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Docs: added documentation for the "prepare time series"-transformation. (#36761)
* added documentation for the prepare time series transformation. * Update docs/sources/developers/plugins/data-frames.md Co-authored-by: Jack Westbrook <jack.westbrook@gmail.com> * Update docs/sources/panels/transformations/types-options.md Co-authored-by: Jack Westbrook <jack.westbrook@gmail.com> * Update docs/sources/panels/transformations/types-options.md Co-authored-by: Marcus Olsson <marcus.olsson@hey.com> * Update docs/sources/panels/transformations/types-options.md Co-authored-by: Marcus Olsson <marcus.olsson@hey.com> * changed according to feedbcak. Co-authored-by: Jack Westbrook <jack.westbrook@gmail.com> Co-authored-by: Marcus Olsson <marcus.olsson@hey.com>
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Marcus Andersson
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@ -30,17 +30,17 @@ In essence, a data frame is a collection of _fields_, where each field correspon
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```ts
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interface Field {
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name: string;
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// Prometheus like Labels / Tags
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labels?: Record<string, string>;
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name: string;
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// Prometheus like Labels / Tags
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labels?: Record<string, string>;
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// For example string, number, time (or more specific primitives in the backend)
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type: FieldType;
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// Array of values all of the same type
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values: Vector<T>;
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// For example string, number, time (or more specific primitives in the backend)
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type: FieldType;
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// Array of values all of the same type
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values: Vector<T>;
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// Optional display data for the field (e.g. unit, name over-ride, etc)
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config: FieldConfig;
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// Optional display data for the field (e.g. unit, name over-ride, etc)
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config: FieldConfig;
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}
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```
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@ -163,6 +163,8 @@ Dimensions: 5 fields by 2 rows
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+---------------------+------------------+------------------+------------------+------------------+
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```
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> **Note:** Not all panels support the wide time series data frame format. To keep full backward compatibility we have introduced a transformation that can be used to convert from the wide to the long format. Read more about how to use it here: [Prepare time series-transformation]({{< relref "../../panels/transformations/types-options.md#prepare-time-series" >}}).
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## Technical references
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This section contains links to technical reference and implementations of data frames.
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@ -23,60 +23,60 @@ Grafana comes with the following transformations:
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- [Rows to fields]({{< relref "./rows-to-fields" >}})
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- [Series to rows]({{< relref "./types-options.md#series-to-rows" >}})
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- [Sort by]({{< relref "./types-options.md#sort-by" >}})
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- [Prepare-time-series]({{< relref "./types-options.md#prepare-time-series" >}})
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Keep reading for detailed descriptions of each type of transformation and the options available for each, as well as suggestions on how to use them.
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## Reduce
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The _Reduce_ transformation will apply a calculation to each field in the frame and return a single value. Time fields are removed when applying
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The _Reduce_ transformation applies a calculation to each field in the frame and return a single value. Time fields are removed when applying
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this transformation.
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Consider the input:
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Query A:
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| Time | Temp | Uptime |
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| ------------------- | ------- | ------- |
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| 2020-07-07 11:34:20 | 12.3 | 256122 |
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| 2020-07-07 11:24:20 | 15.4 | 1230233 |
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| Time | Temp | Uptime |
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| ------------------- | ---- | ------- |
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| 2020-07-07 11:34:20 | 12.3 | 256122 |
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| 2020-07-07 11:24:20 | 15.4 | 1230233 |
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Query B:
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| Time | AQI | Errors |
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| ------------------- | ------- | ------ |
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| 2020-07-07 11:34:20 | 6.5 | 15 |
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| 2020-07-07 11:24:20 | 3.2 | 5 |
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| Time | AQI | Errors |
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| ------------------- | --- | ------ |
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| 2020-07-07 11:34:20 | 6.5 | 15 |
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| 2020-07-07 11:24:20 | 3.2 | 5 |
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The reduce transformer has two modes:
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- **Series to rows -** Creates a row for each field and a column for each calculation.
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- **Reduce fields -** Keeps the existing frame structure, but collapses each field into a single value.
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For example, if you used the **First** and **Last** calculation with a **Series to rows** transformation, then
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the result would be:
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| Field | First | Last |
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| ------- | ------- | ------- |
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| Temp | 12.3 | 15.4 |
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| Uptime | 256122 | 1230233 |
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| AQI | 6.5 | 3.2 |
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| Errors | 15 | 5 |
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| Field | First | Last |
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| ------ | ------ | ------- |
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| Temp | 12.3 | 15.4 |
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| Uptime | 256122 | 1230233 |
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| AQI | 6.5 | 3.2 |
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| Errors | 15 | 5 |
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The **Reduce fields** with the **Last** calculation,
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results in two frames, each with one row:
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Query A:
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| Temp | Uptime |
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| ------- | ------- |
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| 15.4 | 1230233 |
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| Temp | Uptime |
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| ---- | ------- |
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| 15.4 | 1230233 |
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Query B:
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| AQI | Errors |
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| ------- | ------ |
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| 3.2 | 5 |
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| AQI | Errors |
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| --- | ------ |
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| 3.2 | 5 |
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## Merge
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@ -181,7 +181,7 @@ Use this transformation to add a new field calculated from two other fields. Eac
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- **Binary option -** Apply basic math operation(sum, multiply, etc) on values in a single row from two selected fields.
