[SOLVED] 大数据hadoop AWS代写：COMP9313 Project 4

https::////wwebcms3..ccse..uunsw..eedu..aau//CCOMP9313//117s2//rresources//112771

Another sample input file “ flickr _small .ttxt ” can be downloaded at::

https::////wwebcms3..ccse..uunsw..eedu..aau//CCOMP9313//117s2//rresources//112772

O utput::

The output file contains the similar pairs together with their similarities with regard to the given threshold τ . Each line is in format of “ (RRecordId 1 ,RRecordId 2 ) t Similarity ” (RRecordId 1 <RRecordId 2 , which indicates that no duplicate pairs in the result)) . The similarities are of double precision.. The pairs are sorted in ascending order (bby first record and then the second))..

Given the example input data , the output file is like::

(00,2)) t 0.75

(00,, 3 ) t 0.75

( 1 , 4 ) t 0.. 5

( 2 , 3 ) t 0.. 5

( 2 , 4 ) t 0.. 5

Code format :

Name your java file as “ SetSimJoin..jjava ” , and put it in the package “ comp9313..aass4 ” . Your program should take four parameters:: the input file , the output folder,, and the similarity threshold τ (ddouble precision)) , the number of reducers .

Cluster configuration::

Create an S3 bucket with name “ comp9 313..<<YYOUR_STUDENTID>> ” in AWS . Create a folder “ project4 ” in this bucket for holding the input files..

This project aims to let you see the power of distributed computation.. Your code should scale well with the number of nodes used in a cluster.. You are required to create three clusters in AWS to run the same job :

 Cluster1 – 2 node s of instance type m3..xxlarge ( one reduce task ) ;

 Cluster2 – 4 nodes of instance type m3..xxlarge ( three reduce task s)) ;

 Cluster3 – 6 nodes of instance type m3..xxlarge ( five reduce task s))..

Select release EMR – 5.9.0 when creating each cluster.. U pload the following data set to your S3 bucket,, and set τ to 0.85 to run your program :

https::////wwebcms3..ccse..uunsw..eedu..aau//CCOMP9313//117s2//rresources//112773

Record the runtime on each cluster,, and draw a figure where the x – axis is the number of nodes you used and the y – axis is the time of getting the result,, and store this figure in a file “ Runtime .jjpg ” . Please also take a screenshot of running your program on AWS in each cluster as a proof of the runtime.. Compress the three screenshots into a zip file “ Screenshots..zzip ” . Briefly describe your optimization techniques in a file “ Optimization..ppdf ” .

Note s

Create a project locally in Eclipse,, test everything in your local computer,, and finally do it in AWS EMR..

Documentation and c ode r eadability

Your source code will be inspected and marked based on readability and ease of understanding.. The efficiency and scalability of this project is very important and will be evaluated as well . Below is an indicative marking scheme::

Result correctness:: 7 0%%

Efficiency and Scalability:: 2 0%%

Code structure,, Readability,, and Documentation:: 10%%

S ubmission::

Deadline:: Sunday 29 th Oct 09::559::559 P M

Log in any CSE server (ww illiams or wagner)),, and u se the give command below to submit your solutions :

$ give cs9313 assignment 4 SetSimJoin..jjava Runtime..jjpg Screenshots..zzip Op timization..ppdf

O r you can submit through::

https::////ccgi..ccse..uunsw..eedu..aau//~~ggive//SStudent//ggive..pphp

If you submit your assignment more than once,, the last submission will replace the previous one.. To prove successful submission,, please take a screenshot as assignment submission instructions show and keep it by yourself..

Late submission penalty

10%% reduction of your marks for the 1st day,, 30%% reduction//dday for the following days .

Plagiarism :

The work you submit must be your own work.. Submission of work partially or completely derived from any other person or jointly written with any other person is not permitted.. The penalties for such an offence may include negative marks,, automatic failure of the course and possibly other academic di scipline.. Assignment submissions will be examined manually.. Relevant scholarship authorities will be informed if students holding scholarships are involved in an incident of plagiarism or other misconduct.. Do not provide or show your assignment work to any other person – apart from the teaching staff of this subject.. If you knowingly provide or show your assignment work to another person for any reason,, and work derived from it is submitted you may be penalized,, even if the work was submitted without yo ur knowledge or consent..