What Is Downsampling?
Downsampling is the process of collapsing high-frequency historical data points into coarser intervals, replacing many raw samples with aggregates like averages, minimums, and maximums. Recent data stays at full resolution while older data is summarized. This preserves long-term trends at a fraction of the storage and query cost.
Why it matters
Keeping every per-second sample forever is prohibitively expensive and rarely useful. Downsampling lets a system retain months of history for trend analysis without the cost of full-resolution storage.
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