Scott Anderson
GitHub
commit
4e2cfeab06
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@ -24,6 +24,14 @@ svg {
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.geo-region{fill:rgba($svg-geo-region, 0.35);stroke:$svg-geo-region;stroke-width:3;stroke-linejoin:round;stroke-miterlimit:10;}
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.geo-point{fill:$svg-geo-point;}
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}
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&#timed-moving-average {
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margin: 1rem 0 3rem;
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max-width: 425px;
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.st0 {stroke: $article-text;}
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.st1 {fill: $article-text;}
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.st2 {font-family: $rubik; font-weight: $medium}
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}
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}
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//////////////////////////// Styles for SVG legends ////////////////////////////
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@ -1,18 +1,27 @@
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---
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title: Query using conditional logic
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seotitle: Query using conditional logic in Flux
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list_title: Use conditional logic
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list_title: Conditional logic
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description: >
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This guide describes how to use Flux conditional expressions, such as `if`,
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`else`, and `then`, to query and transform data.
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v2.0/tags: [conditionals, flux]
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menu:
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v2_0:
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name: Use conditional logic
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name: Conditional logic
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parent: Query with Flux
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weight: 220
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aliases:
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- /v2.0/query-data/guides/conditional-logic/
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- /v2.0/query-data/guides/conditional-logic/
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related:
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- /v2.0/query-data/flux/query-fields/
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- /v2.0/reference/flux/stdlib/built-in/transformations/filter/
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- /v2.0/reference/flux/stdlib/built-in/transformations/map/
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- /v2.0/reference/flux/stdlib/built-in/transformations/aggregates/reduce/
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list_code_example: |
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```js
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if color == "green" then "008000" else "ffffff"
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```
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---
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Flux provides `if`, `then`, and `else` conditional expressions that allow for powerful and flexible Flux queries.
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|
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@ -8,8 +8,15 @@ weight: 210
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menu:
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v2_0:
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parent: Query with Flux
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name: Query the cumulative sum
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name: Cumulative sum
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v2.0/tags: [query, cumulative sum]
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related:
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- /v2.0/reference/flux/stdlib/built-in/transformations/cumulativesum/
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list_code_example: |
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```js
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data
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|> cumulativeSum()
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```
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---
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Use the [`cumulativeSum()` function](/v2.0/reference/flux/stdlib/built-in/transformations/cumulativesum/)
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|
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@ -1,14 +1,24 @@
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---
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title: Create custom Flux functions
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description: Create your own custom Flux functions to transform and manipulate data.
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list_title: Custom functions
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v2.0/tags: [functions, custom, flux]
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menu:
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v2_0:
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name: Create custom functions
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name: Custom functions
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parent: Query with Flux
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weight: 220
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aliases:
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- /v2.0/query-data/guides/custom-functions/
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- /v2.0/query-data/guides/custom-functions/
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list_code_example: |
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```js
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multByX = (tables=<-, x) =>
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tables
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|> map(fn: (r) => ({ r with _value: r._value * x}))
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data
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|> multByX(x: 2.0)
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```
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---
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Flux's functional syntax allows for custom functions.
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|
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@ -5,10 +5,12 @@ v2.0/tags: [functions, custom, flux, aggregates]
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menu:
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v2_0:
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name: Custom aggregate functions
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parent: Create custom functions
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parent: Custom functions
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weight: 301
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aliases:
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- /v2.0/query-data/guides/custom-functions/custom-aggregate/
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- /v2.0/query-data/guides/custom-functions/custom-aggregate/
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related:
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- /v2.0/reference/flux/stdlib/built-in/transformations/aggregates/reduce/
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---
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To aggregate your data, use the Flux
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|
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@ -1,17 +1,27 @@
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---
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title: Check if a value exists
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seotitle: Use Flux to check if a value exists
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list_title: Exists
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description: >
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Use the Flux `exists` operator to check if an object contains a key or if that
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key's value is `null`.
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v2.0/tags: [exists]
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menu:
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v2_0:
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name: Check if a value exists
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name: Exists
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parent: Query with Flux
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weight: 220
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aliases:
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- /v2.0/query-data/guides/exists/
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- /v2.0/query-data/guides/exists/
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related:
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- /v2.0/query-data/flux/query-fields/
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- /v2.0/reference/flux/stdlib/built-in/transformations/filter/
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list_code_example: |
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##### Filter null values
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```js
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data
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|> filter(fn: (r) => exists r._value)
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```
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---
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Use the Flux `exists` operator to check if an object contains a key or if that
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@ -38,7 +48,7 @@ Use `exists` with row functions (
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[`reduce()`](/v2.0/reference/flux/stdlib/built-in/transformations/aggregates/reduce/))
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to check if a row includes a column or if the value for that column is `null`.
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#### Filter out null values
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#### Filter null values
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```js
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from(bucket: "example-bucket")
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|> range(start: -5m)
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|
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@ -0,0 +1,118 @@
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---
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title: Fill null values in data
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seotitle: Fill null values in data
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list_title: Fill
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description: >
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Use the [`fill()` function](/v2.0/reference/flux/stdlib/built-in/transformations/fill/)
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to replace _null_ values.
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weight: 210
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menu:
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v2_0:
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parent: Query with Flux
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name: Fill
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v2.0/tags: [query, fill]
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related:
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- /v2.0/reference/flux/stdlib/built-in/transformations/fill/
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list_code_example: |
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```js
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data
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|> fill(usePrevious: true)
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```
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---
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Use the [`fill()` function](/v2.0/reference/flux/stdlib/built-in/transformations/fill/)
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to replace _null_ values with:
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- [the previous non-null value](#fill-with-the-previous-value)
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- [a specified value](#fill-with-a-specified-value)
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<!-- -->
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```js
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data
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|> fill(usePrevious: true)
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// OR
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data
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|> fill(value: 0.0)
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```
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{{% note %}}
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#### Fill empty windows of time
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The `fill()` function **does not** fill empty windows of time.
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It only replaces _null_ values in existing data.
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Filling empty windows of time requires time interpolation
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_(see [influxdata/flux#2428](https://github.com/influxdata/flux/issues/2428))_.
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{{% /note %}}
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## Fill with the previous value
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To fill _null_ values with the previous **non-null** value, set the `usePrevious` parameter to `true`.
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{{% note %}}
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Values remain _null_ if there is no previous non-null value in the table.
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{{% /note %}}
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```js
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data
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|> fill(usePrevious: true)
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```
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{{< flex >}}
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{{% flex-content %}}
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**Given the following input:**
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| _time | _value |
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|:----- | ------:|
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| 0001 | null |
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| 0002 | 0.8 |
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| 0003 | null |
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| 0004 | null |
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| 0005 | 1.4 |
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{{% /flex-content %}}
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{{% flex-content %}}
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**`fill(usePrevious: true)` returns:**
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| _time | _value |
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|:----- | ------:|
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| 0001 | null |
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| 0002 | 0.8 |
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| 0003 | 0.8 |
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| 0004 | 0.8 |
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| 0005 | 1.4 |
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{{% /flex-content %}}
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{{< /flex >}}
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## Fill with a specified value
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To fill _null_ values with a specified value, use the `value` parameter to specify the fill value.
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_The fill value must match the [data type](/v2.0/reference/flux/language/types/#basic-types)
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of the [column](/v2.0/reference/flux/stdlib/built-in/transformations/fill/#column)._
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```js
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data
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|> fill(value: 0.0)
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```
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{{< flex >}}
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{{% flex-content %}}
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**Given the following input:**
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| _time | _value |
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|:----- | ------:|
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| 0001 | null |
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| 0002 | 0.8 |
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| 0003 | null |
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| 0004 | null |
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| 0005 | 1.4 |
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{{% /flex-content %}}
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{{% flex-content %}}
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**`fill(value: 0.0)` returns:**
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| _time | _value |
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|:----- | ------:|
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| 0001 | 0.0 |
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| 0002 | 0.8 |
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| 0003 | 0.0 |
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| 0004 | 0.0 |
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| 0005 | 1.4 |
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{{% /flex-content %}}
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{{< /flex >}}
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|
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@ -0,0 +1,162 @@
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---
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||||
title: Query first and last values
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seotitle: Query first and last values in Flux
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||||
list_title: First and last
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description: >
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Use the [`first()`](/v2.0/reference/flux/stdlib/built-in/transformations/selectors/first/) or
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[`last()`](/v2.0/reference/flux/stdlib/built-in/transformations/selectors/last/) functions
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to return the first or last point in an input table.
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weight: 210
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||||
menu:
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||||
v2_0:
|
||||
parent: Query with Flux
|
||||
name: First & last
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||||
v2.0/tags: [query]
|
||||
related:
|
||||
- /v2.0/reference/flux/stdlib/built-in/transformations/selectors/first/
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||||
- /v2.0/reference/flux/stdlib/built-in/transformations/selectors/last/
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list_code_example: |
|
||||
```js
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data
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|> first()
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// OR
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||||
data
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||||
|> last()
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```
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---
|
||||
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||||
Use the [`first()`](/v2.0/reference/flux/stdlib/built-in/transformations/selectors/first/) or
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[`last()`](/v2.0/reference/flux/stdlib/built-in/transformations/selectors/last/) functions
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||||
to return the first or last record in an input table.
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|
||||
```js
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data
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|> first()
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// OR
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data
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|> last()
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```
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{{% note %}}
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By default, InfluxDB returns results sorted by time, however you can use the
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[`sort()` function](/v2.0/reference/flux/stdlib/built-in/transformations/sort/)
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to change how results are sorted.
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||||
`first()` and `last()` respect the sort order of input data and return records
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based on the order they are received in.
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{{% /note %}}
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### first
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`first()` returns the first non-null record in an input table.
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{{< flex >}}
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{{% flex-content %}}
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**Given the following input:**
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|
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| _time | _value |
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||||
| ----- |:------:|
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||||
| 0001 | 1.0 |
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| 0002 | 1.0 |
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| 0003 | 2.0 |
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| 0004 | 3.0 |
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{{% /flex-content %}}
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||||
{{% flex-content %}}
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||||
**The following function returns:**
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```js
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|> first()
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```
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||||
| _time | _value |
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||||
| ----- |:------:|
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||||
| 0001 | 1.0 |
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{{% /flex-content %}}
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{{< /flex >}}
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### last
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`last()` returns the last non-null record in an input table.
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{{< flex >}}
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{{% flex-content %}}
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||||
**Given the following input:**
|
||||
|
||||
| _time | _value |
|
||||
| ----- |:------:|
|
||||
| 0001 | 1.0 |
|
||||
| 0002 | 1.0 |
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||||
| 0003 | 2.0 |
|
||||
| 0004 | 3.0 |
|
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{{% /flex-content %}}
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||||
{{% flex-content %}}
|
||||
**The following function returns:**
|
||||
|
||||
```js
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|> last()
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```
|
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|
||||
| _time | _value |
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||||
| ----- |:------:|
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||||
| 0004 | 3.0 |
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{{% /flex-content %}}
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||||
{{< /flex >}}
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||||
|
||||
## Use first() or last() with aggregateWindow()
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||||
Use `first()` and `last()` with [`aggregateWindow()`](/v2.0/reference/flux/stdlib/built-in/transformations/aggregates/aggregatewindow/)
|
||||
to select the first or last records in time-based groups.
|
||||
`aggregateWindow()` segments data into windows of time, aggregates data in each window into a single
|
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point using aggregate or selector functions, and then removes the time-based segmentation.
|
||||
|
||||
|
||||
{{< flex >}}
|
||||
{{% flex-content %}}
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||||
**Given the following input:**
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||||
|
||||
| _time | _value |
|
||||
|:----- | ------:|
|
||||
| 2020-01-01T00:00:00Z | 10 |
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||||
| 2020-01-01T00:00:15Z | 12 |
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||||
| 2020-01-01T00:00:45Z | 9 |
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||||
| 2020-01-01T00:01:05Z | 9 |
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||||
| 2020-01-01T00:01:10Z | 15 |
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||||
| 2020-01-01T00:02:30Z | 11 |
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||||
{{% /flex-content %}}
|
||||
|
||||
{{% flex-content %}}
|
||||
**The following function returns:**
|
||||
{{< code-tabs-wrapper >}}
|
||||
{{% code-tabs %}}
|
||||
[first](#)
|
||||
[last](#)
|
||||
{{% /code-tabs %}}
|
||||
{{% code-tab-content %}}
|
||||
```js
|
||||
|> aggregateWindow(
|
||||
every: 1h,
|
||||
fn: first
|
||||
)
|
||||
```
|
||||
| _time | _value |
|
||||
|:----- | ------:|
|
||||
| 2020-01-01T00:00:59Z | 10 |
|
||||
| 2020-01-01T00:01:59Z | 9 |
|
||||
| 2020-01-01T00:02:59Z | 11 |
|
||||
{{% /code-tab-content %}}
|
||||
{{% code-tab-content %}}
|
||||
```js
|
||||
|> aggregateWindow(
|
||||
every: 1h,
|
||||
fn: last
|
||||
)
|
||||
```
|
||||
|
||||
| _time | _value |
|
||||
|:----- | ------:|
|
||||
| 2020-01-01T00:00:59Z | 9 |
|
||||
| 2020-01-01T00:01:59Z | 15 |
|
||||
| 2020-01-01T00:02:59Z | 11 |
|
||||
{{% /code-tab-content %}}
|
||||
{{< /code-tabs-wrapper >}}
|
||||
{{%/flex-content %}}
|
||||
{{< /flex >}}
|
||||
|
|
@ -1,5 +1,6 @@
|
|||
---
|
||||
title: Work with geo-temporal data
|
||||
list_title: Geo-temporal data
|
||||
description: >
|
||||
Use the Flux Geo package to filter geo-temporal data and group by geographic location or track.
