Automatic Partitioning of Database Applications

TL;DR

Pyxis automatically partitions database applications into server and database code, reducing latency and improving throughput by minimizing control transfers and data sent, thus simplifying performance optimization.

Contribution

Introduction of Pyxis, an automated system that profiles, analyzes, and partitions database applications to optimize performance without manual conversion to stored procedures.

Findings

Up to 3x reduction in latency

Up to 1.7x increase in throughput

Comparable performance to custom stored procedures

Abstract

Database-backed applications are nearly ubiquitous in our daily lives. Applications that make many small accesses to the database create two challenges for developers: increased latency and wasted resources from numerous network round trips. A well-known technique to improve transactional database application performance is to convert part of the application into stored procedures that are executed on the database server. Unfortunately, this conversion is often difficult. In this paper we describe Pyxis, a system that takes database-backed applications and automatically partitions their code into two pieces, one of which is executed on the application server and the other on the database server. Pyxis profiles the application and server loads, statically analyzes the code's dependencies, and produces a partitioning that minimizes the number of control transfers as well as the amount of data sent during each transfer. Our experiments using TPC-C and TPC-W show that Pyxis is able to generate partitions with up to 3x reduction in latency and 1.7x improvement in throughput when compared to a traditional non-partitioned implementation and has comparable performance to that of a custom stored procedure implementation.