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1 parent 046782a commit d1af4ff7b692ab300d9e3a5685c8b1a664c2e3a2 @mikejihbe committed Feb 8, 2012
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@@ -11,7 +11,9 @@ Instruments
Counters count things.
They implement: inc, dec, clear
They expose: count
@@ -25,8 +27,11 @@ counter.count // 0
Histograms sample a dataset to get a sense of its distribution. These are particularly useful for breaking down the quantiles of how longs things take (requests, method calls, etc). Metrics supports uniform distributions and exponentially decaying samples. Sample sizes and parameters of the distribution are all highly configurable, but the defaults will probably suit your needs. Exponential decay histograms favor more recent data, which is typically what you want
They implement: update, mean, stdDev, percentiles, clear
They expose: count, min, max, sum
@@ -37,6 +42,7 @@ var hist1 = new metrics.createExponentialDecayHistogram()
A meter tracks how often things happen. It exposes a 1 minute rate, a 5 minute rate, and a 15 minute rate using exponentially weighted moving averages (the same strategy that unix load average takes).
They implement: mark, oneMinuteRate, fiveMinuteRate, fifteenMinuteRate, meanRate
@@ -50,6 +56,7 @@ meter.meanRate()
A Timer is a combination of a meter and a histogram. It samples timing data and rate the data is coming in. Everything you could possibly want!
They implement: update, mark, clear, count, min, max, mean, stdDev, percentiles, oneMinuteRate, fiveMinuteRate, fifteenMinuteRate, meanRate

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