COMP9313 2016s2 Assignment 4
Processing Graph Data using MapReduce on EMR
Problem 1 (10 pts): Reverse graph edge direction
Given a directed graph, reverse the direction of all edges.
Input files:
In the input file, each line contains a pair of node ids:
“FromNodeId\tToNodeId”. In the above example, the input contains four
lines: “1\t2”, “1\t3”, “3\t1”, “3\t2”.
The sample file “tiny-web-Stanford.txt” can be downloaded at:
https://webcms3.cse.unsw.edu.au/COMP9313/16s2/resources/5391
Download the entire graph “web-Stanford.txt” at:
https://webcms3.cse.unsw.edu.au/COMP9313/16s2/resources/5392
Output:
The output is the adjacency list of the reversed graph, and the nodes are
sorted in ascending order in each list. Format each line as:
“NodeId\tNeighbor1, Neighbor2, …, Neighborm”, using only a comma to
separate the node IDs in the list.
Given the above example, the output file contains three lines: “1\t3”, “2\t1,
3”, “3\t1”.
Cluster configuration:
Create a cluster with 3 nodes of instance type m3.xlarge. Create an S3
bucket with name “comp9313.
“problem1” in this bucket, and upload the input file “web-Stanford.txt” into
this folder. Save your output folder in “problem1” as well. Finally, please
make the output folder public (right click the folder, and click “Make
public”).
https://webcms3.cse.unsw.edu.au/COMP9313/16s2/resources/5391
https://webcms3.cse.unsw.edu.au/COMP9313/16s2/resources/5392
Code format:
Name your java file as “ReverseGraph.java”, and put it in the package
“comp9313.ass4”. Set the number of reducers to 3 when configuring the
MapReduce job. The input and output are taken from the parameters of the
main function.
Problem 2 (20 pts): Single-source shortest path
Given a graph and a node “s”, find the distances of all nodes to “s”.
Input files:
In the input file, each line is in format of:
“EdgeId FromNodeId ToNodeId Distance”.
In the above example, the input contains:
0 0 1 10.0
1 0 2 5.0
2 1 2 2.0
3 1 3 1.0
4 2 1 3.0
5 2 3 9.0
6 2 4 2.0
7 3 4 4.0
8 4 0 7.0
9 4 3 6.0
This sample file “tiny-graph.txt” can be downloaded at:
https://webcms3.cse.unsw.edu.au/COMP9313/16s2/resources/5393
https://webcms3.cse.unsw.edu.au/COMP9313/16s2/resources/5393
Download the two larger graphs “NA.cedge.txt” and “SF.cedge.txt” at:
https://webcms3.cse.unsw.edu.au/COMP9313/16s2/resources/5394 and
https://webcms3.cse.unsw.edu.au/COMP9313/16s2/resources/5395
Output:
The output file contains distances of all nodes to the given node. Each line is
in format of “QueryNodeId TargetNodeID Distance”. The distances are of
double precision. Remove the nodes that are not reachable to the query node,
and sort the output by TargetNodeID according to its numeric value. Given
the example graph, the output file is like:
0 0 0.0
0 1 8.0
0 2 5.0
0 3 9.0
0 4 7.0
Cluster configuration:
Create a cluster with 3 nodes of instance type m3.xlarge. Create an S3
bucket with name “comp9313.
“problem2” in this bucket, and upload the input files “NA.cedge.txt” and
“SF.cedge.txt” into this folder. Use node “0” as the query node for both
graphs, and save your results in “problem2” as well. Finally, please make
the output folder public (right click the folder, and click “Make public”). Set
the name of the final result folder as: “NA”(“SF”)+“QueryNodeId”, and
store it in the HDFS output folder as specified in the main function
parameters (This means that you need to perform another MapReduce job to
extract the result).
Code format:
Name your java file as “SingleSourceSP.java”, and put it in the package
“comp9313.ass4”. Your program should take three parameters: the input file,
the output folder, and the query node id.
One difficulty of this problem is how to do the iterative MapReduce jobs
and how to check the termination criterion. You can download the code
template at:
https://webcms3.cse.unsw.edu.au/COMP9313/16s2/resources/5396, which
may help you to solve this problem.
https://webcms3.cse.unsw.edu.au/COMP9313/16s2/resources/5394
https://webcms3.cse.unsw.edu.au/COMP9313/16s2/resources/5395
https://webcms3.cse.unsw.edu.au/COMP9313/16s2/resources/5396
Notes
1. Create a project locally in Eclipse, test everything in your local computer,
and finally do it in EMR.
2. In the second problem, generate all intermediate results in HDFS, and
then extract the result as a single file, and save it in S3.
2. In the second problem, you can use more than one reducers when doing
the shortest path computation. However, when extracting the final result,
please just use one reducer to save the output into one file. You can also use
the HDFS API to extract the final result.
3. In problem2, we will randomly select 10 query nodes to check the
correctness of your algorithm.
Documentation and code readability
Your source code will be inspected and marked based on readability and
ease of understanding. The documentation (comments of the codes) in your
source code is also important. Below is an indicative marking scheme:
Result correctness: 80%
Code structure, Readability, and
Documentation: 20%
Submission:
Deadline: Monday 7th November 09:59:59 AM
Log in any CSE server (williams or wagner), and use the give command
below to submit your solutions:
$ give cs9313 assignment4 ReverseGraph.java SingleSourceSP.java
Or you can submit through:
https://cgi.cse.unsw.edu.au/~give/Student/give.php
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.
https://cgi.cse.unsw.edu.au/~give/Student/give.php
Late submission penalty
10% reduction of your marks for the 1st day, 30% reduction/day 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
discipline. 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 your knowledge or consent.