This is archived documentation for InfluxData product versions that are no longer maintained. For newer documentation, see the latest InfluxData documentation.
A FromNode selects a subset of the data flowing through a StreamNode. The stream node allows you to select which portion of the stream you want to process.
Example:
stream
|from()
.database('mydb')
.retentionPolicy('myrp')
.measurement('mymeasurement')
.where(lambda: "host" =~ /logger\d+/)
|window()
...
The above example selects only data points from the database mydb
and retention policy myrp
and measurement mymeasurement
where
the tag host
matches the regex logger\d+
Index
Properties
Chaining Methods
- Alert
- Bottom
- Combine
- Count
- CumulativeSum
- Deadman
- Default
- Delete
- Derivative
- Difference
- Distinct
- Elapsed
- Eval
- First
- Flatten
- From
- 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
- 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.
Database
The database name. If empty any database will be used.
node.database(value string)
GroupBy
Group the data by a set of tags.
Can pass literal * to group by all dimensions. Example:
stream
|from()
.groupBy(*)
node.groupBy(tag ...interface{})
GroupByMeasurement
If set will include the measurement name in the group ID. Along with any other group by dimensions.
Example:
stream
|from()
.database('mydb')
.groupByMeasurement()
.groupBy('host')
The above example selects all measurements from the database 'mydb' and then each point is grouped by the host tag and measurement name. Thus keeping measurements in their own groups.
node.groupByMeasurement()
Measurement
The measurement name If empty any measurement will be used.
node.measurement(value string)
RetentionPolicy
The retention policy name If empty any retention policy will be used.
node.retentionPolicy(value string)
Round
Optional duration for rounding timestamps. Helpful to ensure data points land on specific boundaries Example:
stream
|from()
.measurement('mydata')
.round(1s)
All incoming data will be rounded to the nearest 1 second boundary.
node.round(value time.Duration)
Truncate
Optional duration for truncating timestamps. Helpful to ensure data points land on specific boundaries Example:
stream
|from()
.measurement('mydata')
.truncate(1s)
All incoming data will be truncated to 1 second resolution.
node.truncate(value time.Duration)
Where
Filter the current stream using the given expression. This expression is a Kapacitor expression. Kapacitor expressions are a superset of InfluxQL WHERE expressions. See the expression docs for more information.
Multiple calls to the Where method will AND
together each expression.
Example:
stream
|from()
.where(lambda: condition1)
.where(lambda: condition2)
The above is equivalent to this Example:
stream
|from()
.where(lambda: condition1 AND condition2)
NOTE: Becareful to always use |from
if you want multiple different streams.
Example:
var data = stream
|from()
.measurement('cpu')
var total = data
.where(lambda: "cpu" == 'cpu-total')
var others = data
.where(lambda: "cpu" != 'cpu-total')
The example above is equivalent to the example below, which is obviously not what was intended.
Example:
var data = stream
|from()
.measurement('cpu')
.where(lambda: "cpu" == 'cpu-total' AND "cpu" != 'cpu-total')
var total = data
var others = total
The example below will create two different streams each selecting a different subset of the original stream.
Example:
var data = stream
|from()
.measurement('cpu')
var total = stream
|from()
.measurement('cpu')
.where(lambda: "cpu" == 'cpu-total')
var others = stream
|from()
.measurement('cpu')
.where(lambda: "cpu" != 'cpu-total')
If empty then all data points are considered to match.
node.where(lambda ast.LambdaNode)
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
From
Creates a new stream node that can be further filtered using the Database, RetentionPolicy, Measurement and Where properties. From can be called multiple times to create multiple independent forks of the data stream.
Example:
// Select the 'cpu' measurement from just the database 'mydb'
// and retention policy 'myrp'.
var cpu = stream
|from()
.database('mydb')
.retentionPolicy('myrp')
.measurement('cpu')
// Select the 'load' measurement from any database and retention policy.
var load = stream
|from()
.measurement('load')
// Join cpu and load streams and do further processing.
cpu
|join(load)
.as('cpu', 'load')
...
node|from()
Returns: FromNode
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
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.
node|httpPost(url ...string)
Returns: HTTPPostNode
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
KapacitorLoopback
Create an kapacitor loopback node that will send data back into Kapacitor as a stream.
node|kapacitorLoopback()
Returns: KapacitorLoopbackNode
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
StateCount
Create a node that tracks number of consecutive points in a given state.
node|stateCount(expression ast.LambdaNode)
Returns: StateCountNode
StateDuration
Create a node that tracks duration in a given state.
node|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.
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
Window
Create a new node that windows the stream by time.
NOTE: Window can only be applied to stream edges.
node|window()
Returns: WindowNode