Seminar Database Systems (PhD, MSc, BSc)

Overview and objectives: The area of this year's seminar is Algorithms and Systems for Data Science. Students learn how to critically read and study research papers, how to summarize the contents of a paper, and how to present it in a seminar.

Teaching format: Each participant writes a self-contained report of about 10 pages and gives a 30 minutes presentation (blackboard, without a computer). Each participant has a buddy. Buddies read the report, make suggestions for improvements, and help with the presentation (e.g., dry runs). The first version of the report is due three weeks before the date of the presentation. This first version of the report and presentation will be discussed with the buddy and the teacher about two weeks before the presentation. The final versions of the report are due one week before the presentation.

Setup and Organization: The setup of the seminar will be discussed Tuesday, February 19, 2019 from 16:30 until 18:00 in room (tba) at UZH. At the first meeting the available slots for the seminar will be distributed and papers will be assigned.

Presentations:

• Saturday April 13, BIN 2.A.01
• ​Saturday May 11, CAB H.52 (we meet in front of the south entry (the one closest to the tram stop ETH/Universitätspital) at 8:50)

Participation at all three meetings is compulsory. The assessment depends on the quality of the report, presentation, active participation during the seminar, and input as a buddy.

Useful links:

• organizational slides (PDF, 64 KB)
• How to give talks and read papers: link

Topics

1. Architectures and Systems

• MISO: Souping up Big Data Query Processing with a Multistore System , SIGMOD 2014. (PDF, 2 MB)
• RHEEM: Enabling Cross-Platform Data Processing, PVLDB 2018. (PDF, 1 MB)
• Abstraction for Advanced In-Database Analytics, PVLDB 2018. (PDF, 554 KB)

2. Column Stores

• Column Sketches: A Scan Accelerator for Rapid and Robust Predicate Evaluation, SIGMOD 2018. (PDF, 1 MB)
• Column-Stores vs. Row-Stores: How Different Are TheyReally?, SIGMOD 2008. (PDF, 789 KB)
• Access Path Selection in Main-Memory Optimized Data Systems: Should I Scan or Should I Probe?, SIGMOD 2017. (PDF, 683 KB)

3. Streams

• Incremental Query Processing on Big Data Streams, TKDE 2016. (PDF, 433 KB)
• The Stratosphere Platform for Big Data Analytics , VLDB Journal 2014. (PDF, 2 MB)
• Drizzle: Fast and Adaptable Stream Processing at Scale, SOSP 2017. (PDF, 767 KB)

4. Spark

• Spark SQL: Relational Data Processing in Spark , SIGMOD 2015. (PDF, 984 KB)
• SHC: Distributed Query Processing for Non-Relational Data Store, ICDE 2018. (PDF, 892 KB)
• Flare: Optimizing Apache Spark with Native Compilation for Scale-Up Architectures and Medium-Size Data, OSDI 2018. (PDF, 711 KB)

5. Query Processing

• A Minimal Variance Estimator for the Cardinality of Big Data Set Intersection . KDD 2017. (PDF, 720 KB)
• Orca: A Modular Query Optimizer Architecture for Big Data, SIGMOD 2014. (PDF, 1 MB)
• Optimizing Big Data Queries Using Program Synthesis, SOSP 2017. (PDF, 1018 KB)

6. Clustering

• Clustering with Same-Cluster Queries. NIPS 2016. (PDF, 274 KB)
• A Hierarchical Algorithm for Extreme Clustering. KDD 2017. (PDF, 1 MB)
• Coconut: A Scalable Bottom-Up Approach for Building Data Series Indexes . VLDB 2018. (PDF, 1 MB)

Saturday, April 13, 2019

Saturday, May 11, 2019