Description
The required task is to simulate data partitioning approaches on-top of an open source relational database
management system (i.e., PostgreSQL). Each student must generate a set of Python functions that load the
input data into a relational table, partition the table using different horizontal fragmentation approaches,
and insert new tuples into the rightfragment.
Input Data. The input data is a Movie Rating data set collected from the MovieLens web site
(https://movielens.org). The raw data is available as comma separated text files where all ratings are contained in
the file ratings.dat.
The rating.dat file contains 10 million ratings and 100,000 tag applications applied to 10,000 movies by
72,000 users. Each line of this file represents one rating of one movie by one user, and has the following
format:
UserID::MovieID::Rating::Timestamp
The lines within this file are ordered first by UserID, then, within user, by MovieID. Ratings are made
on a 5-star scale, with half-star increments. Timestamps represent seconds since midnight Coordinated
Universal Time (UTC) of January 1, 1970. A sample of the file contents is given below:
1::122::5::838985046
1::185::5::838983525
1::231::5::838983392
Required Task. Below are the steps you need to follow to fulfill this assignment:
1. Download PostgreSQL (https://www.postgresql.org)
2. Download rating.dat file from the MovieLens website (https://files.grouplens.org/datasets/movielens/ml10m.zip)
3. Implement a Python function Load Ratings() that takes a file system path that contains the rating.dat
file as input. Load Ratings() then load the rating.dat content into a table (saved in PostgreSQL)
named Ratings that has the following schema
UserID – MovieID – Rating
4. Implement a Python function Range Partition() that takes as input: (1) the Ratings table stored in
PostgreSQL and (2) an integer value N; that represents the number of partitions. Range Partition()
then generates N horizontal fragments of the Ratings table and store them in PostgreSQL. The algorithm
should partition the ratings table based on N uniform ranges of the Rating attribute.
5. Implement a Python function RoundRobin Partition() that takes as input: (1) the Ratings table
stored in PostgreSQL and (2) an integer value N; that represents the number of partitions. The
function then generates N horizontal fragments of the Ratings table and stores them in PostgreSQL.
Thealgorithmshouldpartitionthe ratings tableusingthe roundrobinpartitioningapproach(explained
in class).
6. Implement a Python function RoundRobin Insert() that takes as input: (1) Ratings table stored in
PostgreSQL, (2) UserID, (3) ItemID, (4) Rating. RoundRobin Insert() then inserts a new tuple in
the right fragment (of the partitioned ratings table) based on the round robinapproach.
7. Implement a Python function Range Insert() that takes as input: (1) Ratings table stored in PostgreSQL
(2) UserID, (3) ItemID, (4) Rating. Range Insert() then inserts a new tuple in the correct
fragment (of the partitioned ratings table) based upon the Rating value.
8. Implement a Python function Delete Partitions() that deletes all generated partitions as well as
any metadata related to the partitioning scheme.
Frequently Asked Questions:
Partition numbers start from 0, if there are 3 partitions then range_part0, range_part1,
range_part2 are partition table names for range partitions and similar numbering
should be done for round robin partitions.
Do not change partition table names prefix given in assignment_tester.py
Do not hard code input filename.
Do not hard code database name.
Table schema should be equivalent to what has been described in point 3.
Use Python 2.7.x version.
Question with respect to Partitioning:
The number of partitions here refer to the number of tables to be created.
For rating values in [0, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5]
Case N = 1,
One table containing all the values.
Case N = 2,
Two tables,
Partition 1 has values [0,2.5]
Partition 2 has values (2.5,5]
Case N = 3,
Three tables,
Partition 1 has values [0, 1.67]
Partition 2 has values (1.67, 3.34]
Partition 3 has values (3.34, 5]
Uniform ranges means a region is divided uniformly, I hope the example gives a clear picture.
Please make use of Discussion Board extensively to clear any doubts.