Use a connector as a data destination

If you use the web application, set a destination from the Dataset destination option when you configure a new synthetic dataset.

Steps

1. Start a new synthetic dataset in one of two ways.
   • From the Synthetic datasets page, click + New synthetic data and select a trained generator.
   • From the Generators page with a trained generator open, click Generate synthetic data.
2. Click Dataset destination.
3. In the modal window, select a destination connector from the Destination drop-down.
4. For Location, select a destination database.
5. (Optional) Select Overwrite existing table to replace database tables or files that have the same name as in your synthetic data.
   📑

   Note: The best case for overwriting existing tables is when you are delivering multiple times to the same database or cloud bucket.

6. Click Proceed.

Result

Your synthetic dataset now has a destination, and when generated, MOSTLY AI delivers it to the destination.

If you use the Python client, add delivery to your synthetic dataset config dictionary.

To deliver to databases with a schema, use the code snippet below and replace as follows:

• GENERATOR_ID with the generator ID
• DESTINATION_CONNECTOR_ID with the ID of a destination connector
• SCHEMA with the database schema
• TABLE with the table name

g = mostly.generators.get("GENERATOR_ID")
config = {
   "generatorId": "GENERATOR_ID",
   "name": "Databricks US Census",
   "delivery": {
      "destinationConnectorId": "DESTINATION_CONNECTOR_ID",
      "location": "SCHEMA.TABLE"
   }
}
sd = mostly.generate(g, config=config)

To deliver to databases with no schema, use the code snippet below and replace as follows:

• GENERATOR_ID with the generator ID
• DESTINATION_CONNECTOR_ID with the ID of a destination connector
• TABLE with the table name

g = mostly.generate.get("GENERATOR_ID")
config = {
   "generatorId": "GENERATOR_ID",
   "name": "Databricks US Census",
   "delivery": {
      "destinationConnectorId": "DESTINATION_CONNECTOR_ID",
      "location": "TABLE"
   }
}
sd = mostly.generate(g, config=config)

To deliver to cloud buckets, use the code snippet below and replace as follows:

• GENERATOR_ID with the generator ID
• DESTINATION_CONNECTOR_ID with the ID of a destination connector
• path with cloud bucket path to the destination file
• file.csv with the filename and extension (one of .csv, .parquet, or .xslx)

g = mostly.generate.get("GENERATOR_ID")
config = {
   "generatorId": "GENERATOR_ID",
   "name": "Synthetic dataset",
   "delivery": {
      "destinationConnectorId": "DESTINATION_CONNECTOR_ID",
      "location": "/path/file.csv"
   }
}
sd = mostly.generate(g, config=config)