mirror of https://github.com/grafana/grafana
Docs: Added Intro to histograms and heatmaps (#24174)
* Moved files Moved files from guides folder into getting-started folder, added aliases, added Intro to histograms topic * Updated links * Update intro-histograms.md Co-authored-by: Daniel Lee <dan.limerick@gmail.com>pull/24295/head
Diana Payton
5 years ago
committed by
GitHub
parent
f597a686fa
commit
376749ee32
@ -0,0 +1,9 @@ |
||||
+++ |
||||
title = "Getting started" |
||||
type = "docs" |
||||
[menu.docs] |
||||
name = "Getting started" |
||||
identifier = "getting-started" |
||||
weight = 100 |
||||
+++ |
||||
|
||||
@ -0,0 +1,58 @@ |
||||
+++ |
||||
title = "Histograms and heatmaps" |
||||
description = "An introduction to histograms and heatmaps" |
||||
keywords = ["grafana", "heatmap", "panel", "documentation", "histogram"] |
||||
type = "docs" |
||||
[menu.docs] |
||||
name = "intro-to-histograms" |
||||
parent = "panels" |
||||
weight = 400 |
||||
+++ |
||||
|
||||
# Introduction to histograms and heatmaps |
||||
|
||||
A histogram is a graphical representation of the distribution of numerical data. It groups values into buckets |
||||
(sometimes also called bins) and then counts how many values fall into each bucket. |
||||
|
||||
Instead of graphing the actual values, histograms graph the buckets. Each bar represents a bucket, |
||||
and the bar height represents the frequency (such as count) of values that fell into that bucket's interval. |
||||
|
||||
## Histogram example |
||||
|
||||
This histogram shows the value distribution of a couple of time series. You can easily see that |
||||
most values land between 240-300 with a peak between 260-280. |
||||
|
||||
 |
||||
|
||||
Histograms only look at _value distributions_ over a specific time range. The problem with histograms is you cannot see any trend or changes in the distribution over time. |
||||
This is where heatmaps become useful. |
||||
|
||||
## Heatmaps |
||||
|
||||
A _heatmap_ is like a histogram, but over time where each time slice represents its own histogram. Instead of using bar height as a representation of frequency, it uses cells and colors the cell proportional to the number of values in the bucket. |
||||
|
||||
In this example, you can clearly see what values are more common and how they trend over time. |
||||
|
||||
 |
||||
|
||||
## Pre-bucketed data |
||||
|
||||
There are a number of data sources supporting histogram over time like Elasticsearch (by using a Histogram bucket |
||||
aggregation) or Prometheus (with [histogram](https://prometheus.io/docs/concepts/metric_types/#histogram) metric type |
||||
and *Format as* option set to Heatmap). But generally, any data source could be used if it meets the requirements: |
||||
returns series with names representing bucket bound or returns series sorted by the bound in ascending order. |
||||
|
||||
## Raw data vs aggregated |
||||
|
||||
If you use the heatmap with regular time series data (not pre-bucketed), then it's important to keep in mind that your data |
||||
is often already aggregated by your time series backend. Most time series queries do not return raw sample data |
||||
but include a group by time interval or maxDataPoints limit coupled with an aggregation function (usually average). |
||||
|
||||
This all depends on the time range of your query of course. But the important point is to know that the histogram bucketing |
||||
that Grafana performs might be done on already aggregated and averaged data. To get more accurate heatmaps it is better |
||||
to do the bucketing during metric collection or store the data in Elasticsearch, or in the other data source which |
||||
supports doing histogram bucketing on the raw data. |
||||
|
||||
If you remove or lower the group by time (or raise maxDataPoints) in your query to return more data points your heatmap will be |
||||
more accurate but this can also be very CPU and memory taxing for your browser and could cause hangs and crashes if the number of |
||||
data points becomes unreasonably large. |
||||
Loading…
Reference in new issue