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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. Copied out of my work for the CockroachDB metrics system. Based on an algorithm created by Keith Frost. This package contains the source code needed for building packages that reference the following Go import paths: – github.com/spacejam/loghisto
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