Work with geo-temporal data

See the equivalent InfluxDB v2 documentation: Work with geo-temporal data.

Use the Flux Geo package to filter geo-temporal data and group by geographic location or track.

The Geo package is experimental and subject to change at any time. By using it, you agree to the risks of experimental functions.

To work with geo-temporal data:

  1. Import the experimental/geo package.

    import "experimental/geo"
  2. Load geo-temporal data. See below for sample geo-temporal data.

  3. Do one or more of the following:

Sample data

Many of the examples in this section use a sampleGeoData variable that represents a sample set of geo-temporal data. The Bird Migration Sample Data available on GitHub provides sample geo-temporal data that meets the requirements of the Flux Geo package.

Load annotated CSV sample data

Use the experimental csv.from() function to load the sample bird migration annotated CSV data from GitHub:

import `experimental/csv`

sampleGeoData = csv.from(
  url: ""

csv.from(url: ...) downloads sample data each time you execute the query (~1.3 MB). If bandwidth is a concern, use the to() function to write the data to a bucket, and then query the bucket with from().

Write sample data to InfluxDB with line protocol

Use curl and the influx write command to write bird migration line protocol to InfluxDB. Replace db/rp with your destination bucket:

curl --output ./tmp-data
influx write -b db/rp @./tmp-data
rm -f ./tmp-data

Use Flux to query the bird migration data and assign it to the sampleGeoData variable:

sampleGeoData = from(bucket: "db/rp")
    |> range(start: 2019-01-01T00:00:00Z, stop: 2019-12-31T23:59:59Z)
    |> filter(fn: (r) => r._measurement == "migration")

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