added cumulativeSum guide, added flex shortcodes, updates to common queries docs
Scott Anderson
parent
4f5e816f05
commit
af5f3be9d7
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@ -509,6 +509,38 @@ The following options are available:
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{{< ui-message color="green" text="The message displayed in the notification.">}}
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```
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### Flexbox-formatted content blocks
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CSS Flexbox formatting lets you create columns in article content that adjust and
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flow based on the viewable width.
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In article content, this helps if you have narrow tables that could be displayed
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side-by-side, rather than stacked vertically.
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Use the `{{< flex >}}` shortcode to create the Flexbox wrapper.
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Use the `{{% flex-content %}}` shortcode to identify each column content block.
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```md
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{{< flex >}}
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{{% flex-content %}}
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Column 1
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{{% /flex-content %}}
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{{% flex-content %}}
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Column 2
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{{% /flex-content %}}
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{{< /flex >}}
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```
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`{{% flex-content %}}` has an optional width argument that determines the maximum
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width of the column.
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```md
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{{% flex-content "half" %}}
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```
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The following options are available:
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- half _(Default)_
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- third
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- quarter
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### Reference content
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The InfluxDB documentation is "task-based," meaning content primarily focuses on
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what a user is **doing**, not what they are **using**.
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@ -104,6 +104,7 @@
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"article/cloud",
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"article/enterprise",
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"article/feedback",
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"article/flex",
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"article/lists",
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"article/note",
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"article/pagination-btns",
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@ -0,0 +1,24 @@
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/////////////////////////// Flex Content Blocks ///////////////////////////
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.flex-wrapper {
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display: flex;
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flex-wrap: wrap;
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}
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.flex-container {
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margin-right: 1rem;
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&.half { width: calc(50% - 1rem); }
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&.third { width: calc(33.33% - 1rem); }
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&.quarter { width: calc(25% - 1rem); }
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}
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////////////////////////////////////////////////////////////////////////////////
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///////////////////////////////// MEDIA QUERIES ////////////////////////////////
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////////////////////////////////////////////////////////////////////////////////
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@include media(small) {
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.flex-container {
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&.half, &.third { width: calc(100% - 1rem); }
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&.quarter { width: calc(50% - 1rem); }
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}
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}
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@ -11,86 +11,41 @@ v2.0/tags: [query]
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---
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- SELECT-like commands
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- Median
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- Percentile
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- Cumulative Sum
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- Moving Average
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- Increase
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- Rate
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- Delta
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- Window
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- First/Last
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- Histogram
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- Gap filling
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- Last observation carried forward
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- Last point
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{{% note %}}
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#### Example data variable
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Many of the examples provided in the following guides use a `data` variable,
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which represents a basic query which filters data by measurement and field.
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`data` is defined as:
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## SELECT-like commands
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Query fields from InfluxDB
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## Median
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##### Median as an aggregate
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```js
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from(bucket: "example-bucket")
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data = from(bucket: "example-bucket")
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|> range(start: -1h)
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|> filter(fn: (r) =>
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r._measurement == "example-measurement" and
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r._field == "example-key"
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)
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|> aggregateWindow(every: 5m, fn: median)
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```
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##### Median as a selector
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```js
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from(bucket: "example-bucket")
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|> range(start: -1h)
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|> filter(fn: (r) =>
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r._measurement == "example-measurement" and
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r._field == "example-key"
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)
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|> median(method: "exact_selector")
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```
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## Percentile
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##### Percentile as an aggregate
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```js
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from(bucket: "example-bucket")
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|> range(start: -1h)
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|> filter(fn: (r) =>
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r._measurement == "example-measurement" and
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r._field == "example-key"
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)
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|> aggregateWindow(
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every: 5m,
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fn: (tables=<-, column) => tables |> quantile(q: 0.99)
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r._measurement == "example-measurement" and
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r._field == "example-field"
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)
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```
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{{% /note %}}
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##### Percentile as a selector
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```js
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from(bucket: "example-bucket")
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|> range(start: -1h)
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|> filter(fn: (r) =>
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r._measurement == "example-measurement" and
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r._field == "example-key"
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)
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|> quantile(q: 0.99)
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```
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{{< children >}}
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---
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- [x] SELECT-like commands
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- [x] Median
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- [x] Percentile
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- [ ] Cumulative Sum
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- [ ] Moving Average
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- [ ] Increase
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- [ ] Rate
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- [ ] Delta
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- [ ] Window
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- [ ] First/Last
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- [ ] Histogram
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- [ ] Gap filling
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- [ ] Last observation carried forward
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- [ ] Last point
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## Cumulative Sum
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```js
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from(bucket: "example-bucket")
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|> range(start: -1h)
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|> filter(fn: (r) =>
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r._measurement == "example-measurement" and
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r._field == "example-key"
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)
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|> cumulativeSum()
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```
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## Moving Average
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```js
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@ -0,0 +1,67 @@
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---
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title: Query cumulative sum
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seotitle: Query cumulative sum in Flux
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list_title: Cumulative sum
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description: >
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Use the `cumulativeSum()` function to calculate a running total of values.
