A `window`

node caches data within a moving time range. The `period`

property of `window`

defines the time range covered by `window`

.

The `every`

property of `window`

defines the frequency at which the window is emitted to the next node in the pipeline.

The `align`

property of `window`

defines how to align the window edges. (By default, the edges are defined relative to the first data point the `window`

node receives.)

Example:

stream |window() .period(10m) .every(5m) |httpOut('recent')

his example emits the last `10 minute`

period every `5 minutes`

to the pipeline's `httpOut`

node. Because `every`

is less than `period`

, each time the window is emitted it contains `5 minutes`

of new data and `5 minutes`

of the previous period's data.

NOTE: Because no `align`

property is defined, the `window`

edge is defined relative to the first data point.

- Alert
- Bottom
- Combine
- Count
- CumulativeSum
- Deadman
- Default
- Delete
- Derivative
- Difference
- Distinct
- Elapsed
- Eval
- First
- Flatten
- GroupBy
- HoltWinters
- HoltWintersWithFit
- HttpOut
- HttpPost
- InfluxDBOut
- Join
- K8sAutoscale
- KapacitorLoopback
- Last
- Log
- Max
- Mean
- Median
- Min
- Mode
- MovingAverage
- Percentile
- Sample
- Shift
- Spread
- StateCount
- StateDuration
- Stats
- Stddev
- Sum
- Top
- Union
- Where
- Window

Property methods modify state on the calling node. They do not add another node to the pipeline, and always return a reference to the calling node. Property methods are marked using the `.`

operator.

If the `align`

property is not used to modify the `window`

node, then the window alignment is assumed to start at the time of the first data point it receives. If `align`

property is set, the window time edges will be truncated to the `every`

property (For example, if a data point's time is 12:06 and the `every`

property is `5m`

then the data point's window will range from 12:05 to 12:10).

node.align()

How often the current window is emitted into the pipeline. If equal to zero, then every new point will emit the current window.

node.every(value time.Duration)

EveryCount determines how often the window is emitted based on the count of points. A value of 1 means that every new point will emit the window.

node.everyCount(value int64)

FillPeriod instructs the WindowNode to wait till the period has elapsed before emitting the first batch. This only applies if the period is greater than the every value.

node.fillPeriod()

The period, or length in time, of the window.

node.period(value time.Duration)

PeriodCount is the number of points per window.

node.periodCount(value int64)

Chaining methods create a new node in the pipeline as a child of the calling node. They do not modify the calling node. Chaining methods are marked using the `|`

operator.

Create an alert node, which can trigger alerts.

node|alert()

Returns: AlertNode

Select the bottom `num`

points for `field`

and sort by any extra tags or fields.

node|bottom(num int64, field string, fieldsAndTags ...string)

Returns: InfluxQLNode

Combine this node with itself. The data are combined on timestamp.

node|combine(expressions ...ast.LambdaNode)

Returns: CombineNode

Count the number of points.

node|count(field string)

Returns: InfluxQLNode

Compute a cumulative sum of each point that is received. A point is emitted for every point collected.

node|cumulativeSum(field string)

Returns: InfluxQLNode

Helper function for creating an alert on low throughput, a.k.a. deadman's switch.

- Threshold – trigger alert if throughput drops below threshold in points/interval.
- Interval – how often to check the throughput.
- Expressions – optional list of expressions to also evaluate. Useful for time of day alerting.

Example:

var data = stream |from()... // Trigger critical alert if the throughput drops below 100 points per 10s and checked every 10s. data |deadman(100.0, 10s) //Do normal processing of data data...

The above is equivalent to this Example:

var data = stream |from()... // Trigger critical alert if the throughput drops below 100 points per 10s and checked every 10s. data |stats(10s) .align() |derivative('emitted') .unit(10s) .nonNegative() |alert() .id('node \'stream0\' in task \'{{ .TaskName }}\'') .message('{{ .ID }} is {{ if eq .Level "OK" }}alive{{ else }}dead{{ end }}: {{ index .Fields "emitted" | printf "%0.3f" }} points/10s.') .crit(lambda: "emitted" <= 100.0) //Do normal processing of data data...

The `id`

and `message`

alert properties can be configured globally via the 'deadman' configuration section.

Since the AlertNode is the last piece it can be further modified as usual. Example:

var data = stream |from()... // Trigger critical alert if the throughput drops below 100 points per 10s and checked every 10s. data |deadman(100.0, 10s) .slack() .channel('#dead_tasks') //Do normal processing of data data...

