Hadoop Training in Bangalore

Hadoop Training in Bangalore

What is Hadoop?

Hadoop is an open-source software framework for storing data and running applications on clusters of commodity hardware. It provides massive storage for any kind of data, enormous processing power and the ability to handle virtually limitless concurrent tasks or jobs.

Scope of Hadoop

As the size of data increases, the demand for Hadoop technology will rise. There will be need of more Hadoopdevelopers to deal with the big data challenges. IT professionals having Hadoop skills will be benefited with increased salary packages and an accelerated career growth.Sep 6, 2017


Hadoop Training Eligibility

  1. Passion for coding and problem solving.
  2. Passion for keeping you updated as almost every month a new thing comes into Big Data World.
  3. At least understand & be able to write small codes in any one language.
  4. Familiarity with basic Linux commands.
  5. Nice to have RDBMS knowledge.

Hadoop Training Prerequisite

There are not strict prerequisites to start learning Apache Hadoop. However, it makes things easier and if you want to become and expert in Apache Hadoop , these are the good to know things.
So two very basic prerequisites for Apache Hadoop are:
  • Java.
  • Linux.
  • SQL.

Hadoop Training Syllabus in Bangalore

Introduction to Hadoop
 Hadoop Distributed File System
 Hadoop Architecture
 MapReduce & HDFS
Hadoop Eco Systems
 Introduction to Pig
 Introduction to Hive
 Introduction to HBase
 Other eco system Map
Hadoop Developer
 Moving the Data into Hadoop
 Moving The Data out from Hadoop
 Reading and Writing the files in HDFS using java program
 The Hadoop Java API for MapReduce
o Mapper Class
o Reducer Class
o Driver Class
 Writing Basic MapReduce Program In java
 Understanding the MapReduce Internal Components
 Hbase MapReduce Program
 Hive Overview
 Working with Hive
 Pig Overview
 Working with Pig
 Sqoop Overview
 Moving the Data from RDBMS to Hadoop
 Moving the Data from RDBMS to Hbase
 Moving the Data from RDBMS to Hive
 Flume Overview
 Moving The Data from Web server Into Hadoop
 Real Time Example in Hadoop
 Apache Log viewer Analysis
 Market Basket Algorithms

Hadoop Training Batch Timings in Bangalore


Hadoop Training in Bangalore Course Duration



 Hadoop Training Location in Bangalore

  Branch In The Following Areas

East Bangalore

Basavanna Nagar
CV Raman Nagar
New Thippasandra

West Bangalore

Avenue Road
Austin Town
Bharati Nagar

North Bangalore

HBR Layout

South Bangalore


Hadoop Training Trainer Profile in Bangalore

  • Cloudera Certified Professional – Data Scientist (CCP DS)
  • Cloudera Certified Administrator for Hadoop (CCAH)
  • Cloudera Certified Hadoop Developer (CCDH)

Who Should Do Hadoop Training

To learn Hadoop and build an excellent career in Hadoop, having basic knowledge of Linux and knowing the basic programming principles of Java is a must. Thus, to incredibly excel in the entrenched technology of Apache Hadoop, it is recommended that you at least learn Java basics.

Interview Questions FAQ

1) What is the difference between Hadoop and Traditional RDBMS?

Hadoop vs RDBMS




DatatypesProcesses semi-structured and unstructured data.Processes structured data.
SchemaSchema on ReadSchema on Write
Best Fit for ApplicationsData discovery and Massive Storage/Processing of Unstructured data.Best suited for OLTP and complex ACID transactions.
SpeedWrites are FastReads are Fast


2) What do the four V’s of Big Data denote? 

IBM has a nice, simple explanation for the four critical features of big data:
a) Volume –Scale of data
b) Velocity –Analysis of streaming data
c) Variety – Different forms of data
d) Veracity –Uncertainty of data

3) Explain what is shuffling in MapReduce?

The process by which the system performs the sort and transfers the map outputs to the reducer as inputs is known as the shuffle

4) Explain what is distributed Cache in MapReduce Framework?

Distributed Cache is an important feature provided by the MapReduce framework. When you want to share some files across all nodes in Hadoop Cluster, Distributed Cache is used.  The files could be an executable jar files or simple properties file.

