Compact Object Store Workload Representation via Distribution Ensembles
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Solution Overview
Problem
Existing techniques for quantifying and representing object store workloads are excessively bulky, time-consuming, and memory-consuming due to full operation tracing, making it difficult to determine whether reconfiguration is necessary, often relying on 'guesstimates' rather than actionable data.
Innovation Solution
A system that identifies repeating object-storage operation sequences and generates distribution ensembles to compactly represent the workload, reducing memory consumption while maintaining essential information about the object store's operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If full operation tracing is used to quantify object store workload, then measurement precision is improved, but volume of data, memory consumption, and processing time increase excessively
Solution Approach 1:
The patent extracts only the essential information from full operation traces by identifying and retaining only the most frequent operation sequences and their statistical characteristics. Less frequent operations are aggregated or discarded, extracting only the core workload patterns needed for quantification while eliminating the bulk of redundant detailed trace data.
Solution Approach 2:
The patent transforms detailed operation traces into summarized statistical parameters including distribution ensembles, frequency counts, and sequence patterns. This parameter transformation converts voluminous raw trace data into compact quantitative representations that maintain measurement precision while dramatically reducing data volume.
2Measurement precision
If full operation tracing is used to represent workload, then workload representation accuracy is improved, but processing time and memory consumption increase
Solution Approach 1:
The patent performs preliminary processing of operation traces to identify and pre-compute statistical characteristics of operation sequences. By analyzing and summarizing trace data in advance into distribution ensembles and frequency patterns, the system prepares condensed workload representations that can be quickly processed without requiring time-consuming full trace analysis during subsequent evaluation phases.
3Measurement precision
If full operation tracing is used to analyze workload, then analysis accuracy is improved, but device complexity and resource requirements increase
Solution Approach 1:
The patent extracts and focuses analysis only on the most significant operation sequences and their statistical properties, rather than processing every individual operation trace. This selective extraction reduces the complexity of the analysis system by concentrating computational resources on identifying and characterizing the core workload patterns that drive accurate workload representation.
Data Source
AI summary
Systems and techniques that facilitate compact representation of object store workloads are provided. In various embodiments, a system can access a stream of object-storage operation requests associated with an object store. In various aspects, the system can identify a set of repeating object-storage operation sequences, based on the stream of object-storage operation requests. In various instances, the system can generate a set of distribution ensembles that quantify variation of first attributes associated with respective ones of the set of repeating object-storage operation sequences. In various cases, the stream of object-storage operation requests can be considered as fully and/or bulkily representing the workload experienced by the object store. In contrast, the set of distribution ensembles can be considered as compactly representing the workload experienced by the object store (e.g., the set of distribution ensembles can take up far less memory space than the stream of object-storage operation requests).