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Transformers: Support inner vs outer join (#53913)

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Ryan McKinley
2022-08-23 10:14:03 -07:00
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docs/sources/panels/transform-data/index.md
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@ -322,15 +322,77 @@ We would then get :
| server 2 | 88.6 | 90 | 2020-07-07 10:32:20 | Overload |
| server 3 | 59.6 | 62 | 2020-07-07 11:34:20 | OK |
This transformation allows you to extract some key information out of your time series and display them in a convenient way.
This transformation enables you to extract key information from your time series and display it in a convenient way.
### Join by field (outer join)
### Join by field
Use this transformation to join multiple time series from a result set by field.
Use this transformation to join multiple results into a single table. This is especially useful for converting multiple
time series results into a single wide table with a shared time field.
This transformation is especially useful if you want to combine queries so that you can calculate results from the fields.
#### Inner join
In the example below, I have a template query displaying time series data from multiple servers in a table visualization. I can only view the results of one query at a time.
An inner join merges data from multiple tables where all tables share the same value from the selected field. This type of join excludes
data where values do not match in every result.
Use this transformation to combine the results from multiple queries (combining on a passed join field or the first time column) into one result, and drop rows where a successful join cannot occur.
In the following example, two queries return table data. It is visualized as two separate tables before applying the inner join transformation.
Query A:
| Time | Job | Uptime |
| ------------------- | ------- | --------- |
| 2020-07-07 11:34:20 | node | 25260122 |
| 2020-07-07 11:24:20 | postgre | 123001233 |
| 2020-07-07 11:14:20 | postgre | 345001233 |
Query B:
| Time | Server | Errors |
| ------------------- | -------- | ------ |
| 2020-07-07 11:34:20 | server 1 | 15 |
| 2020-07-07 11:24:20 | server 2 | 5 |
| 2020-07-07 11:04:20 | server 3 | 10 |
The result after applying the inner join transformation looks like the following:
| Time | Job | Uptime | Server | Errors |
| ------------------- | ------- | --------- | -------- | ------ |
| 2020-07-07 11:34:20 | node | 25260122 | server 1 | 15 |
| 2020-07-07 11:24:20 | postgre | 123001233 | server 2 | 5 |
#### Outer join
An outer join includes all data from an inner join and rows where values do not match in every input.
Use this transformation to combine the results from multiple queries (combining on a passed join field or the first time column) into one result, and drop rows where a successful join cannot occur - performing an inner join.
In the following example, two queries return table data. It is visualized as two tables before applying the inner join transformation.
Query A:
| Time | Job | Uptime |
| ------------------- | ------- | --------- |
| 2020-07-07 11:34:20 | node | 25260122 |
| 2020-07-07 11:24:20 | postgre | 123001233 |
| 2020-07-07 11:14:20 | postgre | 345001233 |
Query B:
| Time | Server | Errors |
| ------------------- | -------- | ------ |
| 2020-07-07 11:34:20 | server 1 | 15 |
| 2020-07-07 11:24:20 | server 2 | 5 |
| 2020-07-07 11:04:20 | server 3 | 10 |
The result after applying the inner join transformation looks like the following:
| Time | Job | Uptime | Server | Errors |
| ------------------- | ------- | --------- | -------- | ------ |
| 2020-07-07 11:34:20 | node | 25260122 | server 1 | 15 |
| 2020-07-07 11:24:20 | postgre | 123001233 | server 2 | 5 |
In the following example, a template query displays time series data from multiple servers in a table visualization. The results of only one query can be viewed at a time.
{{< figure src="/static/img/docs/transformations/join-fields-before-7-0.png" class="docs-image--no-shadow" max-width= "1100px" >}}
@ -643,32 +705,3 @@ Here is the result after adding a Limit transformation with a value of '3':
| 2020-07-07 11:34:20 | Temperature | 25 |
| 2020-07-07 11:34:20 | Humidity | 22 |
| 2020-07-07 10:32:20 | Humidity | 29 |
### Join by field (Inner join)
Use this transformation to combine the results from multiple queries (combining on a passed join field or the first time column) into one single result and drop rows where a successful join isn't able to occur - performing an inner join.
In the example below, we have two queries returning table data. It is visualized as two separate tables before applying the inner join transformation.
Query A:
| Time | Job | Uptime |
| ------------------- | ------- | --------- |
| 2020-07-07 11:34:20 | node | 25260122 |
| 2020-07-07 11:24:20 | postgre | 123001233 |
| 2020-07-07 11:14:20 | postgre | 345001233 |
Query B:
| Time | Server | Errors |
| ------------------- | -------- | ------ |
| 2020-07-07 11:34:20 | server 1 | 15 |
| 2020-07-07 11:24:20 | server 2 | 5 |
| 2020-07-07 11:04:20 | server 3 | 10 |
Result after applying the inner join transformation:
| Time | Job | Uptime | Server | Errors |
| ------------------- | ------- | --------- | -------- | ------ |
| 2020-07-07 11:34:20 | node | 25260122 | server 1 | 15 |
| 2020-07-07 11:24:20 | postgre | 123001233 | server 2 | 5 |