5) Explain what is NameNode in Hadoop?

NameNode in Hadoop is the node, where Hadoop stores all the file location information in HDFS (Hadoop Distributed File System).  In other words, NameNode is the centerpiece of an HDFS file system.  It keeps the record of all the files in the file system and tracks the file data across the cluster or multiple machines

6) Explain what is JobTracker in Hadoop? What are the actions followed by Hadoop?

In Hadoop for submitting and tracking MapReduce jobs,  JobTracker is used. Job tracker run on its own JVM process

Job Tracker performs following actions in Hadoop

  • Client application submit jobs to the job tracker
  • JobTracker communicates to the Name mode to determine data location
  • Near the data or with available slots JobTracker locates TaskTracker nodes
  • On chosen TaskTracker Nodes, it submits the work
  • When a task fails, Job tracker notifies and decides what to do then.
  • The TaskTracker nodes are monitored by JobTracker

7) Explain what is heartbeat in HDFS?

Heartbeat is referred to a signal used between a data node and Name node, and between task tracker and job tracker, if the Name node or job tracker does not respond to the signal, then it is considered there is some issues with data node or task tracker

8) Explain what combiners are and when you should use a combiner in a MapReduce Job?

To increase the efficiency of MapReduce Program, Combiners are used.  The amount of data can be reduced with the help of combiner’s that need to be transferred across to the reducers. If the operation performed is commutative and associative you can use your reducer code as a combiner.  The execution of combiner is not guaranteed in Hadoop

9) What happens when a data node fails?

When a data node fails

  • Jobtracker and namenode detect the failure
  • On the failed node all tasks are re-scheduled
  • Namenode replicates the user’s data to another node

10) Explain what is Speculative Execution?

In Hadoop during Speculative Execution, a certain number of duplicate tasks are launched.  On a different slave node, multiple copies of the same map or reduce task can be executed using Speculative Execution. In simple words, if a particular drive is taking a long time to complete a task, Hadoop will create a duplicate task on another disk.  A disk that finishes the task first is retained and disks that do not finish first are killed.

11) Explain what are the basic parameters of a Mapper?

The basic parameters of a Mapper are

  • LongWritable and Text
  • Text and IntWritable

12) Explain what is the function of MapReduce partitioner?

The function of MapReduce partitioner is to make sure that all the value of a single key goes to the same reducer, eventually which helps even distribution of the map output over the reducers

13) Explain what is a difference between an Input Split and HDFS Block?

The logical division of data is known as Split while a physical division of data is known as HDFS Block

14) Explain what happens in text format?

In text input format, each line in the text file is a record.  Value is the content of the line while Key is the byte offset of the line. For instance, Key: longWritable, Value: text

15) Mention what are the main configuration parameters that user need to specify to run MapReduce Job?

The user of the MapReduce framework needs to specify

  • Job’s input locations in the distributed file system
  • Job’s output location in the distributed file system
  • Input format
  • Output format
  • Class containing the map function
  • Class containing the reduce function
  • JAR file containing the mapper, reducer and driver classes

16) Explain what is WebDAV in Hadoop?

To support editing and updating files WebDAV is a set of extensions to HTTP.  On most operating system WebDAV shares can be mounted as filesystems, so it is possible to access HDFS as a standard filesystem by exposing HDFS over WebDAV.

17)  Explain what is Sqoop in Hadoop?

To transfer the data between Relational database management (RDBMS) and Hadoop HDFS a tool is used known as Sqoop. Using Sqoop data can be transferred from RDMS like MySQL or Oracle into HDFS as well as exporting data from HDFS file to RDBMS

18) Explain how JobTracker schedules a task?

The task tracker sends out heartbeat messages to Jobtracker usually every few minutes to make sure that JobTracker is active and functioning.  The message also informs JobTracker about the number of available slots, so the JobTracker can stay up to date with wherein the cluster work can be delegated

19) Explain what is Sequencefileinputformat?

Sequencefileinputformat is used for reading files in sequence. It is a specific compressed binary file format which is optimized for passing data between the output of one MapReduce job to the input of some other MapReduce job.

20) Explain what does the conf.setMapper Class do?

Conf.setMapperclass  sets the mapper class and all the stuff related to map job such as reading data and generating a key-value pair out of the mapper

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