DS 4300 — Large-Scale Information Storage and Retrieval
4 semester hoursUndergraduateLectureNUpath ADusually offered: springtypical days: T/FBostonOnlineOnlineTraditional
Introduces data and information storage approaches for structured and unstructured data. Covers how to build large-scale information storage structures using distributed storage facilities. Explores data quality assurance, storage reliability, and challenges of working with very large data volumes. Studies how to model multidimensional data. Implements distributed databases. Considers multitier storage design, storage area networks, and distributed data stores. Applies algorithms, including graph traversal, hashing, and sorting, to complex data storage systems. Considers complexity theory and hardness of large-scale data storage and retrieval. Requires use of nonrelational, document, key-column, key-value, and graph databases and programming in R, Python, and C++.
Prerequisites
Offering history
| Term | Sections | Enrolled | Capacity | Full | Open seats/section |
|---|---|---|---|---|---|
| Spring 2024 | 1 | 196 | 200 | 98% | 4.0 |
| Fall 2024 | 1 | 54 | 87 | 62% | 33.0 |
| Spring 2025 | 1 | 173 | 175 | 99% | 2.0 |
| Spring 2026 | 1 | 273 | 280 | 98% | 7.0 |
Snapshots from scheduled scrapes — not live seat availability. "Full" can exceed 100% when sections over-enroll.
Meeting times
Share of recent sections by weekday: M 33% · T 67% · W 33% · Th 33% · F 67%
Common patterns: TF (67% of sections), MWR (33% of sections) — in patterns, R means Thursday
Professors
Fall
- Mark Fontenot (100% of students) · reviews
Spring
- John Rachlin (73% of students) · reviews
- Mark Fontenot (27% of students) · reviews
Percentages are each professor's average share of the season's enrolled students in recent terms.
Links
Official catalog (DS course descriptions) · Student reviews on RateMyHusky · All DS courses · Plan it at numap.app