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- **Field name -** Select the names of fields you want to use in the calculation for the new field.
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- **Calculation -** If you select **Reduce row** mode, then the **Calculation** field appears. Click in the field to see a list of calculation choices you can use to create the new field. For information about available calculations, refer to the [Calculation list]({{< relref "../calculations-list.md" >}}).
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- **Operation -** If you select **Binary option** mode, then the **Operation** fields appear. These fields allow you to do basic math operations on values in a single row from two selected fields. You can also use numerical values for binary operations.
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- **Operation -** If you select **Binary option** mode, then the **Operation** fields appear. These fields allow you to do basic math operations on values in a single row from two selected fields. You can also use numerical values for binary operations.
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- **Alias -** (Optional) Enter the name of your new field. If you leave this blank, then the field will be named to match the calculation.
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- **Replace all fields -** (Optional) Select this option if you want to hide all other fields and display only your calculated field in the visualization.
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@ -195,8 +195,8 @@ This transformation changes time series results that include labels or tags into
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Given a query result of two time series:
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* Series 1: labels Server=Server A, Datacenter=EU
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* Series 2: labels Server=Server B, Datacenter=EU
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- Series 1: labels Server=Server A, Datacenter=EU
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- Series 2: labels Server=Server B, Datacenter=EU
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This would result in a table like this:
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@ -219,18 +219,18 @@ The labels to fields transformer is internally two separate transformations. The
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To illustrate this, here is an example where you have two queries that return time series with no overlapping labels.
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* Series 1: labels Server=ServerA
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* Series 2: labels Datacenter=EU
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- Series 1: labels Server=ServerA
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- Series 2: labels Datacenter=EU
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This will first result in these two tables:
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| Time | Server | Value |
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| ------------------- | ------- | ----- |
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| 2020-07-07 11:34:20 | ServerA | 10
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| 2020-07-07 11:34:20 | ServerA | 10 |
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| Time | Datacenter | Value |
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| ------------------- | ---------- | ----- |
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| 2020-07-07 11:34:20 | EU | 20
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| 2020-07-07 11:34:20 | EU | 20 |
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After merge:
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@ -244,7 +244,6 @@ After merge:
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This transformation will sort each frame by the configured field, When `reverse` is checked, the values will return in
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the opposite order.
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## Group by
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This transformation groups the data by a specified field (column) value and processes calculations on each group. Click to see a list of calculation choices. For information about available calculations, refer to the [List of calculations]({{< relref "../calculations-list.md" >}}).
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@ -305,26 +304,25 @@ This transformation allows you to extract some key information out of your time
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## Concatenate fields
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This transformation combines all fields from all frames into one result. Consider:
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This transformation combines all fields from all frames into one result. Consider:
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Query A:
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| Temp | Uptime |
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| ------- | ------- |
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| 15.4 | 1230233 |
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| Temp | Uptime |
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| ---- | ------- |
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| 15.4 | 1230233 |
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Query B:
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| AQI | Errors |
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| ------- | ------ |
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| 3.2 | 5 |
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| AQI | Errors |
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| --- | ------ |
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| 3.2 | 5 |
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After you concatenate the fields, the data frame would be:
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| Temp | Uptime | AQI | Errors |
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| ------- | ------- | ------- | ------ |
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| 15.4 | 1230233 | 3.2 | 5 |
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| Temp | Uptime | AQI | Errors |
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| ---- | ------- | --- | ------ |
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| 15.4 | 1230233 | 3.2 | 5 |
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## Series to rows
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@ -437,3 +435,15 @@ In the following example, we are stripping the prefix from event types. In the b
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With the transformation applied, you can see we are left with just the remainder of the string.
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{{< figure src="/static/img/docs/transformations/rename-by-regex-after-7-3.png" class="docs-image--no-shadow" max-width= "1100px" >}}
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## Prepare time series
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> **Note:** This transformation is available in Grafana 7.5.10+ and Grafana 8.0.6+.
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Prepare time series transformation is useful when a data source returns time series data in a format that isn't supported by the panel you want to use. [Read more about the different data frame formats here]({{< relref "../../developers/plugins/data-frames.md" >}}).
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This transformation helps you resolve this issue by converting the time series data from either the wide format to the long format or the other way around.
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Select the `Multi-frame time series` option to transform the time series data frame from the wide to the long format.
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Select the `Wide time series` option to transform the time series data frame from the long to the wide format.
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