Date Transformation - SQL Function Examples

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# Project Name - Date Transformation - SQL Function Examples

# Recipe URL - https://app.lingk.io/a/10932/tf/18552

# Description - This recipe demonstrates how to use a variety of different SQL based date functions that can be utilized for Date transformations.

# Systems -
# Connectors - JSON
# Data Flows - Single Direction
# Connection Type - Data

# Add Recipe notes / Change log information here!

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# CONNECTORS specify what data will be pulled into the in-memory database during processing

connectors:

# Configure JSON connector in your Environment before running this recipe
  # JSON Setup - https://help.lingk.io/en/articles/74-json-connector-reference

# Source data
-
    name: placeholder
    type: json
    properties:
      jsonObject: "[]"

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# STATEMENTS specify how the data should be processed while in memory

statements:

## to_date:
  # convert a string a date object
## to_timestamp: 
  # convert a string a timestamp object
## date_format: 
  #takes a date object and converts to a different format
  - statement: |
      (dates) => select 
              date_format(to_date("01/18/99", 'fd/dd/yy'), 'yyyy-MM-dd'), 
              to_date("01/18/99", 'MM/dd/yy'),
              to_date('2009-07-30 04:17:52'),
              to_date('2016-12-31', 'yyyy-MM-dd'),
              to_timestamp('2016-12-31', 'yyyy-MM-dd'),
              date_format(to_date("01/18/99", 'MM/dd/yy'), 'yyyy-MM-dd'),
              date_format(to_date("2009-07-30 04:17:52"), 'EEE MMM dd HH:mm:ss zzz yyyy'),
              date_format(current_timestamp(), 'EEE MMM dd HH:mm:ss zzz yyyy'),
              date_format(current_timestamp(), "yyyy-MM-dd'T'HH:mm:ss.SSS'Z'")
  - statement: print dates

# Add more statements to convert, join, aggregrate, transform, and integrate your data