Description
Objective:
This assignment will help you learn some key services of AWS platform, and GCP platform. In this assignment,
you are required to work on AWS Lambda/SQS/SNS, Google BigQueryML
Plagiarism Policy:
• This assignment is an individual task. Collaboration of any type amounts to a violation of the
academic integrity policy and will be reported to the AIO.
• Content cannot be copied verbatim from any source(s). Please understand the concept and write in
your own words. In addition, cite the actual source. Failing to do so will be considered as plagiarism
and/or cheating.
• The Dalhousie Academic Integrity policy applies to all material submitted as part of this course.
Please understand the policy, which is available at:
https://www.dal.ca/dept/university_secretariat/academic-integrity.html
Assignment Rubric – based on the discussion board rubric (McKinney, 2018)
Excellent (25%) Proficient (15%) Marginal (5%) Unacceptable (0%) Problem # where
applied
Completeness
including
Citation
All required tasks
are completed
Submission
highlights tasks
completion.
However, missed
some tasks in
between, which
created a
disconnection
Some tasks are
completed, which
are disjoint in
nature.
Incorrect and
irrelevant
Part A
Part B
Correctness All parts of the
given tasks are
correct
Most of the given
tasks are correct
However, some
portions need minor
modifications.
Most of the given
tasks are incorrect.
The submission
requires major
modifications.
Incorrect and
unacceptable
Part A
Part B
Novelty The submission
contains novel
contribution in key
segments, which is
a clear indication
of application
knowledge.
The submission
lacks novel
contributions. There
are some evidence of
novelty, however, it
is not significant
The submission
does not contain
novel
contributions.
However, there is
an evidence of
some effort.
There is no novelty Part A
Part B
Clarity The written or
graphical
materials, and
developed
applications
The written or
graphical materials,
and developed
applications do not
show clear picture of
The written or
graphical materials,
and developed
applications fail to
prove the clarity.
Failed to prove the
clarity. Need proper
background
knowledge to perform
the tasks.
Part A
Part B
provide a clear
picture of the
concept and
highlights the
clarity.
the concept. There is
room for
improvement
Background
knowledge is
needed.
Citation:
McKinney, B. (2018). The impact of program-wide discussion board grading rubrics on students’ and faculty satisfaction. Online
Learning, 22(2), 289-299.
Tasks:
This assignment has 2 parts. Part A is related to coding, development, and testing. Part B is
an experiment related to GCP BigQueryML
Part A. Use AWS Lambda-SQS-SNS:
take screenshots at every step and submit as part of the PDF:
a. Alice and Emily work at HfxDine, which is a cloud kitchen that provides delivery service. They
receive orders online. Alice delivers food parcels, and Emily prepares it.
b. The customers’ orders are added to a Queue (standard SQS) –
• Assume a program is sending random food order messages to HfxDine
• This message simulates how a customer places an order to an online store. (You can
ignore, price/tax etc)
• The program should randomly pick one combo meal from a list, create a message body,
and send to HfxDine
c. Emily periodically (every 500 ms or any delay of your choice) checks, if there is any order in the
Queue.
d. If message is available, it is assumed Emily has packed the combo meal, and then a notification
service (SNS) is triggered which sends the details to Alice’s email (Your email in this case)
Part A – Submission requirement:
Submit screenshots of every steps. Please do not exclude any steps. Include all screenshots as part of a
PDF file. In addition, provide the program/scripts as part of the PDF file. Submit code as part of PDF and also
upload the code in gitlab.
Part B. Use GCP BigQueryML:
take screenshots at every step and submit as part of the PDF:
a. Read and understand GCP BigQueryML, which you will need to create KMeans cluster of the given
dataset.
https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-createkmeans
b. Use the given dataset “SDey_FTP_input.csv” as your training dataset and test dataset to form and
test the model. The dataset contains two columns, vector1 and vector2. Use Euclidean distance as
the distance type to measure distance between the given vectors
Program Standard
Queue
Lambda Poll
SQS
Notification
Service
Fixed Food list containing combo meals
E.g. {(pasta+pop), (pizza+pop) etc.} Random selection
Simulated Customer Emily_lambda Alice
Alice’s Email = Your DAL Email
c. Create a random sampling with 75% of the record that is available in the given file as training set
and remaining 25% as the test set.
d. You can create the two datasets (training and test) before performing the BigQueryML operation.
e. If you need clarification about this specific problem, do not hesitate to ask me (send me email or
message on Teams)
Part B- Submission requirement:
Submit screenshots of every steps. Please do not exclude any steps. Include all screenshots as part of a
PDF file. In addition, provide any program/query as part of the PDF file. Submit any code you write for this
problem as part of PDF and upload the code in gitlab.
