Introduction to the use, design, and implementation of database and data-intensive systems.
This course covers how to build data applications, and key principles on how to build and scale big data systems. Taught by Shiva Shivakumar.
A few key topics:
Prerequisites CS 103 and CS 107 (or equivalent). Basic knowledege of OS and algorithms (in RAM)
Grading Projects: 40% (10 + 30), Exam #1: 20%, Exam #2: 35%, PSETs: 5%
For students taking the course on a credit/no-credit basis: you need to score equivalent to at least a C grade to pass the course. We cannot provide the exact score threshold since the course is curved at the end of the quarter.
We will be offering extra credit for in class participation.
Ed and Gradescope: please access course Ed and Gradescope on the canvas tab.
Conflict in exams or course schedule Due to the large course enrollment number, we won’t be able to accommodate alternate exam schedules for those who have exam conflicts (both midterm and final). Please make sure you do not have a conflict in exam schedules when enrolling in CS 145.
Late Days You can use a total of two late days (24 hours each, not pro-rated) shared between both project deadlines. You do not lose any credit when using a late day. If you run out of late days and need additional time, you can submit after the deadline -- you will receive a 10% deduction for the 1st 24 hours after the deadline, 25% deduction for the next 24 hours, and zero credit after that. It's by 24 hours, no proration (for seconds, hours, etc)
Lectures Lectures occur on Tues/Thurs 4:30-5:50 p.m. in NVIDIA Auditorium. NOTE that while attendance is not mandatory, we will be giving out extra credit for students with insightful in-class participation.
Lecture Videos Lecture videos will be recorded and posted on Canvas.
Students must adhere to The Stanford Honor Code and The Stanford Honor Code as it pertains to CS courses.
We encourage students to form study groups. Students may discuss and work on homework problems in groups. However, each student must write down the solution independently, and without referring to written notes from the joint session.
It is an honor code violation to copy, refer to, or look at written or code solutions from a previous year, including but not limited to: official solutions from a previous year, solutions posted online, and solutions you or someone else may have written up in a previous year. Furthermore, it is an honor code violation to post your assignment solutions online, such as on a public git repo.
The teaching staff will be using plagiarism detection software and if we have reason to believe that you are in violation of the honor code, we will follow the university policy to report it.
| Dates | Topics | Lectures | Run Colabs | Reading from Course Notes | Events |
|---|---|---|---|---|---|
| 9/26 | SQL basics | Intro/Logistics, SQL slides | Colab #1 Section 1 (SQL) | Pg 1-16 | |
| 9/28 | SQL labs (JOINs, Aggregates) | Lecture 1 slides, SQL Project 1 released on Ed | Colab #1 Section 1 (SQL) | Pg 17-23 | SQL Project 1 released on Ed. Signup for GCP credits |
| 10/3 | SQL intermediate (Common Table Expressions, Window functions) | SQL slides | Colab #1 Section 2,3 (SQL) | Pg 24-36 | PSET 0 Due (Pre-reqs) |
| 10/5 | Hybrid of SQL and Alternatives | SQL slides | Colab #1 Section 4 (SQL) | Finish Section 1 | PSET 1 Due (Basic SQL) |
| 10/10 | Systems Primer & nanoDB Storage, BigSort, Hashing Algorithms | nanoDB slides | Colab #2 Section 1 (NanoDB) | Cases 6, 6.1, 6.2 | PSET 2 Due |
| 10/12 | IO Complexity, Basic Indexing | nanoDB slides | Colab #3 (Hashing) | Cases 7-8.3 | SQL Project 1 Due. SQL Project 2 Released |
| 10/17 | Intermediate Indexing | nanoDB slides | Colab #2 Section 2 (NanoDB) | Finish Section 2 | |
| 10/19 | JOIN Algorithms | nanoDB slides | Colab #2 Section 3 (NanoDB) | Cases 10.1, 10.2 | |
| 10/24 | nanoDB slides | NanoDB | Finish Section 3 | ||
| 10/26 | File systems, MapReduce/Spark. Tips for Project 2 | Spark slides | Lecture | PSET #3 due -- no extensions. SQL Project 2 Proposal due | |
| 10/31 | Midterm review | Midterm review | Lecture | ||
| 11/2 | Midterm in class |