|
||||
menu:
|
||||
|
|
@ -7,6 +8,14 @@ menu:
|
|||
name: Geo-temporal data
|
||||
parent: Query with Flux
|
||||
weight: 220
|
||||
list_code_example: |
|
||||
```js
|
||||
import "experimental/geo"
|
||||
|
||||
sampleGeoData
|
||||
|> geo.filterRows(region: {lat: 30.04, lon: 31.23, radius: 200.0})
|
||||
|> geo.groupByArea(newColumn: "geoArea", level: 5)
|
||||
```
|
||||
---
|
||||
|
||||
Use the [Flux Geo package](/v2.0/reference/flux/stdlib/experimental/geo) to
|
||||
|
|
|
|||
|
|
@ -7,6 +7,9 @@ menu:
|
|||
name: Filter by region
|
||||
parent: Geo-temporal data
|
||||
weight: 302
|
||||
related:
|
||||
- /v2.0/reference/flux/stdlib/experimental/geo/
|
||||
- /v2.0/reference/flux/stdlib/experimental/geo/filterrows/
|
||||
list_code_example: |
|
||||
```js
|
||||
import "experimental/geo"
|
||||
|
|
|
|||
|
|
@ -7,6 +7,10 @@ menu:
|
|||
v2_0:
|
||||
parent: Geo-temporal data
|
||||
weight: 302
|
||||
related:
|
||||
- /v2.0/reference/flux/stdlib/experimental/geo/
|
||||
- /v2.0/reference/flux/stdlib/experimental/geo/groupbyarea/
|
||||
- /v2.0/reference/flux/stdlib/experimental/geo/astracks/
|
||||
list_code_example: |
|
||||
```js
|
||||
import "experimental/geo"
|
||||
|
|
|
|||
|
|
@ -8,6 +8,10 @@ menu:
|
|||
name: Shape geo-temporal data
|
||||
parent: Geo-temporal data
|
||||
weight: 301
|
||||
related:
|
||||
- /v2.0/reference/flux/stdlib/experimental/geo/
|
||||
- /v2.0/reference/flux/stdlib/experimental/geo/shapedata/
|
||||
- /v2.0/reference/flux/stdlib/experimental/geo/s2cellidtoken/
|
||||
list_code_example: |
|
||||
```js
|
||||
import "experimental/geo"
|
||||
|
|
@ -32,24 +36,23 @@ Functions in the Geo package require the following data schema:
|
|||
- a **`lat` field** field containing the **latitude in decimal degrees** (WGS 84)
|
||||
- a **`lon` field** field containing the **longitude in decimal degrees** (WGS 84)
|
||||
|
||||
<!-- -->
|
||||
- [Rename latitude and longitude fields](#rename-latitude-and-longitude-fields)
|
||||
- [Generate S2 cell ID tokens](#generate-s2-cell-id-tokens)
|
||||
|
||||
## Rename latitude and longitude fields
|
||||
Use [`map()`](/v2.0/reference/flux/stdlib/built-in/transformations/map/) to rename
|
||||
existing latitude and longitude fields using other names.
|
||||
## Shape geo-temporal data
|
||||
If your data already contains latitude and longitude fields, use the
|
||||
[`geo.shapeData()`function](/v2.0/reference/flux/stdlib/experimental/geo/shapedata/)
|
||||
to rename the fields to match the requirements of the Geo package, pivot the data
|
||||
into row-wise sets, and generate S2 cell ID tokens for each point.
|
||||
|
||||
```js
|
||||
import "experimental/geo"
|
||||
|
||||
from(bucket: "example-bucket")
|
||||
|> range(start: -1h)
|
||||
|> filter(fn: (r) => r._measurement == "example-measurement")
|
||||
|> map(fn: (r) => ({ r with
|
||||
_field:
|
||||
if r._field == "existingLatitudeField" then "lat"
|
||||
else if r._field == "existingLongitudeField" then "lon"
|
||||
else r._field
|
||||
}))
|
||||
|> geo.shapeData(
|
||||
latField: "latitude",
|
||||
lonField: "longitude",
|
||||
level: 10
|
||||
)
|
||||
```
|
||||
|
||||
## Generate S2 cell ID tokens
|
||||
|
|
@ -119,3 +122,8 @@ from(bucket: "example-bucket")
|
|||
s2_cell_id: geo.s2CellIDToken(point: {lon: r.lon, lat: r.lat}, level: 10)
|
||||
}))
|
||||
```
|
||||
|
||||
{{% note %}}
|
||||
The [`geo.shapeData()`function](/v2.0/reference/flux/stdlib/experimental/geo/shapedata/)
|
||||
generates S2 cell ID tokens as well.
|
||||
{{% /note %}}
|
||||
|
|
|
|||
|
|
@ -1,17 +1,25 @@
|
|||
---
|
||||
title: Group data in InfluxDB with Flux
|
||||
list_title: Group data
|
||||
list_title: Group
|
||||
description: >
|
||||
This guide walks through grouping data with Flux by providing examples and
|
||||
illustrating how data is shaped throughout the process.
|
||||
Use the [`group()` function](/v2.0/reference/flux/stdlib/built-in/transformations/group)
|
||||
to group data with common values in specific columns.
|
||||
v2.0/tags: [group]
|
||||
menu:
|
||||
v2_0:
|
||||
name: Group data
|
||||
name: Group
|
||||
parent: Query with Flux
|
||||
weight: 202
|
||||
aliases:
|
||||
- /v2.0/query-data/guides/group-data/
|
||||
- /v2.0/query-data/guides/group-data/
|
||||
related:
|
||||
- /v2.0/reference/flux/stdlib/built-in/transformations/group
|
||||
- /v2.0/reference/flux/stdlib/experimental/group
|
||||
list_code_example: |
|
||||
```js
|
||||
data
|
||||
|> group(columns: ["cpu", "host"], mode: "by")
|
||||
```
|
||||
---
|
||||
|
||||
With Flux, you can group data by any column in your queried data set.
|
||||
|
|
|
|||
|
|
@ -1,15 +1,30 @@
|
|||
---
|
||||
title: Create histograms with Flux
|
||||
list_title: Create histograms
|
||||
description: This guide walks through using the `histogram()` function to create cumulative histograms with Flux.
|
||||
list_title: Histograms
|
||||
description: >
|
||||
Use the [`histogram()` function](/v2.0/reference/flux/stdlib/built-in/transformations/histogram/)
|
||||
to create cumulative histograms with Flux.
|
||||
v2.0/tags: [histogram]
|
||||
menu:
|
||||
v2_0:
|
||||
name: Create histograms
|
||||
name: Histograms
|
||||
parent: Query with Flux
|
||||
weight: 210
|
||||
aliases:
|
||||
- /v2.0/query-data/guides/histograms/
|
||||
- /v2.0/query-data/guides/histograms/
|
||||
related:
|
||||
- /v2.0/reference/flux/stdlib/built-in/transformations/histogram
|
||||
list_code_example: |
|
||||
```js
|
||||
data
|
||||
|> histogram(
|
||||
column: "_value",
|
||||
upperBoundColumn: "le",
|
||||
countColumn: "_value",
|
||||
bins: [50.0, 75.0, 90.0],
|
||||
normalize: false)
|
||||
)
|
||||
```
|
||||
---
|
||||
|
||||
Histograms provide valuable insight into the distribution of your data.
|
||||
|
|
|
|||
|
|
@ -0,0 +1,62 @@
|
|||
---
|
||||
title: Calculate the increase
|
||||
seotitle: Calculate the increase in Flux
|
||||
list_title: Increase
|
||||
description: >
|
||||
Use the [`increase()` function](/v2.0/reference/flux/stdlib/built-in/transformations/aggregates/increase/)
|
||||
to track increases across multiple columns in a table.
|
||||
This function is especially useful when tracking changes in counter values that
|
||||
wrap over time or periodically reset.
|
||||
weight: 210
|
||||
menu:
|
||||
v2_0:
|
||||
parent: Query with Flux
|
||||
name: Increase
|
||||
v2.0/tags: [query, increase, counters]
|
||||
related:
|
||||
- /v2.0/reference/flux/stdlib/built-in/transformations/aggregates/increase/
|
||||
list_code_example: |
|
||||
```js
|
||||
data
|
||||
|> increase()
|
||||
```
|
||||
---
|
||||
|
||||
Use the [`increase()` function](/v2.0/reference/flux/stdlib/built-in/transformations/aggregates/increase/)
|
||||
to track increases across multiple columns in a table.
|
||||
This function is especially useful when tracking changes in counter values that
|
||||
wrap over time or periodically reset.
|
||||
|
||||
```js
|
||||
data
|
||||
|> increase()
|
||||
```
|
||||
|
||||
`increase()` returns a cumulative sum of **non-negative** differences between rows in a table.
|
||||
For example:
|
||||
|
||||
{{< flex >}}
|
||||
{{% flex-content %}}
|
||||
**Given the following input:**
|
||||
|
||||
| _time | _value |
|
||||
|:----- | ------:|
|
||||
| 0001 | 1 |
|
||||
| 0002 | 2 |
|
||||
| 0003 | 8 |
|
||||
| 0004 | 10 |
|
||||
| 0005 | 0 |
|
||||
| 0006 | 4 |
|
||||
{{% /flex-content %}}
|
||||
{{% flex-content %}}
|
||||
**`increase()` returns:**
|
||||
|
||||
| _time | _value |
|
||||
|:----- | ------:|
|
||||
| 0002 | 1 |
|
||||
| 0003 | 7 |
|
||||
| 0004 | 9 |
|
||||
| 0005 | 9 |
|
||||
| 0006 | 13 |
|
||||
{{% /flex-content %}}
|
||||
{{< /flex >}}
|
||||
|
|
@ -1,16 +1,25 @@
|
|||
---
|
||||
title: Join data with Flux
|
||||
seotitle: Join data in InfluxDB with Flux
|
||||
list_title: Join data
|
||||
list_title: Join
|
||||
description: This guide walks through joining data with Flux and outlines how it shapes your data in the process.
|
||||
v2.0/tags: [join, flux]
|
||||
menu:
|
||||
v2_0:
|
||||
name: Join data
|
||||
name: Join
|
||||
parent: Query with Flux
|
||||
weight: 220
|
||||
weight: 210
|
||||
aliases:
|
||||
- /v2.0/query-data/guides/join/
|
||||
- /v2.0/query-data/guides/join/
|
||||
related:
|
||||
- /v2.0/reference/flux/stdlib/built-in/transformations/join
|
||||
list_code_example: |
|
||||
```js
|
||||
join(
|
||||
tables: {t1: stream1, t2: stream2},
|
||||
on: ["_time"]
|
||||
)
|
||||
```
|
||||
---
|
||||
|
||||
The [`join()` function](/v2.0/reference/flux/stdlib/built-in/transformations/join) merges two or more
|
||||
|
|
|
|||
|
|
@ -10,6 +10,14 @@ menu:
|
|||
weight: 220
|
||||
aliases:
|
||||
- /v2.0/query-data/guides/manipulate-timestamps/
|
||||
related:
|
||||
- /v2.0/reference/flux/stdlib/built-in/misc/now/
|
||||
- /v2.0/reference/flux/stdlib/system/time/
|
||||
- /v2.0/reference/flux/stdlib/built-in/transformations/type-conversions/time/
|
||||
- /v2.0/reference/flux/stdlib/built-in/transformations/type-conversions/uint/
|
||||
- /v2.0/reference/flux/stdlib/built-in/transformations/type-conversions/int/
|
||||
- /v2.0/reference/flux/stdlib/experimental/addduration/
|
||||
- /v2.0/reference/flux/stdlib/experimental/subduration/
|
||||
---
|
||||
|
||||
Every point stored in InfluxDB has an associated timestamp.