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weight: 204
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menu:
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v2_0:
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parent: Common queries
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name: Cumulative sum
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v2.0/tags: [query, cumulative sum]
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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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to calculate a running total of values.
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`cumulativeSum` sums the values of subsequent records and returns each row updated with the summed total.
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{{< flex >}}
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{{% flex-content "half" %}}
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**Given the following input table:**
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| _time | _value |
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| ----- |:------:|
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| 0001 | 1 |
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| 0002 | 2 |
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| 0003 | 1 |
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| 0004 | 3 |
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{{% /flex-content %}}
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{{% flex-content "half" %}}
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**`cumulativeSum()` returns:**
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| _time | _value |
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| ----- |:------:|
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| 0001 | 1 |
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| 0002 | 3 |
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| 0003 | 4 |
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| 0004 | 7 |
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{{% /flex-content %}}
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{{< /flex >}}
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{{% note %}}
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The examples below use the [example data variable](/v2.0/query-data/common-queries/#example-data-variable).
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{{% /note %}}
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##### Calculate the running total of values
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```js
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data
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|> cumulativeSum()
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```
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## Use cumulativeSum() with aggregateWindow()
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[`aggregateWindow()`](/v2.0/reference/flux/stdlib/built-in/transformations/aggregates/aggregatewindow/)
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segments data into windows of time, aggregates data in each window into a single
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point, then removes the time-based segmentation.
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It is primarily used to [downsample data](/v2.0/process-data/common-tasks/downsample-data/).
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`aggregateWindow()` expects an aggregate function that returns a single row for each time window.
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To use `cumulativeSum()` with `aggregateWindow`, use `sum` in `aggregateWindow()`,
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then calculate the running total of the aggregate values with `cumulativeSum()`.
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<!-- -->
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```js
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data
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|> aggregateWindow(every: 5m, fn: sum)
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|> cumulativeSum()
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```
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@ -1,15 +1,18 @@
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---
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title: Query median values
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seotitle: Query median values in Flux
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list_title: Median
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description: >
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placeholder
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weight: 201
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Use the `median()` function to return all values within the `0.5` quantile
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(50th percentile) or the median value of input data.
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weight: 202
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menu:
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v2_0:
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parent: Common queries
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name: Median
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v2.0/tags: [query, median]
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related:
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- /v2.0/query-data/common-queries/query-percentile/
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- /v2.0/query-data/common-queries/percentile-quantile/
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---
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Use the [`median()` function](/v2.0/reference/flux/stdlib/built-in/transformations/aggregates/median/)
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@ -18,35 +21,88 @@ to return all values within the `0.5` quantile (50th percentile) or the median v
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## Median calculation methods
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Select from the following methods for calculating the median:
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##### estimate_tdigest
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- [estimate_tdigest](#estimate-tdigest)
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- [exact_mean](#exact-mean)
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- [exact_selector](#exact-selector)
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### estimate_tdigest
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**(Default)** An aggregate method that uses a [t-digest data structure](https://github.com/tdunning/t-digest)
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to compute an accurate quantile estimate on large data sources.
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Returns all values in the `0.5` quantile or 50th percentile.
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Output tables consist of a single row containing the calculated median.
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##### exact_mean
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{{< flex >}}
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{{% flex-content %}}
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**Given the following input table:**
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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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**`estimate_tdigest` returns:**
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| _value |
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|:------:|
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| 1.5 |
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{{% /flex-content %}}
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{{< /flex >}}
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### exact_mean
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An aggregate method that takes the average of the two points closest to the quantile value.
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Output tables consist of a single row containing the calculated median.
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##### exact_selector
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{{< flex >}}
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{{% flex-content %}}
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**Given the following input table:**
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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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**`exact_mean` returns:**
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| _value |
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|:------:|
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| 1.5 |
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{{% /flex-content %}}
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{{< /flex >}}
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### exact_selector
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A selector method that returns the data point for which at least 50% of points are less than.
