QueryNode

Constructor

Chaining Method Description
query ( q string) The query to execute. Must not contain a time condition in the WHERE clause or contain a GROUP BY clause. The time conditions are added dynamically according to the period, offset and schedule. The GROUP BY clause is added dynamically according to the dimensions passed to the groupBy method.

Property Methods

Setters Description
align ( ) Align start and stop times for quiries with even boundaries of the QueryNode.Every property. Does not apply if using the QueryNode.Cron property.
alignGroup ( ) Align the group by time intervals with the start time of the query
cluster ( value string) The name of a configured InfluxDB cluster. If empty the default cluster will be used.
cron ( value string) Define a schedule using a cron syntax.
every ( value time.Duration) How often to query InfluxDB.
fill ( value interface{}) Fill the data. Options are:
groupBy ( d ...interface{}) Group the data by a set of dimensions. Can specify one time dimension.
groupByMeasurement ( ) If set will include the measurement name in the group ID. Along with any other group by dimensions.
offset ( value time.Duration) How far back in time to query from the current time
period ( value time.Duration) The period or length of time that will be queried from InfluxDB

Chaining Methods

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



Description

A QueryNode defines a source and a schedule for processing batch data. The data is queried from an InfluxDB database and then passed into the data pipeline.

Example:

 batch
     |query('''
         SELECT mean("value")
         FROM "telegraf"."default".cpu_usage_idle
         WHERE "host" = 'serverA'
     ''')
         .period(1m)
         .every(20s)
         .groupBy(time(10s), 'cpu')
     ...

In the above example InfluxDB is queried every 20 seconds; the window of time returned spans 1 minute and is grouped into 10 second buckets.

^

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

Align start and stop times for quiries with even boundaries of the QueryNode.Every property. Does not apply if using the QueryNode.Cron property.

query.align()

^

AlignGroup

Align the group by time intervals with the start time of the query

query.alignGroup()

^

Cluster

The name of a configured InfluxDB cluster. If empty the default cluster will be used.

query.cluster(value string)

^

Cron

Define a schedule using a cron syntax.

The specific cron implementation is documented here: https://github.com/gorhill/cronexpr#implementation

The Cron property is mutually exclusive with the Every property.

query.cron(value string)

^

Every

How often to query InfluxDB.

The Every property is mutually exclusive with the Cron property.

query.every(value time.Duration)

^

Fill

Fill the data. Options are:

  • Any numerical value
  • null - exhibits the same behavior as the default
  • previous - reports the value of the previous window
  • none - suppresses timestamps and values where the value is null
  • linear - reports the results of linear interpolation
query.fill(value interface{})

^

GroupBy

Group the data by a set of dimensions. Can specify one time dimension.

This property adds a GROUP BY clause to the query so all the normal behaviors when quering InfluxDB with a GROUP BY apply.

Use group by time when your period is longer than your group by time interval.

Example:

    batch
        |query(...)
            .period(1m)
            .every(1m)
            .groupBy(time(10s), 'tag1', 'tag2'))
            .align()

A group by time offset is also possible.

Example:

    batch
        |query(...)
            .period(1m)
            .every(1m)
            .groupBy(time(10s, -5s), 'tag1', 'tag2'))
            .align()
            .offset(5s)

It is recommended to use QueryNode.Align and QueryNode.Offset in conjunction with group by time dimensions so that the time bounds match up with the group by intervals. To automatically align the group by intervals to the start of the query time, use QueryNode.AlignGroup. This is useful in more complex situations, such as when the groupBy time period is longer than the query frequency.

Example:

    batch
        |query(...)
            .period(5m)
            .every(30s)
            .groupBy(time(1m), 'tag1', 'tag2')
            .align()
            .alignGroup()

For the above example, without QueryNode.AlignGroup, every other query issued by Kapacitor (at :30 past the minute) will align to :00 seconds instead of the desired :30 seconds, which would create 6 group by intervals instead of 5, the first and last of which would only have 30 seconds of data instead of a full minute. If the group by time offset (i.e. time(t, offset)) is used in conjunction with QueryNode.AlignGroup, the alignment will occur first, and will be offset the specified amount after.

NOTE: Since QueryNode.Offset is inherently a negative property the second “offset” argument to the “time” function is negative to match.

query.groupBy(d ...interface{})

^

GroupByMeasurement

If set will include the measurement name in the group ID. Along with any other group by dimensions.

