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Submission: On March 16 via api (March 16th 2022, 8:54:01 pm UTC) from SE — Scanned from DE

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USING THE NEW FLUX “TYPES” PACKAGE

By Sean Brickley / March 7, 2022 March 6, 2022 / Community, Developer, Flux,
Tutorial / Leave a Comment
3 minutes

As a strictly typed language, Flux protects you from a lot of potential runtime
failures. However, if you don’t know the column types on the data you’re
querying, you might encounter some annoying errors.

Suppose you have a bucket that receives regular writes from multiple different
streams, and you want to write a task to downsample a measurement from that
bucket into another bucket. If you know ahead of time that, for example, the
_value column will always be a numeric type, you could run the following task
without any problems:

option task = {name: "write-agg", every: 30m, offset: 1s}

from(bucket: "test-bucket")
       |> range(start: -30m)
       |> filter(fn: (r) => r._measurement == "logs")
       |> aggregateWindow(fn: mean, every: 5m)
       |> to(bucket: "test-downsample")
Copy

But if you don’t know the schema of the data before you query it, you could run
into trouble. It’s possible for this query to fail if, for instance,
_value turns out to be a string instead of a number.



Until now, there has not been a one-size-fits-all solution to this problem. A
filter on _field could do the trick if you know the labels you’re looking for,
but maybe you don’t know those details, or maybe the list of labels you need to
include or exclude is too long to comfortably fit in a filter predicate.

Enter the types package. This package introduces the isType function, which
makes filtering on column types much easier. We can use it to fix our original
query by importing the types package and adding a new filter that checks the
type of r._value.

import "types"

option task = {name: "write-agg", every: 30m, offset: 1s}

from(bucket: "test-bucket")
       |> range(start: -30m)
       |> filter(fn: (r) => r._measurement == "logs")
       |> filter(fn: (r) => types.isType(v: r._value, type: "float"))
       |> aggregateWindow(fn: mean, every: 5m)
       |> to(bucket: "test-downsample")
Copy

Now we can be sure that any data piped into aggregateWindow has a _value column
of type float, and thus avoid any potential type errors. Sure enough, our task
succeeds and successfully writes the downsampled data to our new bucket:



We can also do more complex filtering using isType. Let’s imagine that the logs
measurement we’re reading from the task above has fields with many different
types. We want to aggregate all of them, but we know that some aggregates won’t
work for every type. We can use isType to decide which aggregate function to use
based on the type of data we find.

import "types"

option task = {name: "write-agg", every: 30m, offset: 1s}

from(bucket: "test-bucket")
       |> range(start: -30m)
       |> filter(fn: (r) => r._measurement == "logs")
       |> filter(fn: (r) => {
                 return types.isType(v: r._value, type: "float")
                         or types.isType(v: r._value, type: "int")
                         or types.isType(v: r._value, type: "uint")
       })	
       |> aggregateWindow(fn: mean, every: 5m)
       |> to(bucket: "test-downsample")

from(bucket: "test-bucket")
       |> range(start: -30m)
       |> filter(fn: (r) => r._measurement == "logs")
       |> filter(fn: (r) => {
                return types.isType(v: r._value, type: "string")
                        or types.isType(v: r._value, type: "bool")
       })
      |> aggregateWindow(fn: last, every: 5m)
      |> to(bucket: "test-downsample")
Copy

This new package is included in the latest version of Flux, and is available to
all cloud users. We encourage you to test it out and let us know what you think!

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www.influxdata.com Open in urlscan Pro 2606:4700:10::ac43:29d9 Public Scan

Form analysis 5 forms found in the DOM

GET https://www.influxdata.com/search/r/

GET https://www.influxdata.com/search/r/

POST https://www.influxdata.com/wp-comments-post.php

Text Content

www.influxdata.com Open in urlscan Pro
2606:4700:10::ac43:29d9 Public Scan

Form analysis
5 forms found in the DOM