Hierarchical Stack Trace Tree for Java Profiling
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Solution Overview
Problem
Conventional profiling tools for Java-based systems are limited in detecting memory leaks and system inefficiencies, often requiring VM restarts, leading to high memory consumption and performance issues, especially in large-scale distributed environments.
Innovation Solution
A system and method to generate a hierarchical tree representing stack traces, allowing for on-demand profiling without restarting the VM, using a proprietary interface and infrastructure that embeds profiling components within the JVM, enabling efficient memory management and reduced overhead.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional profiling tools are used to detect memory leaks and system inefficiencies, then profiling information can be obtained, but VM restarts are required leading to high memory consumption and performance issues
Solution Approach 1:
The patent embeds the profiling infrastructure directly within the JVM as a nested component. The profiling agent runs inside the VM process space, allowing memory profiling without requiring external tools that would necessitate VM restarts. This nested architecture enables continuous profiling while maintaining stable memory consumption patterns.
Solution Approach 2:
The patent introduces a proprietary profiling interface as an intermediary between the profiling needs and the JVM internals. This interface layer allows profiling operations to be performed without disrupting the VM runtime, eliminating the need for restarts that cause memory spikes and performance degradation.
2Measurement precision
If conventional profiling tools are used to profile Java applications, then system inefficiencies can be detected, but VM restarts are required causing user sessions to be disrupted
Solution Approach 1:
The patent enables continuous profiling operations without interrupting the VM execution. The profiling agent operates concurrently with application execution, maintaining uninterrupted user sessions while continuously gathering profiling data about system inefficiencies, memory usage, and performance metrics.
Solution Approach 2:
The proprietary profiling interface acts as an intermediary that allows profiling operations to be performed transparently during runtime. This interface enables the system to detect inefficiencies without requiring VM restarts that would disrupt user sessions, maintaining operational continuity throughout the profiling process.
3Quantity of substance
If conventional profiling tools are used in large-scale distributed environments, then profiling data can be collected, but high memory consumption and performance issues occur
Solution Approach 1:
By nesting the profiling infrastructure within the JVM, the patent enables efficient data collection that scales to large distributed environments. The embedded agent collects profiling data with minimal overhead, avoiding the performance penalties associated with external profiling tools that require VM restarts and consume excessive memory resources.
Data Source
AI summary
A system and method are provided to generate a hierarchical tree representing stack traces. In one embodiment, stack trace elements in a plurality of stack traces relating to profiling of an application executing at a first virtual machine are identified, the stack trace elements relating to profiling events being detected during the profiling of the application. The identified stack trace elements are sorted as one of parent elements; parent/child elements, or child elements based on a number of times a stack trace element has appeared in the plurality of stack traces and its relationship with other elements in the plurality of stack traces. A tree having nodes to represent the stack trace elements is created such that that the child elements branch from the parent/child elements or the parent elements, and the parent/child elements branch from the parent elements.