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CS 145

Fall 2026 • Intro to Big Data Systems

Fall 2026 Schedule

Weeks 1 to 10 • Tue and Thu • Nov 3 holiday

SQL Systems nanoDB Transactions Distributed Systems
📅

Key Deadlines at a Glance

Subscribe to Calendar (.ics)
M1PSET M0 Sep 25
M1PSET M1 Oct 5
M2PSET M2 Oct 12
P1Project 1 Oct 16
M3PSET M3 Oct 19
P2Project 2 Proposal Oct 30
P2Project 2 Nov 20
M4PSET M4 Nov 9
M5PSET M5 Dec 4
Final Exam Dec 7, 7-10pm

Attendance Requirements (for non-SCPD students)

  • Final Exam: Mandatory in-class attendance for the Final Exam. No alternate exam schedules for those with exam conflicts. Please ensure you have no exam conflicts before enrolling in CS 145.
  • OAE accommodations: The exam will be on the same day with extended hours
Filter View:
Section Times: Wed 5P · Thu 10A · Fri 5P
Week Lectures (Tue / Thu) Sections (Wed / Thu / Fri) Deliverables
1
Sep 22, 24
M1
Basic SQL
Kickoff. SQLite and BigQuery intro. Mission briefing: gear up with SQL.
Wed / Thu / Fri — Pick One
Setup: BigQuery, Credits & Colab ↗
Setup: Canvas, Gradescope, Ed
Setup: BigQuery, Credits, Colab
Sep 25PSET M0
2
Sep 29, Oct 1
M1
Intermediate SQL
CTEs, subqueries, window functions.
M6
Patterns of Big Data Systems
A quick tour of where SQL actually runs in modern data systems — a preview of M6 before we go deeper later.
The first four "Small Data Patterns" case studies (1–100 GB): 6.1 · SQL vs Pandas & Polars 6.2 · SQL in Mobile (SQLite) 6.3 · Startup Architecture 6.4 · JSONB, Vectors & Geo
Wed / Thu / Fri — Pick One
Walkthrough: SQL Colab ↗
Clarification: PSET M1
No deliverables this week
3
Oct 6, 8
M2
Systems Basics
M3
nanoDB Foundations
BigSort. Hash partition. Foundations for nanoDB.
Wed / Thu / Fri — Pick One
Walkthrough: Systems Primer ↗
Walkthrough: Data Systems Intro ↗
Clarification: PSET M2
Oct 5PSET M1
4
Oct 13, 15
M3
Storage and Joins
Indexes. Joins. Query planning.
Wed / Thu / Fri — Pick One
Walkthrough: NanoDB Storage ↗
Clarification: Project 1 & PSET M3
Oct 12PSET M2
Oct 16Project 1
5
Oct 20, 22
M4
Transactions Intro
ACID properties. Ticketing case study.
Wed / Thu / Fri — Pick One
Walkthrough: Query Plan ↗
Clarification: PSET M3
Oct 19PSET M3
6
Oct 27, 29
M4
Concurrency Control
Concurrency control, 2PL, LSM Trees.
Wed / Thu / Fri — Pick One
Project 2 Deep-Dives
Parallel sessions on Systems and Science.
Clarification: Project 2 Questions
Oct 30Project 2 Proposal
7
Nov 3 (no class), Nov 5
M4
Recovery and Logging
Recovery logs (WAL).
Wed / Fri — Pick One
Walkthrough: Transactions Colab ↗
Full walkthrough: Macroschedules, Microschedules, WAL & Recovery.
No deliverables this week
8
Nov 10, 12
M5
Scaling Analytics
Part 1: Data designs, Parallelism. Distributed systems. Guest Speakers.
Wed / Thu / Fri — Pick One
Walkthrough: Data Systems (M1A) ↗
Walkthrough: Distributed SQL (PySpark) ↗
Clarification: Project 2 Details
Nov 9PSET M4
9
Nov 17, 19
M5
Distributed Systems
Sharding. Replication. Global consistency. Guest Spanner talk.
Wed / Thu / Fri — Pick One
Systems Design & PSET M5 Prep
Sharding, replication, consistency trade-offs.
Clarification: PSET M5 Details
Nov 20Project 2 (Data Science)
Nov 20Project 2 (Data Systems)
10
Nov 24, 26
Thanksgiving Break
—
No section this week
No deliverables this week
11
Dec 1, 3
Lessons from industry
Wed / Thu / Fri — Pick One
Walkthrough: Practice Problems ↗
Dec 4PSET M5
Finals
Dec 7
Final Exam 7–10 pm
—
No section
Dec 7 • Final Exam • 7–10 pm

About Sections

Your weekly section is for hands-on practice. Each session centers on a Colab walkthrough with your CA to build intuition about the underlying systems. Section is collaborative — if you're stuck, ask for help. If you have an insight, share it.

PSETs and Projects are due on Fridays. Attending section earlier in the week ensures you stay on track, resolve conceptual blockers early, and keep up with the material rather than cramming.

We use an online checkoff form strictly to record attendance and progress, not as a race for correct answers. Credit stems from your sincere participation. The ultimate goal is to practice, resolve open questions, and build technical mastery with your TAs and peers.

(Section design and philosophy inspired by Stanford CS111)