|
||||
|
|
|
|||
|
|
@ -2,7 +2,9 @@
|
|||
title: Transform data with mathematic operations
|
||||
seotitle: Transform data with mathematic operations in Flux
|
||||
list_title: Transform data with math
|
||||
description: This guide describes how to use Flux to transform data with mathematic operations.
|
||||
description: >
|
||||
Use the [`map()` function](/v2.0/reference/flux/stdlib/built-in/transformations/map)
|
||||
to remap column values and apply mathematic operations.
|
||||
v2.0/tags: [math, flux]
|
||||
menu:
|
||||
v2_0:
|
||||
|
|
@ -10,7 +12,17 @@ menu:
|
|||
parent: Query with Flux
|
||||
weight: 205
|
||||
aliases:
|
||||
- /v2.0/query-data/guides/mathematic-operations/
|
||||
- /v2.0/query-data/guides/mathematic-operations/
|
||||
related:
|
||||
- /v2.0/reference/flux/stdlib/built-in/transformations/map
|
||||
- /v2.0/reference/flux/stdlib/built-in/transformations/aggregates/reduce/
|
||||
- /v2.0/reference/flux/language/operators/
|
||||
- /v2.0/reference/flux/stdlib/built-in/transformations/type-conversions/
|
||||
list_code_example: |
|
||||
```js
|
||||
data
|
||||
|> map(fn: (r) => ({ r with _value: r._value * r._value }))
|
||||
```
|
||||
---
|
||||
|
||||
[Flux](/v2.0/reference/flux), InfluxData's data scripting and query language,
|
||||
|
|
|
|||
|
|
@ -3,16 +3,23 @@ title: Find median values
|
|||
seotitle: Find median values in Flux
|
||||
list_title: Median
|
||||
description: >
|
||||
Use the `median()` function to return a value representing the `0.5` quantile
|
||||
(50th percentile) or median of input data.
|
||||
Use the [`median()` function](/v2.0/reference/flux/stdlib/built-in/transformations/aggregates/median/)
|
||||
to return a value representing the `0.5` quantile (50th percentile) or median of input data.
|
||||
weight: 210
|
||||
menu:
|
||||
v2_0:
|
||||
parent: Query with Flux
|
||||
name: Find the median
|
||||
name: Median
|
||||
v2.0/tags: [query, median]
|
||||
related:
|
||||
- /v2.0/query-data/flux/percentile-quantile/
|
||||
- /v2.0/reference/flux/stdlib/built-in/transformations/aggregates/median/
|
||||
- /v2.0/reference/flux/stdlib/built-in/transformations/aggregates/quantile/
|
||||
list_code_example: |
|
||||
```js
|
||||
data
|
||||
|> median()
|
||||
```
|
||||
---
|
||||
|
||||
Use the [`median()` function](/v2.0/reference/flux/stdlib/built-in/transformations/aggregates/median/)
|
||||
|
|
|
|||
|
|
@ -9,7 +9,10 @@ menu:
|
|||
parent: Query with Flux
|
||||
weight: 220
|
||||
aliases:
|
||||
- /v2.0/query-data/guides/monitor-states/
|
||||
- /v2.0/query-data/guides/monitor-states/
|
||||
related:
|
||||
- /v2.0/reference/flux/stdlib/built-in/transformations/stateduration/
|
||||
- /v2.0/reference/flux/stdlib/built-in/transformations/statecount/
|
||||
---
|
||||
|
||||
Flux helps you monitor states in your metrics and events:
|
||||
|
|
@ -33,11 +36,11 @@ If you're just getting started with Flux queries, check out the following:
|
|||
- **Unit:** the unit of time (`1s` (by default), `1m`, `1h`) used to increment the state duration.
|
||||
|
||||
```js
|
||||
|> stateDuration(
|
||||
fn: (r) =>
|
||||
r._column_to_search == "value_to_search_for",
|
||||
column: "state_duration",
|
||||
unit: 1s)
|
||||
|> stateDuration(
|
||||
fn: (r) => r._column_to_search == "value_to_search_for",
|
||||
column: "state_duration",
|
||||
unit: 1s
|
||||
)
|
||||
```
|
||||
|
||||
2. Use `stateDuration()` to search each point for the specified value:
|
||||
|
|
@ -65,7 +68,7 @@ In this example, `door_closed` is the **State duration** column. If you write da
|
|||
|
||||
Results for the example query above may look like this (for simplicity, we've omitted the measurement, tag, and field columns):
|
||||
|
||||
```bash
|
||||
```sh
|
||||
_time _value door_closed
|
||||
2019-10-26T17:39:16Z closed 0
|
||||
2019-10-26T17:40:16Z closed 60
|
||||
|
|
@ -77,19 +80,20 @@ _time _value door_closed
|
|||
|
||||
## Count the number of consecutive states
|
||||
|
||||
1. Use the `stateCount()` function and include the following information:
|
||||
1. Use the [`stateCount()` function](/v2.0/reference/flux/stdlib/built-in/transformations/statecount/)
|
||||
and include the following information:
|
||||
|
||||
- **Column to search:** any tag key, tag value, field key, field value, or measurement.
|
||||
- **Value:** to search for in the specified column.
|
||||
- **State count column:** a new column to store the state count─the number of consecutive records in which the specified value exists.
|
||||
- **State count column:** a new column to store the state count─the number of
|
||||
consecutive records in which the specified value exists.
|
||||
|
||||
```js
|
||||
|> stateCount
|
||||
(fn: (r) =>
|
||||
r._column_to_search == "value_to_search_for",
|
||||
column: "state_count"`
|
||||
)
|
||||
```
|
||||
|> stateCount(
|
||||
fn: (r) => r._column_to_search == "value_to_search_for",
|
||||
column: "state_count"
|
||||
)
|
||||
```
|
||||
|
||||
2. Use `stateCount()` to search each point for the specified value:
|
||||
|
||||
|
|
@ -101,12 +105,12 @@ _time _value door_closed
|
|||
The following query searches the `doors` bucket over the past 5 minutes and calculates how many points have `closed` as their `_value`.
|
||||
|
||||
```js
|
||||
from(bucket: "doors")
|
||||
from(bucket: "doors")
|
||||
|> range(start: -5m)
|
||||
|> stateDuration(
|
||||
fn: (r) =>
|
||||
r._value == "closed",
|
||||
column: "door_closed")
|
||||
fn: (r) => r._value == "closed",
|
||||
column: "door_closed"
|
||||
)
|
||||
```
|
||||
|
||||
This example stores the **state count** in the `door_closed` column. If you write data to the `doors` bucket every minute, the state count increases by `1` for each consecutive point where `_value` is `closed`. If `_value` is not `closed`, the state count is reset to `-1`.
|
||||
|
|
@ -129,7 +133,7 @@ _time _value door_closed
|
|||
|
||||
The following query checks the machine state every minute (idle, assigned, or busy). InfluxDB searches the `servers` bucket over the past hour and counts records with a machine state of `idle`, `assigned` or `busy`.
|
||||
|
||||
```
|
||||
```js
|
||||
from(bucket: "servers")
|
||||
|> range(start: -1h)
|
||||
|> filter(fn: (r) =>
|
||||
|
|
|
|||
|
|
@ -0,0 +1,128 @@
|
|||
---
|
||||
title: Calculate the moving average
|
||||
seotitle: Calculate the moving average in Flux
|
||||
list_title: Moving Average
|
||||
description: >
|
||||
Use the [`movingAverage()`](/v2.0/reference/flux/stdlib/built-in/transformations/aggregates/movingaverage/)
|
||||
or [`timedMovingAverage()`](/v2.0/reference/flux/stdlib/built-in/transformations/aggregates/timedmovingaverage/)
|
||||
functions to return the moving average of data.
|
||||
weight: 210
|
||||
menu:
|
||||
v2_0:
|
||||
parent: Query with Flux
|
||||
name: Moving Average
|
||||
v2.0/tags: [query, moving average]
|
||||
related:
|
||||
- /v2.0/reference/flux/stdlib/built-in/transformations/aggregates/movingaverage/
|
||||
- /v2.0/reference/flux/stdlib/built-in/transformations/aggregates/timedmovingaverage/
|
||||
list_code_example: |
|
||||
```js
|
||||
data
|
||||
|> movingAverage(n: 5)
|
||||
|
||||
// OR
|
||||
|
||||
data
|
||||
|> timedMovingAverage(every: 5m, period: 10m)
|
||||
```
|
||||
---
|
||||
|
||||
Use the [`movingAverage()`](/v2.0/reference/flux/stdlib/built-in/transformations/aggregates/movingaverage/)
|
||||
or [`timedMovingAverage()`](/v2.0/reference/flux/stdlib/built-in/transformations/aggregates/timedmovingaverage/)
|
||||
functions to return the moving average of data.
|
||||
|
||||
```js
|
||||
data
|
||||
|> movingAverage(n: 5)
|
||||
|
||||
// OR
|
||||
|
||||
data
|
||||
|> timedMovingAverage(every: 5m, period: 10m)
|
||||
```
|
||||
|
||||
### movingAverage()
|
||||
For each row in a table, `movingAverage()` returns the average of the current value and
|
||||
**previous** values where `n` is the total number of values used to calculate the average.
|
||||
|
||||
If `n = 3`:
|
||||
|
||||
| Row # | Calculation |
|
||||
|:-----:|:----------- |
|
||||
| 1 | _Insufficient number of rows_ |
|
||||
| 2 | _Insufficient number of rows_ |
|
||||
| 3 | (Row1 + Row2 + Row3) / 3 |
|
||||
| 4 | (Row2 + Row3 + Row4) / 3 |
|
||||
| 5 | (Row3 + Row4 + Row5) / 3 |
|
||||
|
||||
{{< flex >}}
|
||||
{{% flex-content %}}
|
||||
**Given the following input:**
|
||||
|
||||
| _time | _value |
|
||||
|:----- | ------:|
|
||||
| 2020-01-01T00:01:00Z | 1.0 |
|
||||
| 2020-01-01T00:02:00Z | 1.2 |
|
||||
| 2020-01-01T00:03:00Z | 1.8 |
|
||||
| 2020-01-01T00:04:00Z | 0.9 |
|
||||
| 2020-01-01T00:05:00Z | 1.4 |
|
||||
| 2020-01-01T00:06:00Z | 2.0 |
|
||||
{{% /flex-content %}}
|
||||
{{% flex-content %}}
|
||||
**The following would return:**
|
||||
|
||||
```js
|
||||
|> movingAverage(n: 3)
|
||||
```
|
||||
|
||||
| _time | _value |
|
||||
|:----- | ------:|
|
||||
| 2020-01-01T00:03:00Z | 1.33 |
|
||||
| 2020-01-01T00:04:00Z | 1.30 |
|
||||
| 2020-01-01T00:05:00Z | 1.36 |
|
||||
| 2020-01-01T00:06:00Z | 1.43 |
|
||||
{{% /flex-content %}}
|
||||
{{< /flex >}}
|
||||
|
||||
### timedMovingAverage()
|
||||
For each row in a table, `timedMovingAverage()` returns the average of the
|
||||
current value and all row values in the **previous** `period` (duration).
|
||||
It returns moving averages at a frequency defined by the `every` parameter.
|
||||
|
||||
Each color in the diagram below represents a period of time used to calculate an
|
||||
average and the time a point representing the average is returned.
|
||||
If `every = 30m` and `period = 1h`:
|
||||
|
||||
{{< svg "/static/svgs/timed-moving-avg.svg" >}}
|
||||
|
||||
{{< flex >}}
|
||||
{{% flex-content %}}
|
||||
**Given the following input:**
|
||||
|
||||
| _time | _value |
|
||||
|:----- | ------:|
|
||||
| 2020-01-01T00:01:00Z | 1.0 |
|
||||
| 2020-01-01T00:02:00Z | 1.2 |
|
||||
| 2020-01-01T00:03:00Z | 1.8 |
|
||||
| 2020-01-01T00:04:00Z | 0.9 |
|
||||
| 2020-01-01T00:05:00Z | 1.4 |
|
||||
| 2020-01-01T00:06:00Z | 2.0 |
|
||||
{{% /flex-content %}}
|
||||
{{% flex-content %}}
|
||||
**The following would return:**
|
||||
|
||||
```js
|
||||
|> timedMovingAverage(
|
||||
every: 2m,
|
||||
period: 4m
|
||||
)
|
||||
```
|
||||
|
||||
| _time | _value |
|
||||
|:----- | ------:|
|
||||
| 2020-01-01T00:02:00Z | 1.000 |
|
||||
| 2020-01-01T00:04:00Z | 1.333 |
|
||||
| 2020-01-01T00:06:00Z | 1.325 |
|
||||
| 2020-01-01T00:06:00Z | 1.150 |
|
||||
{{% /flex-content %}}
|
||||
{{< /flex >}}
|
||||
|
|
@ -9,10 +9,16 @@ weight: 210
|
|||
menu:
|
||||
v2_0:
|
||||
parent: Query with Flux
|
||||
name: Query percentiles & quantiles
|
||||
name: Percentile & quantile
|
||||
v2.0/tags: [query, percentile, quantile]
|
||||
related:
|
||||
- /v2.0/query-data/flux/query-median/
|
||||
- /v2.0/reference/flux/stdlib/built-in/transformations/aggregates/quantile/
|
||||
list_code_example: |
|
||||
```js
|
||||
data
|
||||
|> quantile(q: 0.99)
|
||||
```
|
||||
---
|
||||
|
||||
Use the [`quantile()` function](/v2.0/reference/flux/stdlib/built-in/transformations/aggregates/quantile/)
|
||||
|
|
|
|||
|
|
@ -2,7 +2,7 @@
|
|||
title: Query fields and tags
|
||||
seotitle: Query fields and tags in InfluxDB using Flux
|
||||
description: >
|
||||
Use the `filter()` function to query data based on fields, tags, or any other column value.
