ETL Google Cloud Storage in Oracle Data Integrator

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

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

This article walks through a JDBC-based ETL -- Google Cloud Storage to Oracle. After reverse engineering a data model of Google Cloud Storage 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 appropriate directory:

• UNIX/Linux without Agent: ~/.odi/oracledi/userlib
• UNIX/Linux with Agent: $ODI_HOME/odi/agent/lib
• Windows without Agent: %APPDATA%\Roaming\odi\oracledi\userlib
• Windows with Agent: %APPDATA%\Roaming\odi\agent\lib

Restart ODI to complete the installation.

Reverse Engineer a Model

Reverse engineering the model retrieves metadata about the driver's relational view of Google Cloud Storage data. After reverse engineering, you can query real-time Google Cloud Storage data and create mappings based on Google Cloud Storage 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 GoogleCloudStorage.
   • Technology: Select Generic SQL (for ODI Version 12.2+, select Microsoft SQL Server).
   • Logical Schema: Enter GoogleCloudStorage.
   • Context: Select Global.
3. On the Data Server screen of the resulting dialog, enter the following information:
   • Name: Enter GoogleCloudStorage.
   • Driver List: Select Oracle JDBC Driver.
   • Driver: Enter cdata.jdbc.googlecloudstorage.GoogleCloudStorageDriver
   • URL: Enter the JDBC URL containing the connection string.

     Authenticate with a User Account

     You can connect without setting any connection properties for your user credentials. After setting InitiateOAuth to GETANDREFRESH, you are ready to connect.

     When you connect, the Google Cloud Storage OAuth endpoint opens in your default browser. Log in and grant permissions, then the OAuth process completes

     Authenticate with a Service Account

     Service accounts have silent authentication, without user authentication in the browser. You can also use a service account to delegate enterprise-wide access scopes.

     You need to create an OAuth application in this flow. See the Help documentation for more information. After setting the following connection properties, you are ready to connect:

     • InitiateOAuth: Set this to GETANDREFRESH.
     • OAuthJWTCertType: Set this to "PFXFILE".
     • OAuthJWTCert: Set this to the path to the .p12 file you generated.
     • OAuthJWTCertPassword: Set this to the password of the .p12 file.
     • OAuthJWTCertSubject: Set this to "*" to pick the first certificate in the certificate store.
     • OAuthJWTIssuer: In the service accounts section, click Manage Service Accounts and set this field to the email address displayed in the service account Id field.
     • OAuthJWTSubject: Set this to your enterprise Id if your subject type is set to "enterprise" or your app user Id if your subject type is set to "user".
     • ProjectId: Set this to the Id of the project you want to connect to.

     The OAuth flow for a service account then completes.

     Built-in Connection String Designer

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

     java -jar cdata.jdbc.googlecloudstorage.jar

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

     Below is a typical connection string:

     jdbc:googlecloudstorage:ProjectId='project1';InitiateOAuth=GETANDREFRESH
4. On the Physical Schema screen, enter the following information:
   • Name: Select from the Drop Down menu.
   • Database (Catalog): Enter CData.
   • Owner (Schema): If you select a Schema for Google Cloud Storage, enter the Schema selected, otherwise enter GoogleCloudStorage.
   • Database (Work Catalog): Enter CData.
   • Owner (Work Schema): If you select a Schema for Google Cloud Storage, enter the Schema selected, otherwise enter GoogleCloudStorage.
5. In the opened model click Reverse Engineer to retrieve the metadata for Google Cloud Storage tables.

Edit and Save Google Cloud Storage Data

After reverse engineering you can now work with Google Cloud Storage data in ODI. To view Google Cloud Storage data, expand the Models accordion in the Designer navigator, right-click a table, and click View data.

Create an ETL Project

Follow the steps below to create an ETL from Google Cloud Storage. You will load Buckets 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 Buckets table in Google Cloud Storage: CREATE TABLE ODI_DEMO.TRG_BUCKETS (OWNERID NUMBER(20,0),Name 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_BUCKETS 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_BUCKETS table from the Sales Administration model onto the mapping.
7. Drag the Buckets table from the Google Cloud Storage 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 BUCKETS_AP in TARGET_GROUP.
10. In the BUCKETS_AP properties, select LKM SQL to SQL (Built-In) on the Loading Knowledge Module tab.

You can then run the mapping to load Google Cloud Storage data into Oracle.