Compiling Database Application Programs

TL;DR

This paper presents an automated compiler that specializes database application programs, significantly improving performance over manual optimization by applying advanced compiler techniques and generative programming.

Contribution

It introduces a novel compiler approach for database scripts that automates key optimizations, outperforming manual tuning on a standard benchmark.

Findings

Automated compiler outperforms manual baseline by a factor of two.

Key optimization techniques are identified and their individual impacts analyzed.

Compiler automates complex optimizations for database application programs.

Abstract

There is a trend towards increased specialization of data management software for performance reasons. In this paper, we study the automatic specialization and optimization of database application programs -- sequences of queries and updates, augmented with control flow constructs as they appear in database scripts, UDFs, transactional workloads and triggers in languages such as PL/SQL. We show how to build an optimizing compiler for database application programs using generative programming and state-of-the-art compiler technology. We evaluate a hand-optimized low-level implementation of TPC-C, and identify the key optimization techniques that account for its good performance. Our compiler fully automates these optimizations and, applied to this benchmark, outperforms the manually optimized baseline by a factor of two. By selectively disabling some of the optimizations in the compiler, we derive a clinical and precise way of obtaining insight into their individual performance contributions.