 months to place me,Finally joined in IBM.
Ravi Shankar1 days ago
I have completed Hadoop Training from Real Time Experts . he use to take class in a practical manner with Java projects .My Hadoop Bigdata class was awesome .I have learned very well from him and also got placed in IBM
Chandan3 days ago
Just Completed my Hadoop Training. Experience was good. They have good Hadoop instructors. During class you can have your doubts cleared but apart from that you are not allowed to contact the instructor directly.My Instructor was supported through Hadoop Project Case studies.
Rajesh1 days ago
Just completed my hadoop classes. successfully Completed the Big data and Hadoop course at Realtime Experts. Hadoop Course content is excellent. My trainer was architect in hadoop,attended weekend batch.I paid 14000 Fees
Venkat1 days ago
I joined Real Time Experts for hadoop. I got a better understanding of all the concepts of hadoop. Classes had a better interaction which helps me to get used to real time scenarios. Can gain better knowledge!!
prakash1 days ago
Basically I am from Testing Background, I was not knowing anything related to database. After i joined here, i learnt lot in both Hadoop Bigdata.Thanks to Realtime experts Marathalli.
Jayaram1 days ago
Hi,I am Kasthuri, I have done Hadoop Bigdata in Real Time Experts Bangalore . It was very useful for me to learn and practice.Our Trainer gave me complete Hadoop training during the weekend batch classes . It is very helpful in my Hadoop career .Thanks to Real Time Experts Bangalore.
Kasthuri1 days ago
I have attended hadoop training. The faculty was very good and he eplained all the concepts of hadoop with real time senario. I also got support in develping my own Project. Overall experence in Real Time Experts is very good.
Pavani1 days ago
Best Hadoop Course in Bangalore & Top Hadoop Training
Institute
Course Content for Hadoop Developer
This Course Covers 100% Developer and 40% Administration
Syllabus.
Introduction to BigData, Hadoop:-
 Big Data Introduction
 Hadoop Introduction
 What is Hadoop? Why Hadoop?
 Hadoop History?
 Different types of Components in
Hadoop?
 HDFS, MapReduce, PIG, Hive,
SQOOP, HBASE, OOZIE, Flume, Zookeeper and so on…
 What is the scope of Hadoop?
Deep Drive in HDFS (for Storing the Data):-
 Introduction of HDFS
 HDFS Design
 HDFS role in Hadoop
 Features of HDFS
 Daemons of Hadoop and its functionality
o Name Node
o Secondary Name Node
o Job Tracker
o Data Node
o Task Tracker
 Anatomy of File Wright
 Anatomy of File Read
 Network Topology
o Nodes
o Racks
o Data Center
 Parallel Copying using DistCp
 Basic Configuration for HDFS
 Data Organization
o Blocks and
o Replication
 Rack Awareness
 Heartbeat Signal
 How to Store the Data into HDFS
 How to Read the Data from HDFS
 Accessing HDFS (Introduction of Basic
UNIX commands)
 CLI commands
MapReduce using Java (Processing the Data):-
 The introduction of MapReduce.
 MapReduce Architecture
 Data flow in MapReduce
o Splits
o Mapper
o Portioning
o Sort and shuffle
o Combiner
o Reducer
 Understand Difference Between Block and
InputSplit
 Role of RecordReader
 Basic Configuration of MapReduce
 MapReduce life cycle
o Driver Code
o Mapper
o and Reducer
 How MapReduce Works
 Writing and Executing the Basic
MapReduce Program using Java
 Submission & Initialization of
MapReduce Job.
 File Input/Output Formats in
MapReduce Jobs
o Text Input Format
o Key Value Input Format
o Sequence File Input Format
o NLine Input Format
 Joins
o Map-side Joins
o Reducer-side Joins
 Word Count Example
 Partition MapReduce Program
 Side Data Distribution
o Distributed Cache (with Program)
 Counters (with Program)
o Types of Counters
o Task Counters
o Job Counters
o User Defined Counters
o Propagation of Counters
 Job Scheduling
PIG:-
 Introduction to Apache PIG
 Introduction to PIG Data Flow Engine
 MapReduce vs. PIG in detail
 When should PIG use?
 Data Types in PIG
 Basic PIG programming
 Modes of Execution in PIG
o Local Mode and
o MapReduce Mode
 Execution Mechanisms
o Grunt Shell
o Script
o Embedded
 Operators/Transformations in PIG
 PIG UDF’s with Program
 Word Count Example in PIG
 The difference between the MapReduce
and PIG
SQOOP:-
 Introduction to SQOOP
 Use of SQOOP
 Connect to mySql database
 SQOOP commands
o Import
o Export
o Eval
o Codegen etc…
 Joins in SQOOP
 Export to MySQL
 Export to HBase
HIVE:-
 Introduction to HIVE
 HIVE Meta Store
 HIVE Architecture
 Tables in HIVE
o Managed Tables
o External Tables
 Hive Data Types
o Primitive Types
o Complex Types
 Partition
 Joins in HIVE
 HIVE UDF’s and UADF’s with Programs
 Word Count Example
HBASE:-
 Introduction to HBASE
 Basic Configurations of HBASE
 Fundamentals of HBase
 What is NoSQL?
 HBase Data Model
o Table and Row
o Column Family and Column Qualifier
o Cell and its Versioning
 Categories of NoSQL Data Bases
o Key-Value Database
o Document Database
o Column Family Database
 HBASE Architecture
o HMaster
o Region Servers
o Regions
o MemStore
o Store
 SQL vs. NOSQL
 How HBASE is differed from RDBMS
 HDFS vs. HBase
 Client-side buffering or bulk uploads
 HBase Designing Tables
 HBase Operations
o Get
o Scan
o Put
o Delete
MongoDB:–
 What is MongoDB?
 Where to Use?
 Configuration On Windows
 Inserting the data into MongoDB?
 Reading the MongoDB data.
Cluster Setup:–
 Downloading and installing the
Ubuntu12.x
 Installing Java
 Installing Hadoop
 Creating Cluster
 Increasing Decreasing the Cluster size
 Monitoring the Cluster Health
 Starting and Stopping the Nodes
Zookeeper
 Introduction Zookeeper
 Data Modal
 Operations
OOZIE
 Introduction to OOZIE
 Use of OOZIE
 Where to use?
Flume
 Introduction to Flume
 Uses of Flume
 Flume Architecture
o Flume Master
o Flume Collectors
o Flume Agents
Project Explanation with Architecture