Definition ∞ Coarse-grained sampling is a data collection method that acquires information at a broad, generalized level rather than with fine detail. This technique involves selecting a smaller, less precise subset of data points from a larger set. It prioritizes efficiency and computational resource conservation over granular accuracy. This approach is useful when a general overview or trend identification suffices for analysis.
Context ∞ In blockchain and distributed systems, coarse-grained sampling can be applied to reduce the computational load for validators or nodes, particularly in scaling solutions. A key consideration is balancing the reduction in data processing with maintaining sufficient integrity for network operations. Future advancements may involve adaptive sampling methods that adjust granularity based on network conditions or security requirements.
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