91猎奇

Course and Contact Information

• Instructor: Suneuy Kim
• Office Location: MacQuarrie Hall 217 (MH217)
• Telephone: 408-924-5122
• E-mail: suneuy.kim@sjsu.edu (Preferred mode of contact is via email.)
  • When you send me an e-mail to ask a question, use [Q] in a subject line to get a reply from me within a reasonable response time. Here is an example subject line to ask a question.

    [Q] lecture note

• Office Hours: M,W 11:50 AM - 12:50 PM at Zoom: (Meeting ID: 838 0090 4104)
• Class Days/Time/Classroom
  • Section 80 (Lecture): MW 9:00 am - 10:15 am at Zoom: Register in advance for this meeting:
  • Section 81 (Lecture): MW 10:30 am - 11:45 am at Zoom: Register in advance for this meeting:
• Course Prerequisites: CS157A (or a grade of C- or better)
  • This course involves a substantial amount of troubleshooting for system setup and deployment. Troubleshooting is entirely the student's responsibility. If this is something you don't expect from the course, you may reconsider taking it.
• at http://www.cs.sjsu.edu/~kim/cs157c
  Announcements and course materials will appear here. It is updated frequently. You are strongly encouraged to check out this course web page regularly.

Course Description

Course Learning Outcomes

• Know the main NoSQL data models: Key-value, column-family, document, and graph stores
• Perform comparative analysis on NoSQL data models and relational data model
• Understand data distribution methods: replication and sharding
• Understand master-slave and peer-to-peer replications
• Understand Brewer's CAP Theorem and its implications for NoSQL database systems
• Understand the essentials of NoSQL data management through the CRUD operations and the querying mechanisms
• Understand NoSQL database system components and their communication protocols for the read and write process
• Select an appropriate NoSQL database for the use case at hand and design applications to efficiently work with the chosen database

Course Topics

Required Texts/Readings

• Textbook: None required
• References (available online at 91猎奇 library)
  • NoSQL Distilled: A Brief Guide to the Emerging World of Polyglot Persistence by Parmod J. Sadalage and Martin Fowler
  • MongoDB: The Definitive Guide: Powerful and Scalable Data Storage, 3nd Edition by Kristina Chodorow, December 2020
  • The Definitive Guide to MongoDB: A Complete Guide to Dealing with Big Data using MongoDB, 3rd Edition by David Hows, Peter Membrey, Eelco Plugge and Tim Hawkins, December, 2015
  • Mastering Apache Cassandra 3.x, 3rd Edition by Nishant Neeraj, Tejaswi Malepati and Aaron Ploetz, October 2018
  • Cassandra: The Definitive Guide: Distributed Data at Web Scale by Jeff Carpenter and Eben Hewitt, July 2016
  • Seven Databases in Seven Weeks: A Guide to Modern Databases and the NoSQL Movement, 2nd Edition by Luc Perkins, Eric Redmond, and Jim Wilson, April 2018
  • Other readings: A list of additional references will be provided per topic as needed.

Course Requirements and Assignments

• Each class consists of a review about the previous class, the main lecture (recorded PowerPoint presentation), and a quiz through Zoom poll. The recording of the PowerPoint presentation will be paused at the end of each page for Q&A. Also, the recording will be frequently paused as needed to present relevant examples on the board. The zoom classes will not be recorded. Students can freely ask questions without concerns being recorded. However, the PowerPoint presentation recording will be available after each class. Notice that the PowerPoint presentation recordings alone cannot serve the purpose of fully learning the materials without supporting materials presented on the board which will not be recorded.
• Assignments: 4-5 individual assignments are given, unless otherwise specified.
• Team Project
  • A team of three people conducts the project.
  • The project involves configuring and deploying a NoSQL database, data population, and programming using API.
  • A 25 minute-long project presentation per team may be scheduled in case that the final report does not present the project work clearly and sufficiently.
  • The final result of the project will be submitted through the project submission link on the course web site.
  • I expect students to turn on video through out the class to keep lively atmosphere of teaching and learning.
• Submission/Late Policy
  • Any assignments/project turned in past the deadline will get a penalty: For each late day, a 20% of the maximum obtainable score of the work will be taken out of what you earned. (a late day is one 24 hour period beyond the due date). For example, suppose the maximum score of an assignment is 100, and you earned 80 points. If the submission is late by two days, the final score of the assignment would be 80 - 2 * 20 = 40.
  • Any submission turned in more than 48 hours past the deadline will result in a grade of zero for that assignment.
  • On-line submission: You can submit your work multiple times. If then, the latest one will be considered as the final submission. If the final submission is late, the late policy will be applied.
  • E-mail submissions will not be accepted for grading.
• Teamwork Policy
  • Once a team is formed, it will last throughout the semester. If you dissolve your team, a significant amount of penalty will be determined by the instructor and given to both parties.
  • For the project, students are expected to submit their peer evaluation in addition to the final report. The responsibility and contribution of every team member must be precisely documented in a peer evaluation form.
• Software (Students are responsible for setting up and deploy required software products. The instructor may not involve with troubleshooting.)
  • MongoDB
  • Cassandra
  • Docker
  • GIT
  • Linux (Ubuntu)
  • Programming Language: Java and/or Python
• Success in this course is based on the expectation that students will spend, for each unit of credit, a minimum of 45 hours over the length of the course (normally three hours per unit per week) for instruction, preparation/studying, or course related activities, including but not limited to internships, labs, and clinical practice. Other course structures will have equivalent workload expectations as described in the syllabus.

