*Min step* | Set a lower limit for the Prometheus step option. Step controls how big the jumps are when the Prometheus query engine performs range queries. Sadly there is no official prometheus documentation to link to for this very important option.
*Min step* | Set a lower limit for the Prometheus step option. Step controls how big the jumps are when the Prometheus query engine performs range queries. Sadly there is no official prometheus documentation to link to for this very important option.
*Resolution* | Controls the step option. Small steps create high-resolution graphs but can be slow over larger time ranges, lowering the resolution can speed things up. `1/2` will try to set step option to generate 1 data point for every other pixel. A value of `1/10` will try to set step option so there is a data point every 10 pixels.
*Resolution* | Controls the step option. Small steps create high-resolution graphs but can be slow over larger time ranges, lowering the resolution can speed things up. `1/2` will try to set step option to generate 1 data point for every other pixel. A value of `1/10` will try to set step option so there is a data point every 10 pixels.
*Metric lookup* | Search for metric names in this input field.
*Metric lookup* | Search for metric names in this input field.
*Format as* | **(New in v4.3)** Switch between Table & Time series. Table format will only work in the Table panel.
*Format as* | **(New in v4.3)** Switch between Table, Time series or Heatmap. Table format will only work in the Table panel. Heatmap format is suitable for displaying metrics having histogram type on Heatmap panel. Under the hood, it converts cumulative histogram to regular and sorts series by the bucket bound.
@@ -56,26 +56,39 @@ Data and bucket options can be found in the `Axes` tab.
...
@@ -56,26 +56,39 @@ Data and bucket options can be found in the `Axes` tab.
Data format | Description
Data format | Description
------------ | -------------
------------ | -------------
*Time series* | Grafana does the bucketing by going through all time series values. The bucket sizes & intervals will be determined using the Buckets options.
*Time series* | Grafana does the bucketing by going through all time series values. The bucket sizes & intervals will be determined using the Buckets options.
*Time series buckets* | Each time series already represents a Y-Axis bucket. The time series name (alias) needs to be a numeric value representing the upper interval for the bucket. Grafana does no bucketing so the bucket size options are hidden.
*Time series buckets* | Each time series already represents a Y-Axis bucket. The time series name (alias) needs to be a numeric value representing the upper or lower interval for the bucket. Grafana does no bucketing so the bucket size options are hidden.
### Bucket bound
When Data format is *Time series buckets* datasource returns series with names representing bucket bound. But depending
on datasource, a bound may be *upper* or *lower*. This option allows to adjust a bound type. If *Auto* is set, a bound
option will be chosen based on panels' datasource type.
### Bucket Size
### Bucket Size
The Bucket count & size options are used by Grafana to calculate how big each cell in the heatmap is. You can
The Bucket count & size options are used by Grafana to calculate how big each cell in the heatmap is. You can
define the bucket size either by count (the first input box) or by specifying a size interval. For the Y-Axis
define the bucket size either by count (the first input box) or by specifying a size interval. For the Y-Axis
the size interval is just a value but for the X-bucket you can specify a time range in the *Size* input, for example,
the size interval is just a value but for the X-bucket you can specify a time range in the *Size* input, for example,
the time range `1h`. This will make the cells 1h wide on the X-axis.
the time range `1h`. This will make the cells 1h wide on the X-axis.
### Pre-bucketed data
### Pre-bucketed data
If you have a data that is already organized into buckets you can use the `Time series buckets` data format. This format requires that your metric query return regular time series and that each time series has a numeric name
If you have a data that is already organized into buckets you can use the `Time series buckets` data format. This format
that represent the upper or lower bound of the interval.
requires that your metric query return regular time series and that each time series has a numeric name that represent
the upper or lower bound of the interval.
There are a number of datasources 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 datasource could be used if it meets the requirements:
returns series with names representing bucket bound or returns sereis sorted by the bound in ascending order.
With Elasticsearch you control the size of the buckets using the Histogram interval (Y-Axis) and the Date Histogram interval (X-axis).
The only data source that supports histograms over time is Elasticsearch. You do this by adding a *Histogram*
