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README.md | ||
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histogram_test.go |
README.md
Histogram Aggregator Plugin
The histogram aggregator plugin creates histograms containing the counts of field values within a range.
Values added to a bucket are also added to the larger buckets in the distribution. This creates a cumulative histogram.
Like other Telegraf aggregators, the metric is emitted every period
seconds.
By default bucket counts are not reset between periods and will be non-strictly
increasing while Telegraf is running. This behavior can be changed by setting the
reset
parameter to true.
Design
Each metric is passed to the aggregator and this aggregator searches
histogram buckets for those fields, which have been specified in the
config. If buckets are found, the aggregator will increment +1 to the appropriate
bucket otherwise it will be added to the +Inf
bucket. Every period
seconds this data will be forwarded to the outputs.
The algorithm of hit counting to buckets was implemented on the base of the algorithm which is implemented in the Prometheus client.
Configuration
# Configuration for aggregate histogram metrics
[[aggregators.histogram]]
## The period in which to flush the aggregator.
period = "30s"
## If true, the original metric will be dropped by the
## aggregator and will not get sent to the output plugins.
drop_original = false
## If true, the histogram will be reset on flush instead
## of accumulating the results.
reset = false
## Example config that aggregates all fields of the metric.
# [[aggregators.histogram.config]]
# ## The set of buckets.
# buckets = [0.0, 15.6, 34.5, 49.1, 71.5, 80.5, 94.5, 100.0]
# ## The name of metric.
# measurement_name = "cpu"
## Example config that aggregates only specific fields of the metric.
# [[aggregators.histogram.config]]
# ## The set of buckets.
# buckets = [0.0, 10.0, 20.0, 30.0, 40.0, 50.0, 60.0, 70.0, 80.0, 90.0, 100.0]
# ## The name of metric.
# measurement_name = "diskio"
# ## The concrete fields of metric
# fields = ["io_time", "read_time", "write_time"]
The user is responsible for defining the bounds of the histogram bucket as well as the measurement name and fields to aggregate.
Each histogram config section must contain a buckets
and measurement_name
option. Optionally, if fields
is set only the fields listed will be
aggregated. If fields
is not set all fields are aggregated.
The buckets
option contains a list of floats which specify the bucket
boundaries. Each float value defines the inclusive upper bound of the bucket.
The +Inf
bucket is added automatically and does not need to be defined.
Measurements & Fields:
The postfix bucket
will be added to each field key.
- measurement1
- field1_bucket
- field2_bucket
Tags:
All measurements are given the tag le
. This tag has the border value of
bucket. It means that the metric value is less than or equal to the value of
this tag. For example, let assume that we have the metric value 10 and the
following buckets: [5, 10, 30, 70, 100]. Then the tag le
will have the value
10, because the metrics value is passed into bucket with right border value
10
.
Example Output:
cpu,cpu=cpu1,host=localhost,le=0.0 usage_idle_bucket=0i 1486998330000000000
cpu,cpu=cpu1,host=localhost,le=10.0 usage_idle_bucket=0i 1486998330000000000
cpu,cpu=cpu1,host=localhost,le=20.0 usage_idle_bucket=1i 1486998330000000000
cpu,cpu=cpu1,host=localhost,le=30.0 usage_idle_bucket=2i 1486998330000000000
cpu,cpu=cpu1,host=localhost,le=40.0 usage_idle_bucket=2i 1486998330000000000
cpu,cpu=cpu1,host=localhost,le=50.0 usage_idle_bucket=2i 1486998330000000000
cpu,cpu=cpu1,host=localhost,le=60.0 usage_idle_bucket=2i 1486998330000000000
cpu,cpu=cpu1,host=localhost,le=70.0 usage_idle_bucket=2i 1486998330000000000
cpu,cpu=cpu1,host=localhost,le=80.0 usage_idle_bucket=2i 1486998330000000000
cpu,cpu=cpu1,host=localhost,le=90.0 usage_idle_bucket=2i 1486998330000000000
cpu,cpu=cpu1,host=localhost,le=100.0 usage_idle_bucket=2i 1486998330000000000
cpu,cpu=cpu1,host=localhost,le=+Inf usage_idle_bucket=2i 1486998330000000000