|
||||
Use the [`filter()` function](/v2.0/reference/flux/stdlib/built-in/transformations/filter/) to query data based on fields, tags, or any other column value.
|
||||
`filter()` performs operations similar to the `SELECT` statement and the `WHERE`
|
||||
clause in InfluxQL and other SQL-like query languages.
|
||||
weight: 201
|
||||
|
|
@ -10,6 +10,20 @@ menu:
|
|||
v2_0:
|
||||
parent: Query with Flux
|
||||
v2.0/tags: [query, select, where]
|
||||
related:
|
||||
- /v2.0/reference/flux/stdlib/built-in/transformations/filter/
|
||||
- /v2.0/query-data/flux/conditional-logic/
|
||||
- /v2.0/query-data/flux/regular-expressions/
|
||||
list_code_example: |
|
||||
```js
|
||||
from(bucket: "example-bucket")
|
||||
|> range(start: -1h)
|
||||
|> filter(fn: (r) =>
|
||||
r._measurement == "example-measurement" and
|
||||
r._field == "example-field" and
|
||||
r.tag == "example-tag"
|
||||
)
|
||||
```
|
||||
---
|
||||
|
||||
Use the [`filter()` function](/v2.0/reference/flux/stdlib/built-in/transformations/filter/)
|
||||
|
|
|
|||
|
|
@ -0,0 +1,189 @@
|
|||
---
|
||||
title: Calculate the rate of change
|
||||
seotitle: Calculate the rate of change in Flux
|
||||
list_title: Rate
|
||||
description: >
|
||||
Use the [`derivative()` function](/v2.0/reference/flux/stdlib/built-in/transformations/aggregates/derivative/)
|
||||
to calculate the rate of change between subsequent values or the
|
||||
[`aggregate.rate()` function](/v2.0/reference/flux/stdlib/experimental/aggregate/rate/)
|
||||
to calculate the average rate of change per window of time.
|
||||
If time between points varies, these functions normalize points to a common time interval
|
||||
making values easily comparable.
|
||||
weight: 210
|
||||
menu:
|
||||
v2_0:
|
||||
parent: Query with Flux
|
||||
name: Rate
|
||||
v2.0/tags: [query, rate]
|
||||
related:
|
||||
- /v2.0/reference/flux/stdlib/built-in/transformations/aggregates/derivative/
|
||||
- /v2.0/reference/flux/stdlib/experimental/aggregate/rate/
|
||||
list_code_example: |
|
||||
```js
|
||||
data
|
||||
|> derivative(unit: 1s, nonNegative: true)
|
||||
```
|
||||
```js
|
||||
import "experimental/aggregate"
|
||||
|
||||
data
|
||||
|> aggregate.rate(every: 1m, unit: 1s)
|
||||
```
|
||||
---
|
||||
|
||||
|
||||
Use the [`derivative()` function](/v2.0/reference/flux/stdlib/built-in/transformations/aggregates/derivative/)
|
||||
to calculate the rate of change between subsequent values or the
|
||||
[`aggregate.rate()` function](/v2.0/reference/flux/stdlib/experimental/aggregate/rate/)
|
||||
to calculate the average rate of change per window of time.
|
||||
If time between points varies, these functions normalize points to a common time interval
|
||||
making values easily comparable.
|
||||
|
||||
- [Rate of change between subsequent values](#rate-of-change-between-subsequent-values)
|
||||
- [Average rate of change per window of time](#average-rate-of-change-per-window-of-time)
|
||||
|
||||
## Rate of change between subsequent values
|
||||
Use the [`derivative()` function](/v2.0/reference/flux/stdlib/built-in/transformations/aggregates/derivative/)
|
||||
to calculate the rate of change per unit of time between subsequent _non-null_ values.
|
||||
|
||||
```js
|
||||
data
|
||||
|> derivative(unit: 1s)
|
||||
```
|
||||
|
||||
By default, `derivative()` returns only positive derivative values and replaces negative values with _null_.
|
||||
Cacluated values are returned as [floats](/v2.0/reference/flux/language/types/#numeric-types).
|
||||
|
||||
|
||||
{{< flex >}}
|
||||
{{% flex-content %}}
|
||||
**Given the following input:**
|
||||
|
||||
| _time | _value |
|
||||
|:----- | ------:|
|
||||
| 2020-01-01T00:00:00Z | 250 |
|
||||
| 2020-01-01T00:04:00Z | 160 |
|
||||
| 2020-01-01T00:12:00Z | 150 |
|
||||
| 2020-01-01T00:19:00Z | 220 |
|
||||
| 2020-01-01T00:32:00Z | 200 |
|
||||
| 2020-01-01T00:51:00Z | 290 |
|
||||
| 2020-01-01T01:00:00Z | 340 |
|
||||
{{% /flex-content %}}
|
||||
{{% flex-content %}}
|
||||
**`derivative(unit: 1m)` returns:**
|
||||
|
||||
| _time | _value |
|
||||
|:----- | ------:|
|
||||
| 2020-01-01T00:04:00Z | |
|
||||
| 2020-01-01T00:12:00Z | |
|
||||
| 2020-01-01T00:19:00Z | 10.0 |
|
||||
| 2020-01-01T00:32:00Z | |
|
||||
| 2020-01-01T00:51:00Z | 4.74 |
|
||||
| 2020-01-01T01:00:00Z | 5.56 |
|
||||
{{% /flex-content %}}
|
||||
{{< /flex >}}
|
||||
|
||||
Results represent the rate of change **per minute** between subsequent values with
|
||||
negative values set to _null_.
|
||||
|
||||
### Return negative derivative values
|
||||
To return negative derivative values, set the `nonNegative` parameter to `false`,
|
||||
|
||||
{{< flex >}}
|
||||
{{% flex-content %}}
|
||||
**Given the following input:**
|
||||
|
||||
| _time | _value |
|
||||
|:----- | ------:|
|
||||
| 2020-01-01T00:00:00Z | 250 |
|
||||
| 2020-01-01T00:04:00Z | 160 |
|
||||
| 2020-01-01T00:12:00Z | 150 |
|
||||
| 2020-01-01T00:19:00Z | 220 |
|
||||
| 2020-01-01T00:32:00Z | 200 |
|
||||
| 2020-01-01T00:51:00Z | 290 |
|
||||
| 2020-01-01T01:00:00Z | 340 |
|
||||
{{% /flex-content %}}
|
||||
{{% flex-content %}}
|
||||
**The following returns:**
|
||||
|
||||
```js
|
||||
|> derivative(
|
||||
unit: 1m,
|
||||
nonNegative: false
|
||||
)
|
||||
```
|
||||
|
||||
| _time | _value |
|
||||
|:----- | ------:|
|
||||
| 2020-01-01T00:04:00Z | -22.5 |
|
||||
| 2020-01-01T00:12:00Z | -1.25 |
|
||||
| 2020-01-01T00:19:00Z | 10.0 |
|
||||
| 2020-01-01T00:32:00Z | -1.54 |
|
||||
| 2020-01-01T00:51:00Z | 4.74 |
|
||||
| 2020-01-01T01:00:00Z | 5.56 |
|
||||
{{% /flex-content %}}
|
||||
{{< /flex >}}
|
||||
|
||||
Results represent the rate of change **per minute** between subsequent values and
|
||||
include negative values.
|
||||
|
||||
## Average rate of change per window of time
|
||||
|
||||
Use the [`aggregate.rate()` function](/v2.0/reference/flux/stdlib/experimental/aggregate/rate/)
|
||||
to calculate the average rate of change per window of time.
|
||||
|
||||
```js
|
||||
import "experimental/aggregate"
|
||||
|
||||
data
|
||||
|> aggregate.rate(
|
||||
every: 1m,
|
||||
unit: 1s,
|
||||
groupColumns: ["tag1", "tag2"]
|
||||
)
|
||||
```
|
||||
|
||||
`aggregate.rate()` returns the average rate of change (as a [float](/v2.0/reference/flux/language/types/#numeric-types))
|
||||
per `unit` for time intervals defined by `every`.
|
||||
Negative values are replaced with _null_.
|
||||
|
||||
{{% note %}}
|
||||
`aggregate.rate()` does not support `nonNegative: false`.
|
||||
{{% /note %}}
|
||||
|
||||
{{< flex >}}
|
||||
{{% flex-content %}}
|
||||
**Given the following input:**
|
||||
|
||||
| _time | _value |
|
||||
|:----- | ------:|
|
||||
| 2020-01-01T00:00:00Z | 250 |
|
||||
| 2020-01-01T00:04:00Z | 160 |
|
||||
| 2020-01-01T00:12:00Z | 150 |
|
||||
| 2020-01-01T00:19:00Z | 220 |
|
||||
| 2020-01-01T00:32:00Z | 200 |
|
||||
| 2020-01-01T00:51:00Z | 290 |
|
||||
| 2020-01-01T01:00:00Z | 340 |
|
||||
{{% /flex-content %}}
|
||||
{{% flex-content %}}
|
||||
**The following returns:**
|
||||
|
||||
```js
|
||||
|> aggregate.rate(
|
||||
every: 20m,
|
||||
unit: 1m
|
||||
)
|
||||
```
|
||||
|
||||
| _time | _value |
|
||||
|:----- | ------:|
|
||||
| 2020-01-01T00:20:00Z | |
|
||||
| 2020-01-01T00:40:00Z | 10.0 |
|
||||
| 2020-01-01T01:00:00Z | 4.74 |
|
||||
| 2020-01-01T01:20:00Z | 5.56 |
|
||||
{{% /flex-content %}}
|
||||
{{< /flex >}}
|
||||
|
||||
Results represent the **average change rate per minute** of every **20 minute interval**
|
||||
with negative values set to _null_.
|
||||
Timestamps represent the right bound of the time window used to average values.
|
||||
|
|
@ -1,15 +1,23 @@
|
|||
---
|
||||
title: Use regular expressions in Flux
|
||||
list_title: Use regular expressions
|
||||
list_title: Regular expressions
|
||||
description: This guide walks through using regular expressions in evaluation logic in Flux functions.
|
||||
v2.0/tags: [regex]
|
||||
menu:
|
||||
v2_0:
|
||||
name: Use regular expressions
|
||||
name: Regular expressions
|
||||
parent: Query with Flux
|
||||
weight: 220
|
||||
aliases:
|
||||
- /v2.0/query-data/guides/regular-expressions/
|
||||
- /v2.0/query-data/guides/regular-expressions/
|
||||
related:
|
||||
- /v2.0/query-data/flux/query-fields/
|
||||
- /v2.0/reference/flux/stdlib/regexp/
|
||||
list_code_example: |
|
||||
```js
|
||||
data
|
||||
|> filter(fn: (r) => r.tag =~ /^foo[0-9]/)
|
||||
```
|
||||
---
|
||||
|
||||
Regular expressions (regexes) are incredibly powerful when matching patterns in large collections of data.
|
||||
|
|
|
|||
|
|
@ -14,6 +14,16 @@ related:
|
|||
- /v2.0/reference/flux/stdlib/built-in/transformations/stream-table/
|
||||
aliases:
|
||||
- /v2.0/query-data/guides/scalar-values/
|
||||
list_code_example: |
|
||||
```js
|
||||
scalarValue = {
|
||||
_record =
|
||||
data
|
||||
|> tableFind(fn: key => true)
|
||||
|> getRecord(idx: 0)
|
||||
return _record._value
|
||||
}
|
||||
```
|
||||
---
|
||||
|
||||
Use Flux [stream and table functions](/v2.0/reference/flux/stdlib/built-in/transformations/stream-table/)
|
||||
|
|
|
|||
|
|
@ -1,22 +1,35 @@
|
|||
---
|
||||
title: Sort and limit data with Flux
|
||||
seotitle: Sort and limit data in InfluxDB with Flux
|
||||
list_title: Sort and limit data
|
||||
list_title: Sort and limit
|
||||
description: >
|
||||
This guide walks through sorting and limiting data with Flux and outlines how
|
||||
it shapes your data in the process.
