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counters and logarithmically bucketed histograms for distributed systems
A metric system for high performance counters and histograms. Unlike popular metric systems today, this does not destroy the accuracy of histograms by sampling. Instead, a logarithmic bucketing function compresses values, generally within 1% of their true value (although between 0 and 1 the precision loss may not be within this boundary). This allows for extreme compression, which allows us to calculate arbitrarily high percentiles with no loss of accuracy - just a small amount of precision. This is particularly useful for highly-clustered events that are tolerant of a small precision loss, but for which you REALLY care about what the tail looks like, such as measuring latency across a distributed system.
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