This is archived documentation for InfluxData product versions that are no longer maintained. For newer documentation, see the latest InfluxData documentation.
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.
Index
Properties
Chaining Methods
- Alert
- Bottom
- Combine
- Count
- CumulativeSum
- Deadman
- Default
- Delete
- Derivative
- Difference
- Distinct
- Elapsed
- Eval
- First
- Flatten
- GroupBy
- HoltWinters
- HoltWintersWithFit
- HttpOut
- InfluxDBOut
- Join
- K8sAutoscale
- Last
- Log
- Max
- Mean
- Median
- Min
- Mode
- MovingAverage
- Percentile
- Sample
- Shift
- Spread
- Stats
- Stddev
- Sum
- Top
- Union
- Where
- Window
Properties
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.
Align
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()
Every
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
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
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()
Period
The period, or length in time, of the window.
node.period(value time.Duration)
PeriodCount
PeriodCount is the number of points per window.
node.periodCount(value int64)
Chaining Methods
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.
Alert
Create an alert node, which can trigger alerts.
node|alert()
Returns: AlertNode
Bottom
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
Combine this node with itself. The data is combined on timestamp.
node|combine(expressions ...ast.LambdaNode)
Returns: CombineNode
Count
Count the number of points.
node|count(field string)
Returns: InfluxQLNode
CumulativeSum
Compute a cumulative sum of each point that is received. A point is emitted for every point collected.
node|cumulativeSum(field string)
Returns: InfluxQLNode
Deadman
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
Default
Create a node that can set defaults for missing tags or fields.
node|default()
Returns: DefaultNode
Delete
Create a node that can delete tags or fields.
node|delete()
Returns: DeleteNode
Derivative
Create a new node that computes the derivative of adjacent points.
node|derivative(field string)
Returns: DerivativeNode
Difference
Compute the difference between points independent of elapsed time.
node|difference(field string)
Returns: InfluxQLNode
Distinct
Produce batch of only the distinct points.
node|distinct(field string)
Returns: InfluxQLNode
Elapsed
Compute the elapsed time between points
node|elapsed(field string, unit time.Duration)
Returns: InfluxQLNode
Eval
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
First
Select the first point.
node|first(field string)
Returns: InfluxQLNode
Flatten
Flatten points with similar times into a single point.
node|flatten()
Returns: FlattenNode
GroupBy
Group the data by a set of tags.
Can pass literal * to group by all dimensions. Example:
|groupBy(*)
node|groupBy(tag ...interface{})
Returns: GroupByNode
HoltWinters
Compute the holt-winters forecast of a data set.
node|holtWinters(field string, h int64, m int64, interval time.Duration)
Returns: InfluxQLNode
HoltWintersWithFit
Compute the 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
HttpOut
Create an HTTP output node that caches the most recent data it has received.
The cached data is 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
InfluxDBOut
Create an influxdb output node that will store the incoming data into InfluxDB.
node|influxDBOut()
Returns: InfluxDBOutNode
Join
Join this node with other nodes. The data is joined on timestamp.
node|join(others ...Node)
Returns: JoinNode
K8sAutoscale
Create a node that can trigger autoscale events for a kubernetes cluster.
node|k8sAutoscale()
Returns: K8sAutoscaleNode
Last
Select the last point.
node|last(field string)
Returns: InfluxQLNode
Log
Create a node that logs all data it receives.
node|log()
Returns: LogNode
Max
Select the maximum point.
node|max(field string)
Returns: InfluxQLNode
Mean
Compute the mean of the data.
node|mean(field string)
Returns: InfluxQLNode
Median
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
Min
Select the minimum point.
node|min(field string)
Returns: InfluxQLNode
Mode
Compute the mode of the data.
node|mode(field string)
Returns: InfluxQLNode
MovingAverage
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
Percentile
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
Sample
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
Shift
Create a new node that shifts the incoming points or batches in time.
node|shift(shift time.Duration)
Returns: ShiftNode
Spread
Compute the difference between min
and max
points.
node|spread(field string)
Returns: InfluxQLNode
Stats
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
Stddev
Compute the standard deviation.
node|stddev(field string)
Returns: InfluxQLNode
Sum
Compute the sum of all values.
node|sum(field string)
Returns: InfluxQLNode
Top
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
Union
Perform the union of this node and all other given nodes.
node|union(node ...Node)
Returns: UnionNode
Where
Create a new node that filters the data stream by a given expression.
node|where(expression ast.LambdaNode)
Returns: WhereNode
Window
Create a new node that windows the stream by time.
NOTE: Window can only be applied to stream edges.
node|window()
Returns: WindowNode