Sliding Window

Computes an aggregated value sliding over a single time series over time. E.g. with a configuration to sum 2 minute windows and a 5 values spaced at one minute intervals, values 1 and 2 are summed, then 2 and 3, then 3 and 4, etc. This can be used to smooth volatile time series.

Fields include:

Name	Data Type	Required	Description	Default	Example
aggregator	String	Required	The aggregation function to use on each window.	null	sum
windowSize	String	Required	A TSDB style duration for the window.	null	15m
infectiousNan	Boolean	Optional	Whether or not NaNs from the source data should infect each bucket when aggregating values. E.g. if one value out of 20 are NaN in a bucket and this is true, the bucket will return a NaN. If all values in a bucket are NaN then the result will be NaN regardless..	false	true

Note that interpolation is not required here. If a “window” is missing data, it’s simply skipped.

This node can also be used to compute a cumulative sum (or any accumulation) by setting the window size to the query width.

While this node will compute a basic moving average, see the Moving Average notes for a more configurable average computation, especially if you need to compute over a number of values instead of time.

Assume a config of aggregator=sum, window=30s and an input set:

Series	T0	T + 10s	T + 20s	T + 30s	T + 40s	T + 50s	T + 60s
TS1	1	3	2	1	4	2	5
TS2	1	2	N/A	2	1	1	3

The result would be:

Series	T0	T + 10s	T + 20s	T + 30s	T + 40s	T + 50s	T + 60s
TS1	1	4	6	6	7	7	11
TS2	1	3	3	4	3	4	5

Example:

{
    "start": "1h-ago",
    "executionGraph": [{
                    "id": "m1",
                    "type": "TimeSeriesDataSource",
                    "metric": {
                            "type": "MetricLiteral",
                            "metric": "sys.if.in"
                    }
            },
            {
                    "id": "ds1",
                    "type": "downsample",
                    "aggregator": "sum",
                    "interval": "1m",
                    "runAll": false,
                    "fill": true,
                    "interpolatorConfigs": [{
                            "dataType": "numeric",
                            "fillPolicy": "NAN",
                            "realFillPolicy": "NONE"
                    }],
                    "sources": ["m1"]
            },
            {
                    "id": "sw1",
                    "type": "SlidingWindow",
               "aggregator": "avg",
         "windowSize": "15m"
                    "sources": ["ds1"]
            }
    ]
}