| title |
seotitle |
list_title |
description |
weight |
menu |
influxdb/v2.1/tags |
related |
list_query_example |
| Query cumulative sum |
Query cumulative sum in Flux |
Cumulative sum |
Use the `cumulativeSum()` function to calculate a running total of values.
|
210 |
| influxdb_2_1 |
| parent |
name |
| Query with Flux |
Cumulative sum |
|
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| /{{< latest "flux" >}}/stdlib/universe/cumulativesum/ |
|
cumulative_sum |
Use the [cumulativeSum() function](/{{< latest "flux" >}}/stdlib/universe/cumulativesum/)
to calculate a running total of values.
cumulativeSum sums the values of subsequent records and returns each row updated with the summed total.
{{< flex >}}
{{% flex-content "half" %}}
Given the following input table:
| _time |
_value |
| 0001 |
1 |
| 0002 |
2 |
| 0003 |
1 |
| 0004 |
3 |
| {{% /flex-content %}} |
|
| {{% flex-content "half" %}} |
|
cumulativeSum() returns: |
|
| _time |
_value |
| 0001 |
1 |
| 0002 |
3 |
| 0003 |
4 |
| 0004 |
7 |
| {{% /flex-content %}} |
|
| {{< /flex >}} |
|
{{% note %}}
The examples below use the example data variable.
{{% /note %}}
Calculate the running total of values
data
|> cumulativeSum()
Use cumulativeSum() with aggregateWindow()
[aggregateWindow()](/{{< latest "flux" >}}/stdlib/universe/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.
aggregateWindow() expects an aggregate function that returns a single row for each time window.
To use cumulativeSum() with aggregateWindow, use sum in aggregateWindow(),
then calculate the running total of the aggregate values with cumulativeSum().
data
|> aggregateWindow(every: 5m, fn: sum)
|> cumulativeSum()