|
||||
Use the [`sort()`function](/v2.0/reference/flux/stdlib/built-in/transformations/sort)
|
||||
to order records within each table by specific columns and the
|
||||
[`limit()` function](/v2.0/reference/flux/stdlib/built-in/transformations/limit)
|
||||
to limit the number of records in output tables to a fixed number, `n`.
|
||||
v2.0/tags: [sort, limit]
|
||||
menu:
|
||||
v2_0:
|
||||
name: Sort and limit data
|
||||
name: Sort and limit
|
||||
parent: Query with Flux
|
||||
weight: 203
|
||||
aliases:
|
||||
- /v2.0/query-data/guides/sort-limit/
|
||||
- /v2.0/query-data/guides/sort-limit/
|
||||
related:
|
||||
- /v2.0/reference/flux/stdlib/built-in/transformations/sort
|
||||
- /v2.0/reference/flux/stdlib/built-in/transformations/limit
|
||||
list_code_example: |
|
||||
```js
|
||||
data
|
||||
|> sort(columns: ["host", "_value"])
|
||||
|> limit(n: 10)
|
||||
```
|
||||
---
|
||||
|
||||
The [`sort()`function](/v2.0/reference/flux/stdlib/built-in/transformations/sort)
|
||||
orders the records within each table.
|
||||
Use the [`sort()`function](/v2.0/reference/flux/stdlib/built-in/transformations/sort)
|
||||
to order records within each table by specific columns and the
|
||||
[`limit()` function](/v2.0/reference/flux/stdlib/built-in/transformations/limit)
|
||||
to limit the number of records in output tables to a fixed number, `n`.
|
||||
|
||||
If you're just getting started with Flux queries, check out the following:
|
||||
|
||||
|
|
|
|||
|
|
@ -1,6 +1,7 @@
|
|||
---
|
||||
title: Query SQL data sources
|
||||
seotitle: Query SQL data sources with InfluxDB
|
||||
list_title: Query SQL data
|
||||
description: >
|
||||
The Flux `sql` package provides functions for working with SQL data sources.
|
||||
Use `sql.from()` to query SQL databases like PostgreSQL and MySQL
|
||||
|
|
@ -8,9 +9,22 @@ v2.0/tags: [query, flux, sql]
|
|||
menu:
|
||||
v2_0:
|
||||
parent: Query with Flux
|
||||
list_title: SQL data
|
||||
weight: 220
|
||||
aliases:
|
||||
- /v2.0/query-data/guides/sql/
|
||||
- /v2.0/query-data/guides/sql/
|
||||
related:
|
||||
- /v2.0/reference/flux/stdlib/sql/
|
||||
list_code_example: |
|
||||
```js
|
||||
import "sql"
|
||||
|
||||
sql.from(
|
||||
driverName: "postgres",
|
||||
dataSourceName: "postgresql://user:password@localhost",
|
||||
query: "SELECT * FROM example_table"
|
||||
)
|
||||
```
|
||||
---
|
||||
|
||||
The [Flux](/v2.0/reference/flux) `sql` package provides functions for working with SQL data sources.
|
||||
|
|
|
|||
|
|
@ -1,18 +1,28 @@
|
|||
---
|
||||
title: Window and aggregate data with Flux
|
||||
seotitle: Window and aggregate data in InfluxDB with Flux
|
||||
list_title: Window & aggregate data
|
||||
list_title: Window & aggregate
|
||||
description: >
|
||||
This guide walks through windowing and aggregating data with Flux and outlines
|
||||
how it shapes your data in the process.
|
||||
menu:
|
||||
v2_0:
|
||||
name: Window & aggregate data
|
||||
name: Window & aggregate
|
||||
parent: Query with Flux
|
||||
weight: 204
|
||||
v2.0/tags: [flux, aggregates]
|
||||
aliases:
|
||||
- /v2.0/query-data/guides/window-aggregate/
|
||||
- /v2.0/query-data/guides/window-aggregate/
|
||||
related:
|
||||
- /v2.0/reference/flux/stdlib/built-in/transformations/aggregates/aggregatewindow
|
||||
- /v2.0/reference/flux/stdlib/built-in/transformations/window
|
||||
- /v2.0/reference/flux/stdlib/built-in/transformations/aggregates
|
||||
- /v2.0/reference/flux/stdlib/built-in/transformations/selectors
|
||||
list_code_example: |
|
||||
```js
|
||||
data
|
||||
|> aggregateWindow(every: 5m, fn: mean)
|
||||
```
|
||||
---
|
||||
|
||||
A common operation performed with time series data is grouping data into windows of time,
|
||||
|
|
|
|||
|
|
@ -9,6 +9,8 @@ menu:
|
|||
name: buckets
|
||||
parent: built-in-inputs
|
||||
weight: 401
|
||||
related:
|
||||
- https://docs.influxdata.com/influxdb/latest/query_language/schema_exploration/#show-databases, InfluxQL - SHOW DATABASES]()
|
||||
---
|
||||
|
||||
The `buckets()` function returns a list of buckets in the organization.
|
||||
|
|
@ -18,8 +20,3 @@ _**Function type:** Input_
|
|||
```js
|
||||
buckets()
|
||||
```
|
||||
|
||||
<hr style="margin-top:4rem"/>
|
||||
|
||||
##### Related InfluxQL functions and statements:
|
||||
[SHOW DATABASES](https://docs.influxdata.com/influxdb/latest/query_language/schema_exploration/#show-databases)
|
||||
|
|
|
|||
|
|
@ -9,6 +9,8 @@ menu:
|
|||
name: from
|
||||
parent: built-in-inputs
|
||||
weight: 401
|
||||
related:
|
||||
- https://docs.influxdata.com/influxdb/latest/query_language/data_exploration/#from-clause, InfluxQL - FROM
|
||||
---
|
||||
|
||||
The `from()` function retrieves data from an InfluxDB data source.
|
||||
|
|
@ -46,8 +48,4 @@ from(bucket: "example-bucket")
|
|||
```js
|
||||
from(bucketID: "0261d8287f4d6000")
|
||||
```
|
||||
|
||||
<hr style="margin-top:4rem"/>
|
||||
|
||||
##### Related InfluxQL functions and statements:
|
||||
[FROM](https://docs.influxdata.com/influxdb/latest/query_language/data_exploration/#from-clause)
|
||||
[FROM]()
|
||||
|
|
|
|||
|
|
@ -9,6 +9,8 @@ menu:
|
|||
name: to
|
||||
parent: built-in-outputs
|
||||
weight: 401
|
||||
related:
|
||||
- https://docs.influxdata.com/influxdb/latest/query_language/data_exploration/#the-into-clause, InfluxQL – SELECT INTO
|
||||
---
|
||||
|
||||
The `to()` function writes data to an **InfluxDB v2.0** bucket.
|
||||
|
|
@ -174,9 +176,3 @@ _tag1=a hum=55.3,temp=100.1 0005
|
|||
_tag1=a hum=55.4,temp=99.3 0006
|
||||
_tag1=a hum=55.5,temp=99.9 0007
|
||||
```
|
||||
|
||||
<hr style="margin-top:4rem"/>
|
||||
|
||||
##### Related InfluxQL functions and statements:
|
||||
|
||||
[SELECT INTO](https://docs.influxdata.com/influxdb/latest/query_language/data_exploration/#the-into-clause)
|
||||
|
|
|
|||
|
|
@ -9,6 +9,8 @@ menu:
|
|||
name: yield
|
||||
parent: built-in-outputs
|
||||
weight: 401
|
||||
related:
|
||||
- https://docs.influxdata.com/influxdb/latest/query_language/data_exploration/#the-basic-select-statement, InfluxQL – SELECT AS
|
||||
---
|
||||
|
||||
The `yield()` function indicates the input tables received should be delivered as a result of the query.
|
||||
|
|
@ -41,8 +43,3 @@ from(bucket: "example-bucket")
|
|||
|> range(start: -5m)
|
||||
|> yield(name: "1")
|
||||
```
|
||||
|
||||
<hr style="margin-top:4rem"/>
|
||||
|
||||
##### Related InfluxQL functions and statements:
|
||||
[SELECT AS](https://docs.influxdata.com/influxdb/latest/query_language/data_exploration/#the-basic-select-statement)
|
||||
|
|
|
|||
|
|
@ -12,6 +12,8 @@ menu:
|
|||
identifier: built-in-aggregates
|
||||
weight: 401
|
||||
v2.0/tags: [aggregates, built-in, functions]
|
||||
related:
|
||||
- /v2.0/query-data/flux/window-aggregate/
|
||||
---
|
||||
|
||||
Flux's built-in aggregate functions take values from an input table and aggregate them in some way.
|
||||
|
|
|
|||
|
|
@ -9,6 +9,10 @@ menu:
|
|||
name: aggregateWindow
|
||||
parent: built-in-aggregates
|
||||
weight: 501
|
||||
related:
|
||||
- /v2.0/query-data/flux/window-aggregate/
|
||||
- https://docs.influxdata.com/influxdb/latest/query_language/functions/#aggregations – InfluxQL – Aggregate functions
|
||||
- https://docs.influxdata.com/influxdb/latest/query_language/data_exploration/#the-group-by-clause – InfluxQL – GROUP BY time()
|
||||
---
|
||||
|
||||
The `aggregateWindow()` function applies an aggregate or selector function
|
||||
|
|
@ -129,10 +133,3 @@ aggregateWindow = (every, fn, column="_value", timeSrc="_stop", timeDst="_time",
|
|||
|> duplicate(column:timeSrc, as:timeDst)
|
||||
|> window(every:inf, timeColumn:timeDst)
|
||||
```
|
||||
|
||||
<hr style="margin-top:4rem"/>
|
||||
|
||||
##### Related InfluxQL functions and statements:
|
||||
|
||||
[InfluxQL aggregate functions](https://docs.influxdata.com/influxdb/latest/query_language/functions/#aggregations)
|
||||
[GROUP BY time()](https://docs.influxdata.com/influxdb/latest/query_language/data_exploration/#the-group-by-clause)
|
||||
|
|
|
|||
|
|
@ -9,6 +9,8 @@ menu:
|
|||
name: count
|
||||
parent: built-in-aggregates
|
||||
weight: 501
|
||||
related:
|
||||
- https://docs.influxdata.com/influxdb/latest/query_language/functions/#count, InfluxQL – COUNT()
|
||||
---
|
||||
|
||||
The `count()` function outputs the number of records in a column.
|
||||
|
|
@ -53,8 +55,3 @@ from(bucket: "example-bucket")
|
|||
|> range(start: -5m)
|
||||
|> count(column: "_value")
|
||||
```
|
||||
|
||||
<hr style="margin-top:4rem"/>
|
||||
|
||||
##### Related InfluxQL functions and statements:
|
||||
[COUNT()](https://docs.influxdata.com/influxdb/latest/query_language/functions/#count)
|
||||
|
|
|
|||
|
|
@ -9,6 +9,9 @@ menu:
|
|||
name: derivative
|
||||
parent: built-in-aggregates
|
||||
weight: 501
|
||||
related:
|
||||
- /v2.0/query-data/flux/rate/
|
||||
- https://docs.influxdata.com/influxdb/latest/query_language/functions/#derivative, InfluxQL – DERIVATIVE()
|
||||
---
|
||||
|
||||
The `derivative()` function computes the rate of change per [`unit`](#unit) of time between subsequent non-null records.
|
||||
|
|
@ -59,8 +62,3 @@ from(bucket: "example-bucket")
|
|||
|> range(start: -5m)
|
||||
|> derivative(unit: 1s, nonNegative: true)
|
||||
```
|
||||
|
||||
<hr style="margin-top:4rem"/>
|
||||
|
||||
##### Related InfluxQL functions and statements:
|
||||
[DERIVATIVE()](https://docs.influxdata.com/influxdb/latest/query_language/functions/#derivative)
|
||||
|
|
|
|||
|
|
@ -9,6 +9,8 @@ menu:
|
|||
name: difference
|
||||
parent: built-in-aggregates
|
||||
weight: 501
|
||||
related:
|
||||
- https://docs.influxdata.com/influxdb/latest/query_language/functions/#difference, InfluxQL – DIFFERENCE()
|
||||
---
|
||||
|
||||
The `difference()` function computes the difference between subsequent records.
|
||||
|
|
@ -115,8 +117,3 @@ from(bucket: "example-bucket")
|
|||
| 0003 | -2 | tv |
|
||||
| 0004 | 6 | tv |
|
||||
| 0005 | null | tv |
|
||||
|
||||
<hr style="margin-top:4rem"/>
|
||||
|
||||
##### Related InfluxQL functions and statements:
|
||||
[DIFFERENCE()](https://docs.influxdata.com/influxdb/latest/query_language/functions/#difference)
|
||||
|
|
|
|||
|
|
@ -1,6 +1,8 @@
|
|||
---
|
||||
title: increase() function
|
||||
description: The `increase()` function calculates the total non-negative difference between values in a table.
