Use the CData SSIS Components to Insert New or Update Existing Spark Records from SQL Server

SQL Server databases are commonly used to store enterprise records. It is often necessary to move this data to other locations. The CData SSIS Components for Spark allow you to easily transfer data from SQL Server to Spark.

This article demonstrates how to use the CData SSIS Components for Spark inside of a SQL Server Integration Services workflow to export data from SQL Server to Spark, utilizing a lookup component to find and update any existing records or insert new records.

Add the Components

To get started, add a new OLE DB source, CData Spark lookup, and two CData Spark destinations (one to handle a lookup with a match and one to handle a lookup without a match) to a new data flow task.

Configure the OLE DB Source

Follow the steps below to specify properties required to connect to the SQL Server instance.

1. Open the OLE DB Source and add a new connection. Enter your server and database information here.
2. In the Data access mode menu, select "Table or view" and select the table or view to export into Spark.
3. Close the OLE DB Source wizard and connect it to the CData Spark Destination.

Create a New Connection Manager for Spark

Follow the steps below to save connection properties in the Connection Manager.

1. Create a new Connection manager: In the Connection Manager window, right-click and then click New Connection. The Add SSIS Connection Manager dialog is displayed.
2. In the Connection Manager type menu, select the CData Spark Connection Manager.
3. Configure the connection properties. A typical Spark connection requires:
   • User
   • Password
   • AccessToken

Configure the Spark Lookup

In the lookup component Transform Editor, define mappings from the SQL Server source table into the Spark lookup table.

1. Double-click the Spark lookup to open the lookup component editor.
2. In the Connection tab, select the Connection manager previously created.
3. On the Connection tab, specify the Connection manager (or create a new one) and the table into which the data will be upserted. In this case, you will transfer Account records.
4. On the Columns tab, configure the mapping of the primary key from the input columns to the primary key of the lookup columns.

Configure the Spark Destinations

Using the lookup component, you know which entries from the data source already exist in Spark and which ones are new. Configure two Spark components to handle the situation where a match is found and a match is not found.

Lookup Match Destination

If the lookup component returns a match, update the existing record in Spark.

1. Map the Lookup Match Output to a Spark destination component.
2. Double-click the Spark destination to open the destination component editor.
3. In the Connection Manager tab, select the Connection manager previously created.
4. Specify the table which will be updated and set the Action to "Update."
5. On the Column Mappings tab, configure the mappings from the input columns to the destination columns (be sure to map the SQL Server primary key column to the Spark primary key column).

Lookup No Match Destination

If the lookup component does not return a match, add a new record to Spark.

1. Map the Lookup No Match Output to a Spark destination component.
2. Double-click the Spark destination to open the destination component editor.
3. In the Connection Manager tab, select the Connection manager previously created.
4. Specify the table into which the new record will be inserted and set the Action to "Insert."
5. On the Column Mappings tab, configure the mappings from the input columns to the destination columns.

Run the Project

You can now run the project. After the SSIS Task has finished executing, data from your SQL table will be exported to the chosen table.