Documentation

Manipulate timestamps with Flux

This page documents an earlier version of InfluxDB OSS. InfluxDB OSS v2 is the latest stable version. See the InfluxDB v2 documentation.

Every point stored in InfluxDB has an associated timestamp. Use Flux to process and manipulate timestamps to suit your needs.

If you’re just getting started with Flux queries, check out the following:

Convert timestamp format

Unix nanosecond to RFC3339

Use the time() function to convert a Unix nanosecond timestamp to an RFC3339 timestamp.

time(v: 1568808000000000000)
// Returns 2019-09-18T12:00:00.000000000Z
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RFC3339 to Unix nanosecond

Use the uint() function to convert an RFC3339 timestamp to a Unix nanosecond timestamp.

uint(v: 2019-09-18T12:00:00.000000000Z)
// Returns 1568808000000000000
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Calculate the duration between two timestamps

Flux doesn’t support mathematical operations using time type values. To calculate the duration between two timestamps:

  1. Use the uint() function to convert each timestamp to a Unix nanosecond timestamp.
  2. Subtract one Unix nanosecond timestamp from the other.
  3. Use the duration() function to convert the result into a duration.
time1 = uint(v: 2019-09-17T21:12:05Z)
time2 = uint(v: 2019-09-18T22:16:35Z)

duration(v: time2 - time1)
// Returns 25h4m30s
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Flux doesn’t support duration column types. To store a duration in a column, use the string() function to convert the duration to a string.

Retrieve the current time

Current UTC time

Use the now() function to return the current UTC time in RFC3339 format.

now()
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now() is cached at runtime, so all instances of now() in a Flux script return the same value.

Current system time

Import the system package and use the system.time() function to return the current system time of the host machine in RFC3339 format.

import "system"

system.time()
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system.time() returns the time it is executed, so each instance of system.time() in a Flux script returns a unique value.

Normalize irregular timestamps

To normalize irregular timestamps, truncate all _time values to a specified unit with the truncateTimeColumn() function. This is useful in join() and pivot() operations where points should align by time, but timestamps vary slightly.

data
  |> truncateTimeColumn(unit: 1m)
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Input:

_time_value
2020-01-01T00:00:49Z2.0
2020-01-01T00:01:01Z1.9
2020-01-01T00:03:22Z1.8
2020-01-01T00:04:04Z1.9
2020-01-01T00:05:38Z2.1

Output:

_time_value
2020-01-01T00:00:00Z2.0
2020-01-01T00:01:00Z1.9
2020-01-01T00:03:00Z1.8
2020-01-01T00:04:00Z1.9
2020-01-01T00:05:00Z2.1

Use timestamps and durations together

Add a duration to a timestamp

The experimental.addDuration() function adds a duration to a specified time and returns the resulting time.

By using experimental.addDuration(), you accept the risks of experimental functions.

import "experimental"

experimental.addDuration(
  d: 6h,
  to: 2019-09-16T12:00:00Z,
)

// Returns 2019-09-16T18:00:00.000000000Z
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Subtract a duration from a timestamp

The experimental.subDuration() function subtracts a duration from a specified time and returns the resulting time.

By using experimental.subDuration(), you accept the risks of experimental functions.

import "experimental"

experimental.subDuration(
  d: 6h,
  from: 2019-09-16T12:00:00Z,
)

// Returns 2019-09-16T06:00:00.000000000Z
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The future of Flux

Flux is going into maintenance mode. You can continue using it as you currently are without any changes to your code.

Read more

InfluxDB 3 Core and Enterprise are now in Beta

InfluxDB 3 Core and Enterprise are now available for beta testing, available under MIT or Apache 2 license.

InfluxDB 3 Core is a high-speed, recent-data engine that collects and processes data in real-time, while persisting it to local disk or object storage. InfluxDB 3 Enterprise is a commercial product that builds on Core’s foundation, adding high availability, read replicas, enhanced security, and data compaction for faster queries. A free tier of InfluxDB 3 Enterprise will also be available for at-home, non-commercial use for hobbyists to get the full historical time series database set of capabilities.

For more information, check out: