Histogram Aggregator Plugin
The histogram aggregator plugin creates histograms containing the counts of
field values within a range.
If cumulative
is set to true, values added to a bucket are also added to the
larger buckets in the distribution. This creates a cumulative histogram.
Otherwise, values are added to only one bucket, which creates an ordinary 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
## Whether bucket values should be accumulated. If set to false, "gt" tag will be added.
## Defaults to true.
cumulative = true
## Example config that aggregates all fields of the metric.
# [[aggregators.histogram.config]]
# ## Right borders of buckets (with +Inf implicitly added).
# 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]]
# ## Right borders of buckets (with +Inf implicitly added).
# 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 (right) bound of the bucket.
The +Inf
bucket is added automatically and does not need to be defined.
(For left boundaries, these specified bucket borders and -Inf
will be used).
Measurements & Fields:
The postfix bucket
will be added to each field key.
- measurement1
- field1_bucket
- field2_bucket
cumulative = true
(default):
le
: Right bucket border. It means that the metric value is less than or
equal to the value of this tag. If a metric value is sorted into a bucket,
it is also sorted into all larger buckets. As a result, the value of
<field>_bucket
is rising with rising le
value. When le
is +Inf
,
the bucket value is the count of all metrics, because all metric values are
less than or equal to positive infinity.
cumulative = false
:
gt
: Left bucket border. It means that the metric value is greater than
(and not equal to) the value of this tag.
le
: Right bucket border. It means that the metric value is less than or
equal to the value of this tag.
- As both
gt
and le
are present, each metric is sorted in only exactly
one bucket.
Example Output:
Let assume we have the buckets [0, 10, 50, 100] and the following field values
for usage_idle
: [50, 7, 99, 12]
With cumulative = true
:
cpu,cpu=cpu1,host=localhost,le=0.0 usage_idle_bucket=0i 1486998330000000000 # none
cpu,cpu=cpu1,host=localhost,le=10.0 usage_idle_bucket=1i 1486998330000000000 # 7
cpu,cpu=cpu1,host=localhost,le=50.0 usage_idle_bucket=2i 1486998330000000000 # 7, 12
cpu,cpu=cpu1,host=localhost,le=100.0 usage_idle_bucket=4i 1486998330000000000 # 7, 12, 50, 99
cpu,cpu=cpu1,host=localhost,le=+Inf usage_idle_bucket=4i 1486998330000000000 # 7, 12, 50, 99
With cumulative = false
:
cpu,cpu=cpu1,host=localhost,gt=-Inf,le=0.0 usage_idle_bucket=0i 1486998330000000000 # none
cpu,cpu=cpu1,host=localhost,gt=0.0,le=10.0 usage_idle_bucket=1i 1486998330000000000 # 7
cpu,cpu=cpu1,host=localhost,gt=10.0,le=50.0 usage_idle_bucket=1i 1486998330000000000 # 12
cpu,cpu=cpu1,host=localhost,gt=50.0,le=100.0 usage_idle_bucket=2i 1486998330000000000 # 50, 99
cpu,cpu=cpu1,host=localhost,gt=100.0,le=+Inf usage_idle_bucket=0i 1486998330000000000 # none