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chore: clean up all markdown lint errors in aggregator plugins (#10151)

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38
plugins/aggregators/basicstats/README.md
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@ -3,7 +3,7 @@
The BasicStats aggregator plugin give us count,diff,max,min,mean,non_negative_diff,sum,s2(variance), stdev for a set of values, The BasicStats aggregator plugin give us count,diff,max,min,mean,non_negative_diff,sum,s2(variance), stdev for a set of values,
emitting the aggregate every `period` seconds. emitting the aggregate every `period` seconds.
### Configuration: ## Configuration
```toml ```toml
# Keep the aggregate basicstats of each metric passing through. # Keep the aggregate basicstats of each metric passing through.
@ -20,32 +20,32 @@ emitting the aggregate every `period` seconds.
``` ```
- stats - stats
- If not specified, then `count`, `min`, `max`, `mean`, `stdev`, and `s2` are aggregated and pushed as fields. `sum`, `diff` and `non_negative_diff` are not aggregated by default to maintain backwards compatibility. - If not specified, then `count`, `min`, `max`, `mean`, `stdev`, and `s2` are aggregated and pushed as fields. `sum`, `diff` and `non_negative_diff` are not aggregated by default to maintain backwards compatibility.
- If empty array, no stats are aggregated - If empty array, no stats are aggregated
### Measurements & Fields: ## Measurements & Fields
- measurement1 - measurement1
- field1_count - field1_count
- field1_diff (difference) - field1_diff (difference)
- field1_rate (rate per second) - field1_rate (rate per second)
- field1_max - field1_max
- field1_min - field1_min
- field1_mean - field1_mean
- field1_non_negative_diff (non-negative difference) - field1_non_negative_diff (non-negative difference)
- field1_non_negative_rate (non-negative rate per second) - field1_non_negative_rate (non-negative rate per second)
- field1_sum - field1_sum
- field1_s2 (variance) - field1_s2 (variance)
- field1_stdev (standard deviation) - field1_stdev (standard deviation)
- field1_interval (interval in nanoseconds) - field1_interval (interval in nanoseconds)
### Tags: ## Tags
No tags are applied by this aggregator. No tags are applied by this aggregator.
### Example Output: ## Example Output
``` ```shell
$ telegraf --config telegraf.conf --quiet $ telegraf --config telegraf.conf --quiet
system,host=tars load1=1 1475583980000000000 system,host=tars load1=1 1475583980000000000
system,host=tars load1=1 1475583990000000000 system,host=tars load1=1 1475583990000000000

28
plugins/aggregators/derivative/README.md
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@ -1,42 +1,47 @@
# Derivative Aggregator Plugin # Derivative Aggregator Plugin
The Derivative Aggregator Plugin estimates the derivative for all fields of the The Derivative Aggregator Plugin estimates the derivative for all fields of the
aggregated metrics. aggregated metrics.
### Time Derivatives ## Time Derivatives
In its default configuration it determines the first and last measurement of In its default configuration it determines the first and last measurement of
the period. From these measurements the time difference in seconds is the period. From these measurements the time difference in seconds is
calculated. This time difference is than used to divide the difference of each calculated. This time difference is than used to divide the difference of each
field using the following formula: field using the following formula:
```
```text
field_last - field_first field_last - field_first
derivative = -------------------------- derivative = --------------------------
time_difference time_difference
``` ```
For each field the derivative is emitted with a naming pattern For each field the derivative is emitted with a naming pattern
`<fieldname>_rate`. `<fieldname>_rate`.
### Custom Derivation Variable ## Custom Derivation Variable
The plugin supports to use a field of the aggregated measurements as derivation The plugin supports to use a field of the aggregated measurements as derivation
variable in the denominator. This variable is assumed to be a monotonically variable in the denominator. This variable is assumed to be a monotonically
increasing value. In this feature the following formula is used: increasing value. In this feature the following formula is used:
```
```text
field_last - field_first field_last - field_first
derivative = -------------------------------- derivative = --------------------------------
variable_last - variable_first variable_last - variable_first
``` ```
**Make sure the specified variable is not filtered and exists in the metrics passed to this aggregator!** **Make sure the specified variable is not filtered and exists in the metrics passed to this aggregator!**
When using a custom derivation variable, you should change the `suffix` of the derivative name. When using a custom derivation variable, you should change the `suffix` of the derivative name.
