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Course Syllabus: CS591 K1 Data Stream Processing and Analytics (Spring 2020)

Instructor Name: Vasiliki Kalavri
Office Location: MCS 206
Contact Information: vkalavri@bu.edu
Course Time & Location: Tue/Thu 9:30-10:45, MCS B33
Office Hours: Tue 11:00-12:30, Thu 15:00-16:30, MCS 206

Courseware

• We will use the course website to maintain an up-to-date class schedule.
• We will use Piazza for discussions on course topics, as well as questions and clarifications regarding the assignments and the final project. You may also post on Piazza if you have any question on course logistics.
• We will use Blackboard for quizzes, assignment announcements and assignment submissions.

Course Description

For a description of topics covered in this course, please see the overview in the course website. During the semester, you will learn about the following three aspects of stream processing:

• Systems
  • Architecture and design
  • Scalability and elasticity
  • Fault-tolerance and processing guarantees
  • State management
• Algorithms
  • Windowing semantics and optimizations
  • Basic data stream mining
  • Probabilistic streaming algorithms
• Streaming applications and use-cases

Course Objectives

The course aims at training students in fundamental and emerging topics of data stream processing. At the end of the course, successful students will have acquired the necessary knowledge in order to:

• know when to use stream processing
• be able to comprehensively compare the features and processing guarantees of streaming systems
• efficiently use Apache Flink and Kafka to build end-to-end, scalable, and reliable streaming applications
• have a solid understanding of how stream processing systems work and what factors affect their performance
• be aware of the challenges and trade-offs one needs to consider when designing and deploying streaming applications

Course Materials

There is no required textbook for this class. After each lecture, slides will be published on the course website, in the “Slides” column of the lecture schedule. Further publicly available resources are listed in the course website, under “Readings”. Parts of the resources listed there will be given as (non-graded) reading assignments during the course. You should be able to access all of these for free when connected to the campus network.

Class Schedule

Please see the schedule on the course website.

Grading Scheme

The course consists of lectures, exercises, and a final semester project. There is no formal examination at the end of the course. Your final grade will be determined as follows:

• 5 in-class quizzes (10%):
  • Each quiz contributes 2% to the final grade.
• 3 hands-on assignments (40%):
  • Assignment #1 contributes 10%.
  • Assignment #2 contributes 10%.
  • Assignment #3 contirbutes 20%.
• The final project (50%):
  • One (1) written report of maximum 5 pages will contribte 10%.
  • The full code implementing the analytics tasks as defined in the project description document, as well as any auxiliary code for data pre-processing, deployment, and testing will contribute 40%. To be considered complete, code deliverables must be accompanied by sufficient documentation.

Assignment Submission

All assignments and the final project will be submitted via the course Blackboard. All assignments, as well as the final project, are due by latest 11:59pm on the day of the respective deadline.

Late work policy

Students who submit homework late will only be eligible for up to 50% of the original score.

Attendance

Students are expected to attend each class session unless they have a valid reason for being absent. Acceptable excused absences include observing religious holidays and illness. In such cases, students are advised to contact the instructor as soon as possible, so that reasonable accommodations can be provided. Please review the BU attendance policy and the BU Policy on Religious Observance for more information.

Academic Conduct

All assignments must be completed individually. Discussion with fellow students via Piazza or in-person are encouraged, but presenting the work of another person as your own is expressly forbidden. This includes “borrowing”, “stealing”, copying programs/solutions or parts of them from others. Note that we may use an automated plagiarism checker. Cheating will not be tolerated under any circumstances.

Please review the BU Academic Conduct Code for more information.

Supporting Students With Disabilities

If you are a student with a disability or believe you might have a disability that requires accommodations, please contact the Office for Disability Services (ODS) at (617) 353-3658 or access@bu.edu to coordinate any reasonable accommodation requests. ODS is located at 25 Buick Street on the 3rd floor.