Hadoop Training in Hyderabad

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Hadoop
Training
by
Address Flat no 204, 2nd floor, Annapurna
Block, Aditya Enclave, Ameerpet,
Hyderabad-16. Email IDinfo_at_OrienIT.com 040
6514 2345, 91 970 320 2345
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About Us
OrienIT offers HADOOP training by the experienced
faculty at affordable price. It is proud to be
one of the leading Institute of HADOOP training
in hyderabad. The expertise we acquired through
this helped us to improve our skills in training.
We provided the classroom training with
theoretical stuff . Hadoop Training in Hyderabad
is mostly suited for both graduates and working
professionals in the Industry level . Most of the
Organizations are actively looking for the Hadoop
expert to hire them in the company.
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What is Hadoop?

• Hadoop is an open source, Java-based scheduling
  framework that supports the processing and
  storage of extremely large data sets in a
  distributed computing environment. It is part of
  the Apache project sponsored by the Apache
  Software Foundation.
• Hadoop is an open-source structure that allows to
  store and procedure tremendous data in an
  appropriated space across over gatherings of PCs
  using basic programming models. It is intended to
  scale up from single servers to thousands of
  machines, each offering adjacent retribution and
  stockpiling.
• Hadoop is a Java-based open-source stage proposed
  to change gigantic measures of data in a coursed
  handling environment . Hadoops key advancements
  lay in its ability to store and access tremendous
  measures of data over a considerable number PCs
  and to normally demonstrate that data.

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• Hadoop Components
• Hadoop Course is described by two Components
• Hadoop Distributed File System (HDFS)
• MapReduce.
• HDFS
• The Hadoop Distributed File System (HDFS)
  offers a way to store large files across multiple
  machines, rather than requiring a single machine
  to have disk capacity equal to/greater than the
  summed total size of the files.
• HDFS is designed to be fault-tolerant due to
  data replication and distribution of data. When a
  file is loaded into HDFS, it is replicated and
  broken up into blocks of data, which are stored
  across the cluster nodes designated for storage,
  a.k.a. Data Nodes.

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• MapReduce
• The MapReduce paradigm for parallel
  processing comprises two sequential steps map
  and reduce.
• MAP
• In the map phase, the input is a set of
  key-value pairs and the desired function is
  executed over each key/value pair in order to
  generate a set of intermediate key/value pairs.
• Reduce
• In the reduce phase, the intermediate
  key/value pairs are grouped by key and the values
  are combined together according to the reduce
  code provided by the user for example, summing.
  It is also possible that no reduce phase is
  required, given the type of operation coded by
  the user.

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Why Importance of Hadoop Training ?

• Hadoop Training is expanding fast reputation,
  equally this is used by various broadly acclaimed
  destinations like Google, Yahoo, Facebook,
  Amazon, Apple, IBM etcetera.
• Hadoop Training is enormous names demonstrate the
  noteworthiness of this mind
• boggling programming for business use, in todays
  not kidding competition of Internet Marketing.
• Hadoop training breaks down the informations
  experiences which guarantee that the reporting
  and dashboard is regulated successfully.
• When you complete Hadoop training, you will
  become into a Developer . Hadoop
• training is being declared as a crucial portion
  of the present day data basic building.

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• Hadoop Interview Questions
• 1.Why the name Hadoop?
• Hadoop doesnt have any expanding version like
  oops. The charming yellow elephant you see is
  basically named after Dougs sons toy
  elephant!2.What is MapReduce?
• It is a framework or a programming model that is
  used for processing large data sets over clusters
  of computers using distributed programming.
• 3.Is there any benefit of learning MapReduce,
  then?
• Yes, MapReduce is a paradigm used by many big
  data tools including Spark as well.
• It is extremely relevant to use MapReduce when
  the data grows bigger and bigger.
• Most tools like Pig and Hive convert their
  queries into MapReduce phases to
• optimize them better.

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4. How is Hadoop different from other data
processing tools? In Hadoop, based upon your
requirements, you can increase or decrease the
number of mappers without bothering about the
volume of data to be processed. this is the
beauty of parallel processing in contrast to the
other data processing tools available. 5. What is
the difference between an HDFS Block and Input
Split? HDFS Block is the physical division of the
data and Input Split is the logical division of
the data. 6. What is InputSplit in Hadoop?When a
Hadoop job is run, it splits input files into
chunks and assign each split to a mapper to
process. This is called Input Split . 7. How is
the splitting of file invoked in Hadoop Framework
?It is invoked by the Hadoop framework by
running getInputSplit() method of the Input
format class (like FileInputFormat) defined by
the user 
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8.Consider case scenario In M/R system,    -
HDFS bloc size is 64 MB    - Input format is
FileInputFormat    - We have 3 files of size
64K, 65Mb and 127Mb then how many input splits
will be made by Hadoop framework?Hadoop will
make 5 splits as follows - 1 split for 64K
files - 2  splits for 65Mb files - 2 splits for
127Mb file  9. Have you ever used Counters in
Hadoop. Give us an example scenario ?Anybody who
claims to have worked on a Hadoop project is
expected to use counters. 10.Is it possible to
have Hadoop job output in multiple directories.
If yes then how ? Yes, by using Multiple Outputs
class
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Thank You
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