Table Input
Table Input reads chosen columns from an input table or view into the transformation pipeline. This component will also work with external tables.
Properties
Name = string
A human-readable name for the component.
Database = drop-down
The Snowflake database. The special value [Environment Default] uses the database defined in the environment. Read Databases, Tables and Views - Overview to learn more.
Schema = drop-down
The Snowflake schema. The special value [Environment Default] uses the schema defined in the environment. Read Database, Schema, and Share DDL to learn more.
Target Table = drop-down
The name of the input table or view. The tables and views found in the currently selected environment are provided to choose from.
Column Names = dual listbox
The columns to include in the input. If you wish to rename the column names, consider using the Rename component to change them.
Time Offset = integer
Offsets the table contents by the number of specified seconds. This is a function of Snowflake's Time Travel feature, allowing you to see a table as it was X seconds ago.
Name = string
A human-readable name for the component.
Catalog = drop-down
Select a Databricks Unity Catalog. The special value [Environment Default] uses the catalog defined in the environment. Selecting a catalog will determine which databases are available in the next parameter.
Schema Database = drop-down
The Databricks schema. The special value [Environment Default] uses the schema defined in the environment. Read Create and manage schemasto learn more.
Target Table = drop-down
The name of the input table or view. The tables and views found in the currently selected environment are provided to choose from.
Column Names = dual listbox
The columns to include in the input. If you wish to rename the column names, consider using the Rename component to change them.
Offset Type = drop-down
Select how the table contents will be offset. Options are:
- None: No offset.
- Timestamp: Unlocks the Timestamp Offset property.
- Version: Unlocks the Version Offset property.
Timestamp Offset = integer
Enter a number of seconds to offset the table by. This is a function of Databricks Delta Lake's Time Travel feature, allowing you to see a table as it was X seconds ago.
Version Offset = string
Enter the table version to offset to. This is a function of Databricks Delta Lake's Time Travel feature, allowing you to see a table as it was at a defined version.
Name = string
A human-readable name for the component.
Database = drop-down (optional)
Cross-query two databases. Specify a separate database to the one selected in the connection (that uses the environment default database). For more information, read Querying data across databases. There are limitations as to whether an additional database can be queried. For more information, read Considerations and Limitations. These limitations will prevent cross database connections, and any deviation from the environment default database will fail.
Note
- You will need to be connected to either an RA3 or Serverless Redshift cluster type for a cross database connection to work.
- On RA3 or Serverless Redshift clusters, you will also need the necessary permissions to view schemas and tables outside of your environment's default database.
Schema = drop-down
Select the table schema. The special value [Environment Default] uses the schema defined in the environment. For more information on using multiple schemas, read Schemas.
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`Target Table` = _drop-down_
The name of the input table or view. The tables and views found in the currently selected environment are provided to choose from.
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`Column Names` = _dual listbox_
The columns to include in the input. If you wish to rename the column names, consider using the [Rename](/data-productivity-cloud/designer/docs/rename) component to change them.
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`Trim Columns` = _drop-down_
Wraps the column names in a BTRIM function, which will strip out all the leading and trailing spaces. Read the [Redshift documentation](http://docs.aws.amazon.com/redshift/latest/dg/r_BTRIM.html){:target="_blank"} for details.
| Snowflake | Databricks | Amazon Redshift |
|---|---|---|
| ✅ | ✅ | ✅ |