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Output tables consist of a single row containing the calculated median.
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{{% note %}}
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#### Example data variable
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To focus on using the `median()` function, the examples below use a `data` variable
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which represents a base queried dataset.
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{{< flex >}}
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{{% flex-content %}}
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**Given the following input table:**
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```js
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data = from(bucket: "example-bucket")
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|> range(start: -1h)
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|> filter(fn: (r) =>
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r._measurement == "example-measurement" and
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r._field == "example-field"
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)
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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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**`exact_selector` returns:**
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| _time | _value |
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| ----- |:------:|
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| 0002 | 1.0 |
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{{% /flex-content %}}
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{{< /flex >}}
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{{% note %}}
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The examples below use the [example data variable](/v2.0/query-data/common-queries/#example-data-variable).
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{{% /note %}}
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## Query all values in the 50th percentile
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## Query the value that represents the median
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Use the default method, `"estimate_tdigest"`, to return all rows in a table that
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contain values in the 50th percentile of data in the table.
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@ -64,7 +120,7 @@ data
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|> median(method: "exact_mean")
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```
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## Query the median value
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## Query the point with the median value
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Use the `exact_selector` method to return a single row per input table containing the
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value that 50% of values in the table are less than.
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@ -73,16 +129,13 @@ data
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|> median(method: "exact_selector")
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```
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## Use median with aggregateWindow()
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## Use median() with aggregateWindow()
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[`aggregateWindow()`](/v2.0/reference/flux/stdlib/built-in/transformations/aggregates/aggregatewindow/)
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segments data into windows of time, aggregates data in each window into a single
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point, then removes the time-based segmentation.
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It is primarily used to [downsample data](/v2.0/process-data/common-tasks/downsample-data/).
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`aggregateWindow()` expects a single point from each time window.
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Use either the `exact_mean` or `exact_mode` median calculation method.
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To specify parameters of the aggregate function in `aggregateWindow()`, use the
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To specify the [median calculation method](#median-calculation-methods) in `aggregateWindow()`, use the
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[full function syntax](/v2.0/reference/flux/stdlib/built-in/transformations/aggregates/aggregatewindow/#specify-parameters-of-the-aggregate-function):
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```js
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@ -0,0 +1,161 @@
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---
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title: Query percentile and quantile values
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seotitle: Query percentile and quantile values in Flux
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list_title: Percentile & quantile
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description: >
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Use the `quantile()` function to return all values within the `q` quantile or
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percentile of input data.
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weight: 203
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menu:
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v2_0:
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parent: Common queries
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name: Percentile & quantile
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v2.0/tags: [query, percentile, quantile]
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related:
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- /v2.0/query-data/common-queries/query-median/
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---
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Use the [`quantile()` function](/v2.0/reference/flux/stdlib/built-in/transformations/aggregates/quantile/)
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to return all values within the `q` quantile or percentile of input data.
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## Percentile versus quantile
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Percentiles and quantiles are very similar, differing only in the number used to calculate return values.
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A percentile is calculated using numbers between `0` and `100`.
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A quantile is calculated using numbers between `0.0` and `1.0`.
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For example, the **`0.5` quantile** is the same as the **50th percentile**.
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## Quantile calculation methods
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Select from the following methods for calculating the quantile:
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- [estimate_tdigest](#estimate-tdigest)
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- [exact_mean](#exact-mean)
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- [exact_selector](#exact-selector)
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### estimate_tdigest
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**(Default)** An aggregate method that uses a [t-digest data structure](https://github.com/tdunning/t-digest)
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to compute an accurate quantile estimate on large data sources.
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Output tables consist of a single row containing the calculated quantile.
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|
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If calculating the `0.5` quantile or 50th percentile:
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{{< flex >}}
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{{% flex-content %}}
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**Given the following input table:**
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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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**`estimate_tdigest` returns:**
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| _value |
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|:------:|
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| 1.5 |
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{{% /flex-content %}}
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{{< /flex >}}
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### exact_mean
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An aggregate method that takes the average of the two points closest to the quantile value.
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Output tables consist of a single row containing the calculated quantile.
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|
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If calculating the `0.5` quantile or 50th percentile:
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{{< flex >}}
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{{% flex-content %}}
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**Given the following input table:**
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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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**`exact_mean` returns:**
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| _value |
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|:------:|
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| 1.5 |
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{{% /flex-content %}}
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{{< /flex >}}
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### exact_selector
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A selector method that returns the data point for which at least `q` points are less than.
