Graph-Based Metric Compression With Time-Slice Delta Encoding
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Solution Overview
Problem
Conventional metric compression systems are inflexible and inefficient due to their reliance on static compression dictionaries and temporal compression methods, leading to high computational and bandwidth demands, as well as limited flexibility in adapting to changing metric metadata and values.
Innovation Solution
The implementation of a graph-based compression dictionary that dynamically updates nodes and edges, allowing for delta compression across time slices and windows, enabling flexible and efficient compression of metric data through shared dictionaries across computing devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional static compression dictionaries are used, then system simplicity is maintained, but adaptability to changing metric metadata and values deteriorates
Solution Approach 1:
The patent implements dynamic compression dictionaries that automatically update their content based on observed metric metadata patterns. The system transitions from static pre-defined dictionaries to dynamic structures that adapt their compression mappings in real-time, resolving the contradiction between adaptability and complexity by making the system flexible rather than rigid.
Solution Approach 2:
The compression system performs self-updates by automatically learning from incoming metric data patterns and adjusting its dictionary content without external intervention. This self-service capability enables the system to adapt to changing metric metadata autonomously, improving adaptability while keeping operational complexity manageable through automation.
2Productivity
If conventional temporal compression methods are used, then implementation simplicity is maintained, but compression efficiency deteriorates due to high computational demands
Solution Approach 1:
The patent segments the compression process into distinct phases: pattern identification, dictionary update, and compression execution. By dividing the computational workload into manageable segments and performing pattern analysis only when necessary, the system achieves higher compression efficiency without requiring continuously high computational complexity.
Solution Approach 2:
The system performs dictionary updates periodically or event-driven rather than continuously, reducing computational overhead. Compression operations use the established dictionary efficiently without repeated analysis, achieving high productivity while maintaining manageable computational complexity through rhythmic rather than continuous processing.
3Adaptability or versatility
If conventional compression systems are used, then bandwidth usage is reduced, but flexibility in adapting to changing metric values deteriorates
Solution Approach 1:
The system performs preliminary pattern analysis and dictionary construction before actual compression operations. By preparing the compression mappings in advance based on observed patterns, the system achieves both adaptability to changing values and efficient bandwidth utilization during the actual compression phase, avoiding the need for frequent retransmissions.
4Productivity
If static compression dictionaries are used, then system resource consumption is reduced, but compression effectiveness deteriorates due to inability to handle metric changes
Solution Approach 1:
The system implements dynamic dictionaries that adapt their content based on observed metric patterns, achieving high compression effectiveness for changing data. The computational resource consumption is managed through event-driven updates rather than continuous processing, resolving the contradiction between effectiveness and resource usage.
Data Source
AI summary
The present disclosure relates to systems, methods, and non-transitory computer-readable media that generate compressed metric data for digital metrics utilizing a graph-based compression dictionary and time slice compression. For instance, the disclosed systems can utilize a dynamically modifiable graph-based compression dictionary to generate compressed metric label identifiers for metric labels of digital metrics. The graph-based compression dictionary can include nodes and edges corresponding to metric label segments and metric label identifier values, respectively. The disclosed systems can traverse the graph-based compression dictionary using a metric label to determine the corresponding compressed metric label identifier. The disclosed systems can further generate delta compression values for the metric values of the digital metrics. For instance, the disclosed systems can compare metric values within a single time slice (e.g., a time stamp) to generate corresponding delta compression values. In some cases, the disclosed systems further compare the metric values across a time window.