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Making an Embedded DBMS JIT-friendly

Authors Carl Friedrich Bolz, Darya Kurilova, Laurence Tratt

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Carl Friedrich Bolz
Darya Kurilova
Laurence Tratt

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Carl Friedrich Bolz, Darya Kurilova, and Laurence Tratt. Making an Embedded DBMS JIT-friendly. In 30th European Conference on Object-Oriented Programming (ECOOP 2016). Leibniz International Proceedings in Informatics (LIPIcs), Volume 56, pp. 4:1-4:24, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)
https://doi.org/10.4230/LIPIcs.ECOOP.2016.4

Abstract

While database management systems (DBMSs) are highly optimized, interactions across the boundary between the programming language (PL) and the DBMS are costly, even for in-process embedded DBMSs. In this paper, we show that programs that interact with the popular embedded DBMS SQLite can be significantly optimized -- by a factor of 3.4 in our benchmarks -- by inlining across the PL / DBMS boundary. We achieved this speed-up by replacing parts of SQLite's C interpreter with RPython code and composing the resulting meta-tracing virtual machine (VM) -- called SQPyte -- with the PyPy VM. SQPyte does not compromise stand-alone SQL performance and is 2.2% faster than SQLite on the widely used TPC-H benchmark suite.
Keywords
  • DBMSs
  • JIT
  • performance
  • tracing

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