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Output tables consist of a single row containing the calculated quantile.
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If calculating the `0.5` quantile or 50th percentile:
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{{< flex >}}
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{{% flex-content %}}
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**Given the following input table:**
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| _time | _value |
|
||||
| ----- |:------:|
|
||||
| 0001 | 1.0 |
|
||||
| 0002 | 1.0 |
|
||||
| 0003 | 2.0 |
|
||||
| 0004 | 3.0 |
|
||||
{{% /flex-content %}}
|
||||
{{% flex-content %}}
|
||||
**`exact_selector` returns:**
|
||||
|
||||
| _time | _value |
|
||||
| ----- |:------:|
|
||||
| 0002 | 1.0 |
|
||||
{{% /flex-content %}}
|
||||
{{< /flex >}}
|
||||
|
||||
{{% note %}}
|
||||
The examples below use the [example data variable](/v2.0/query-data/common-queries/#example-data-variable).
|
||||
{{% /note %}}
|
||||
|
||||
## Query the value representing the 99th percentile
|
||||
Use the default method, `"estimate_tdigest"`, to return all rows in a table that
|
||||
contain values in the 50th percentile of data in the table.
|
||||
|
||||
```js
|
||||
data
|
||||
|> quantile(q: 0.99)
|
||||
```
|
||||
|
||||
## Query the average of values closest to the quantile
|
||||
Use the `exact_mean` method to return a single row per input table containing the
|
||||
average of the two values closest to the mathematical quantile of data in the table.
|
||||
|
||||
```js
|
||||
data
|
||||
|> quantile(q: 0.99, method: "exact_mean")
|
||||
```
|
||||
|
||||
## Query the point with the quantile value
|
||||
Use the `exact_selector` method to return a single row per input table containing the
|
||||
value that `q * 100`% of values in the table are less than.
|
||||
|
||||
```js
|
||||
data
|
||||
|> quantile(q: 0.99, method: "exact_selector")
|
||||
```
|
||||
|
||||
## Use quantile() with aggregateWindow()
|
||||
[`aggregateWindow()`](/v2.0/reference/flux/stdlib/built-in/transformations/aggregates/aggregatewindow/)
|
||||
segments data into windows of time, aggregates data in each window into a single
|
||||
point, then removes the time-based segmentation.
|
||||
It is primarily used to [downsample data](/v2.0/process-data/common-tasks/downsample-data/).
|
||||
|
||||
To specify the [quantile calculation method](#quantile-calculation-methods) in
|
||||
`aggregateWindow()`, use the [full function syntax](/v2.0/reference/flux/stdlib/built-in/transformations/aggregates/aggregatewindow/#specify-parameters-of-the-aggregate-function):
|
||||
|
||||
```js
|
||||
data
|
||||
|> aggregateWindow(
|
||||
every: 5m,
|
||||
fn: (tables=<-, column) =>
|
||||
tables
|
||||
|> quantile(q: 0.99, method: "exact_selector")
|
||||
)
|
||||
```
|
||||
|
|
@ -4,7 +4,7 @@ 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.
|
||||
If familiar with InfluxQL or other SQL-like query languages, `filter()` performs
|
||||
operations similar to the `SELECT` statement and `WHERE` clause.
|
||||
operations similar to the `SELECT` statement and the `WHERE` clause.
|
||||
weight: 201
|
||||
menu:
|
||||
v2_0:
|
||||
|
|
@ -15,7 +15,7 @@ v2.0/tags: [query, select, where]
|
|||
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.
|
||||
If familiar with InfluxQL or other SQL-like query languages, `filter()` performs
|
||||
operations similar to the `SELECT` statement and `WHERE` clause.
|
||||
operations similar to the `SELECT` statement and the `WHERE` clause.
|
||||
|
||||
## The filter() function
|
||||
`filter()` has an `fn` parameter that expects a [predicate function](/v2.0/reference/glossary/#predicate-function),
|
||||
|
|
|
|||
|
|
@ -1,102 +0,0 @@
|
|||
---
|
||||
title: Query percentile values
|
||||
seotitle: Query percentile values in Flux
|
||||
description: >
|
||||
placeholder
|
||||
weight: 201
|
||||
menu:
|
||||
v2_0:
|
||||
parent: Common queries
|
||||
v2.0/tags: [query, percentile, quantile]
|
||||
related:
|
||||
- /v2.0/query-data/common-queries/query-median/
|
||||
---
|
||||
|
||||
Use the [`quantile()` function](/v2.0/reference/flux/stdlib/built-in/transformations/aggregates/quantile/)
|
||||
to return all values within the `q` quantile or percentile of input data.
