Please use this identifier to cite or link to this item:
https://scholarbank.nus.edu.sg/handle/10635/164190
Title: | EFFICIENT OLAP FOR BIG DATA | Authors: | XIE ZHONGLE | ORCID iD: | orcid.org/0000-0002-2924-6974 | Keywords: | OLAP, DATABASE SYSTEM, COHORT ANALYSIS, INDEX, SKIP LIST, TIME SERIES ANALYSIS | Issue Date: | 20-Dec-2019 | Citation: | XIE ZHONGLE (2019-12-20). EFFICIENT OLAP FOR BIG DATA. ScholarBank@NUS Repository. | Abstract: | OnLine Analytical Processing (OLAP) faces many challenges in the era of big data. The exploded volume of the immutable data hinders OLAP system achieving high service level agreement with traditional indexing mechanisms. Further, the traditional OLAP system can hardly support new analysis queries such as cohort query or its variant in user behavioral data. In this dissertation, starting from the data indexing in storage layer to query processing engine, we present a general framework for emerging OLAP system in a bottom-up manner. | URI: | https://scholarbank.nus.edu.sg/handle/10635/164190 |
Appears in Collections: | Ph.D Theses (Open) |
Show full item record
Files in This Item:
File | Description | Size | Format | Access Settings | Version | |
---|---|---|---|---|---|---|
XieZL.pdf | 5.03 MB | Adobe PDF | OPEN | None | View/Download |
Google ScholarTM
Check
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.