Example:

 batch
      |query('SELECT sum("value") FROM "telegraf"."autogen"./process_.*/')
          .groupByMeasurement()
          .groupBy('host')

The above example selects data from several measurements matching `/process_.*/ and then each point is grouped by the host tag and measurement name. Thus keeping measurements in their own groups.

query.groupByMeasurement()

^

Offset

How far back in time to query from the current time

For example an Offest of 2 hours and an Every of 5m, Kapacitor will query InfluxDB every 5 minutes for the window of data 2 hours ago.

This applies to Cron schedules as well. If the cron specifies to run every Sunday at 1 AM and the Offset is 1 hour. Then at 1 AM on Sunday the data from 12 AM will be queried.

query.offset(value time.Duration)

^

Period

The period or length of time that will be queried from InfluxDB

query.period(value time.Duration)

^

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.

query|alert()

Returns: AlertNode

^

Bottom

Select the bottom num points for field and sort by any extra tags or fields.

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

Returns: InfluxQLNode

^

Combine

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

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

Returns: CombineNode

^

Count

Count the number of points.

query|count(field string)

Returns: InfluxQLNode

^

CumulativeSum

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

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

Returns: AlertNode

^

Default

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

query|default()

Returns: DefaultNode

^

Delete

Create a node that can delete tags or fields.

query|delete()

Returns: DeleteNode

^

Derivative

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

query|derivative(field string)

Returns: DerivativeNode

^

Difference

Compute the difference between points independent of elapsed time.

query|difference(field string)

Returns: InfluxQLNode

^

Distinct

Produce batch of only the distinct points.

query|distinct(field string)

Returns: InfluxQLNode

^

Elapsed

Compute the elapsed time between points

query|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.

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

Returns: EvalNode

^

First

Select the first point.

query|first(field string)

Returns: InfluxQLNode

^

Flatten

Flatten points with similar times into a single point.

query|flatten()

Returns: FlattenNode

^

HoltWinters

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

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

Returns: InfluxQLNode

^

HoltWintersWithFit

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.

query|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 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.

query|httpOut(endpoint string)

Returns: HTTPOutNode

^

HttpPost

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.

query|httpPost(url ...string)

Returns: HTTPPostNode

^

InfluxDBOut

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

query|influxDBOut()

Returns: InfluxDBOutNode

^

Join

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

query|join(others ...Node)

Returns: JoinNode

^

K8sAutoscale

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

query|k8sAutoscale()

Returns: K8sAutoscaleNode

^

KapacitorLoopback

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

query|kapacitorLoopback()

Returns: KapacitorLoopbackNode

^

Last

Select the last point.

query|last(field string)

Returns: InfluxQLNode

^

Log

Create a node that logs all data it receives.

query|log()

Returns: LogNode

^

Max

Select the maximum point.

query|max(field string)

Returns: InfluxQLNode

^

Mean

Compute the mean of the data.

query|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).

query|median(field string)

Returns: InfluxQLNode

^

Min

Select the minimum point.

query|min(field string)

Returns: InfluxQLNode

^

Mode

Compute the mode of the data.

query|mode(field string)

Returns: InfluxQLNode

^

MovingAverage

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

query|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.

query|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.

query|sample(rate interface{})

Returns: SampleNode

^

Shift

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

query|shift(shift time.Duration)

Returns: ShiftNode

^

Sideload

Create a node that can load data from external sources

query|sideload()

Returns: SideloadNode

^

Spread

Compute the difference between min and max points.

query|spread(field string)

Returns: InfluxQLNode

^

StateCount

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

query|stateCount(expression ast.LambdaNode)

Returns: StateCountNode

^

StateDuration

Create a node that tracks duration in a given state.

query|stateDuration(expression ast.LambdaNode)

Returns: StateDurationNode

^

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.

query|stats(interval time.Duration)

Returns: StatsNode

^

Stddev

Compute the standard deviation.

query|stddev(field string)

Returns: InfluxQLNode

^

Sum

Compute the sum of all values.

query|sum(field string)

Returns: InfluxQLNode

^

SwarmAutoscale

Create a node that can trigger autoscale events for a docker swarm cluster.

query|swarmAutoscale()

Returns: SwarmAutoscaleNode

^

Top

Select the top num points for field and sort by any extra tags or fields.

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

Returns: InfluxQLNode

^

Union

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

query|union(node ...Node)

Returns: UnionNode

^

Where

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

query|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.

query|window()

Returns: WindowNode

^

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