Q Big Data Assignment Help Big Data Assignment Help - Want To Secure A++ In Big Data Assignments? Get Best and Most Trusted Big Data Assignment Help at Miracleskills!! Previous << >> Next GET ASSURED A++ GRADE IN EACH BIG DATA ASSIGNMENT ORDER - ORDER FOR ORIGINALLY WRITTEN SOLUTIONS! CST4070 Applied Data Analytics - Tools, Practical Big Data Handling, Cloud Distribution Assignment - Middlesex University, UK Assessment Title - Big Data 1. General information - You are required to submit your work via the dedicated Unihub assignment link by the specified deadline. This link will 'timeout' at the submission deadline. Your work may not be accepted as an email attachment if you miss this deadline. Therefore, you are strongly advised to allow plenty of time to upload your work prior to the deadline. You are required to solve the exercises illustrated below. Each exercise should be accompanied by: i. A short introduction where you describe the problem and your high level solution. ii. Your step-by-step process supported by screenshots. Each screenshot needs to be accompanied by a short explanatory text. iii. Eventually, if necessary, conclude each task with brief summary of what you have done. Exercises - Follow the lab instructions to install Apache Hadoop into a virtual server running on Linux Ubuntu Server. Once you have Apache Hadoop installed and running, execute the following exercise tasks. HND assignment seems to be a daunting and time-consuming task. Thankfully now you can hire subject professionals from the HND assignment help to achieve the task on time and get high grades. Exercise 1 - Implement one executable Hadoop MapReduce job that counts the total number of words having an even and odd number of characters. As an example, if the text in input is Hello world , the output should be even:0, odd:2 , because both Hello and world contain an odd number of characters. Whereas, if the input us My name is Alice the output should be even: 3, odd: 1. The job needs to be executed by a mapper and a reducer. Both mapper and reducer needs to be written in Python and tested in Linux Ubuntu before running them on Hadoop MapReduce. NO PLAGIARISM POLICY - ORDER NEW BIG DATA ASSIGNMENT & GET WELL WRITTEN SOLUTIONS DOCUMENTS WITH FREE TURNTIN REPORT! Exercise 2 - Implement one executable Hadoop MapReduce job that receives in input a .csv table having the structure 'StudentId, Module, Grade' and returns in output the minimum and maximum grade of each student along as her total number of modules she has passed. Therefore, if your input is: StudentId Module Grade S001 Statistic 75 S002 Statistic 72 S001 Big Data 78 S003 Big Data 66 S001 Programming 70 S002 Programming 55 S001 Machine Learning 65 S002 Machine Learning 61 Your output need to be: StudentId MinGrade MaxGrade Modules S001 65 78 4 S002 55 72 3 S003 66 66 1 The job needs to be executed by a mapper and a reducer. Both mapper and reducer needs to be written in Python and tested in Linux Ubuntu before running them on Hadoop MapReduce. ENDLESS SUPPORT IN BIG DATA ASSIGNMENTS WRITING SERVICES - YOU GET REVISED OR MODIFIED WORK TILL YOU ARE SATISFIED WITH OUR BIG DATA ASSIGNMENT HELP SERVICES! Exercise 3 - Implement one executable Hadoop MapReduce job that receives in input two .csv tables having the structure: User: UserId, Name, DOB Follows: UserIdFollower, UserIdFollowing The MapReduce job needs to perform the following SQL query: select U.UserId, U.Name as NameFollower, F.Name as NameFollowing from User as U join Follows as F on U.UserId = F.UserId where F.DOB <= '2002-03-01' Therefore, if the two original tables are: UserId Name DOB U001 Alice 2005-01-05 U002 Tom 2001-02-07 U003 John 1998-06-02 U004 Alex 2006-02-01 UserIdFollower UserIdFollowing U001 U002 U001 U003 U002 U001 U002 U004 U003 U001 U004 U001 The final table needs to be UserId NameFollower NameFollowing U001 Alice Tom U001 Alice John The job needs to be executed by a mapper and a reducer. Both mapper and reducer needs to be written in Python and tested in Linux Ubuntu before running them on Hadoop MapReduce. GET READYMADE BIG DATA ASSIGNMENT SOLUTIONS - 100% PLAGIARISM FREE WORK DOCUMENT AT NOMINAL CHARGES! 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