|
||||
description: >
|
||||
The `increase()` function calculates the cumulative sum of **non-negative** differences
|
||||
between subsequent values.
|
||||
aliases:
|
||||
- /v2.0/reference/flux/functions/transformations/aggregates/increase
|
||||
- /v2.0/reference/flux/functions/built-in/transformations/aggregates/increase/
|
||||
|
|
@ -9,10 +11,12 @@ menu:
|
|||
name: increase
|
||||
parent: built-in-aggregates
|
||||
weight: 501
|
||||
related:
|
||||
- /v2.0/query-data/flux/increase/
|
||||
---
|
||||
|
||||
The `increase()` function calculates the total non-negative difference between
|
||||
subsequent values.
|
||||
The `increase()` function calculates the cumulative sum of **non-negative** differences
|
||||
between subsequent values.
|
||||
A main use case is tracking changes in counter values which may wrap over time
|
||||
when they hit a threshold or are reset.
|
||||
In the case of a wrap/reset, we can assume that the absolute delta between two
|
||||
|
|
@ -58,8 +62,8 @@ Given the following input table:
|
|||
| _time | _value |
|
||||
| ----- | ------ |
|
||||
| 00002 | 4 |
|
||||
| 00003 | 7 |
|
||||
| 00004 | 8 |
|
||||
| 00003 | 4 |
|
||||
| 00004 | 5 |
|
||||
|
||||
## Function definition
|
||||
```js
|
||||
|
|
|
|||
|
|
@ -9,6 +9,8 @@ menu:
|
|||
name: integral
|
||||
parent: built-in-aggregates
|
||||
weight: 501
|
||||
related:
|
||||
- https://docs.influxdata.com/influxdb/latest/query_language/functions/#integral, InfluxQL – INTEGRAL()
|
||||
---
|
||||
|
||||
The `integral()` function computes the area under the curve per [`unit`](#unit) of time of subsequent non-null records.
|
||||
|
|
@ -44,8 +46,3 @@ from(bucket: "example-bucket")
|
|||
)
|
||||
|> integral(unit:10s)
|
||||
```
|
||||
|
||||
<hr style="margin-top:4rem"/>
|
||||
|
||||
##### Related InfluxQL functions and statements:
|
||||
[INTEGRAL()](https://docs.influxdata.com/influxdb/latest/query_language/functions/#integral)
|
||||
|
|
|
|||
|
|
@ -9,6 +9,8 @@ menu:
|
|||
name: mean
|
||||
parent: built-in-aggregates
|
||||
weight: 501
|
||||
related:
|
||||
- https://docs.influxdata.com/influxdb/latest/query_language/functions/#mean, InfluxQL – MEAN()
|
||||
---
|
||||
|
||||
The `mean()` function computes the mean or average of non-null records in the input table.
|
||||
|
|
@ -38,8 +40,3 @@ from(bucket:"example-bucket")
|
|||
|> window(every:10m)
|
||||
|> mean()
|
||||
```
|
||||
|
||||
<hr style="margin-top:4rem"/>
|
||||
|
||||
##### Related InfluxQL functions and statements:
|
||||
[MEAN()](https://docs.influxdata.com/influxdb/latest/query_language/functions/#mean)
|
||||
|
|
|
|||
|
|
@ -11,6 +11,9 @@ menu:
|
|||
name: median
|
||||
parent: built-in-aggregates
|
||||
weight: 501
|
||||
related:
|
||||
- /v2.0/query-data/flux/median/
|
||||
- https://docs.influxdata.com/influxdb/latest/query_language/functions/#median, InfluxQL – MEDIAN()
|
||||
---
|
||||
|
||||
The `median()` function is a special application of the [`quantile()` function](/v2.0/reference/flux/stdlib/built-in/transformations/aggregates/quantile)
|
||||
|
|
@ -110,8 +113,3 @@ median = (method="estimate_tdigest", compression=0.0, tables=<-) =>
|
|||
compression:compression
|
||||
)
|
||||
```
|
||||
|
||||
<hr style="margin-top:4rem"/>
|
||||
|
||||
##### Related InfluxQL functions and statements:
|
||||
[MEDIAN()](https://docs.influxdata.com/influxdb/latest/query_language/functions/#median)
|
||||
|
|
|
|||
|
|
@ -10,6 +10,8 @@ menu:
|
|||
name: mode
|
||||
parent: built-in-aggregates
|
||||
weight: 501
|
||||
related:
|
||||
- https://docs.influxdata.com/influxdb/latest/query_language/functions/#mode, InfluxQL – MODE()
|
||||
---
|
||||
|
||||
The `mode()` function computes the mode or value that occurs most often in a
|
||||
|
|
@ -55,8 +57,3 @@ from(bucket: "example-bucket")
|
|||
|> window(every:10m)
|
||||
|> mode()
|
||||
```
|
||||
|
||||
<hr style="margin-top:4rem"/>
|
||||
|
||||
##### Related InfluxQL functions and statements:
|
||||
[MODE()](https://docs.influxdata.com/influxdb/latest/query_language/functions/#mode)
|
||||
|
|
|
|||
|
|
@ -10,6 +10,7 @@ menu:
|
|||
parent: built-in-aggregates
|
||||
weight: 501
|
||||
related:
|
||||
- /v2.0/query-data/flux/moving-average/
|
||||
- /v2.0/reference/flux/stdlib/built-in/transformations/aggregates/timedmovingaverage/
|
||||
- /v2.0/reference/flux/stdlib/built-in/transformations/aggregates/exponentialmovingaverage/
|
||||
- /v2.0/reference/flux/stdlib/built-in/transformations/aggregates/doubleema/
|
||||
|
|
|
|||
|
|
@ -10,6 +10,9 @@ menu:
|
|||
name: quantile
|
||||
parent: built-in-aggregates
|
||||
weight: 501
|
||||
related:
|
||||
- /v2.0/query-data/flux/percentile-quantile/
|
||||
- https://docs.influxdata.com/influxdb/latest/query_language/functions/#percentile, InfluxQL – PERCENTILE()
|
||||
---
|
||||
|
||||
The `quantile()` function returns records from an input table with `_value`s that fall within
|
||||
|
|
@ -99,8 +102,3 @@ from(bucket: "example-bucket")
|
|||
method: "exact_selector"
|
||||
)
|
||||
```
|
||||
|
||||
<hr style="margin-top:4rem"/>
|
||||
|
||||
##### Related InfluxQL functions and statements:
|
||||
[PERCENTILE()](https://docs.influxdata.com/influxdb/latest/query_language/functions/#percentile)
|
||||
|
|
|
|||
|
|
@ -11,6 +11,9 @@ menu:
|
|||
parent: built-in-aggregates
|
||||
weight: 501
|
||||
v2.0/tags: [exists]
|
||||
related:
|
||||
- /v2.0/query-data/flux/custom-functions/custom-aggregate/
|
||||
- /v2.0/query-data/flux/conditional-logic/
|
||||
---
|
||||
|
||||
The `reduce()` function aggregates records in each table according to the reducer,
|
||||
|
|
|
|||
|
|
@ -9,6 +9,8 @@ menu:
|
|||
name: spread
|
||||
parent: built-in-aggregates
|
||||
weight: 501
|
||||
related:
|
||||
- https://docs.influxdata.com/influxdb/latest/query_language/functions/#spread, InfluxQL – SPREAD()
|
||||
---
|
||||
|
||||
The `spread()` function outputs the difference between the minimum and maximum values in a specified column.
|
||||
|
|
@ -42,8 +44,3 @@ from(bucket: "example-bucket")
|
|||
)
|
||||
|> spread()
|
||||
```
|
||||
|
||||
<hr style="margin-top:4rem"/>
|
||||
|
||||
##### Related InfluxQL functions and statements:
|
||||
[SPREAD()](https://docs.influxdata.com/influxdb/latest/query_language/functions/#spread)
|
||||
|
|
|
|||
|
|
@ -9,6 +9,8 @@ menu:
|
|||
name: stddev
|
||||
parent: built-in-aggregates
|
||||
weight: 501
|
||||
related:
|
||||
- https://docs.influxdata.com/influxdb/latest/query_language/functions/#stddev, InfluxQL – STDDEV()
|
||||
---
|
||||
|
||||
The `stddev()` function computes the standard deviation of non-null records in a specified column.
|
||||
|
|
@ -55,8 +57,3 @@ from(bucket: "example-bucket")
|
|||
)
|
||||
|> stddev()
|
||||
```
|
||||
|
||||
<hr style="margin-top:4rem"/>
|
||||
|
||||
##### Related InfluxQL functions and statements:
|
||||
[STDDEV()](https://docs.influxdata.com/influxdb/latest/query_language/functions/#stddev)
|
||||
|
|
|
|||
|
|
@ -9,6 +9,8 @@ menu:
|
|||
name: sum
|
||||
parent: built-in-aggregates
|
||||
weight: 501
|
||||
related:
|
||||
- https://docs.influxdata.com/influxdb/latest/query_language/functions/#sum, InfluxQL – SUM()
|
||||
---
|
||||
|
||||
The `sum()` function computes the sum of non-null records in a specified column.
|
||||
|
|
@ -38,8 +40,3 @@ from(bucket: "example-bucket")
|
|||
)
|
||||
|> sum()
|
||||
```
|
||||
|
||||
<hr style="margin-top:4rem"/>
|
||||
|
||||
##### Related InfluxQL functions and statements:
|
||||
[SUM()](https://docs.influxdata.com/influxdb/latest/query_language/functions/#sum)
|
||||
|
|
|
|||
|
|
@ -12,6 +12,11 @@ menu:
|
|||
name: columns
|
||||
parent: built-in-transformations
|
||||
weight: 401
|
||||
related:
|
||||
- https://docs.influxdata.com/influxdb/latest/query_language/schema_exploration/#show-measurements, InfluxQL – SHOW MEASUREMENTS
|
||||
- https://docs.influxdata.com/influxdb/latest/query_language/schema_exploration/#show-field-keys, InfluxQL – SHOW FIELD KEYS
|
||||
- https://docs.influxdata.com/influxdb/latest/query_language/schema_exploration/#show-tag-keys, InfluxQL – SHOW TAG KEYS
|
||||
- https://docs.influxdata.com/influxdb/latest/query_language/schema_exploration/#show-tag-keys, InfluxQL – SHOW SERIES
|
||||
---
|
||||
|
||||
The `columns()` function lists the column labels of input tables.
|
||||
|
|
@ -50,11 +55,3 @@ from(bucket: "example-bucket")
|
|||
|> group()
|
||||
|> distinct()
|
||||
```
|
||||
|
||||
<hr style="margin-top:4rem"/>
|
||||
|
||||
##### Related InfluxQL functions and statements:
|
||||
[SHOW MEASUREMENTS](https://docs.influxdata.com/influxdb/latest/query_language/schema_exploration/#show-measurements)
|
||||
[SHOW FIELD KEYS](https://docs.influxdata.com/influxdb/latest/query_language/schema_exploration/#show-field-keys)
|
||||
[SHOW TAG KEYS](https://docs.influxdata.com/influxdb/latest/query_language/schema_exploration/#show-tag-keys)
|
||||
[SHOW SERIES](https://docs.influxdata.com/influxdb/latest/query_language/schema_exploration/#show-tag-keys)
|
||||
|
|
|
|||
|
|
@ -9,6 +9,9 @@ menu:
|
|||
name: cumulativeSum
|
||||
parent: built-in-transformations
|
||||
weight: 401
|
||||
related:
|
||||
- /v2.0/query-data/flux/cumulativesum/
|
||||
- https://docs.influxdata.com/influxdb/latest/query_language/functions/#cumulative-sum, InfluxQL – CUMULATIVE_SUM()
|
||||
---
|
||||
|
||||
The `cumulativeSum()` function computes a running sum for non-null records in the table.
|
||||
|
|
@ -39,8 +42,3 @@ from(bucket: "example-bucket")
|
|||
)
|
||||
|> cumulativeSum(columns: ["_value"])
|
||||
```
|
||||
|
||||
<hr style="margin-top:4rem"/>
|
||||
|
||||
##### Related InfluxQL functions and statements:
|
||||
[CUMULATIVE_SUM()](https://docs.influxdata.com/influxdb/latest/query_language/functions/#cumulative-sum)
|
||||
|
|
|
|||
|
|
@ -65,9 +65,3 @@ from(bucket: "example-bucket")
|
|||
|> range(start: -5m)
|
||||
|> drop(fn: (column) => column =~ /usage*/)
|
||||
```
|
||||
|
||||
<hr style="margin-top:4rem"/>
|
||||
|
||||
##### Related InfluxQL functions and statements:
|
||||
|
||||
[DROP MEASUREMENT](https://docs.influxdata.com/influxdb/latest/query_language/database_management/#delete-measurements-with-drop-measurement)
|
||||
|
|
|
|||
|
|
@ -9,6 +9,9 @@ menu:
|
|||
name: fill
|
||||
parent: built-in-transformations
|
||||
weight: 401
|
||||
related:
|
||||
- /v2.0/query-data/flux/fill/
|
||||
- https://docs.influxdata.com/influxdb/latest/query_language/data_exploration/#group-by-time-intervals-and-fill, InfluxQL – FILL
|
||||
---
|
||||
|
||||
The `fill()` function replaces all null values in an input stream with a non-null value.