See the next section on [customizing the derivative name](#customize-the-derivative-name) for details. See the next section on [customizing the derivative name](#customize-the-derivative-name) for details.
### Customize the Derivative Name ## Customize the Derivative Name
The derivatives generated by the aggregator are named `<fieldname>_rate`, i.e. they are composed of the field name and a suffix `_rate`. The derivatives generated by the aggregator are named `<fieldname>_rate`, i.e. they are composed of the field name and a suffix `_rate`.
You can configure the suffix to be used by changing the `suffix` parameter. You can configure the suffix to be used by changing the `suffix` parameter.
### Roll-Over to next Period ## Roll-Over to next Period
Calculating the derivative for a period requires at least two distinct measurements during that period. Calculating the derivative for a period requires at least two distinct measurements during that period.
Whether those are available depends on the configuration of the aggregator `period` and the agent `interval`. Whether those are available depends on the configuration of the aggregator `period` and the agent `interval`.
@ -47,7 +52,7 @@ replace the roll-over metric. A main benefit of this roll-over is the ability to
cope with multiple "quiet" periods, where no new measurement is pushed to the cope with multiple "quiet" periods, where no new measurement is pushed to the
aggregator. The roll-over will take place at most `max_roll_over` times. aggregator. The roll-over will take place at most `max_roll_over` times.
#### Example of Roll-Over ### Example of Roll-Over
Let us assume we have an input plugin, that generates a measurement with a single metric "test" every 2 seconds. Let us assume we have an input plugin, that generates a measurement with a single metric "test" every 2 seconds.
Let this metric increase the first 10 seconds from 0.0 to 10.0 and then decrease the next 10 seconds form 10.0 to 0.0: Let this metric increase the first 10 seconds from 0.0 to 10.0 and then decrease the next 10 seconds form 10.0 to 0.0:
@ -130,7 +135,7 @@ Thoses changes are omitted with `max_roll_over = 0` but are respected with `max_
That there are no more differences in the calculated derivatives is due to the example data, which has constant derivatives in during the first and last period, even when including the gap between the periods. That there are no more differences in the calculated derivatives is due to the example data, which has constant derivatives in during the first and last period, even when including the gap between the periods.
Using `max_roll_over` with a value greater 0 may be important, if you need to detect changes between periods, e.g. when you have very few measurements in a period or quasi-constant metrics with only occasional changes. Using `max_roll_over` with a value greater 0 may be important, if you need to detect changes between periods, e.g. when you have very few measurements in a period or quasi-constant metrics with only occasional changes.
### Configuration ## Configuration
```toml ```toml
[[aggregators.derivative]] [[aggregators.derivative]]
@ -151,13 +156,14 @@ Using `max_roll_over` with a value greater 0 may be important, if you need to de
period = "30s" period = "30s"
``` ```
### Tags: ### Tags
No tags are applied by this aggregator. No tags are applied by this aggregator.
Existing tags are passed throug the aggregator untouched. Existing tags are passed throug the aggregator untouched.
### Example Output ## Example Output
``` ```text
net bytes_recv=15409i,packets_recv=164i,bytes_sent=16649i,packets_sent=120i 1508843640000000000 net bytes_recv=15409i,packets_recv=164i,bytes_sent=16649i,packets_sent=120i 1508843640000000000
net bytes_recv=73987i,packets_recv=364i,bytes_sent=87328i,packets_sent=452i 1508843660000000000 net bytes_recv=73987i,packets_recv=364i,bytes_sent=87328i,packets_sent=452i 1508843660000000000
net bytes_recv_by_packets_recv=292.89 1508843660000000000 net bytes_recv_by_packets_recv=292.89 1508843660000000000

11
plugins/aggregators/final/README.md
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@ -11,7 +11,7 @@ discrete time series such as procstat, cgroup, kubernetes etc.
When a series has not been updated within the time defined in When a series has not been updated within the time defined in
`series_timeout`, the last metric is emitted with the `_final` appended. `series_timeout`, the last metric is emitted with the `_final` appended.
### Configuration ## Configuration
```toml ```toml
[[aggregators.final]] [[aggregators.final]]
@ -25,20 +25,21 @@ When a series has not been updated within the time defined in
series_timeout = "5m" series_timeout = "5m"
``` ```
### Metrics ## Metrics
Measurement and tags are unchanged, fields are emitted with the suffix Measurement and tags are unchanged, fields are emitted with the suffix
`_final`. `_final`.
