CONVERTFROMUTC Function
Converts Datetime value to corresponding value of the specified time zone. Input can be a column of Datetime values, a literal Datetime value, or a function returning Datetime values.
input Datetime value is assumed to be in UTC time zone. Inputs with time zone offsets are invalid.
Specified time zone must be a string literal of one of the supported time zone values.
Wrangle vs. SQL: This function is part of Wrangle, a proprietary data transformation language. Wrangle is not SQL. For more information, see Wrangle Language.
Basic Usage
Column reference values:
convertfromutc(myUTCtimestamp,'US/Eastern')
Output: Returns the values of the myUTCtimestamp
converted to US Eastern time zone.
Syntax and Arguments
<span>convertfromutc</span><span>(date, 'enum-timezone')</span>
Argument | Required? | Data Type | Description |
---|---|---|---|
date | Y | datetime | Name of Datetime column, Datetime literal, or function returning a Datetime value. |
enum-timezone-string | Y | string | Case-sensitive string literal value corresponding to the target time zone. |
For more information on syntax standards, see Language Documentation Syntax Notes.
date
Name of a column containing Datetime values, a literal Datetime value, or a function returning Datetime values to convert.
提示
Use the DATEFORMAT function to wrap values into acceptable formats. See DATEFORMAT Function.
Values are assumed to be in UTC time zone format. Coordinated Universal Time is the primary standard time by which clocks are coordinated around the world.
UTC is also known as Greenwich Mean Time.
UTC does not change for daylight savings time.
For more information, see https://en.wikipedia.org/wiki/Coordinated_Universal_Time.
If an input value is invalid for Datetime data type, a null value is returned.
Column references with time zone offsets are invalid.
Missing values for this function in the source data result in missing values in the output.
Multiple columns and wildcards are not supported.
Usage Notes:
Required? | Data Type | Example Value |
---|---|---|
Yes | Datetime (column reference, function, or literal) | sourceTime |
enum-timezone-string
String literal value for the time zone to which to convert.
注意
These values are case-sensitive.
Example values:
'America/Puerto_Rico' 'US/Eastern' 'US/Central' 'US/Mountain' 'US/Pacific' 'US/Alaska' 'US/Hawaii'
Examples
提示
For additional examples, see Common Tasks.
Example - Time zone conversion
This example shows how you can use functions to convert Datetime values to different time zones.
Functions:
Item | Description |
---|---|
CONVERTFROMUTC Function | Converts Datetime value to corresponding value of the specified time zone. Input can be a column of Datetime values, a literal Datetime value, or a function returning Datetime values. |
CONVERTTOUTC Function | Converts Datetime value in specified time zone to corresponding value in UTC time zone. Input can be a column of Datetime values, a literal Datetime value, or a function returning Datetime values. |
CONVERTTIMEZONE Function | Converts Datetime value in specified time zone to corresponding value second specified time zone. Input can be a column of Datetime values, a literal Datetime value, or a function returning Datetime values. |
ISMISMATCHED Function | Tests whether a set of values is not valid for a specified data type. |
Source:
row | datetime |
---|---|
1 | 2020-03-15 |
2 | 2020-03-15 0:00:00 |
3 | 2020-03-15 +08:00 |
4 | 2020-03-15 1:02:03 |
5 | 2020-03-15 4:02:03 |
6 | 2020-03-15 8:02:03 |
7 | 2020-03-15 12:02:03 |
8 | 2020-03-15 16:02:03 |
9 | 2020-03-15 20:02:03 |
10 | 2020-03-15 23:02:03 |
Transformation:
When you import the above dates, Designer Cloud may not recognize the column as a set of dates. You can use the column menus to format the date values to the following standardized format:
yyyy*mm*dd*HH:MM:SS
Transformation Name | |
---|---|
Parameter: Columns | datetime |
Parameter: New type | Date/Time |
Parameter: Date/Time type | yyyy*mm*dd*HH:MM:SS |
When the type has been changed, row 1 and row 3 have been identified as invalid. You can use the following transformation to remove these rows:
Transformation Name | |
---|---|
Parameter: Condition | Custom formula |
Parameter: Type of formula | Custom single |
Parameter: Condition | ISMISMATCHED(datetime, ['Datetime','yy-mm-dd hh:mm:ss','yyyy*mm*dd*HH:MM:SS']) |
Parameter: Action | Delete matching rows |
When the Datetime values are consistently formatted, you can use the following transformations to perform conversions. The following tranformation converts the values from UTC to US/Eastern time zone:
Transformation Name | |
---|---|
Parameter: Formula type | Single row formula |
Parameter: Formula | CONVERTFROMUTC(datetime, 'US\/Eastern') |
Parameter: New column name | 'datetimeUTC2Eastern' |
This transformation now assumes that the date values are in US/Pacific time zone and converts them to UTC:
Transformation Name | |
---|---|
Parameter: Formula type | Single row formula |
Parameter: Formula | CONVERTTOUTC(datetime, 'US\/Pacific') |
Parameter: New column name | 'datetimePacific2UTC' |
The final transformation converts the date time values between arbitrary time zones. In this case, the values are assumed to be in US/Alaska time zone and are converted to US/Hawaii time zone:
Transformation Name | |
---|---|
Parameter: Formula type | Single row formula |
Parameter: Formula | CONVERTTIMEZONE(datetime, 'US\/Alaska', 'US\/Hawaii') |
Parameter: New column name | 'datetimeAlaska2Hawaii' |
Results:
row | datetime | datetimeAlaska2Hawaii | datetimePacific2UTC | datetimeUTC2Eastern |
---|---|---|---|---|
2 | 2020-03-15 00:00:00 | 2020-03-14 22:00:00 | 2020-03-15 07:00:00 | 2020-03-14 20:00:00 |
4 | 2020-03-15 01:02:03 | 2020-03-14 23:02:03 | 2020-03-15 08:02:03 | 2020-03-14 21:02:03 |
5 | 2020-03-15 04:02:03 | 2020-03-15 02:02:03 | 2020-03-15 11:02:03 | 2020-03-15 00:02:03 |
6 | 2020-03-15 08:02:03 | 2020-03-15 06:02:03 | 2020-03-15 15:02:03 | 2020-03-15 04:02:03 |
7 | 2020-03-15 12:02:03 | 2020-03-15 10:02:03 | 2020-03-15 19:02:03 | 2020-03-15 08:02:03 |
8 | 2020-03-15 16:02:03 | 2020-03-15 14:02:03 | 2020-03-15 23:02:03 | 2020-03-15 12:02:03 |
9 | 2020-03-15 20:02:03 | 2020-03-15 18:02:03 | 2020-03-16 03:02:03 | 2020-03-15 16:02:03 |
10 | 2020-03-15 23:02:03 | 2020-03-15 21:02:03 | 2020-03-16 06:02:03 | 2020-03-15 19:02:03 |