Error Correlation via Unique Processing Step Identifiers
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Solution Overview
Problem
In distributed data processing systems, correlating errors to specific processing steps and data records is laborious and time-consuming, especially when errors occur across multiple nodes in a cluster, as it requires manual analysis of text log files, making debugging inefficient.
Innovation Solution
A system and method that utilize unique identifiers for processing steps and data records to automatically correlate errors by collecting and processing error information across nodes, generating correlations that indicate the cause and location of errors, and providing this information to users in the context of processing steps, using graphs and optimization techniques to preserve tag information and limit error data collection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual analysis of text log files is used to correlate errors to processing steps and data records, then error correlation can be achieved, but the process becomes laborious, cumbersome, and time-consuming
Solution Approach 1:
The system performs preliminary actions by assigning unique identifiers to processing steps and embedding them in error information before errors occur. This pre-tagging approach enables automatic correlation when errors happen, eliminating the need for manual analysis of log files and significantly reducing debugging time while maintaining accurate error-source mapping.
Solution Approach 2:
The patent introduces an intermediary mechanism (unique identifiers and error information structures) that bridges the gap between errors and their source processing steps. This intermediary automatically captures and transmits correlation data, replacing manual analysis and reducing the time required to debug distributed processing systems while preserving accurate error attribution.
2Reliability
If error information is collected from all nodes in a distributed cluster, then complete error correlation is achieved, but the complexity of error data collection and processing increases
Solution Approach 1:
The system segments error information collection by node, with each node independently capturing error data with embedded unique identifiers. This segmentation allows parallel, distributed collection without centralized coordination complexity, maintaining complete error correlation across the cluster while simplifying the overall data collection architecture through independent, standardized node-level operations.
Solution Approach 2:
The patent changes the parameter of error information from unstructured text to structured data with embedded unique identifiers. This parameter transformation enables automatic correlation processing and reduces the complexity of data collection and analysis, while maintaining complete and reliable error tracking across distributed nodes through standardized information formats.
3Productivity
If unique identifiers are assigned to all processing steps, then automatic error correlation is enabled, but the system complexity increases due to identifier management
Solution Approach 1:
The unique identifier system serves multiple functions simultaneously: it identifies processing steps, traces error sources, and enables automatic correlation. This multi-functionality reduces the need for separate tracking mechanisms, thereby improving debugging efficiency while actually reducing overall system complexity by consolidating identification and tracing functions into a single universal identifier system.
Data Source
AI summary
A computer program file or a sequence of processing steps from an authoring environment of a data processing system is used to generate a graph including nodes representing the processing steps is generated. Unique identifiers (tags) are assigned to the nodes. One or more processing steps are optionally modified while preserving the original identifiers. If an error occurs during execution, error information is saved including the processing step that failed and data records that triggered the failure. The identifier of the failed processing step is attached to the error information. The error information is collected and processed. The collected error information is used to correlate the error to the failed processing step and to data records triggering the error using the identifier of the failed processing step recorded with the error information. The correlated error information indicates cause and location of the error.