## Summary

```
rawsum(<expression>[,metrics|sources|sourceTags|pointTags|<pointTagKey>])
```

Returns the raw sum of the set of time series described by the expression.
The results are computed from real reported data values only.
Use `sum()`

to include interpolated values.

## Parameters

Parameter | Description |
---|---|

expression | Expression describing the set of time series to be summed. |

metrics|sources|sourceTags|pointTags|<pointTagKey> | Optional 'group by' parameter for organizing the time series into subgroups and then returning a raw sum for each subgroup. Use one or more parameters to group by metric names, source names, source tag names, point tag names, values for a particular point tag key, or any combination of these items. Specify point tag keys by name. |

## Description

The `rawsum()`

aggregation function adds together the data values reported at each moment in time, across the time series that are represented by the expression.

By default, `rawsum()`

returns a single series of sums by aggregating data values across all time series. You can optionally group the time series based on one or more characteristics, and obtain a separate series of sums for each group.

A raw sum is computed only from real values reported at a given moment in time.
No interpolation is performed to fill in data gaps in any time series.
Use `sum()`

if you want the sums to include interpolated values wherever possible. Using `rawsum()`

instead of `sum()`

can significantly improve query performance.

### Grouping

Like all aggregation functions, `rawsum()`

returns a single series of results by default. You can include a ‘group by’ parameter to obtain separate raw sums for groups of time series that share common metric names, source names, source tags, point tags, or values for a particular point tag key.
The function returns a separate series of results corresponding to each group.

You can specify multiple ‘group by’ parameters to group the time series based on multiple characteristics. For example, `rawsum(ts("cpu.cpu*"), metrics, Customer)`

first groups by metric names, and then groups by the values of the `Customer`

point tag.

## Examples

The following chart for returns a single line that sums the load average for all time series.

You can **group by** point tag for each line. The following example groups the query above by environment.