Query Optimization In Compressed Database Systems

Over the last decades, improvements in CPU speed have outpaced improvements in main memory and disk access rates by orders of magnitude, enabling the use of data compression techniques to improve the performance of database systems. Previous work describes the benefits of compression for numerical attributes, where data is stored in compressed format on disk. Despite the abundance of stringvalued attributes in relational schemas there is little work on compression for string attributes in a database context. Moreover, none of the previous work suitably addresses the role of the query optimizer: During query execution, data is either eagerly decompressed when it is read into main memory, or data lazily stays compressed in main memory and is decompressed on demand only. In this paper, we present an effective approach for database compression based on lightweight, attribute-level compression techniques. We propose a Hierarchical Dictionary Encoding strategy that intelligently selects the...

• Type: Conference
• Year: 2001
• Where: SIGMOD
• Authors: Zhiyuan Chen, Johannes Gehrke, Flip Korn
• Keywords: Compressed Attributes, Data Compression Techniques, Database, SIGMOD 2001, String Compression Methods