Data Compression Schemes as Compiler Transformations
Supervisor
Amir Shaikhha
(Research Associate, University College Research Associate, University College)
Suitable for
Abstract
Compression algorithms can improve the runtime performance and memory usage of database systems. This improvement is more
obvious in the context of column-store database systems. On the other hand, with the advent of in-memory database systems,
query compilers are getting more important. As a result, using compilation techniques in database development is gaining more
attention. DBLAB is a framework for building database systems using high-level programming, producing optimized code in a
low-level language like C. This is achieved through compilation techniques implemented in an extensible optimizing compiler
called SC (Systems Compiler). The suggested project combines these two aspects. To be more concrete, we would like to implement
different compression schemes using compilation transformations, which will be encoded using SC and added to DBLAB.