The fastload() function writes records from a Pandas DataFrame to Vantage using Fastload, and can be used to quickly load large amounts of data in an empty table on Vantage.
FastLoad opens multiple data transfer connections to the database. The number of data transfer sessions can be set using argument open_sessions. If this argument is not set, by default, data transfer sessions opened by teradataml is the smaller of 8 and the number of available AMPs in Vantage.
Teradata recommends using fastload() function when number of rows in the Pandas DataFrame is greater than 100,000 for better performance. To insert lesser rows, you can use the copy_to_sql() function for optimized performance. The data is loaded in batches.
- FastLoad API cannot load duplicate rows in the DataFrame if the table is a MULTISET table with Primary Index.
- FastLoad API does not support all Advanced SQL Engine data types.
For example, target table having BLOB and CLOB data type columns cannot be loaded.
- If there are any incorrect rows due to constraint violations, data type conversion errors, etc., FastLoad protocol ignores those rows and inserts all valid rows.
- Rows in the DataFrame that failed to get inserted are categorized into errors and warnings by FastLoad protocol and these errors and warnings are stored into respective error and warning tables by FastLoad API.
- If 'save_errors' argument is set to True, the names of error and warning tables are shown once the fastload operation is complete. These tables will be persisted using copy_to_sql.
- errors_dataframe: It is a Pandas DataFrame containing error messages thrown by fastload.
DataFrame is empty if there are no errors.
- warnings_dataframe: It is a Pandas DataFrame containing warning messages thrown by fastload.
DataFrame is empty if there are no warnings.
- errors_table: Name of the table containing errors.
It is None, if argument save_errors is set to 'False'.
- warnings_table: Name of the table containing warnings.
It is None, if argument save_errors is set to 'False'.
See the FastLoad section of https://pypi.org/project/teradatasql/ for more information about FastLoad protocol through teradatasql driver.
Minimum version requirements for fastload()
[Teradata Database] [Error 3706] Syntax error: expected something between the beginning of the request and the word 'teradata_require_fastloadINSERT'.
AttributeError: 'Index' object has no attribute 'to_list'Install pandas >= 0.24 to solve this issue.
Example Setup
>>> from teradataml.dataframe.fastload import fastload >>> from teradatasqlalchemy.types import * >>> import pandas as pd
>>> df = {'emp_name': ['A1', 'A2', 'A3', 'A4'], 'emp_sage': [100, 200, 300, 400], 'emp_id': [133, 144, 155, 177], 'marks': [99.99, 97.32, 94.67, 91.00] }
>>> pandas_df = pd.DataFrame(df)
Example 1: Save a Pandas DataFrame with default signature
>>> fastload(df = pandas_df, table_name = 'my_table')
Example 2: Save a Pandas DataFrame with primary_index
>>> pandas_df = pandas_df.set_index(['emp_id'])
>>> fastload(df = pandas_df, table_name = 'my_table_1', primary_index='emp_id')
Example 3: Save a Pandas DataFrame with index and primary_index
>>> fastload(df = pandas_df, table_name = 'my_table_2', index=True, primary_index='index_label')
Example 4: Save a Pandas DataFrame with types, appending to an existing table
>>> fastload(df = pandas_df, table_name = 'my_table_3', schema_name = 'alice', index = True, index_label = 'my_index_label', primary_index = ['emp_id'], if_exists = 'append', types = {'emp_name': VARCHAR, 'emp_sage':INTEGER, 'emp_id': BIGINT, 'marks': DECIMAL})
Example 5: Save a Pandas DataFrame using levels in index of type MultiIndex, replacing an existing table
>>> pandas_df = pandas_df.set_index(['emp_id', 'emp_name'])
>>> fastload(df = pandas_df, table_name = 'my_table_4', schema_name = 'alice', index = True, index_label = ['index1', 'index2'], primary_index = ['index1'], if_exists = 'replace'
Example 6: Save a Pandas DataFrame by opening given number of Teradata data transfer sessions
This example saves a Pandas DataFrame by opening two Teradata data transfer sessions.
>>> fastload(df = pandas_df, table_name = 'my_table_5', open_sessions = 2)