Java Heap Dump Graph Visualization for Memory Leak Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current profiling tools for Java heap dumps have limited capability in analyzing the contents of memory snapshots, making it difficult to identify issues such as unintended object graphs and memory leaks, which can lead to inefficient memory usage and data breaches.
Innovation Solution
A method is introduced to convert Java heap dump content into a graph representation compatible with graph databases, allowing for visualization and analysis of object relationships, enabling the identification of complex problems and inefficiencies through clustering and routing algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional profiling tools are used to analyze heap dumps, then some basic memory analysis is provided, but the capability to identify complex issues such as unintended object graphs and memory leaks is limited
Solution Approach 1:
The patent introduces a graph database as an intermediary system between the heap dump and the analysis process. The heap dump is converted into a graph representation with nodes representing objects and edges representing relationships, which can then be loaded into a graph database for comprehensive analysis. This intermediary graph database structure enables complex queries and algorithms to identify memory issues that traditional tools cannot handle.
Solution Approach 2:
The patent transforms the traditional linear/sequential memory representation into a multi-dimensional graph structure. By representing memory objects as nodes and their relationships as edges in a graph, the system adds relational and structural dimensions to memory analysis, enabling visualization and complex pattern recognition that traditional profiling tools lack.
2Reliability
If heap dump content is converted to graph representation and loaded into graph database, then comprehensive visualization and analysis is enabled, but processing time and system complexity increase
Solution Approach 1:
The patent performs preliminary conversion of the heap dump into a graph representation before analysis. By pre-processing the heap dump and creating the graph structure in advance, the system prepares the data in an optimized format that enables fast querying and analysis in the graph database, reducing the time needed for subsequent memory issue identification.
Solution Approach 2:
The patent creates a copy of the memory structure in graph format rather than analyzing the original heap dump directly. This graphical copy preserves all relationships and object information while enabling more efficient storage, querying, and visualization, separating the analysis process from the original data structure.
3Manufacturing precision
If heap dump is processed sequentially to build object graphs, then complete object relationship mapping is achieved, but processing speed decreases significantly for large heaps
Solution Approach 1:
The patent segments the heap dump processing into distinct phases: first converting the heap dump into graph-compatible files, then loading these files into the graph database for processing. This segmentation allows for more efficient handling of large datasets by working with structured graph data rather than sequentially processing the entire heap dump at once.
Solution Approach 2:
The patent changes the data structure parameter from sequential heap dump format to graph database format. This parameter change fundamentally alters how the data is stored and processed, enabling parallel queries and optimized data access patterns that significantly improve processing speed while maintaining complete object relationship mapping.
Data Source
AI summary
A computer-implemented method is disclosed that includes receiving content associated with a heap dump of a computer application, generating a plurality of files based on the heap dump content, and loading the files into the graph database. The files so generated are compatible with the graph database. In some implementations, additional analysis and route finding (e.g., finding the relationship between two nodes) may be performed on the resulting object graph.