Evaluation (Exams)

• There will be one midterm exam and one comprehensive final exam. The exams are scheduled as below. The dates of midterm exams are subject to change with fair notice, but the final exam date is firm and cannot be changed.
  • Midterm Exam (Take-Home Exam): TBA
  • Final Exam (Traditional Exam): See the schedule below.
• Makeup Exam Policy Absolutely no make-up exams will be offered under any circumstances. For those who couldn't take the exam or worked hard but had a bad day on the exam day, ending up with a low score, I offer the following opportunity to replace your midterm score with the final score. (Only) If your final exam (percentage) grade is higher than your midterm (percentage) grade, then I will replace the midterm grade with your final exam grade. For example, if you have a 60% on your midterm and you receive an 80% on the final exam, I will replace the 60% by 80% in the computation of your course grade.

• I do not give any separate reviews for the final exam. In each class, I review what we learned in the previous class. Make sure to get these reviews, and then the collection of these reviews will serve as the review for the final. Also, I often explicitly emphasize particular topics due to their importance during the lecture. Do not miss them! They will greatly help you prepare for the final. Remember the lectures are not recorded.

Grading Information

• You will receive the final grade based on the weighted average score on your performance. The grading weights are as follows.
  
  • Assignments: 25%
  • Midterm: 24%
  • Final Exam: 35%
  • Project: 13%
  • Participation: 3% (poll in class)

• First I try scores of 90, 80, and 70 to cutoff letter grades of A-, B-, and C-, respectively. If overall class performance is too low to use these cut offs, I set a cut off of C- to a lower score than the class total average but a higher score than 60 (this number may change), and divide the students' group above the cut off of C- into A+, A, A-, B+, B, B-, C+, C, C-. The rest of students will be given by a grade of D+, D, D-, F or WU depending on their class performance.
• The same method will be applied to every student enrolled in the class including graduate students.

Technology Requirements

Students are responsible for ensuring that they have access to reliable Wi-Fi during tests. If students are unable to have reliable Wi-Fi, they must inform the instructor, as soon as possible or at the latest one week before the test date. See Learn Anywhere website (/learnanywhere/equipment/index.php) for current Wi-Fi options on campus.

Recording Zoom Classes

Online Exams

Proctoring Software and Exams

Testing Environment: Setup

• No earbuds, headphones, or headsets
• The environment is free of other people besides the student taking the test.
• No other browser or windows besides Canvas opened.
• A workplace that is clear of clutter (i.e., reference materials, notes, textbooks, cellphone, tablets, smart watches, monitors, keyboards, gaming consoles, etc.)
• Well-lit environment. Can see the students鈥� eyes and their whole face. Avoid having backlight from a window or other light source opposite the camera.

• Remain in the testing environment throughout the duration of the test.
• Keep full face in full view of the webcam

Technical difficulties

Contact the 91猎奇 technical support for Canvas:

Technical Support for Canvas Email: ecampus@sjsu.edu Phone: (408) 924-颅鈥�2337
/ecampus/support/

Classroom Protocol

• Policy on Academic Integrity
  • Any cheating on an exam will result in a grade of F in the class.
  • If duplicate programs are found, both the provider and the copier will receive 0 point on the assignment. A second offense results in a grade of F in the class.
  • Any incident of academic dishonesty will be reported to University for disciplinary action.
• Attendance: at http://www.sjsu.edu/senate/docs/F15-12.pdf states that "Students should attend all meetings of their classes, not only because they are responsible for material discussed therein, but because active participation is frequently essential to insure maximum benefit for all members of the class. Attendance per se shall not be used as a criterion for grading."
• Consent for Recording of Class and Public Sharing of Instructor Material
  : , http://www.sjsu.edu/senate/docs/S12-7.pdf, requires students to obtain instructor's permission to record the course:
  • "Common courtesy and professional behavior dictate that you notify someone when you are recording him/her. You must obtain the instructor's permission to make audio or video recordings in this class. Such permission allows the recordings to be used for your private, study purposes only. The recordings are the intellectual property of the instructor; you have not been given any rights to reproduce or distribute the material."
  • "Course material cannot be shared publicly without his/her approval. You may not publicly share or upload instructor generated material for this course such as exam questions, lecture notes, or homework solutions without instructor consent."

University Policies

• Per University Policy S16-9, university-wide policy information relevant to all courses, such as academic integrity, accommodations, etc. will be available on web page at http://www.sjsu.edu/gup/syllabusinfo/"
• Reference to deadlines pertaining to Spring 2023, please refer to /registrar/calendar/spring-2023.php

COVID-19 and Monkeypox

CS157C: NoSQL Database Systems, Spring 2023: Semester Schedule