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Difference between revisions of "TPTP Java Profilers Anatomy"
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=== Call Graph Profiler === | === Call Graph Profiler === | ||
| + | There are two modes which can be applied to Call Graph profiling - execution details and aggregated. The difference for users between these two modes is in execution details mode provides more detailed profiling information, and it can render call graph in workbench. However, it will run slower than aggregated mode. To support these two modes, different implementations are used in call graph profiler design. | ||
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| + | The first difference is data structure used for profiling data storage. | ||
=== Heap Profiler === | === Heap Profiler === | ||
Revision as of 03:15, 27 August 2009
Contents
Introduction
TPTP provides with not only a profiling framework Martini, but also several Java profilers. Call graph, memory and thread anlysis are three basic profiling scenarios.
Profilers Design Overview
To abstract common operations in diffrent profilers, a class named "CBaseProf" is added. The design pattern Template is used here. BaseProf defines several template methods and subclasses of it need to implement these template methods.
Besides BaseProf, profiling data will be stored for different profiling. We will discuss the data structure of them later. All these profiling data and handlers which point to components outside of profilers such as JPIAgent is stored in a profiling context class named "CProfEnv".
Different handler classes are added for process different Martini profiling events such as enter a method or a new thread start etc. These classes is packaged with concrete profilers.
Profiliers Anatomy
BaseProf: Base class for Concrete Profilers
ProfEnv: Profiling Environmental Information Storage for Profilers
Call Graph Profiler
There are two modes which can be applied to Call Graph profiling - execution details and aggregated. The difference for users between these two modes is in execution details mode provides more detailed profiling information, and it can render call graph in workbench. However, it will run slower than aggregated mode. To support these two modes, different implementations are used in call graph profiler design.
The first difference is data structure used for profiling data storage.