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NOTE:  Designer Cloud Educational is a free product with limitations on its features. Some features in the documentation do not apply to this product edition. See Product Limitations.



Designer Cloud Educational supports a variety of Datetime formats, each of which has additional variations to it.

Date Range

Supported Date Ranges:  

  • Earliest: January 1, 1400
  • Latest: December 31, 2599

You can use dates in the Gregorian calendar system only. Dates in the Julian calendar are not supported.

Data Validation

When values are validated against the Datetime data type, the Designer Cloud application does not compare them to an underlying calendar system. Instead, the application validates the values using regular expressions. This regular expression method checks for general Datetime validation and is fast to evaluate.

However, some values may follow the regular expression validation pattern but are not accurate dates. For example, every four years, February 29 is a valid date. When this date is validated against the Datetime data type, it may be detected as a valid value, while the date is changed in the application to be incremented to a close accurate date, such as March 1 in this example.

Formatting Tokens

You can use the following tokens to change the format of a column of dates:

LetterDate or Time ComponentPresentationExamples
MMonth in yearNumber1
MMMonth in yearNumber01
MMMMMonth in yearMonthJanuary
MMMMonth in yearMonthJan
DDay in yearNumber352
dDay in monthNumber9
ddDay in a monthNumber09
EEE Day in week (three-letter abbreviation)TextWed
EEEEDay in weekTextWednesday

Hour in day (1-12)

NOTE: Requires an AM/PM indicator (a).


Hour in am/pm (01-12)

NOTE: Requires an AM/PM indicator (a).

HHour in day (1-12)Number2
HHHour in day (0-23)Number20
mMinute in an hourNumber9


Minute in an hourNumber09
sSecond in a minuteNumber3
ssSecond in a minuteNumber03
SSS MillisecondNumber218
XTime zoneISO 8601 time zone-08:00
aAM/PM indicatorStringAM

Tip: If your DateTime column contains data in multiple formats, you must change the format of the DateTime column to one format and then add a transformation to convert that data to the other format. When all formats of your source date values are converted to a single format, the application should infer the appropriate date and time format.

Supported Separators:

  • Date separators: blank space, comma, single hyphen, or forward slash
  • Time separators: blank space, comma, single hyphen, colon, t or T
  • Non-delimited Datetime values are supported. For example, yyyymmdd, yyyymmddThhmmssX.

ISO 8601 Time Zone Notes:

  • Support for timezone offset from UTC indicated by +hh:mm, +hhmm, or +hh. For example, the date '2013-11-18 11:55-04:00' is recognized as a DateTime value.

  • Datetime part functions (for example, Hour) truncate time zones and return local time.
  • If you have a column with multiple time zones, you can convert the column to Unixtime so you can perform Date/Time operations with a standardized time zone. If you want to work with local times, you can truncate the time zone or use other Datetime functions. See UNIXTIME Function.

Supported Datetime Formats

For more information on the available formats and examples of each one, see Datetime Formats (PDF).

For more information on supported date formatting strings, see DATEFORMAT Function.

Supported Time Zones

For more information, see Supported Time Zone Values.

Job Execution

Datetime data typing involves the basic type definition, plus any supported formatting options. Depending on where the job is executed, there may be variation in how the Datetime data type is interpreted. 

  • Some running environments may perform additional inference on the typing.

    NOTE: During job execution on Spark, inputs of Datetime data type may result in row values being inferred for data type individually. For example, the String value 01/10/2020 may be inferred by date transformations as 1st Oct, 2020 or 10th Jan, 2020. Resulting outputs of Datetime values may not be deterministic in this scenario.

  • Some formatting options may not be supported. 

Differences between Trifacta Photon and Spark running environments

If your Datetime data does not contain time zone information, by default:

  • Spark uses the time zone of the Alteryx node for Datetime values.
  • Trifacta Photon uses the UTC time zone for Datetime values.

This difference in how the values are treated can result in differences in Datetime-based calculations, such as the DATEDIF function.


You can do one of the following:

  • Set the time zone for the Alteryx node to be UTC. You must also set the time zone for your Spark running environment to UTC.
  • Apply the following Spark property overrides:

      "props": {
        "spark.driver.extraJavaOptions" : "-Duser.timezone=\"UTC\"",
        "spark.executor.extraJavaOptions" : "-Duser.timezone=\"UTC\""

    For more information, see Spark Execution Properties Settings.

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