CISC 5950, Fall 2020 Big Data Programming
CISC 5950 — Lab 1
We have completed three tasks in class,
1. Set up a 3-node cluster with Hadoop Distributed File System and run examples.
2. On top of HDFS, set up the cluster with MapReduce programming framework.
3. Run examples of MapReduce programs.
Based on our examples, we will develop our own MapReduce program to analysis a simple log
file. The following figure shows the structure of the log file.
Each line is a record of visit, which consists of IP Address, Time, Type of HTTP Request,
Requested File, HTTP Version and Status, etc.
Example Programs
We have provided two examples that related to this lab.
• logstat: It counts the number of visits for each IP address in the log file.
• logstat2: It counts the number of visits for each IP address in the same hour.
As discussed in the lectures, MapReduce programming framework seperates the data and op-
eration (two stages). It uses Hadoop Stream, which represents by sys.stdin in Python and
Writable, Text in Java.
Figure 1: Map Phase of logstat in Python
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CISC 5950, Fall 2020 Big Data Programming
Figure 2: Map Phase of logstat in Java
In Map phase, we have to process the raw files and extract the related information, line and
IP.
Figure 3: Reduce Phase of logstat in Python
In the Reduce phase, we start counting the records based on the same IP addresses. After that,
we can sort the result and print it out. As Fig. 5 and 6 present, the Map Phase for logstat2
is different than the previous version since we need to consider the time. Since we have pro-
cessed data at Map Phase, the intermediate data of Map is already at the granularity of a hour.
Therefore, the Reduce Phase is the same as logstat.
Lab 1 Assignment: Part 1 and 2
The given programs of logstat and logstat2 were written in both JAVA and Python.
Lab 1 consists of the following two parts.
1. Output the top-3 IP addresses with the granularity of an hour
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CISC 5950, Fall 2020 Big Data Programming
Figure 4: Reduce Phase of logstat in Java
Figure 5: Map Phase of logstat2 in Python
• You should read the two examples.
• Develop your code based on examples. The program may take more than one round
of MapReduce.
2. Make your program like a database search
• Your program should be able to accept parameters from users, such as 0-1, which
means from time 00:00 to 01:00, and output the top-3 IP addresses in the given time
period.
• Run it along with three other examples, WordCount, Sort, Grep, at the same time,
and test fair and capacity schedulers.
Grading Rubric
You should complete the lab in groups of 4 students.
(80%) Part 1;
(15%) Part 2;
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CISC 5950, Fall 2020 Big Data Programming
Figure 6: Map Phase of logstat2 in Java
(5%) Report about the your design and experiments, please include screenshots for run-
ning your code on the cloud;
Submission
You should email your submission (one per a group) by the end of Oct. 16.
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