### Example Output ## Example Output
``` ```text
counter,host=bar i_final=3,j_final=6 1554281635115090133 counter,host=bar i_final=3,j_final=6 1554281635115090133
counter,host=foo i_final=3,j_final=6 1554281635112992012 counter,host=foo i_final=3,j_final=6 1554281635112992012
``` ```
Original input: Original input:
```
```text
counter,host=bar i=1,j=4 1554281633101153300 counter,host=bar i=1,j=4 1554281633101153300
counter,host=foo i=1,j=4 1554281633099323601 counter,host=foo i=1,j=4 1554281633099323601
counter,host=bar i=2,j=5 1554281634107980073 counter,host=bar i=2,j=5 1554281634107980073

31
plugins/aggregators/histogram/README.md
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@ -12,7 +12,7 @@ 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 increasing while Telegraf is running. This behavior can be changed by setting the
`reset` parameter to true. `reset` parameter to true.
#### Design ## Design
Each metric is passed to the aggregator and this aggregator searches Each metric is passed to the aggregator and this aggregator searches
histogram buckets for those fields, which have been specified in the histogram buckets for those fields, which have been specified in the
@ -24,7 +24,7 @@ The algorithm of hit counting to buckets was implemented on the base
of the algorithm which is implemented in the Prometheus of the algorithm which is implemented in the Prometheus
[client](https://github.com/prometheus/client_golang/blob/master/prometheus/histogram.go). [client](https://github.com/prometheus/client_golang/blob/master/prometheus/histogram.go).
### Configuration ## Configuration
```toml ```toml
# Configuration for aggregate histogram metrics # Configuration for aggregate histogram metrics
@ -73,40 +73,39 @@ boundaries. Each float value defines the inclusive upper (right) bound of the b
The `+Inf` bucket is added automatically and does not need to be defined. 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). (For left boundaries, these specified bucket borders and `-Inf` will be used).
### Measurements & Fields: ## Measurements & Fields
The postfix `bucket` will be added to each field key. The postfix `bucket` will be added to each field key.
- measurement1 - measurement1
- field1_bucket - field1_bucket
- field2_bucket - field2_bucket
### Tags: ### Tags
* `cumulative = true` (default): - `cumulative = true` (default):
* `le`: Right bucket border. It means that the metric value is less than or - `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, 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 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`, `<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 the bucket value is the count of all metrics, because all metric values are
less than or equal to positive infinity. less than or equal to positive infinity.
* `cumulative = false`: - `cumulative = false`:
* `gt`: Left bucket border. It means that the metric value is greater than - `gt`: Left bucket border. It means that the metric value is greater than
(and not equal to) the value of this tag. (and not equal to) the value of this tag.
* `le`: Right bucket border. It means that the metric value is less than or - `le`: Right bucket border. It means that the metric value is less than or
equal to the value of this tag. equal to the value of this tag.
* As both `gt` and `le` are present, each metric is sorted in only exactly - As both `gt` and `le` are present, each metric is sorted in only exactly
one bucket. one bucket.
## Example Output
### Example Output:
Let assume we have the buckets [0, 10, 50, 100] and the following field values Let assume we have the buckets [0, 10, 50, 100] and the following field values
for `usage_idle`: [50, 7, 99, 12] for `usage_idle`: [50, 7, 99, 12]
With `cumulative = true`: With `cumulative = true`:
``` ```text
cpu,cpu=cpu1,host=localhost,le=0.0 usage_idle_bucket=0i 1486998330000000000 # none 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=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=50.0 usage_idle_bucket=2i 1486998330000000000 # 7, 12
@ -116,7 +115,7 @@ cpu,cpu=cpu1,host=localhost,le=+Inf usage_idle_bucket=4i 1486998330000000000 #
With `cumulative = false`: With `cumulative = false`:
``` ```text
cpu,cpu=cpu1,host=localhost,gt=-Inf,le=0.0 usage_idle_bucket=0i 1486998330000000000 # none 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=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=10.0,le=50.0 usage_idle_bucket=1i 1486998330000000000 # 12

4
plugins/aggregators/merge/README.md
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@ -7,7 +7,7 @@ Use this plugin when fields are split over multiple metrics, with the same
measurement, tag set and timestamp. By merging into a single metric they can measurement, tag set and timestamp. By merging into a single metric they can
be handled more efficiently by the output. be handled more efficiently by the output.
