Winter 2025
[Previous Offerings: Winter 2019,
Winter 2020,
Winter 2021,
Winter 2022,
Winter 2023,
Winter 2024]
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Instructor: Mohammad Sadoghi |
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Teaching Fellow: Apratim Shukla |
Teaching Fellow: Shaokang Xie |
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Lecture |
Discussions Sessions |
This is an innovative data management course that provides an introduction
to the design and development of fundamental concepts in relational database
management systems (DBMS). You will learn the theory and design behind database
systems, the issues that affect their functionality and performance, and
most importantly, what it takes to effectively utilize modern databases in practice.
The course has completely been redesigned; all students are expected to work
in groups of five on an exciting, open-ended, data-oriented, quarter-long project,
in a sense, operating and simulating startup environments. Needless to say,
this rewarding experience is accompanied by a significant development effort (in Python)
that spans hands-on experience on concepts such as memory and disk management,
synchronization and concurrency, logging and recovery, and query optimization
and evaluation, to name a few. To materialize these objectives, together this quarter,
we will be building simplified L-Store
[Paper, Slides]
from scratch, an Hybrid Transactional and Analytical Processing (HTAP) database.
The coursework is complementary to the classical well-formed, prescriptive
model of assignments/projects that are indeed effective and invaluable in practice.
Instead by design, the project is intended to be open-ended, namely, minimal
instructions and requirements will be provided, as such it rewards and values
research & development, taking risks, above all, it is aimed to foster and
tap into the creativity of each individual.
The quarter-long project is broken into a set of three milestones. You will have
a choice on how your milestone will be graded. Either (1) the entire grade will
be determined by the autograder
or (2) 50% of the grade will be determined by the
autograder and 50% will be
determined through oral presentation. Prior to the deadline
for each milestone, each group must decide between option (1) or (2); once each group
submits their choice, this cannot be changed for that milestone. Each group must vote on
option (1) or (2) internally, and the vote of the majority will determine the choice.
For those who choose the presentation option, it must be done by all five group members,
and each group member must be ready to answer questions about any aspect of the project;
the latter is the utmost importance of ensuring a comprehensive learning experience and
fair division of work among all members.
Furthermore, in each milestone, a bonus of up to 10% can be gained to further encourage
taking a risk, going the extra mile, and to just be curious & creative. Part of the
bonus is reserved for the fastest and the most optimized implementation of L-Store in
class, e.g., how many read/write operations per second (adjusted based on the number of
cores, CPU clock frequency, amount of memory, cache size, and other hardware metrics to
ensure comparable results).
The design bonus will be only determined as part of the presentation, while the
performance bonus will be determined by the
autograder.
A fact of life is that when there is group work, whether at school or in society,
there are occasional conflicts; it is crucial to learn how to
resolve our differences and be receptive, open, and kind to one another. In
kindness and reflection, we shall aim to resolve all conflicts. It is the group
responsibility to handle all internal affairs, and only when absolutely necessary
involving the instructor. But note, only under very rare exceptional circumstances,
a group re-structuring would be granted because once the group is formed, at least
for 10 weeks, we must learn how to work with each other in harmony.
For each group, it is recommended that each member lead one aspect of the project
while contributing and learning about other parts; roughly, the main components
are
(1) memory management (e.g., bufferpool),
(2) disk management (e.g., persistence and logging),
(3) in-memory indexing (e.g., hashing or tree),
(4) data access methods (e.g., APIs and query language),
(5) multi-threading and synchronization (e.g., data structures latching),
(6) transaction and concurrency (e.g., record-level locking), and
(7) testing and benchmarking (correctness verification and performance measurements).
As for the lectures, the list of topics covered would include but not limited to:
Grades will be made available on your Canvas account.
