Regular expressions

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Regular expressions are a sequence of characters used to identify patterns in identifiers and string values. InfluxQL supports regular expressions in the following operations:

Identifying fields and tags to query in the SELECT clause.
Identifying measurements to query in the FROM clause.
Testing tag values and string field values in the WHERE clause.
Identifying tag keys to group by in the GROUP BY clause

Query performance

Regular expression comparisons are more computationally intensive than exact string comparisons. Queries with regular expressions are not as performant as those without.

Regular expression syntax

InfluxQL Regular expressions are surrounded by / characters and use the Go regular expression syntax.

/regular_expression/

Regular expression flags

Regular expression flags modify the pattern-matching behavior of the expression. InfluxQL supports the following regular expression flags:

Flag	Description
i	case-insensitive
m	multi-line mode: `^` and `$` match begin/end line in addition to begin/end text
s	let `.` match `\n`
U	ungreedy: swap meaning of `x` and `x?`, `x+` and `x+?`, etc.

Include regular expression flags at the beginning of your regular expression pattern enclosed in parentheses (()) and preceded by a question mark (?).

/(?iU)foo*/

Regular expression operators

InfluxQL provides the following regular expression operators that test if a string operand matches a regular expression:

=~: Returns true if the string matches the regular expression
!~: Returns true if the string does not match the regular expression

InfluxQL regular expression operators are used to test string column values in the WHERE clause.

Regular expression examples

The examples below use the following sample data sets:

Use a regular expression to specify field keys and tag keys in the SELECT clause

time	temp_avg	temp_max	temp_min
2020-01-01T00:00:00Z	52	66	44
2020-01-01T00:00:00Z	53	59	47
2020-01-01T00:00:00Z	50	57	44
2020-01-02T00:00:00Z	54	61	49
2020-01-02T00:00:00Z	51	60	44
2020-01-02T00:00:00Z	53	66	42
…	…	…	…

Use a regular expression to specify measurements in the FROM clause

time	temp	temp_avg	temp_max	temp_min
2020-01-01T00:00:00Z		52	66	44
2020-01-01T00:00:00Z		53	59	47
2020-01-01T00:00:00Z		50	57	44
2020-01-02T00:00:00Z		54	61	49
2020-01-02T00:00:00Z		51	60	44
2020-01-02T00:00:00Z		53	66	42
…	…	…	…	…

Use a regular expression to specify tag values in the WHERE clause

time	location	precip	temp_avg	temp_max	temp_min	wind_avg
2020-01-01T00:00:00Z	Concord	0	52	66	44	3.13
2020-01-01T00:00:00Z	Hayward	0	50	57	44	2.24
2020-01-02T00:00:00Z	Concord	0	53	66	42	3.13
2020-01-02T00:00:00Z	Hayward	0	51	60	44	3.8
2020-01-03T00:00:00Z	Concord	0	49	60	38	2.68
2020-01-03T00:00:00Z	Hayward	0	50	62	41	3.13
…	…	…	…	…	…	…

Use a regular expression to specify a tag with no value in the WHERE clause

time	co	hum	location	precip	room	temp	temp_avg	temp_max	temp_min	wind_avg
2022-01-01T08:00:00Z	0	35.9			Kitchen	21
2022-01-01T08:00:00Z	0	35.9			Living Room	21.1
2022-01-01T09:00:00Z	0	36.2			Kitchen	23
2022-01-01T09:00:00Z	0	35.9			Living Room	21.4
2022-01-01T10:00:00Z	0	36.1			Kitchen	22.7
2022-01-01T10:00:00Z	0	36			Living Room	21.8
…	…	…	…	…	…	…	…	…	…	…

Use a regular expression to specify tag keys in the GROUP BY clause

time	max
2021-10-24T00:00:00Z	4.53

time	max
2022-12-31T00:00:00Z	4.34

time	max
2021-10-24T00:00:00Z	4.02

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