MAP REDUCEThere are 2 questions (and their sub-questions) you need to work on in this assignment.No late submission will be accepted.Question 1 (50 pts)------------------...

please help me to solve theses questions


MAP REDUCE There are 2 questions (and their sub-questions) you need to work on in this assignment. No late submission will be accepted. Question 1 (50 pts)------------------ -------------------------------------------------- Input Data File: dept_salary.txt (attached to this assignment) The first column of the data file has the id of a dept and the second column a salary amount. Write a map-reduce program to get the MINIMUM salary per department. Please submit python mapper and reducer similar to ones given in lab along with detailed instructions on how to use. Expected files to be submitted:1. Mapper in python2. Reducer in python3. A file of instructions explaining how to use the mapper, reducer, and the data file Rubric of the Grades:- Correct Mapper code (8 pts),- Correct Reducer code (8 pts),- Executable MapReduce job (8 pts),- Producing correct output (8 pts),- Complete set of instructions showing all steps that needs to be run to produce a result (10 pts),- Screen snapshot provided and matching to the execution of the submitted mapper and reducer codes (8 pts) Question 2 (50 pts)------ --------------------------------------------- -------- Input Data File: shakespeare_100.txt (download it from this link) In the Word count example we output all words with their count. What if we only want the words with top 20 counts (This is very common problemin the industry). Think about using multiple map-reduce steps. Please submit python mapper and reducer similar to ones given in lab along withdetailed instructions on how to use. If using multiple map-reduce steps, explanation of the steps should be included in your documentation Expected files to be submitted:1. Mapper(s) in python2. Reducer(s) in python3. A file of instructions explaining how to use the mapper(s), reducer(s), and the data file Rubric of the Grades:- Correct Mapper code(s). If multiple mappers the total grade will be split between them (8 pts),- Correct Reducer code(s). If multiple reducers the total grade will be split between them (8 pts), - Executable MapReduce job(s). If multiple execution steps the total grade will be split between them (8 pts),- Producing correct output(s). If multiple execution steps the total grade will be split between them (8 pts),- Complete set of instructions showing all steps that needs to be run to produce a result (10 pts),- Screen snapshot provided and matching to the execution(s) of the submitted mapper(s) and/or reducer(s) codes (8 pts)Start Date