Starting from:

$29

Assignment 3 Generic parallel sort

Assignment 3
Maximum possible points: 6
The required task is to build a generic parallel sort and parallel join algorithm.
1. Implement a Python function ParallelSort() that takes as input: (1) InputTable stored in
a PostgreSQL database, (2) SortingColumnName the name of the column used to order
the tuples by. ParallelSort() then sorts all tuples (using five parallelized threads) and
stores the sorted tuples for in a table named OutputTable (the output table name is
passed to the function). The OutputTable contains all the tuple present in InputTable
sorted in ascending order.
Function Interface: -
ParallelSort (InputTable, SortingColumnName, OutputTable, openconnection)
InputTable – Name of the table on which sorting needs to be done.
SortingColumnName – Name of the column on which sorting needs to be done, would
be either of type integer or real or float. Basically Numeric format. Will be Sorted in
Ascending order.
OutputTable – Name of the table where the output needs to be stored.
openconnection – connection to the database.
2. Implement a Python function ParallelJoin() that takes as input: (1) InputTable1 and
InputTable2 table stored in a PostgreSQL database, (2) Table1JoinColumn and
Table2JoinColumn that represent the join key in each input table respectively.
ParallelJoin() then joins both InputTable1 and InputTable2 (using five parallelized
threads) and stored the resulting joined tuples in a table named OutputTable (the output
table name is passed to the function). The schema of OutputTable should be
InputTable1.Column1, InputTable.Column2, …, InputTable2.Column1,
InputTable2.Column2….
Function Interface: -
ParallelJoin (InputTable1, InputTable2, Table1JoinColumn, Table2JoinColumn,
OutputTable, openconnection)
InputTable1 – Name of the first table on which you need to perform join.
InputTable2 – Name of the second table on which you need to perform join.
Table1JoinColumn – Name of the column from first table i.e. join key for first table.
Table2JoinColumn – Name of the column from second table i.e. join key for second
table.
OutputTable - Name of the table where the output needs to be stored.
openconnection – connection to the database.
Naming Convention to be followed strictly:
Database name – ddsassignment3
Postgres User name – postgres
Postgres password – 1234
Instructions on how this will be tested: -
Please follow these instructions closely.
1. Two tables would be created in the database manually.
2. The created tables would contain at least an integer field, which would be used for both
Parallel Sorting and Parallel Joining.
3. Then, the ParallelSort() and ParallelJoin() Function would be called to check the
correctness of the program.
4. Your code should use 5 threads for both ParallelSort() as well as ParallelJoin().
5. Your code should be able to handle table irrespective of its schema.
6. Do not make your code dependent on any particular table; it should be able to work on
any table and any given input columns.
2 Instructions for Assignment: -
Please follow these instructions closely else Marks will be deducted.
1. Please follow the function signature as provided in the Assignment3_Interfacy.py.
2. Please use the same database name, table name, user name and password as provided in
the assignment to keep it consistent.
3. Please make sure to run the file before submitting and make sure there is no indentation
error. In case of any compilation error, 0 marks will be given.
4. Do not modify any function signature in Assignment3_Interface.py. In case any
modification is needed, please post the same on discussion board.
5. For any case of doubt in the assignment, PLEASE USE Discussion Boards, Individual
mails would not be entertained.
6. Also, It is an individual’s responsibilities to clarify his/her doubts, so read and use
Discussion Board extensively.
Submission Instructions: -
Submit Assignment3_Interface.py directly to Canvas. Do not upload *.zip files or change its name.
Note: -
Failure to follow the instructions provided in the document will result in 0.5 point loss.

More products