Skip to content

Wildcard Table Input

BigQuery allows the creation of 'Wildcard' tables that combines all tables found through a wildcard expression.

A wildcard expression can be any string followed by the wildcard character, *, that will then represent any other possible string. Thus, for example, using the wildcard expression Flights_20* might return Flights_2014, Flights_2015, Flights_2016 and Flights_20Temp as a single, united table.

For full information, see the Google Cloud Platform documentation querying wildcard tables.


Properties

Name = string

A human-readable name for the component.


Project = drop-down

Select the Google Cloud project. The special value, [Environment Default], will use the project defined in the environment. For more information, read Creating and managing projects.


Dataset = drop-down

Select the Google BigQuery dataset to load data into. The special value, [Environment Default], will use the dataset defined in the environment. For more information, read Introduction to datasets.


Table Prefix = string

A prefix that all united tables must have. The wildcard character is positioned exactly after this prefix.


Include Table Suffix = drop-down

  • Yes: The remaining string after the table prefix is removed from each table name is to be given in a column, showing the origin table of each row.
  • No: Do not store suffixes in the wildcard table.

Table Suffix Column Name = string

Name of the column where table suffixes are listed. Property only visible if Include Table Suffix is Yes.


Where Clause = string

Adds an option freeform SQL filter that is appended to the SELECT statement generated by the component. This allows a user to filter which tables the component unions.

Snowflake Delta Lake on Databricks Amazon Redshift Google BigQuery Azure Synapse Analytics