# Using Data Catalog tables for the data source
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For all data sources except Amazon S3 and connectors, a table must exist in the AWS Glue Data Catalog for the source type that you choose. AWS Glue does not create the Data Catalog table.

**To configure a data source node based on a Data Catalog table**

1. Go to the visual editor for a new or saved job.

1. Choose a data source node in the job diagram.

1. Choose the **Data source properties** tab, and then enter the following information:
   + **S3 source type**: (For Amazon S3 data sources only) Choose the option **Select a Catalog table** to use an existing AWS Glue Data Catalog table.
   + **Database**: Choose the database in the Data Catalog that contains the source table you want to use for this job. You can use the search field to search for a database by its name.
   + **Table**: Choose the table associated with the source data from the list. This table must already exist in theAWS Glue Data Catalog. You can use the search field to search for a table by its name.
   + **Partition predicate**: (For Amazon S3 data sources only) Enter a Boolean expression based on Spark SQL that includes only the partitioning columns. For example: `"(year=='2020' and month=='04')"`
   + **Temporary directory**: (For Amazon Redshift data sources only) Enter a path for the location of a working directory in Amazon S3 where your ETL job can write temporary intermediate results.
   + **Role associated with the cluster**: (For Amazon Redshift data sources only) Enter a role for your ETL job to use that contains permissions for Amazon Redshift clusters. For more information, see [Data source and data target permissions](getting-started-min-privs-job.md#getting-started-min-privs-data).