This is archived documentation for InfluxData product versions that are no longer maintained. For newer documentation, see the latest InfluxData documentation.

Joins the data from any number of nodes. As each data point is received from a parent node it is paired with the next data points from the other parent nodes with a matching timestamp. Each parent node contributes at most one point to each joined point. A tolerance can be supplied to join points that do not have perfectly aligned timestamps. Any points that fall within the tolerance are joined on the timestamp. If multiple points fall within the same tolerance window than they are joined in the order they arrive.

Aliases are used to prefix all fields from the respective nodes.

The join can be an inner or outer join, see the JoinNode.Fill property.


    var errors = stream
    var requests = stream
    // Join the errors and requests streams
            // Provide prefix names for the fields of the data points.
            .as('errors', 'requests')
            // points that are within 1 second are considered the same time.
            // fill missing values with 0, implies outer join.
            // name the resulting stream
        // Both the "value" fields from each parent have been prefixed
        // with the respective names 'errors' and 'requests'.
        .eval(lambda: "errors.value" / "requests.value"))

In the above example the errors and requests streams are joined and then transformed to calculate a combined field.


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.


Prefix names for all fields from the respective nodes. Each field from the parent nodes will be prefixed with the provided name and a '.'. See the example above.

The names cannot have a dot '.' character. ...string)


Fill the data. The fill option implies the type of join: inner or full outer Options are:

  • none - (default) skip rows where a point is missing, inner join.
  • null - fill missing points with null, full outer join.
  • Any numerical value - fill fields with given value, full outer join.

    node.fill(value interface{})


The name of this new joined data stream. If empty the name of the left parent is used.

node.streamName(value string)


The maximum duration of time that two incoming points can be apart and still be considered to be equal in time. The joined data point's time will be rounded to the nearest multiple of the tolerance duration.

node.tolerance(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.


Create an alert node, which can trigger alerts.


Returns: AlertNode


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

node.derivative(field string)

Returns: DerivativeNode


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 and results of previous expressions are made available to later expressions.

node.eval(expressions ...tick.Node)

Returns: EvalNode


Group the data by a set of tags.

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

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

Returns: GroupByNode


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 "/api/v1/task/<task_name>" and endpoint is "top10", then the data can be requested from "/api/v1/task/<task_name>/top10".

node.httpOut(endpoint string)

Returns: HTTPOutNode


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


Returns: InfluxDBOutNode


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

node.join(others ...Node)

Returns: JoinNode


Perform a map-reduce operation on the data. The built-in functions under influxql provide the selection,aggregation, and transformation functions from the InfluxQL language.

MapReduce may be applied to either a batch or a stream edge. In the case of a batch each batch is passed to the mapper idependently. In the case of a stream all incoming data points that have the exact same time are combined into a batch and sent to the mapper.

node.mapReduce(mr MapReduceInfo)

Returns: ReduceNode


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


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 tick.Node)

Returns: WhereNode


Create a new node that windows the stream by time.

NOTE: Window can only be applied to stream edges.


Returns: WindowNode