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ETL Snowflake in Oracle Data Integrator

This article shows how to transfer Snowflake data into a data warehouse using Oracle Data Integrator.

Leverage existing skills by using the JDBC standard to read and write to Snowflake: Through drop-in integration into ETL tools like Oracle Data Integrator (ODI), the CData JDBC Driver for Snowflake connects real-time Snowflake data to your data warehouse, business intelligence, and Big Data technologies.

JDBC connectivity enables you to work with Snowflake just as you would any other database in ODI. As with an RDBMS, you can use the driver to connect directly to the Snowflake APIs in real time instead of working with flat files.

This article walks through a JDBC-based ETL -- Snowflake to Oracle. After reverse engineering a data model of Snowflake entities, you will create a mapping and select a data loading strategy -- since the driver supports SQL-92, this last step can easily be accomplished by selecting the built-in SQL to SQL Loading Knowledge Module.

Install the Driver

To install the driver, copy the driver JAR and .lic file, located in the installation folder, into the ODI userlib directory:

On Unix: ~/.odi/oracledi/userlib On Windows: %APPDATA%\Roaming\odi\oracledi\userlib

Restart ODI to complete the installation.

Reverse Engineer a Model

Reverse engineering the model retrieves metadata about the driver's relational view of Snowflake data. After reverse engineering, you can query real-time Snowflake data and create mappings based on Snowflake tables.

  1. In ODI, connect to your repository and click New -> Model and Topology Objects.
  2. On the Model screen of the resulting dialog, enter the following information:
    • Name: Enter Snowflake.
    • Technology: Select Generic SQL (for ODI Version 12.2+, select Microsoft SQL Server).
    • Logical Schema: Enter Snowflake.
    • Context: Select Global.
  3. On the Data Server screen of the resulting dialog, enter the following information:
    • Name: Enter Snowflake.
    • Driver List: Select Oracle JDBC Driver.
    • Driver: Enter cdata.jdbc.snowflake.SnowflakeDriver
    • URL: Enter the JDBC URL containing the connection string.

      To connect to Snowflake:

      1. Set User and Password to your Snowflake credentials and set the AuthScheme property to PASSWORD or OKTA.
      2. Set URL to the URL of the Snowflake instance (i.e.: https://myaccount.snowflakecomputing.com).
      3. Set Warehouse to the Snowflake warehouse.
      4. (Optional) Set Account to your Snowflake account if your URL does not conform to the format above.
      5. (Optional) Set Database and Schema to restrict the tables and views exposed.

      See the Getting Started guide in the CData driver documentation for more information.

      Built-in Connection String Designer

      For assistance in constructing the JDBC URL, use the connection string designer built into the Snowflake JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.

      java -jar cdata.jdbc.snowflake.jar

      Fill in the connection properties and copy the connection string to the clipboard.

      Below is a typical connection string:

      jdbc:snowflake:User=Admin;Password=test123;Server=localhost;Database=Northwind;Warehouse=TestWarehouse;Account=Tester1;
  4. On the Physical Schema screen, enter the following information:
    • Schema (Schema): Enter Snowflake.
    • Schema (Work Schema): Enter Snowflake.
  5. In the opened model click Reverse Engineer to retrieve the metadata for Snowflake tables.

Edit and Save Snowflake Data

After reverse engineering you can now work with Snowflake data in ODI. To edit and save Snowflake data, expand the Models accordion in the Designer navigator, right-click a table, and click Data. Click Refresh to pick up any changes to the data. Click Save Changes when you are finished making changes.

Create an ETL Project

Follow the steps below to create an ETL from Snowflake. You will load Products entities into the sample data warehouse included in the ODI Getting Started VM.

  1. Open SQL Developer and connect to your Oracle database. Right-click the node for your database in the Connections pane and click new SQL Worksheet.

    Alternatively you can use SQLPlus. From a command prompt enter the following:

    sqlplus / as sysdba
  2. Enter the following query to create a new target table in the sample data warehouse, which is in the ODI_DEMO schema. The following query defines a few columns that match the Products table in Snowflake: CREATE TABLE ODI_DEMO.TRG_PRODUCTS (PRODUCTNAME NUMBER(20,0),Id VARCHAR2(255));
  3. In ODI expand the Models accordion in the Designer navigator and double-click the Sales Administration node in the ODI_DEMO folder. The model is opened in the Model Editor.
  4. Click Reverse Engineer. The TRG_PRODUCTS table is added to the model.
  5. Right-click the Mappings node in your project and click New Mapping. Enter a name for the mapping and clear the Create Empty Dataset option. The Mapping Editor is displayed.
  6. Drag the TRG_PRODUCTS table from the Sales Administration model onto the mapping.
  7. Drag the Products table from the Snowflake model onto the mapping.
  8. Click the source connector point and drag to the target connector point. The Attribute Matching dialog is displayed. For this example, use the default options. The target expressions are then displayed in the properties for the target columns.
  9. Open the Physical tab of the Mapping Editor and click PRODUCTS_AP in TARGET_GROUP.
  10. In the PRODUCTS_AP properties, select LKM SQL to SQL (Built-In) on the Loading Knowledge Module tab.

You can then run the mapping to load Snowflake data into Oracle.