Documentation

Work with arrays

An array type is an ordered sequence of values of the same type.

Array syntax

An array literal contains a sequence of values (also known as elements) enclosed in square brackets ([]). Values are comma-separated and must be the same type.

Example arrays
["1st", "2nd", "3rd"]

[1.23, 4.56, 7.89]

[10, 25, -15]

Reference values in an array

Use bracket notation to reference reference a value in an array. Flux arrays use zero-based indexing. Provide the index of the value to reference.

arr = ["1st", "2nd", "3rd"]

arr[0]
// Returns 1st

arr[2]
// Returns 3rd

Operate on arrays

Iterate over an array

  1. Import the experimental/array package.
  2. Use array.map to iterate over elements in an array, apply a function to each element, and then return a new array.
import "experimental/array"

a = [
    {fname: "John", lname: "Doe", age: 42},
    {fname: "Jane", lname: "Doe", age: 40},
    {fname: "Jacob", lname: "Dozer", age: 21},
]

a |> array.map(fn: (x) => ({statement: "${x.fname} ${x.lname} is ${x.age} years old."}))

// Returns
// [
//     {statement: "John Doe is 42 years old."},
//     {statement: "Jane Doe is 40 years old."},
//     {statement: "Jacob Dozer is 21 years old."}
// ]

Check if a value exists in an array

Use the contains function to check if a value exists in an array.

names = ["John", "Jane", "Joe", "Sam"]

contains(value: "Joe", set: names)
// Returns true

Get the length of an array

Use the length function to get the length of an array (number of elements in the array).

names = ["John", "Jane", "Joe", "Sam"]

length(arr: names)
// Returns 4

Create a stream of tables from an array

  1. Import the array package.
  2. Use array.from() to return a stream of tables. The input array must be an array of records. Each key-value pair in the record represents a column and its value.
import "array"

arr = [
    {fname: "John", lname: "Doe", age: "37"},
    {fname: "Jane", lname: "Doe", age: "32"},
    {fname: "Jack", lname: "Smith", age: "56"},
]

array.from(rows: arr)
Output
fname lname age
John Doe 37
Jane Doe 32
Jack Smith 56

Compare arrays

Use the == comparison operator to check if two arrays are equal. Equality is based on values, their type, and order.

[1,2,3,4] == [1,3,2,4]
// Returns false

[12300.0, 34500.0] == [float(v: "1.23e+04"), float(v: "3.45e+04")]
// Returns true

Filter an array

  1. Import the experimental/array package.
  2. Use array.filter to iterate over and evaluate elements in an array with a predicate function and then return a new array with only elements that match the predicate.
import "experimental/array"

a = [1, 2, 3, 4, 5]

a |> array.filter(fn: (x) => x >= 3)
// Returns [3, 4, 5]

Merge two arrays

  1. Import the experimental/array package.
  2. Use array.concat to merge two arrays.
import "experimental/array"

a = [1, 2, 3]
b = [4, 5, 6]

a |> array.concat(v: b)
// Returns [1, 2, 3, 4, 5, 6]

Return the string representation of an array

Use display() to return Flux literal representation of an array as a string.

arr = [1, 2, 3]

display(v: arr)

// Returns "[1, 2, 3]"

Include the string representation of an array in a table

Use display() to return Flux literal representation of an array as a string and include it as a column value.

import "sampledata"

sampledata.string()
    |> map(fn: (r) => ({_time: r._time, exampleArray: display(v: [r.tag, r._value])}))

Output

_time (time) exampleArray (string)
2021-01-01T00:00:00Z [t1, smpl_g9qczs]
2021-01-01T00:00:10Z [t1, smpl_0mgv9n]
2021-01-01T00:00:20Z [t1, smpl_phw664]
2021-01-01T00:00:30Z [t1, smpl_guvzy4]
2021-01-01T00:00:40Z [t1, smpl_5v3cce]
2021-01-01T00:00:50Z [t1, smpl_s9fmgy]
2021-01-01T00:00:00Z [t2, smpl_b5eida]
2021-01-01T00:00:10Z [t2, smpl_eu4oxp]
2021-01-01T00:00:20Z [t2, smpl_5g7tz4]
2021-01-01T00:00:30Z [t2, smpl_sox1ut]
2021-01-01T00:00:40Z [t2, smpl_wfm757]
2021-01-01T00:00:50Z [t2, smpl_dtn2bv]

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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: