Create histograms with Flux
Histograms provide valuable insight into the distribution of your data.
This guide walks through using Flux’s histogram() function to transform your data into a cumulative histogram.
histogram() function
The histogram() function approximates the
cumulative distribution of a dataset by counting data frequencies for a list of “bins.”
A bin is simply a range in which a data point falls.
All data points that are less than or equal to the bound are counted in the bin.
In the histogram output, a column is added (le) that represents the upper bounds of of each bin.
Bin counts are cumulative.
from(bucket:"telegraf/autogen")
|> range(start: -5m)
|> filter(fn: (r) =>
r._measurement == "mem" and
r._field == "used_percent"
)
|> histogram(bins: [0.0, 10.0, 20.0, 30.0])
Values output by the
histogramfunction represent points of data aggregated over time. Since values do not represent single points in time, there is no_timecolumn in the output table.
Bin helper functions
Flux provides two helper functions for generating histogram bins.
Each generates and outputs an array of floats designed to be used in the histogram() function’s bins parameter.
linearBins()
The linearBins() function generates a list of linearly separated floats.
linearBins(start: 0.0, width: 10.0, count: 10)
// Generated list: [0, 10, 20, 30, 40, 50, 60, 70, 80, 90, +Inf]
logarithmicBins()
The logarithmicBins() function generates a list of exponentially separated floats.
logarithmicBins(start: 1.0, factor: 2.0, count: 10, infinty: true)
// Generated list: [1, 2, 4, 8, 16, 32, 64, 128, 256, 512, +Inf]
Examples
Generating a histogram with linear bins
from(bucket:"telegraf/autogen")
|> range(start: -5m)
|> filter(fn: (r) =>
r._measurement == "mem" and
r._field == "used_percent"
)
|> histogram(
bins: linearBins(
start:65.5,
width: 0.5,
count: 20,
infinity:false
)
)
Output table
Table: keys: [_start, _stop, _field, _measurement, host]
_start:time _stop:time _field:string _measurement:string host:string le:float _value:float
------------------------------ ------------------------------ ---------------------- ---------------------- ------------------------ ---------------------------- ----------------------------
2018-11-07T22:19:58.423658000Z 2018-11-07T22:24:58.423658000Z used_percent mem Scotts-MacBook-Pro.local 65.5 5
2018-11-07T22:19:58.423658000Z 2018-11-07T22:24:58.423658000Z used_percent mem Scotts-MacBook-Pro.local 66 6
2018-11-07T22:19:58.423658000Z 2018-11-07T22:24:58.423658000Z used_percent mem Scotts-MacBook-Pro.local 66.5 8
2018-11-07T22:19:58.423658000Z 2018-11-07T22:24:58.423658000Z used_percent mem Scotts-MacBook-Pro.local 67 9
2018-11-07T22:19:58.423658000Z 2018-11-07T22:24:58.423658000Z used_percent mem Scotts-MacBook-Pro.local 67.5 9
2018-11-07T22:19:58.423658000Z 2018-11-07T22:24:58.423658000Z used_percent mem Scotts-MacBook-Pro.local 68 10
2018-11-07T22:19:58.423658000Z 2018-11-07T22:24:58.423658000Z used_percent mem Scotts-MacBook-Pro.local 68.5 12
2018-11-07T22:19:58.423658000Z 2018-11-07T22:24:58.423658000Z used_percent mem Scotts-MacBook-Pro.local 69 12
2018-11-07T22:19:58.423658000Z 2018-11-07T22:24:58.423658000Z used_percent mem Scotts-MacBook-Pro.local 69.5 15
2018-11-07T22:19:58.423658000Z 2018-11-07T22:24:58.423658000Z used_percent mem Scotts-MacBook-Pro.local 70 23
2018-11-07T22:19:58.423658000Z 2018-11-07T22:24:58.423658000Z used_percent mem Scotts-MacBook-Pro.local 70.5 30
2018-11-07T22:19:58.423658000Z 2018-11-07T22:24:58.423658000Z used_percent mem Scotts-MacBook-Pro.local 71 30
2018-11-07T22:19:58.423658000Z 2018-11-07T22:24:58.423658000Z used_percent mem Scotts-MacBook-Pro.local 71.5 30
2018-11-07T22:19:58.423658000Z 2018-11-07T22:24:58.423658000Z used_percent mem Scotts-MacBook-Pro.local 72 30
2018-11-07T22:19:58.423658000Z 2018-11-07T22:24:58.423658000Z used_percent mem Scotts-MacBook-Pro.local 72.5 30
2018-11-07T22:19:58.423658000Z 2018-11-07T22:24:58.423658000Z used_percent mem Scotts-MacBook-Pro.local 73 30
2018-11-07T22:19:58.423658000Z 2018-11-07T22:24:58.423658000Z used_percent mem Scotts-MacBook-Pro.local 73.5 30
2018-11-07T22:19:58.423658000Z 2018-11-07T22:24:58.423658000Z used_percent mem Scotts-MacBook-Pro.local 74 30
2018-11-07T22:19:58.423658000Z 2018-11-07T22:24:58.423658000Z used_percent mem Scotts-MacBook-Pro.local 74.5 30
2018-11-07T22:19:58.423658000Z 2018-11-07T22:24:58.423658000Z used_percent mem Scotts-MacBook-Pro.local 75 30
Generating a histogram with logarithmic bins
from(bucket:"telegraf/autogen")
|> range(start: -5m)
|> filter(fn: (r) =>
r._measurement == "mem" and
r._field == "used_percent"
)
|> histogram(
bins: logarithmicBins(
start:0.5,
factor: 2.0,
count: 10,
infinity:false
)
)
Output table
Table: keys: [_start, _stop, _field, _measurement, host]
_start:time _stop:time _field:string _measurement:string host:string le:float _value:float
------------------------------ ------------------------------ ---------------------- ---------------------- ------------------------ ---------------------------- ----------------------------
2018-11-07T22:23:36.860664000Z 2018-11-07T22:28:36.860664000Z used_percent mem Scotts-MacBook-Pro.local 0.5 0
2018-11-07T22:23:36.860664000Z 2018-11-07T22:28:36.860664000Z used_percent mem Scotts-MacBook-Pro.local 1 0
2018-11-07T22:23:36.860664000Z 2018-11-07T22:28:36.860664000Z used_percent mem Scotts-MacBook-Pro.local 2 0
2018-11-07T22:23:36.860664000Z 2018-11-07T22:28:36.860664000Z used_percent mem Scotts-MacBook-Pro.local 4 0
2018-11-07T22:23:36.860664000Z 2018-11-07T22:28:36.860664000Z used_percent mem Scotts-MacBook-Pro.local 8 0
2018-11-07T22:23:36.860664000Z 2018-11-07T22:28:36.860664000Z used_percent mem Scotts-MacBook-Pro.local 16 0
2018-11-07T22:23:36.860664000Z 2018-11-07T22:28:36.860664000Z used_percent mem Scotts-MacBook-Pro.local 32 0
2018-11-07T22:23:36.860664000Z 2018-11-07T22:28:36.860664000Z used_percent mem Scotts-MacBook-Pro.local 64 2
2018-11-07T22:23:36.860664000Z 2018-11-07T22:28:36.860664000Z used_percent mem Scotts-MacBook-Pro.local 128 30
2018-11-07T22:23:36.860664000Z 2018-11-07T22:28:36.860664000Z used_percent mem Scotts-MacBook-Pro.local 256 30