Description

CSCI312 Big Data Management
Assignment 1

Scope
The objectives of Assignment 1 include implementation of HDFS applications, implementation of simple MapReduce applications, and describing an implementation of complex MapReduce application.

This assignment is worth 10% of the total evaluation in the subject.

The assignment consists of 4 tasks and specification of each task starts from a new page.

Only electronic submission through Moodle at:
https://moodle.uowplatform.edu.au/login/index.php
will be accepted. A submission procedure is explained at the end of Assignment 1 specification.

Only one submission of Assignment 1 is allowed and only one submission per student is accepted.

A submission marked by Moodle as “late” is always treated as a late submission no matter how many seconds it is late.

A submission that contains an incorrect file attached is treated as a correct submission with all consequences coming from the evaluation of the file attached.

All files left on Moodle in a state “Draft(not submitted)” will not be evaluated.

A submission of compressed files (zipped, gzipped, rared, tared, 7-zipped, lhzed, … etc) is not allowed. The compressed files will not be evaluated.

Task 1 (2 marks)
Implementation of HDFS application

Implement a HDFS application that merges two files located in HDFS into one file also located in HDFS.

The application must have the following parameters.
(1) A path to, and a name of the first input file in HDFS.
(2) A path to, and a name of the second input file in HDFS.
(3) A path to, and a new name of an output file to be created in HDFS. The file supposed to contain the contents of the first input file followed by the contents of the second input file.

Perform the following steps.

Implement the application and save its source code in a file solution1.java.

Upload to two files to HDFS. The contents, the name, and the locations of the files in HDSF are up to you.

When ready, compile, create jar file, and process your application. Display the results created by the application.

Use Hadoop to provide an evidence, that two files uploaded into HDFS has been successful merged in one file in HDFS.

Deliverables
A file solution1.java with a source code of the application that merges two HDFS files. A file solution1.pdf that contains the contents of Terminal window with a report from compilation, creation of jar file, uploading to HDFS two small files for testing, processing of the application, and an evidence that two files uploaded into HDFS has been successful merges in one file in HDFS.

Task 2 (3 marks)
Implementation of MapReduce application

For example, a sample file with the speed measurements contains the following lines:

Assume, that a speed limit in a location of the speed camera is 60 kilometres per hour.

Your task is to implement a MapReduce application, that finds an average speed of all cars, that exceeded a speed limit in the location of the speed camera.

An input file with the speed measurements must include the lines listed above and it must contain at least 20 measurements. All additional measurements are up to you.

Save your solution in a file solution2.java.

When ready, compile, create jar file, and process your application. Display the results created by the application. Next, list your input file with the speed measurements. When finished, Copy and Paste the messages from a Terminal screen into a file solution2.pdf.

Deliverables
A file solution2.java with a source code of the application that implement the functionality of SELECT statement given above. A file solution2.pdf with a report from compilation, creating jar file, processing, displaying the results of processing solution2.java, and listing of your input file with the speed measurements.

Task 3 (2 marks)
Implementation of MapReduce application

An application MinMax described in an Exercise 2 has the functionality the same as the following SQL statement.

SELECT key, MIN(value), MAX(value)
FROM Sequence-of-key-value-pairs
GROUP BY key;

Extend Java code of the application such that it implements the functionality the same as the following SQL statement.

SELECT key, key, MIN(value), MAX(value), SUM(value), AVG(value)
FROM Sequence-of-key-value-pairs
GROUP BY key;

Save your solution in a file solution3.java.

When ready, compile, create jar file, and process your application. To test your application, you can use a file sales.txt included in a folder with a specification of Exercise 2. Display the results created by the application. When finished, Copy and Paste the messages from a Terminal screen into a file solution3.pdf.

Deliverables
A file solution3.java with a source code of the application that implement the functionality of SELECT statement given above. A file solution3.pdf with a report from compilation, creating jar file, processing, and displaying the results of processing solution3.java.

Task 4 (3 marks)
Describing MapReduce implementation of join operation

Assume, that a file car.txt contains the technical descriptions of the cars. A single row in the file contains a car registration number, maximum speed and fuel consumption

PKR856 180 10
UPS234 200 15 … …

Assume that both files have been loaded to HDFS.

Write the comprehensive explanations how would you implement in Java a MapReduce application that finds the cars, that reached its maximum speed at the speed checkpoint.

Save you explanations in a file solution4.pdf. This task does not require you to write any code in Java. However, the comprehensive explanations related to all stages of data processing are expected. You are allowed to support your explanations with the fragments of pseudocode. Try to be as specific as it is possible.

Deliverables
A file solution4.pdf with the comprehensive explanations how would you implement in Java a MapReduce application that finds the cars that reached its maximum speed at the speed checkpoint.

Submission of Assignment 1

Note, that you have only one submission. So, make it absolutely sure that you submit the correct files with the correct contents. No other submission is possible !

Submit the files solution1.java, solution1.pdf, solution2.java, solution2.pdf, solution2.java, solution3.java, solution3.pdf, and solution4.pdf through Moodle in the following way:
(1) Access Moodle at http://moodle.uowplatform.edu.au/
(2) To login use a Login link located in the right upper corner the Web page or in the middle of the bottom of the Web page
(3) When logged select a site ISIT312 (SP421) Big Data Management
(4) Scroll down to a section SUBMISSIONS
(5) Click at In this place you can submit the outcomes of your work on the tasks included in Assignment 1 link.
(6) Click at a button Add Submission
(7) Move a file solution1.java into an area You can drag and drop files here to add them. You can also use a link Add…
(8) Repeat step (7) for the remaining files solution1.pdf, solution2.java, solution2.pdf, solution2.java, solution3.java, solution3.pdf, and solution4.pdf
(9) Click at a button Save changes
(10) Click at a button Submit assignment
(11) Click at the checkbox with a text attached: By checking this box, I confirm that this submission is my own work, … in order to confirm authorship of your submission.
(12) Click at a button Continue

End of specification