forked from TrueCloudLab/distribution
69 lines
2.8 KiB
Go
69 lines
2.8 KiB
Go
// Copyright 2017, OpenCensus Authors
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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//
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/*
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Package stats contains support for OpenCensus stats recording.
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OpenCensus allows users to create typed measures, record measurements,
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aggregate the collected data, and export the aggregated data.
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Measures
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A measure represents a type of data point to be tracked and recorded.
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For example, latency, request Mb/s, and response Mb/s are measures
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to collect from a server.
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Measure constructors such as Int64 and Float64 automatically
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register the measure by the given name. Each registered measure needs
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to be unique by name. Measures also have a description and a unit.
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Libraries can define and export measures. Application authors can then
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create views and collect and break down measures by the tags they are
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interested in.
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Recording measurements
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Measurement is a data point to be collected for a measure. For example,
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for a latency (ms) measure, 100 is a measurement that represents a 100ms
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latency event. Measurements are created from measures with
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the current context. Tags from the current context are recorded with the
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measurements if they are any.
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Recorded measurements are dropped immediately if no views are registered for them.
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There is usually no need to conditionally enable and disable
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recording to reduce cost. Recording of measurements is cheap.
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Libraries can always record measurements, and applications can later decide
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on which measurements they want to collect by registering views. This allows
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libraries to turn on the instrumentation by default.
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Exemplars
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For a given recorded measurement, the associated exemplar is a diagnostic map
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that gives more information about the measurement.
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When aggregated using a Distribution aggregation, an exemplar is kept for each
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bucket in the Distribution. This allows you to easily find an example of a
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measurement that fell into each bucket.
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For example, if you also use the OpenCensus trace package and you
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record a measurement with a context that contains a sampled trace span,
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then the trace span will be added to the exemplar associated with the measurement.
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When exported to a supporting back end, you should be able to easily navigate
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to example traces that fell into each bucket in the Distribution.
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*/
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package stats // import "go.opencensus.io/stats"
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