In-Memory Database Trace Mining and Detangling
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Solution Overview
Problem
In-memory database traces are challenging due to interleaved trace lines from different threads or connections, leading to tangled and difficult-to-read logs with redundant header information and misleading timestamps, which existing software programs cannot effectively manage.
Innovation Solution
A trace analysis component that mines and detangles trace data, correcting timestamp order and removing redundancy to produce a clearer, easier-to-analyze output file.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If trace data is logged from multiple threads concurrently, then the database can process operations in parallel with high speed, but the trace lines become interleaved and tangled making them difficult to read and analyze
Solution Approach 1:
The patent segments the tangled trace data by creating separate trace files or sections for each thread or connection. This is achieved by identifying unique thread identifiers in the trace data and organizing the interleaved log entries into distinct segments, making it easier to read and analyze each thread's operations independently while preserving the parallel execution benefits
Solution Approach 2:
The patent introduces an intermediary processing layer that acts as a mediator between the parallel trace generation and the final output. This intermediary component sorts, filters, and reorganizes the interleaved trace lines from multiple threads into a structured format, allowing concurrent processing to continue at high speed while producing readable organized output
2Loss of information
If trace headers are repeated for each trace line to identify context, then the trace information remains accurate and complete, but redundant header information increases file size and complexity
Solution Approach 1:
The patent merges consecutive trace lines that share the same header information into combined entries. By detecting when multiple trace lines belong to the same thread and time context, the system consolidates them under a single header, reducing redundancy while preserving all necessary contextual information for accurate trace analysis
Solution Approach 2:
The patent applies local quality by making header repetition selective rather than universal. Headers are repeated only when necessary to maintain context accuracy—such as when switching between different threads or connections—while being omitted or consolidated when consecutive lines belong to the same context, thereby reducing overall file complexity without losing essential information
3Measurement precision
If timestamps are recorded for each trace line to maintain execution order, then the chronological sequence is preserved, but misleading timestamps from parallel execution create confusion about actual operation order
Solution Approach 1:
The patent applies dynamics by making the timestamp presentation adaptive based on thread context. When displaying trace data, the system dynamically adjusts timestamp interpretation and presentation to account for parallel execution, showing timestamps in the context of each thread's execution flow rather than as a single global sequence, thereby resolving confusion about actual operation order while preserving accurate timing information
Data Source
AI summary
In an example embodiment, a solution is provided to mine trace data, detangle it, and rewrite the trace data without redundancy. In an example embodiment, mining may take place before detangling, but such an ordering is not mandatory. Combining mining with detangling solves the technical problem of the production of difficult-to-read service traces, as it mines the “interesting” parts, corrects the timestamp order, and removes redundancy.