|
||||
|
|
@ -70,8 +73,3 @@ from(bucket: "example-bucket")
|
|||
)
|
||||
|> fill(usePrevious: true)
|
||||
```
|
||||
|
||||
<hr style="margin-top:4rem"/>
|
||||
|
||||
##### Related InfluxQL functions and statements:
|
||||
[FILL](https://docs.influxdata.com/influxdb/latest/query_language/data_exploration/#group-by-time-intervals-and-fill)
|
||||
|
|
|
|||
|
|
@ -10,6 +10,11 @@ menu:
|
|||
parent: built-in-transformations
|
||||
weight: 401
|
||||
v2.0/tags: [exists]
|
||||
related:
|
||||
- /v2.0/query-data/flux/query-fields/
|
||||
- /v2.0/query-data/flux/conditional-logic/
|
||||
- /v2.0/query-data/flux/exists/
|
||||
- https://docs.influxdata.com/influxdb/latest/query_language/data_exploration/#the-basic-select-statement, InfluxQL – SELECT
|
||||
---
|
||||
|
||||
The `filter()` function filters data based on conditions defined in a predicate function ([`fn`](#fn)).
|
||||
|
|
@ -99,9 +104,3 @@ from(bucket: "example-bucket")
|
|||
|> filter(fn: (r) => r._measurement == "events" and r._field == "open")
|
||||
|> filter(fn: (r) => r.doorId =~ /^2.*/, onEmpty: "keep")
|
||||
```
|
||||
|
||||
<hr style="margin-top:4rem"/>
|
||||
|
||||
##### Related InfluxQL functions and statements:
|
||||
|
||||
[SELECT](https://docs.influxdata.com/influxdb/latest/query_language/data_exploration/#the-basic-select-statement)
|
||||
|
|
|
|||
|
|
@ -9,6 +9,9 @@ menu:
|
|||
name: group
|
||||
parent: built-in-transformations
|
||||
weight: 401
|
||||
related:
|
||||
- /v2.0/query-data/flux/group-data/
|
||||
- https://docs.influxdata.com/influxdb/latest/query_language/data_exploration/#the-group-by-clause, InfluxQL – GROUP BY
|
||||
---
|
||||
|
||||
The `group()` function groups records based on their values for specific columns.
|
||||
|
|
@ -78,8 +81,3 @@ from(bucket: "example-bucket")
|
|||
|> range(start: -30m)
|
||||
|> group()
|
||||
```
|
||||
|
||||
<hr style="margin-top:4rem"/>
|
||||
|
||||
##### Related InfluxQL functions and statements:
|
||||
[GROUP BY](https://docs.influxdata.com/influxdb/latest/query_language/data_exploration/#the-group-by-clause) _(similar but different)_
|
||||
|
|
|
|||
|
|
@ -9,6 +9,8 @@ menu:
|
|||
name: histogram
|
||||
parent: built-in-transformations
|
||||
weight: 401
|
||||
related:
|
||||
- /v2.0/query-data/flux/histograms/
|
||||
---
|
||||
|
||||
The `histogram()` function approximates the cumulative distribution of a dataset by counting data frequencies for a list of bins.
|
||||
|
|
|
|||
|
|
@ -10,6 +10,7 @@ menu:
|
|||
parent: built-in-transformations
|
||||
weight: 401
|
||||
related:
|
||||
- /v2.0/query-data/flux/join/
|
||||
- /v2.0/reference/flux/stdlib/built-in/transformations/union/
|
||||
---
|
||||
|
||||
|
|
|
|||
|
|
@ -12,6 +12,11 @@ menu:
|
|||
name: keys
|
||||
parent: built-in-transformations
|
||||
weight: 401
|
||||
related:
|
||||
- https://docs.influxdata.com/influxdb/latest/query_language/schema_exploration/#show-measurements, InfluxQL – SHOW MEASUREMENTS
|
||||
- https://docs.influxdata.com/influxdb/latest/query_language/schema_exploration/#show-field-keys, InfluxQL – SHOW FIELD KEYS
|
||||
- https://docs.influxdata.com/influxdb/latest/query_language/schema_exploration/#show-tag-keys, InfluxQL – SHOW TAG KEYS
|
||||
- https://docs.influxdata.com/influxdb/latest/query_language/schema_exploration/#show-tag-keys, InfluxQL – SHOW SERIES
|
||||
---
|
||||
|
||||
The `keys()` function outputs the group key of input tables.
|
||||
|
|
@ -50,11 +55,3 @@ from(bucket: "example-bucket")
|
|||
|> group()
|
||||
|> distinct()
|
||||
```
|
||||
|
||||
<hr style="margin-top:4rem"/>
|
||||
|
||||
##### Related InfluxQL functions and statements:
|
||||
[SHOW MEASUREMENTS](https://docs.influxdata.com/influxdb/latest/query_language/schema_exploration/#show-measurements)
|
||||
[SHOW FIELD KEYS](https://docs.influxdata.com/influxdb/latest/query_language/schema_exploration/#show-field-keys)
|
||||
[SHOW TAG KEYS](https://docs.influxdata.com/influxdb/latest/query_language/schema_exploration/#show-tag-keys)
|
||||
[SHOW SERIES](https://docs.influxdata.com/influxdb/latest/query_language/schema_exploration/#show-tag-keys)
|
||||
|
|
|
|||
|
|
@ -9,6 +9,12 @@ menu:
|
|||
name: keyValues
|
||||
parent: built-in-transformations
|
||||
weight: 401
|
||||
related:
|
||||
- https://docs.influxdata.com/influxdb/latest/query_language/schema_exploration/#show-measurements, InfluxQL – SHOW MEASUREMENTS
|
||||
- https://docs.influxdata.com/influxdb/latest/query_language/schema_exploration/#show-field-keys, InfluxQL – SHOW FIELD KEYS
|
||||
- https://docs.influxdata.com/influxdb/latest/query_language/schema_exploration/#show-tag-keys, InfluxQL – SHOW TAG KEYS
|
||||
- https://docs.influxdata.com/influxdb/latest/query_language/schema_exploration/#show-tag-values, InfluxQL – SHOW TAG VALUES
|
||||
- https://docs.influxdata.com/influxdb/latest/query_language/schema_exploration/#show-serie, InfluxQL – SHOW SERIES
|
||||
---
|
||||
|
||||
The `keyValues()` function returns a table with the input table's group key plus two columns,
|
||||
|
|
@ -74,14 +80,4 @@ from(bucket: "example-bucket")
|
|||
|> range(start: -30m)
|
||||
|> filter(fn: (r) => r._measurement == "cpu")
|
||||
|> keyValues(fn: (schema) => schema.columns |> filter(fn: (r) => r.label =~ /usage_.*/))
|
||||
```
|
||||
|
||||
<hr style="margin-top:4rem"/>
|
||||
|
||||
##### Related InfluxQL functions and statements:
|
||||
|
||||
[SHOW MEASUREMENTS](https://docs.influxdata.com/influxdb/latest/query_language/schema_exploration/#show-measurements)
|
||||
[SHOW FIELD KEYS](https://docs.influxdata.com/influxdb/latest/query_language/schema_exploration/#show-field-keys)
|
||||
[SHOW TAG KEYS](https://docs.influxdata.com/influxdb/latest/query_language/schema_exploration/#show-tag-keys)
|
||||
[SHOW TAG VALUES](https://docs.influxdata.com/influxdb/latest/query_language/schema_exploration/#show-tag-values)
|
||||
[SHOW SERIES](https://docs.influxdata.com/influxdb/latest/query_language/schema_exploration/#show-series)
|
||||
```
|
||||
|
|
|
|||
|
|
@ -10,6 +10,7 @@ menu:
|
|||
parent: built-in-transformations
|
||||
weight: 401
|
||||
related:
|
||||
- /v2.0/query-data/flux/sort-limit/
|
||||
- /v2.0/reference/flux/stdlib/built-in/transformations/tail/
|
||||
- https://docs.influxdata.com/influxdb/latest/query_language/data_exploration/#the-limit-and-slimit-clauses, InfluxQL LIMIT
|
||||
---
|
||||
|
|
|
|||
|
|
@ -10,6 +10,9 @@ menu:
|
|||
parent: built-in-transformations
|
||||
weight: 401
|
||||
v2.0/tags: [exists]
|
||||
related:
|
||||
- /v2.0/query-data/flux/conditional-logic/
|
||||
- /v2.0/query-data/flux/mathematic-operations/
|
||||
---
|
||||
|
||||
The `map()` function applies a function to each record in the input tables.
|
||||
|
|
|
|||
|
|
@ -9,6 +9,8 @@ menu:
|
|||
name: range
|
||||
parent: built-in-transformations
|
||||
weight: 401
|
||||
related:
|
||||
- https://docs.influxdata.com/influxdb/latest/query_language/data_exploration/#the-where-clause, InfluxQL – WHERE
|
||||
---
|
||||
|
||||
The `range()` function filters records based on time bounds.
|
||||
|
|
@ -71,8 +73,3 @@ from(bucket:"example-bucket")
|
|||
|> range(start:2018-05-22T23:30:00Z, stop: 2018-05-23T00:00:00Z)
|
||||
// ...
|
||||
```
|
||||
|
||||
<hr style="margin-top:4rem"/>
|
||||
|
||||
##### Related InfluxQL functions and statements:
|
||||
[WHERE](https://docs.influxdata.com/influxdb/latest/query_language/data_exploration/#the-where-clause)
|
||||
|
|
|
|||
|
|
@ -12,6 +12,8 @@ menu:
|
|||
identifier: built-in-selectors
|
||||
weight: 401
|
||||
v2.0/tags: [selectors, built-in, functions]
|
||||
related:
|
||||
- /v2.0/query-data/flux/window-aggregate/
|
||||
---
|
||||
|
||||
Flux's built-in selector functions return one or more records based on function logic.
|
||||
|
|
|
|||
|
|
@ -9,6 +9,8 @@ menu:
|
|||
name: bottom
|
||||
parent: built-in-selectors
|
||||
weight: 501
|
||||
related:
|
||||
- https://docs.influxdata.com/influxdb/latest/query_language/functions/#bottom, InfluxQL – BOTTOM()
|
||||
---
|
||||
|
||||
The `bottom()` function sorts a table by columns and keeps only the bottom `n` records.
|
||||
|
|
@ -56,8 +58,3 @@ _sortLimit = (n, desc, columns=["_value"], tables=<-) =>
|
|||
bottom = (n, columns=["_value"], tables=<-) =>
|
||||
_sortLimit(n:n, columns:columns, desc:false)
|
||||
```
|
||||
|
||||
<hr style="margin-top:4rem"/>
|
||||
|
||||
##### Related InfluxQL functions and statements:
|
||||
[BOTTOM()](https://docs.influxdata.com/influxdb/latest/query_language/functions/#bottom)
|
||||
|
|
|
|||
|
|
@ -9,6 +9,8 @@ menu:
|
|||
name: distinct
|
||||
parent: built-in-selectors
|
||||
weight: 501
|
||||
related:
|
||||
- https://docs.influxdata.com/influxdb/latest/query_language/functions/#distinct, InfluxQL – DISTINCT()
|
||||
---
|
||||
|
||||
The `distinct()` function returns the unique values for a given column.
|
||||
|
|
@ -36,8 +38,3 @@ from(bucket: "example-bucket")
|
|||
|> filter(fn: (r) => r._measurement == "cpu")
|
||||
|> distinct(column: "host")
|
||||
```
|
||||
|
||||
<hr style="margin-top:4rem"/>
|
||||
|
||||
##### Related InfluxQL functions and statements:
|
||||
[DISTINCT()](https://docs.influxdata.com/influxdb/latest/query_language/functions/#distinct)
|
||||
|
|
|
|||
|
|
@ -9,6 +9,9 @@ menu:
|
|||
name: first
|
||||
parent: built-in-selectors
|
||||
weight: 501
|
||||
related:
|
||||
- /v2.0/query-data/flux/first-last/
|
||||
- https://docs.influxdata.com/influxdb/latest/query_language/functions/#first, InfluxQL – FIRST()
|
||||
---
|
||||
|
||||
The `first()` function selects the first non-null record from an input table.
