Hadoop Training In Hyderabad

1. Hadoop Training by Address: Flat no : 204, 2nd floor, Annapurna Block, Aditya Enclave, Ameerpet, Hyderabad-16. Email ID:info@OrienIT.com 040 6514 2345, +91 970 320 2345 http://www.orienit.com/

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3. 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. http://www.orienit.com/

4. 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 . Hadoop‘s 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. http://www.orienit.com/

5. 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. http://www.orienit.com/

6. 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. http://www.orienit.com/

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8. 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 today’s not kidding competition of Internet Marketing. Hadoop training breaks down the information’s 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. http://www.orienit.com/

9. Hadoop Interview Questions • 1.Why the name ‘Hadoop’? • Hadoop doesn’t have any expanding version like ‘oops’. The charming yellow elephant you see is basically named after Doug’s son’s 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. • http://www.orienit.com/

10. 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  • http://www.orienit.com/

11. 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 http://www.orienit.com/

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