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Data Compression Schemes as Compiler Transformations

Supervisor

Amir Shaikhha
(Research Associate, University College Research Associate, University College)

Suitable for

Mathematics and Computer Science, Part C
Computer Science, Part C
Computer Science and Philosophy, Part C
Computer Science, Part B

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.