|
||||
|
|
@ -30,8 +33,3 @@ from(bucket:"example-bucket")
|
|||
)
|
||||
|> first()
|
||||
```
|
||||
|
||||
<hr style="margin-top:4rem"/>
|
||||
|
||||
##### Related InfluxQL functions and statements:
|
||||
[FIRST()](https://docs.influxdata.com/influxdb/latest/query_language/functions/#first)
|
||||
|
|
|
|||
|
|
@ -9,6 +9,9 @@ menu:
|
|||
name: last
|
||||
parent: built-in-selectors
|
||||
weight: 501
|
||||
related:
|
||||
- /v2.0/query-data/flux/first-last/
|
||||
- https://docs.influxdata.com/influxdb/latest/query_language/functions/#last, InfluxQL – LAST()
|
||||
---
|
||||
|
||||
The `last()` function selects the last non-null record from an input table.
|
||||
|
|
@ -30,8 +33,3 @@ from(bucket:"example-bucket")
|
|||
)
|
||||
|> last()
|
||||
```
|
||||
|
||||
<hr style="margin-top:4rem"/>
|
||||
|
||||
##### Related InfluxQL functions and statements:
|
||||
[LAST()](https://docs.influxdata.com/influxdb/latest/query_language/functions/#last)
|
||||
|
|
|
|||
|
|
@ -9,6 +9,8 @@ menu:
|
|||
name: max
|
||||
parent: built-in-selectors
|
||||
weight: 501
|
||||
related:
|
||||
- https://docs.influxdata.com/influxdb/latest/query_language/functions/#max, InfluxQL – MAX()
|
||||
---
|
||||
|
||||
The `max()` function selects record with the highest `_value` from the input table.
|
||||
|
|
@ -38,8 +40,3 @@ from(bucket:"example-bucket")
|
|||
)
|
||||
|> max()
|
||||
```
|
||||
|
||||
<hr style="margin-top:4rem"/>
|
||||
|
||||
##### Related InfluxQL functions and statements:
|
||||
[MAX()](https://docs.influxdata.com/influxdb/latest/query_language/functions/#max)
|
||||
|
|
|
|||
|
|
@ -9,6 +9,8 @@ menu:
|
|||
name: min
|
||||
parent: built-in-selectors
|
||||
weight: 501
|
||||
related:
|
||||
- https://docs.influxdata.com/influxdb/latest/query_language/functions/#min, InfluxQL – MIN()
|
||||
---
|
||||
|
||||
The `min()` function selects record with the lowest `_value` from the input table.
|
||||
|
|
@ -38,8 +40,3 @@ from(bucket:"example-bucket")
|
|||
)
|
||||
|> min()
|
||||
```
|
||||
|
||||
<hr style="margin-top:4rem"/>
|
||||
|
||||
##### Related InfluxQL functions and statements:
|
||||
[MIN()](https://docs.influxdata.com/influxdb/latest/query_language/functions/#min)
|
||||
|
|
|
|||
|
|
@ -9,6 +9,8 @@ menu:
|
|||
name: sample
|
||||
parent: built-in-selectors
|
||||
weight: 501
|
||||
related:
|
||||
- https://docs.influxdata.com/influxdb/latest/query_language/functions/#sample, InfluxQL – SAMPLE()
|
||||
---
|
||||
|
||||
The `sample()` function selects a subset of the records from the input table.
|
||||
|
|
@ -45,8 +47,3 @@ from(bucket:"example-bucket")
|
|||
)
|
||||
|> sample(n: 5, pos: 1)
|
||||
```
|
||||
|
||||
<hr style="margin-top:4rem"/>
|
||||
|
||||
##### Related InfluxQL functions and statements:
|
||||
[SAMPLE()](https://docs.influxdata.com/influxdb/latest/query_language/functions/#sample)
|
||||
|
|
|
|||
|
|
@ -9,6 +9,8 @@ menu:
|
|||
name: sort
|
||||
parent: built-in-transformations
|
||||
weight: 401
|
||||
related:
|
||||
- /v2.0/query-data/flux/sort-limit/
|
||||
---
|
||||
|
||||
The `sort()` function orders the records within each table.
|
||||
|
|
|
|||
|
|
@ -9,6 +9,8 @@ menu:
|
|||
name: stateCount
|
||||
parent: built-in-transformations
|
||||
weight: 401
|
||||
related:
|
||||
- /v2.0/query-data/flux/monitor-states/
|
||||
---
|
||||
|
||||
The `stateCount()` function computes the number of consecutive records in a given state.
|
||||
|
|
|
|||
|
|
@ -9,6 +9,8 @@ menu:
|
|||
name: stateDuration
|
||||
parent: built-in-transformations
|
||||
weight: 401
|
||||
related:
|
||||
- /v2.0/query-data/flux/monitor-states/
|
||||
---
|
||||
|
||||
The `stateDuration()` function computes the duration of a given state.
|
||||
|
|
|
|||
|
|
@ -13,6 +13,8 @@ menu:
|
|||
name: Stream & table
|
||||
parent: built-in-transformations
|
||||
v2.0/tags: [transformations, built-in, functions, stream, table]
|
||||
related:
|
||||
- /v2.0/query-data/flux/scalar-values/
|
||||
---
|
||||
|
||||
Use stream and table functions to extract a table from a stream of tables and access its
|
||||
|
|
|
|||
|
|
@ -10,6 +10,8 @@ menu:
|
|||
name: getColumn
|
||||
parent: Stream & table
|
||||
weight: 501
|
||||
related:
|
||||
- /v2.0/query-data/flux/scalar-values/
|
||||
---
|
||||
|
||||
The `getColumn()` function extracts a column from a table given its label.
|
||||
|
|
|
|||
|
|
@ -10,6 +10,8 @@ menu:
|
|||
name: getRecord
|
||||
parent: Stream & table
|
||||
weight: 501
|
||||
related:
|
||||
- /v2.0/query-data/flux/scalar-values/
|
||||
---
|
||||
|
||||
The `getRecord()` function extracts a record from a table given the record's index.
|
||||
|
|
|
|||
|
|
@ -10,6 +10,8 @@ menu:
|
|||
name: tableFind
|
||||
parent: Stream & table
|
||||
weight: 501
|
||||
related:
|
||||
- /v2.0/query-data/flux/scalar-values/
|
||||
---
|
||||
|
||||
The `tableFind()` function extracts the first table in a stream of tables whose
|
||||
|
|
|
|||
|
|
@ -9,6 +9,9 @@ menu:
|
|||
name: window
|
||||
parent: built-in-transformations
|
||||
weight: 401
|
||||
related:
|
||||
- /v2.0/query-data/flux/window-aggregate/
|
||||
- https://docs.influxdata.com/influxdb/latest/query_language/data_exploration/#the-group-by-clause, InfluxQL – GROUP BY time()
|
||||
---
|
||||
|
||||
The `window()` function groups records based on a time value.
|
||||
|
|
@ -127,8 +130,3 @@ from(bucket:"example-bucket")
|
|||
|> range(start:-12h)
|
||||
|> window(intervals: intervals(every:1d, period:8h, offset:9h))
|
||||
```
|
||||
|
||||
<hr style="margin-top:4rem"/>
|
||||
|
||||
##### Related InfluxQL functions and statements:
|
||||
[GROUP BY time()](https://docs.influxdata.com/influxdb/latest/query_language/data_exploration/#the-group-by-clause)
|
||||
|
|
|
|||
|
|
@ -7,6 +7,8 @@ menu:
|
|||
name: aggregate.rate
|
||||
parent: Aggregate
|
||||
weight: 301
|
||||
related:
|
||||
- /v2.0/query-data/flux/rate/
|
||||
---
|
||||
|
||||
The `aggregate.rate()` function calculates the rate of change per windows of time.
|
||||
|
|
@ -14,7 +16,7 @@ The `aggregate.rate()` function calculates the rate of change per windows of tim
|
|||
_**Function type:** Transformation_
|
||||
|
||||
```js
|
||||
import "experimental/query"
|
||||
import "experimental/aggregate"
|
||||
|
||||
aggregate.rate(
|
||||
every: 1m,
|
||||
|
|
|
|||
|
|
@ -11,6 +11,8 @@ menu:
|
|||
parent: Experimental
|
||||
weight: 301
|
||||
v2.0/tags: [functions, package, geo]
|
||||
related:
|
||||
- /v2.0/query-data/flux/geo/
|
||||
---
|
||||
|
||||
The Flux Geo package provides tools for working with geo-temporal data,
|
||||
|
|
|
|||
|
|
@ -8,6 +8,8 @@ menu:
|
|||
parent: Geo
|
||||
weight: 401
|
||||
v2.0/tags: [functions, geo]
|
||||
related:
|
||||
- /v2.0/query-data/flux/geo/
|
||||
---
|
||||
|
||||
The `geo.asTracks()` function groups rows into tracks (sequential, related data points).
|
||||
|
|
|
|||
|
|
@ -12,6 +12,7 @@ v2.0/tags: [functions, geo]
|
|||
related:
|
||||
- /v2.0/reference/flux/stdlib/experimental/geo/gridfilter/
|
||||
- /v2.0/reference/flux/stdlib/experimental/geo/strictfilter/
|
||||
- /v2.0/query-data/flux/geo/
|
||||
---
|
||||
|
||||
The `geo.filterRows()` function filters data by a specified geographic region with
|
||||
|
|
|
|||
|
|
@ -11,6 +11,7 @@ v2.0/tags: [functions, geo]
|
|||
related:
|
||||
- /v2.0/reference/flux/stdlib/experimental/geo/strictfilter/
|
||||
- /v2.0/reference/flux/stdlib/experimental/geo/filterRows/
|
||||
- /v2.0/query-data/flux/geo/
|
||||
---
|
||||
|
||||
The `geo.gridFilter()` function filters data by a specified geographic region.
|
||||
|
|
|
|||
|
|
@ -8,6 +8,8 @@ menu:
|
|||
parent: Geo
|
||||
weight: 401
|
||||
v2.0/tags: [functions, geo]
|
||||
related:
|
||||
- /v2.0/query-data/flux/geo/
|
||||
---
|
||||
|
||||
The `geo.groupByArea()` function groups rows by geographic area.
|
||||
|
|
|
|||
|
|
@ -8,6 +8,8 @@ menu:
|
|||
parent: Geo
|
||||
weight: 401
|
||||
v2.0/tags: [functions, geo]
|
||||
related:
|
||||
- /v2.0/query-data/flux/geo/
|
||||
---
|
||||
|
||||
The `geo.s2CellIDToken()` function returns an S2 cell ID token.
|
||||
|
|
|
|||
|
|
@ -10,6 +10,8 @@ menu:
|
|||
parent: Geo
|
||||
weight: 401
|
||||
v2.0/tags: [functions, geo]
|
||||
related:
|
||||
- /v2.0/query-data/flux/geo/
|
||||
---
|
||||
|
||||
The `geo.shapeData()` function renames existing latitude and longitude fields to
|
||||
|
|
|
|||
|
|
@ -12,6 +12,7 @@ related:
|
|||
- /v2.0/reference/flux/stdlib/experimental/geo/gridfilter/
|
||||
- /v2.0/reference/flux/stdlib/experimental/geo/filterRows/
|
||||
- /v2.0/reference/flux/stdlib/experimental/geo/toRows/
|
||||
- /v2.0/query-data/flux/geo/
|
||||
---
|
||||
|
||||
The `geo.strictFilter()` function filters data by latitude and longitude in a specified region.
|
||||
|
|
|
|||
|
|
@ -9,6 +9,7 @@ menu:
|
|||
weight: 401
|
||||
v2.0/tags: [functions, geo]
|
||||
related:
|
||||
- /v2.0/query-data/flux/geo/
|
||||
- /v2.0/reference/flux/stdlib/built-in/transformations/pivot/
|
||||
---
|
||||
|
||||
|
|
|
|||
|
|
@ -12,6 +12,8 @@ menu:
|
|||
parent: Flux standard library
|
||||
weight: 202
|
||||
v2.0/tags: [math, functions]
|
||||
related:
|
||||
- /v2.0/query-data/flux/mathematic-operations/
|
||||
---
|
||||
|
||||
The Flux math package provides basic constants and mathematical functions.
|
||||
|
|
|
|||
|
|
@ -13,6 +13,8 @@ menu:
|
|||
parent: Flux standard library
|
||||
weight: 202
|
||||
v2.0/tags: [functions, sql, package, mysql, postgres]
|
||||
related:
|
||||
- /v2.0/query-data/flux/sql/
|
||||
---
|
||||
|
||||
SQL Flux functions provide tools for working with data in SQL databases such as
|
||||
|
|
|
|||
|
|
@ -0,0 +1,63 @@
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After Width: | Height: | Size: 3.8 KiB |
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Reference in New Issue