LEFTERIS SIDIROURGOS's TALK ON DB SEMINAR

Title: "Column Imprints: A Secondary Index Structure"
 

Abstract:
Large scale data warehouses rely heavily on secondary indexes, such as bitmaps and b-trees, to limit access to slow IO devices. However, with the advent of large main memory systems, cache conscious secondary indexes are needed to improve also the transfer bandwidth between memory and cpu. In this presentation, we introduce column imprint, a simple but efficient cache conscious secondary index. A column imprint is a collection of many small bit vectors, each indexing the data points of a single cacheline. An imprint is used during query evaluation to limit data access and thus minimize memory traffic. The compression for imprints is cpu friendly and exploits the empirical observation that data often
exhibits local clustering or partial ordering as a side-effect of the construction process. Most importantly, column imprint compression remains effective and robust even in the case of unclustered data, while other state-of-the-art solutions fail. We conducted an extensive experimental evaluation to assess the applicability and the performance impact of the column imprints. The storage overhead, when experimenting with real world datasets, is just a few percent over the size of the columns being indexed. The evaluation time for over 40000 range queries of varying selectivity revealed the efficiency of the proposed index compared to zonemaps and bitmaps with WAH compression.

Bio:
Lefteris Sidirourgos is a doctoral candidate at Centrum Wiskunde & Informatica (CWI) in Amsterdam. His research interests include database system design and data management. He received his Bachelor's degree in Mathematics and his Master's in Computer Science from University of Crete.