Vertical partitioning algorithms for database design

By S. Navathe, S. Ceri, Gio Wiederhold, J. Dou. 1984

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Weijie Zhao
2. Mark D. Hill
3. Rui Ding
4. A. Ailamaki
5. David J. DeWitt
6. Mingming Sun
7. Yulei Qian
8. P. Li

Citations in the corpus

• Split learning for health: Distributed deep learning without sharing raw patient data (2018, background): “That said, with regards to non-neural network based federated learning techniques, the work in [27] shows their applicability to vertically partitioned distributed data [33, 34, 26, 35] shows applicability to multi-task learning in distributed settings.”
• Weaving Relations for Cache Performance (2001, background): “Vertical partitioning is the process of striping a relation into sub-relations, each containing the values of a subset of the initial relation’s attributes, in order to reduce I/O-related costs [24].”
• Distributed Hierarchical GPU Parameter Server for Massive Scale Deep Learning Ads Systems (2020, background): “It is another research axis–vertical partitioning (Navathe et al., 1984; Zhao et al., 2015) that is beyond the scope of this paper.”