### Configuration ## Configuration
```toml ```toml
[[aggregators.merge]] [[aggregators.merge]]
@ -16,7 +16,7 @@ be handled more efficiently by the output.
drop_original = true drop_original = true
``` ```
### Example ## Example
```diff ```diff
- cpu,host=localhost usage_time=42 1567562620000000000 - cpu,host=localhost usage_time=42 1567562620000000000

14
plugins/aggregators/minmax/README.md
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@ -3,7 +3,7 @@
The minmax aggregator plugin aggregates min & max values of each field it sees, The minmax aggregator plugin aggregates min & max values of each field it sees,
emitting the aggrate every `period` seconds. emitting the aggrate every `period` seconds.
### Configuration: ## Configuration
```toml ```toml
# Keep the aggregate min/max of each metric passing through. # Keep the aggregate min/max of each metric passing through.
@ -16,19 +16,19 @@ emitting the aggrate every `period` seconds.
drop_original = false drop_original = false
``` ```
### Measurements & Fields: ## Measurements & Fields
- measurement1 - measurement1
- field1_max - field1_max
- field1_min - field1_min
### Tags: ## Tags
No tags are applied by this aggregator. No tags are applied by this aggregator.
### Example Output: ## Example Output
``` ```shell
$ telegraf --config telegraf.conf --quiet $ telegraf --config telegraf.conf --quiet
system,host=tars load1=1.72 1475583980000000000 system,host=tars load1=1.72 1475583980000000000
system,host=tars load1=1.6 1475583990000000000 system,host=tars load1=1.6 1475583990000000000

26
plugins/aggregators/quantile/README.md
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@ -3,7 +3,7 @@
The quantile aggregator plugin aggregates specified quantiles for each numeric field The quantile aggregator plugin aggregates specified quantiles for each numeric field
per metric it sees and emits the quantiles every `period`. per metric it sees and emits the quantiles every `period`.
### Configuration ## Configuration
```toml ```toml
[[aggregators.quantile]] [[aggregators.quantile]]
@ -33,8 +33,10 @@ per metric it sees and emits the quantiles every `period`.
# compression = 100.0 # compression = 100.0
``` ```
#### Algorithm types ## Algorithm types
##### t-digest
### t-digest
Proposed by [Dunning & Ertl (2019)][tdigest_paper] this type uses a Proposed by [Dunning & Ertl (2019)][tdigest_paper] this type uses a
special data-structure to cluster data. These clusters are later used special data-structure to cluster data. These clusters are later used
to approximate the requested quantiles. The bounds of the approximation to approximate the requested quantiles. The bounds of the approximation
@ -47,7 +49,8 @@ where exact quantile calculation isn't required.
For implementation details see the underlying [golang library][tdigest_lib]. For implementation details see the underlying [golang library][tdigest_lib].
##### exact R7 and R8 ### exact R7 and R8
These algorithms compute quantiles as described in [Hyndman & Fan (1996)][hyndman_fan]. These algorithms compute quantiles as described in [Hyndman & Fan (1996)][hyndman_fan].
The R7 variant is used in Excel and NumPy. The R8 variant is recommended The R7 variant is used in Excel and NumPy. The R8 variant is recommended
by Hyndman & Fan due to its independence of the underlying sample distribution. by Hyndman & Fan due to its independence of the underlying sample distribution.
@ -57,8 +60,8 @@ a lot of memory when used with a large number of series or a
large number of samples. They are slower than the `t-digest` large number of samples. They are slower than the `t-digest`
algorithm and are recommended only to be used with a small number of samples and series. algorithm and are recommended only to be used with a small number of samples and series.
## Benchmark (linux/amd64)
#### Benchmark (linux/amd64)
The benchmark was performed by adding 100 metrics with six numeric The benchmark was performed by adding 100 metrics with six numeric
(and two non-numeric) fields to the aggregator and the derive the aggregation (and two non-numeric) fields to the aggregator and the derive the aggregation
result. result.
@ -72,7 +75,8 @@ result.
| exact R7 | 100 | 7868816 ns/op | | exact R7 | 100 | 7868816 ns/op |
| exact R8 | 100 | 8099612 ns/op | | exact R8 | 100 | 8099612 ns/op |
### Measurements ## Measurements
Measurement names are passed trough this aggregator. Measurement names are passed trough this aggregator.
