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Enable doc-validator for specific directories (#63524)

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* Enable doc-validator for specific directories

Signed-off-by: Jack Baldry <jack.baldry@grafana.com>

* Fix one linting error to trigger CI

Signed-off-by: Jack Baldry <jack.baldry@grafana.com>

* Update doc-validator to latest release

Signed-off-by: Jack Baldry <jack.baldry@grafana.com>

* Update make-docs procedure

Signed-off-by: Jack Baldry <jack.baldry@grafana.com>

* Use doc-validator version from CI in local make target

Signed-off-by: Jack Baldry <jack.baldry@grafana.com>

* Revert to 1.11.0

Signed-off-by: Jack Baldry <jack.baldry@grafana.com>

* adds missing descriptions

* Fix titles and headings

Signed-off-by: Jack Baldry <jack.baldry@grafana.com>

* Fix link formats

Signed-off-by: Jack Baldry <jack.baldry@grafana.com>

* Fix easy to resolve anchors

Signed-off-by: Jack Baldry <jack.baldry@grafana.com>

* Remove broken anchor link

This anchor appears to have been broken for a long time.

Signed-off-by: Jack Baldry <jack.baldry@grafana.com>

* Use doc-validator image with support for numbered anchors

Signed-off-by: Jack Baldry <jack.baldry@grafana.com>

* Update make-docs procedure to support doc-validator 2.0.x

Signed-off-by: Jack Baldry <jack.baldry@grafana.com>

* Fix a bunch of broken anchors

Signed-off-by: Jack Baldry <jack.baldry@grafana.com>

* Ignore old whatsnew content

Signed-off-by: Jack Baldry <jack.baldry@grafana.com>

* Update doc-validator to v2.0.x and use reviewdog to report errors

Signed-off-by: Jack Baldry <jack.baldry@grafana.com>

* removes broken links

---------

Signed-off-by: Jack Baldry <jack.baldry@grafana.com>
Co-authored-by: Chris Moyer <chris.moyer@grafana.com>
This commit is contained in:
Jack Baldry
2023-05-18 15:50:20 +01:00
committed by GitHub
parent 44b1dae16d
commit 560f49b3dc
94 changed files with 903 additions and 800 deletions
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6
docs/sources/fundamentals/timeseries-dimensions/index.md
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@@ -18,7 +18,7 @@ weight: 600
# Time series dimensions
In [Introduction to time series]({{< relref "timeseries/#time-series-databases" >}}), the concept of _labels_, also called _tags_, is introduced:
In [Introduction to time series]({{< relref "../timeseries#time-series-databases" >}}), the concept of _labels_, also called _tags_, is introduced:
> Another feature of a TSDB is the ability to filter measurements using _tags_. Each data point is labeled with a tag that adds context information, such as where the measurement was taken.
@@ -86,10 +86,10 @@ In this case the labels that represent the dimensions will have two keys based o
> **Note:** More than one dimension is currently only supported in the Logs queries within the Azure Monitor service as of version 7.1.
> **Note:** Multiple dimensions are not supported in a way that maps to multiple alerts in Grafana, but rather they are treated as multiple conditions to a single alert. For more information, see See the documentation on [creating alerts with multiple series]({{< relref "../../alerting/alerting-rules/create-grafana-managed-rule/#single-and-multi-dimensional-rule" >}}).
> **Note:** Multiple dimensions are not supported in a way that maps to multiple alerts in Grafana, but rather they are treated as multiple conditions to a single alert. For more information, see See the documentation on [creating alerts with multiple series]({{< relref "../../alerting/alerting-rules/create-grafana-managed-rule#single-and-multi-dimensional-rule" >}}).
### Multiple values
In the case of SQL-like data sources, more than one numeric column can be selected, with or without additional string columns to be used as dimensions. For example, `AVG(Temperature) AS AvgTemp, MAX(Temperature) AS MaxTemp`. This, if combined with multiple dimensions, can result in a lot of series. Selecting multiple values is currently only designed to be used with visualization.
Additional technical information on tabular time series formats and how dimensions are extracted can be found in [the developer documentation on data frames as time series]({{< relref "../../developers/plugins/data-frames/#data-frames-as-time-series" >}}).
Additional technical information on tabular time series formats and how dimensions are extracted can be found in [the developer documentation on data frames as time series]({{< relref "../../developers/plugins/data-frames#data-frames-as-time-series" >}}).