Performance Profiling with EndoScope, an Acquisitional Software Monitoring Framework

Alvin Cheung, Samuel Madden

Proceedings of VLDB 2008

Abstract

We propose EndoScope, a software monitoring framework that allows users to pose declarative queries that monitor the state and performance of running programs. Unlike most existing monitoring tools, EndoScope is acquisitional, meaning that it only instruments the portions of the program that need to be monitored to answer queries. The use of a high level declarative language allows EndoScope to search for efficient physical instantiations of queries by applying a suite of optimizations, including control flow graph analysis, and traditional database query optimization techniques, such as predicate pushdown and join optimization, to minimize the number of program instrumentation points and overhead to the monitored program. Furthermore, a flexible, high level language and the ability to attach to running programs enable developers to build various program analysis and monitoring applications beyond traditional software profilers with EndoScope.

We describe a prototype implementation of the EndoScope framework and a simple profiler for Java programs implemented with EndoScope. We show results from using our profiler on a collection of real-world programs, including a TPC-C implementation using the Derby database and the petstore application running on top of Tomcat application server. Our results show the benefit of our optimization framework and demonstrate that our declarative, acquisitional approach can yield program instrumentation overheads that are dramatically lower than conventional profiling tools (for example, when profiling the Derby Database running TPC-C, our system's overhead ranges from 1% to about 25%, whereas the fastest existing profiler we measured imposes a minimum overhead of about 30%.)

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