|
||||
|
||||
## Percentile versus quantile
|
||||
Percentiles and quantiles are very similar, differing only in the number used to calculate return values.
|
||||
A percentile is calculated using numbers between `0` and `100`.
|
||||
A quantile is calculated using numbers between `0.0` and `1.0`.
|
||||
For example, the **`0.5` quantile** is the same as the **50th percentile**.
|
||||
|
||||
## Quantile calculation methods
|
||||
Select from the following methods for calculating the quantile:
|
||||
|
||||
##### estimate_tdigest
|
||||
(Default) An aggregate method that uses a [t-digest data structure](https://github.com/tdunning/t-digest)
|
||||
to compute an accurate quantile estimate on large data sources.
|
||||
Returns all values in the `q` quantile.
|
||||
|
||||
##### exact_mean
|
||||
An aggregate method that takes the average of the two points closest to the quantile value.
|
||||
Output tables consist of a single row containing the calculated quantile.
|
||||
|
||||
##### exact_selector
|
||||
A selector method that returns the data point for which at least `q` points are less than.
|
||||
Output tables consist of a single row containing the calculated quantile.
|
||||
|
||||
{{% note %}}
|
||||
#### Example data variable
|
||||
To focus on using the `quantile()` function, the examples below use a `data` variable
|
||||
which represents a base queried dataset.
|
||||
|
||||
```js
|
||||
data = from(bucket: "example-bucket")
|
||||
|> range(start: -1h)
|
||||
|> filter(fn: (r) =>
|
||||
r._measurement == "example-measurement" and
|
||||
r._field == "example-field"
|
||||
)
|
||||
```
|
||||
{{% /note %}}
|
||||
|
||||
## Query all values in the 50th percentile
|
||||
Use the default method, `"estimate_tdigest"`, to return all rows in a table that
|
||||
contain values in the 50th percentile of data in the table.
|
||||
|
||||
```js
|
||||
data
|
||||
|> quantile(q: 0.99)
|
||||
```
|
||||
|
||||
## Query the average of values closest to the quantile
|
||||
Use the `exact_mean` method to return a single row per input table containing the
|
||||
average of the two values closest to the mathematical quantile of data in the table.
|
||||
|
||||
```js
|
||||
data
|
||||
|> quantile(q: 0.99, method: "exact_mean")
|
||||
```
|
||||
|
||||
## Query the quantile value
|
||||
Use the `exact_selector` method to return a single row per input table containing the
|
||||
value that 50% of values in the table are less than.
|
||||
|
||||
```js
|
||||
data
|
||||
|> quantile(q: 0.99, method: "exact_selector")
|
||||
```
|
||||
|
||||
## Use quantile with aggregateWindow()
|
||||
[`aggregateWindow()`](/v2.0/reference/flux/stdlib/built-in/transformations/aggregates/aggregatewindow/)
|
||||
segments data into windows of time, aggregates data in each window into a single
|
||||
point, then removes the time-based segmentation.
|
||||
It is primarily used to [downsample data](/v2.0/process-data/common-tasks/downsample-data/).
|
||||
|
||||
`aggregateWindow()` expects a single point from each time window.
|
||||
Use either the `exact_mean` or `exact_mode` quantile calculation method.
|
||||
|
||||
To specify parameters of the aggregate function in `aggregateWindow()`, use the
|
||||
[full function syntax](/v2.0/reference/flux/stdlib/built-in/transformations/aggregates/aggregatewindow/#specify-parameters-of-the-aggregate-function):
|
||||
|
||||
```js
|
||||
data
|
||||
|> aggregateWindow(
|
||||
every: 5m,
|
||||
fn: (tables=<-, column) =>
|
||||
tables
|
||||
|> quantile(q: 0.99, method: "exact_selector")
|
||||
)
|
||||
```
|
||||
|
|
@ -0,0 +1,5 @@
|
|||
{{ $width := .Get 0 | default "half" }}
|
||||
{{ $_hugo_config := `{ "version": 1 }` }}
|
||||
<div class="flex-container {{ $width }}">
|
||||
{{ .Inner }}
|
||||
</div>
|
||||
|
|
@ -0,0 +1,4 @@
|
|||
{{ $_hugo_config := `{ "version": 1 }` }}
|
||||
<div class="flex-wrapper">
|
||||
{{ .Inner }}
|
||||
</div>
|
||||
Loading…
Reference in New Issue