DataFrame Creation on Primary Time Index Tables is Partially Supported - Teradata Python Package

DataFrame creation on Primary Time Index (PTI) tables is partially supported. DataFrame is created when the underlying PTI table is not created with 'timebucket' duration.

Example

Create a PTI table without 'timebucket_duration', using copy_to_sql and then create a DataFrame on it.

>>> load_example_data("sessionize", "sessionize_table")
>>> df3 = DataFrame('sessionize_table')
>>> copy_to_sql(df3, "test_copyto_pti",
                timecode_column='clicktime',
                columns_list='event')

>>> DataFrame("test_copyto_pti")
                      TD_TIMECODE partition_id adid productid
event                                                       
click  2009-03-19 16:43:26.000000         1199    1      1001
click  2009-07-04 09:18:17.000000         1231    1      1001
click  2009-07-04 09:18:17.000000         1231    1      1001
click  2009-07-16 11:18:16.000000         1039    4      1001
click  2009-07-16 11:18:16.000000         1039    4      1001
click  2009-07-24 04:18:10.000000         1167    2      1001
view   2009-02-09 15:17:59.000000         1263    4      1001
view   2009-03-09 21:17:59.000000         1199    2      1001
view   2009-03-09 21:17:59.000000         1199    2      1001
view   2009-03-13 17:17:59.000000         1071    4      1001

Example

Create a PTI table with 'timebucket_duration', DataFrame creation on the PTI table fails.

>>> load_example_data("sessionize", "sessionize_table")
>>> df3 = DataFrame('sessionize_table')
>>> copy_to_sql(df3, "test_copyto_pti1", 
           	timecode_column='clicktime', 
                columns_list='event', 
			   timebucket_duration="HOURS(2)")

>>> DataFrame("test_copyto_pti1")
/anaconda3/lib/python3.6/site-packages/sqlalchemy/engine/reflection.py:888: SAWarning: index key 'TD_TIMEBUCKET' was not located in columns for table 'test_copyto_pti1'
  "columns for table '%s'" % (flavor, c, table_name)
Traceback (most recent call last):
  File "/Users/pp186043/Github_Repos/teradataml_repo/pyTeradata/teradataml/dataframe/dataframe.py", line 163, in __init__
    self._metaexpr = self._get_metaexpr()
  File "/Users/pp186043/Github_Repos/teradataml_repo/pyTeradata/teradataml/dataframe/dataframe.py", line 395, in _get_metaexpr
    return _MetaExpression(t, column_order = self.columns)
  File "/Users/pp186043/Github_Repos/teradataml_repo/pyTeradata/teradataml/dataframe/sql.py", line 164, in __init__
    self.__t = _SQLTableExpression(table, **kw)
  File "/Users/pp186043/Github_Repos/teradataml_repo/pyTeradata/teradataml/dataframe/sql.py", line 460, in __init__
    raise ValueError('Reflected column names do not match those in DataFrame.columns')
ValueError: Reflected column names do not match those in DataFrame.columns
 
The above exception was the direct cause of the following exception:
 
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/Users/pp186043/Github_Repos/teradataml_repo/pyTeradata/teradataml/dataframe/dataframe.py", line 171, in __init__
    raise TeradataMlException(Messages.get_message(MessageCodes.TDMLDF_CREATE_FAIL), MessageCodes.TDMLDF_CREATE_FAIL) from err
teradataml.common.exceptions.TeradataMlException: [Teradata][teradataml](TDML_2010) Failed to create Teradata DataFrame.