Cast To Different Types-2
===========

This node creates a new DataFrame by casting the specified columns into new types

Input
--------------
This type of node takes in a DataFrame and transforms it to another DataFrame

Output
--------------
This node casts the data type of columns as specified

Type
--------- 

transform

Class
--------- 

fire.nodes.etl.NodeMultiCastColumnType2

Fields
--------- 

.. list-table::
      :widths: 10 5 10
      :header-rows: 1

      * - Name
        - Title
        - Description
      * - inputColNames
        - Columns
        - Columns
      * - outputColTypes
        - New Data Type
        - New data type(INTEGER, DOUBLE, STRING, LONG, SHORT)
      * - replaceExistingCols
        - Replace Existing Cols
        - Whether to replace existing Columns or create New Ones
      * - formats
        - Formats
        - Formats like yyy-MM-dd used in input & output. Use precision,scale for Decimal Type (Eg. 12,3).


Details
-------
This node creates a new DataFrame by casting the specified columns into new types.


Option to replace existing column or create a new column after conversion can be selected in the node. 


New format for the Date column can be specified.


Examples
-------
Incoming Dataframe has following rows:


::

    INV_NO    |    INV_DATE               |    INV_AMT       
    ----------------------------------------------------
    STRING    |    timestamp              |    STRING       
    ----------------------------------------------------
    INV001    |    2010-12-28 10:11:12.0  |    1000.0        
    INV002    |    2020-10-15 09:11:12.0  |    1500.0        
    INV003    |    2010-01-01 10:11:12.0  |    100.0         


if MultiCastColumnType2 node is configured to perform conversion as below:


::

    COLUMNS    |    NEW DATA TYPE    |    REPLACE EXISTING COLS    |    FORMATS     
    -----------------------------------------------------------------------------------
    INV_DATE   |    STRING           |    false                    |    yyyy/MMM/dd


then new column would be added in outgoing Dataframe as below after conversion:


::

    INV_NO    |    INV_DATE               |    INV_AMT    |    INV_DATE-new       

-------------------------------------------------------------------------------  

::

    STRING    |    timestamp              |    STRING     |    STRING    
    -------------------------------------------------------------------------------
    INV001    |    2010-12-28 10:11:12.0  |    1000.0     |    2010/Dec/28        
    INV002    |    2020-10-15 09:11:12.0  |    1500.0     |    2020/Oct/15        
    INV003    |    2010-01-01 10:11:12.0  |    100.0      |    2010/Jan/01