Micro-Specialization: Dynamic Code Specialization in DBMSes

Abstract

Database management systems (DBMSes) form a cornerstone of modern IT infrastructure, and it is essential that they have excellent performance. In this research, we exploit the opportunities of applying dynamic code specialization to DBMSes, particularly by focusing on runtime invariant present in DBMSes during query evaluation. Query evaluation involves extensive references to the relational schema, predicate values, and join types, which are all invariant during query evaluation, and thus are subject to dynamic value-based code specialization. We observe that DBMSes are general in the sense that they must contend with arbitrary schemas, queries, and modifications; this generality is implemented using runtime metadata lookups and tests that ensure that control is channelled to the appropriate code in all cases. Unfortunately, these lookups and tests are carried out even when information is available that renders some of these operations superfluous, leading to unnecessary runtime overheads. We introduce micro-specialization, an approach that uses relation- and query-specific information to specialize the DBMS code at runtime and thereby eliminate some of these overheads. We develop a taxonomy of approaches and specialization times and propose a general architecture that isolates most of the creation and execution of the specialized code sequences in a separate DBMS-independent module. We show that this approach requires minimal changes to a DBMS and can improve the performance simultaneously across a wide range of queries, modifications, and bulk-loading, in terms of storage, CPU usage, and I/O time of the TPC-H and TPC-C benchmarks. We also discuss an integrated development environment that helps DBMS developers apply micro-specializations to identified target code sequences.