Documentation

Miscellaneous SQL functions

The InfluxDB SQL implementation supports the following miscellaneous functions for performing a variety of operations:

arrow_cast

Casts a value to a specific Arrow data type.

arrow_cast(expression, datatype)

Arguments

  • expression: Expression to cast. Can be a constant, column, or function, and any combination of arithmetic or string operators.
  • datatype: Arrow data type to cast to.

View arrow_cast query example

arrow_typeof

Returns the underlying Arrow data type of the the expression:

arrow_typeof(expression)
Arguments
  • expression: Expression to evaluate. Can be a constant, column, or function, and any combination of arithmetic or string operators.

View arrow_typeof query example

interpolate

Fills null values in a specified aggregated column by interpolating values from existing values. Must be used with date_bin_gapfill.

interpolate(aggregate_expression)
Arguments
  • aggregate_expression: Aggregate operation on a specified expression. The operation can use any aggregate function. The expression can be a constant, column, or function, and any combination of arithmetic operators supported by the aggregate function.

date_bin_gapfill, locf

View interpolate query example

locf

Fills null values in a specified aggregated column by carrying the last observed value forward. Must be used with date_bin_gapfill.

LOCF is an initialism of “last observation carried forward.”

locf(aggregate_expression)
Arguments
  • aggregate_expression: Aggregate operation on a specified expression. The operation can use any aggregate function. The expression can be a constant, column, or function, and any combination of arithmetic operators supported by the aggregate function.

date_bin_gapfill, interpolate

View locf query example


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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.

Flux is going into maintenance mode and will not be supported in InfluxDB 3.0. This was a decision based on the broad demand for SQL and the continued growth and adoption of InfluxQL. We are continuing to support Flux for users in 1.x and 2.x so you can continue using it with no changes to your code. If you are interested in transitioning to InfluxDB 3.0 and want to future-proof your code, we suggest using InfluxQL.

For information about the future of Flux, see the following:

InfluxDB Cloud Serverless