You can specify additional lambda expressions to further constrain when the deadman's switch is triggered. Example:

var data = stream |from()... // Trigger critical alert if the throughput drops below 100 points per 10s and checked every 10s. // Only trigger the alert if the time of day is between 8am-5pm. data |deadman(100.0, 10s, lambda: hour("time") >= 8 AND hour("time") <= 17) //Do normal processing of data data...

node|deadman(threshold float64, interval time.Duration, expr ...ast.LambdaNode)

Returns: AlertNode

Create a node that can set defaults for missing tags or fields.

node|default()

Returns: DefaultNode

Create a node that can delete tags or fields.

node|delete()

Returns: DeleteNode

Create a new node that computes the derivative of adjacent points.

node|derivative(field string)

Returns: DerivativeNode

Compute the difference between points independent of elapsed time.

node|difference(field string)

Returns: InfluxQLNode

Produce batch of only the distinct points.

node|distinct(field string)

Returns: InfluxQLNode

Compute the elapsed time between points

node|elapsed(field string, unit time.Duration)

Returns: InfluxQLNode

Create an eval node that will evaluate the given transformation function to each data point. A list of expressions may be provided and will be evaluated in the order they are given. The results are available to later expressions.

node|eval(expressions ...ast.LambdaNode)

Returns: EvalNode

Select the first point.

node|first(field string)

Returns: InfluxQLNode

Flatten points with similar times into a single point.

node|flatten()

Returns: FlattenNode

Group the data by a set of tags.

Can pass literal * to group by all dimensions. Example:

|groupBy(*)

node|groupBy(tag ...interface{})

Returns: GroupByNode

Compute the holt-winters (https://docs.influxdata.com/influxdb/latest/query_language/functions/#holt-winters) forecast of a data set.

node|holtWinters(field string, h int64, m int64, interval time.Duration)

Returns: InfluxQLNode

Compute the holt-winters (https://docs.influxdata.com/influxdb/latest/query_language/functions/#holt-winters) forecast of a data set. This method also outputs all the points used to fit the data in addition to the forecasted data.

node|holtWintersWithFit(field string, h int64, m int64, interval time.Duration)

Returns: InfluxQLNode

Create an HTTP output node that caches the most recent data it has received. The cached data are available at the given endpoint. The endpoint is the relative path from the API endpoint of the running task. For example, if the task endpoint is at `/kapacitor/v1/tasks/<task_id>`

and endpoint is `top10`

, then the data can be requested from `/kapacitor/v1/tasks/<task_id>/top10`

.

node|httpOut(endpoint string)

Returns: HTTPOutNode

Creates an HTTP Post node that POSTS received data to the provided HTTP endpoint. HttpPost expects 0 or 1 arguments. If 0 arguments are provided, you must specify an endpoint property method.

node|httpPost(url ...string)

Returns: HTTPPostNode

Create an influxdb output node that will store the incoming data into InfluxDB.

node|influxDBOut()

Returns: InfluxDBOutNode

Join this node with other nodes. The data are joined on timestamp.

node|join(others ...Node)

Returns: JoinNode

Create a node that can trigger autoscale events for a kubernetes cluster.

node|k8sAutoscale()

Returns: K8sAutoscaleNode

Create an kapacitor loopback node that will send data back into Kapacitor as a stream.

node|kapacitorLoopback()

Returns: KapacitorLoopbackNode

Select the last point.

node|last(field string)

Returns: InfluxQLNode

Create a node that logs all data it receives.

node|log()

Returns: LogNode

Select the maximum point.

node|max(field string)

Returns: InfluxQLNode

Compute the mean of the data.

node|mean(field string)

Returns: InfluxQLNode

Compute the median of the data. Note, this method is not a selector, if you want the median point use `.percentile(field, 50.0)`

.

node|median(field string)

Returns: InfluxQLNode

Select the minimum point.

node|min(field string)

Returns: InfluxQLNode

Compute the mode of the data.

node|mode(field string)

Returns: InfluxQLNode

Compute a moving average of the last window points. No points are emitted until the window is full.

node|movingAverage(field string, window int64)

Returns: InfluxQLNode

Select a point at the given percentile. This is a selector function, no interpolation between points is performed.

node|percentile(field string, percentile float64)

Returns: InfluxQLNode

Create a new node that samples the incoming points or batches.

One point will be emitted every count or duration specified.

node|sample(rate interface{})

Returns: SampleNode

Create a new node that shifts the incoming points or batches in time.

node|shift(shift time.Duration)

Returns: ShiftNode

Compute the difference between `min`

and `max`

points.

node|spread(field string)

Returns: InfluxQLNode

Create a node that tracks number of consecutive points in a given state.

node|stateCount(expression ast.LambdaNode)

Returns: StateCountNode

Create a node that tracks duration in a given state.

node|stateDuration(expression ast.LambdaNode)

Returns: StateDurationNode

Create a new stream of data that contains the internal statistics of the node. The interval represents how often to emit the statistics based on real time. This means the interval time is independent of the times of the data points the source node is receiving.

node|stats(interval time.Duration)

Returns: StatsNode

Compute the standard deviation.

node|stddev(field string)

Returns: InfluxQLNode

Compute the sum of all values.

node|sum(field string)

Returns: InfluxQLNode

Select the top `num`

points for `field`

and sort by any extra tags or fields.

node|top(num int64, field string, fieldsAndTags ...string)

Returns: InfluxQLNode

Perform the union of this node and all other given nodes.

node|union(node ...Node)

Returns: UnionNode

Create a new node that filters the data stream by a given expression.

node|where(expression ast.LambdaNode)

Returns: WhereNode

Create a new node that windows the stream by time.

NOTE: Window can only be applied to stream edges.

node|window()

Returns: WindowNode

© 2015 InfluxData, Inc.

Licensed under the MIT license.

https://docs.influxdata.com/kapacitor/v1.3/nodes/window_node/