### Fields ### Fields
@ -82,6 +86,7 @@ fields are aggregated in the form `<fieldname>_<quantile*100>`. Other field
types (e.g. boolean, string) are ignored and dropped from the output. types (e.g. boolean, string) are ignored and dropped from the output.
For example passing in the following metric as *input*: For example passing in the following metric as *input*:
- somemetric - somemetric
- average_response_ms (float64) - average_response_ms (float64)
- minimum_response_ms (float64) - minimum_response_ms (float64)
@ -89,7 +94,8 @@ For example passing in the following metric as *input*:
- status (string) - status (string)
- ok (boolean) - ok (boolean)
and the default setting for `quantiles ` you get the following *output* and the default setting for `quantiles` you get the following *output*
- somemetric - somemetric
- average_response_ms_025 (float64) - average_response_ms_025 (float64)
- average_response_ms_050 (float64) - average_response_ms_050 (float64)
@ -110,18 +116,18 @@ Tags are passed through to the output by this aggregator.
### Example Output ### Example Output
``` ```text
cpu,cpu=cpu-total,host=Hugin usage_user=10.814851731872487,usage_system=2.1679541490155687,usage_irq=1.046598554697342,usage_steal=0,usage_guest_nice=0,usage_idle=85.79616247197244,usage_nice=0,usage_iowait=0,usage_softirq=0.1744330924495688,usage_guest=0 1608288360000000000 cpu,cpu=cpu-total,host=Hugin usage_user=10.814851731872487,usage_system=2.1679541490155687,usage_irq=1.046598554697342,usage_steal=0,usage_guest_nice=0,usage_idle=85.79616247197244,usage_nice=0,usage_iowait=0,usage_softirq=0.1744330924495688,usage_guest=0 1608288360000000000
cpu,cpu=cpu-total,host=Hugin usage_guest=0,usage_system=2.1601016518428664,usage_iowait=0.02541296060990694,usage_irq=1.0165184243964942,usage_softirq=0.1778907242693666,usage_steal=0,usage_guest_nice=0,usage_user=9.275730622616953,usage_idle=87.34434561626493,usage_nice=0 1608288370000000000 cpu,cpu=cpu-total,host=Hugin usage_guest=0,usage_system=2.1601016518428664,usage_iowait=0.02541296060990694,usage_irq=1.0165184243964942,usage_softirq=0.1778907242693666,usage_steal=0,usage_guest_nice=0,usage_user=9.275730622616953,usage_idle=87.34434561626493,usage_nice=0 1608288370000000000
cpu,cpu=cpu-total,host=Hugin usage_idle=85.78199052131747,usage_nice=0,usage_irq=1.0476428036915637,usage_guest=0,usage_guest_nice=0,usage_system=1.995510102269591,usage_iowait=0,usage_softirq=0.1995510102269662,usage_steal=0,usage_user=10.975305562484735 1608288380000000000 cpu,cpu=cpu-total,host=Hugin usage_idle=85.78199052131747,usage_nice=0,usage_irq=1.0476428036915637,usage_guest=0,usage_guest_nice=0,usage_system=1.995510102269591,usage_iowait=0,usage_softirq=0.1995510102269662,usage_steal=0,usage_user=10.975305562484735 1608288380000000000
cpu,cpu=cpu-total,host=Hugin usage_guest_nice_075=0,usage_user_050=10.814851731872487,usage_guest_075=0,usage_steal_025=0,usage_irq_025=1.031558489546918,usage_irq_075=1.0471206791944527,usage_iowait_025=0,usage_guest_050=0,usage_guest_nice_050=0,usage_nice_075=0,usage_iowait_050=0,usage_system_050=2.1601016518428664,usage_irq_050=1.046598554697342,usage_guest_nice_025=0,usage_idle_050=85.79616247197244,usage_softirq_075=0.1887208672481664,usage_steal_075=0,usage_system_025=2.0778058770562287,usage_system_075=2.1640279004292173,usage_softirq_050=0.1778907242693666,usage_nice_050=0,usage_iowait_075=0.01270648030495347,usage_user_075=10.895078647178611,usage_nice_025=0,usage_steal_050=0,usage_user_025=10.04529117724472,usage_idle_025=85.78907649664495,usage_idle_075=86.57025404411868,usage_softirq_025=0.1761619083594677,usage_guest_025=0 