An Algebraic Compression Framework for Query Results

Decision-support applications in emerging environments require that SQL query results or intermediate results are shipped to clients for further analysis and presentation. These clients may use low bandwidth connections or have severe memory restrictions. Consequently, there is a need to compress the results of a query for efficient transfer and client-side access. This paper explores a variety of techniques that address this issue. We present a framework to represent "compression plans" formed by composing primitive compression operators. We also present optimization algorithms that enumerate valid compression plans and choose an optimal plan. The factors that influence this choice include statistical and semantic information on the query result. Using queries adapted from the TPC-D benchmark, we demonstrate that our techniques can on average result in 86% greater compression than standard tools like WinZip. 1 Introduction Most database applications have multi-tier client-server arc..