1608288390000000000 cpu,cpu=cpu-total,host=Hugin usage_guest_nice_075=0,usage_user_050=10.814851731872487,usage_guest_075=0,usage_steal_025=0,usage_irq_025=1.031558489546918,usage_irq_075=1.0471206791944527,usage_iowait_025=0,usage_guest_050=0,usage_guest_nice_050=0,usage_nice_075=0,usage_iowait_050=0,usage_system_050=2.1601016518428664,usage_irq_050=1.046598554697342,usage_guest_nice_025=0,usage_idle_050=85.79616247197244,usage_softirq_075=0.1887208672481664,usage_steal_075=0,usage_system_025=2.0778058770562287,usage_system_075=2.1640279004292173,usage_softirq_050=0.1778907242693666,usage_nice_050=0,usage_iowait_075=0.01270648030495347,usage_user_075=10.895078647178611,usage_nice_025=0,usage_steal_050=0,usage_user_025=10.04529117724472,usage_idle_025=85.78907649664495,usage_idle_075=86.57025404411868,usage_softirq_025=0.1761619083594677,usage_guest_025=0 1608288390000000000
``` ```
# References ## References
- Dunning & Ertl: "Computing Extremely Accurate Quantiles Using t-Digests", arXiv:1902.04023 (2019) [pdf][tdigest_paper] - Dunning & Ertl: "Computing Extremely Accurate Quantiles Using t-Digests", arXiv:1902.04023 (2019) [pdf][tdigest_paper]
- Hyndman & Fan: "Sample Quantiles in Statistical Packages", The American Statistician, vol. 50, pp. 361-365 (1996) [pdf][hyndman_fan] - Hyndman & Fan: "Sample Quantiles in Statistical Packages", The American Statistician, vol. 50, pp. 361-365 (1996) [pdf][hyndman_fan]
[tdigest_paper]: https://arxiv.org/abs/1902.04023 [tdigest_paper]: https://arxiv.org/abs/1902.04023
[tdigest_lib]: https://github.com/caio/go-tdigest [tdigest_lib]: https://github.com/caio/go-tdigest
[hyndman_fan]: http://www.maths.usyd.edu.au/u/UG/SM/STAT3022/r/current/Misc/Sample%20Quantiles%20in%20Statistical%20Packages.pdf [hyndman_fan]: http://www.maths.usyd.edu.au/u/UG/SM/STAT3022/r/current/Misc/Sample%20Quantiles%20in%20Statistical%20Packages.pdf

20
plugins/aggregators/valuecounter/README.md
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@ -15,7 +15,7 @@ Counting fields with a high number of potential values may produce significant
amounts of new fields and memory usage, take care to only count fields with a amounts of new fields and memory usage, take care to only count fields with a
limited set of values. limited set of values.
### Configuration: ## Configuration
```toml ```toml
[[aggregators.valuecounter]] [[aggregators.valuecounter]]
@ -29,22 +29,23 @@ limited set of values.
fields = ["status"] fields = ["status"]
``` ```
### Measurements & Fields: ### Measurements & Fields
- measurement1 - measurement1
- field_value1 - field_value1
- field_value2 - field_value2
### Tags: ### Tags
No tags are applied by this aggregator. No tags are applied by this aggregator.
### Example Output: ## Example Output
Example for parsing a HTTP access log. Example for parsing a HTTP access log.
telegraf.conf: telegraf.conf:
```
```toml
[[inputs.logparser]] [[inputs.logparser]]
files = ["/tmp/tst.log"] files = ["/tmp/tst.log"]
[inputs.logparser.grok] [inputs.logparser.grok]
@ -57,13 +58,14 @@ telegraf.conf:
``` ```
/tmp/tst.log /tmp/tst.log
```
```text
/some/path 200 /some/path 200
/some/path 401 /some/path 401
/some/path 200 /some/path 200
``` ```
``` ```shell
$ telegraf --config telegraf.conf --quiet $ telegraf --config telegraf.conf --quiet
access,url=/some/path,path=/tmp/tst.log,host=localhost.localdomain response="200" 1511948755991487011 access,url=/some/path,path=/tmp/tst.log,host=localhost.localdomain response="200" 1511948755991487011