ETL Google Search in Oracle Data Integrator

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

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

This article covers a JDBC-based ETL -- Google Search to Oracle. After reverse engineering a data model of Google Search 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 (cdata.jdbc.googlesearch.jar) and .lic file (cdata.jdbc.googlesearch.lic), located in the installation folder, into the ODI appropriate directory:

• UNIX/Linux without Agent: ~/.odi/oracledi/userlib
• UNIX/Linux with Agent: ~/.odi/oracledi/userlib and $ODI_HOME/odi/agent/lib
• Windows without Agent: %APPDATA%\Roaming\odi\oracledi\userlib
• Windows with Agent: %APPDATA%\odi\oracledi\userlib and %APPDATA%\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 Search results. After reverse engineering, you can query real-time Google Search results and create mappings based on Google Search tables.

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

     To search with a Google custom search engine, you need to set the CustomSearchId and ApiKey connection properties.

     To obtain the CustomSearchId property, sign into Google Custom Search Engine and create a new search engine.

     To obtain the ApiKey property, you must enable the Custom Search API in the Google API Console.

     Built-in Connection String Designer

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

     java -jar cdata.jdbc.googlesearch.jar
     

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

     👁 Using the built-in connection string designer to generate a JDBC URL (Salesforce is shown.)
     

     Below is a typical connection string:

     jdbc:googlesearch:CustomSearchId=def456;ApiKey=abc123;
     

   👁 Configuring the Data Server
   
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 Search, enter the Schema selected, otherwise enter GoogleSearch.
   • Database (Work Catalog): Enter CData.
   • Owner (Work Schema): If you select a Schema for Google Search, enter the Schema selected, otherwise enter GoogleSearch.
   👁 Configuring the Physical Schema
   
5. In the opened model click Reverse Engineer to retrieve the metadata for Google Search tables. 👁 Reverse Engineer the Model
   

Edit and Save Google Search Results

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

Create an ETL Project

Follow the steps below to create an ETL from Google Search. You will load VideoSearch 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 VideoSearch table in Google Search:

   CREATE TABLE ODI_DEMO.TRG_VIDEOSEARCH (VIEWCOUNT NUMBER(20,0),Title 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_VIDEOSEARCH 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_VIDEOSEARCH table from the Sales Administration model onto the mapping.
7. Drag the VideoSearch table from the Google Search 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 VIDEOSEARCH_AP in TARGET_GROUP.
10. In the VIDEOSEARCH_AP properties, select LKM SQL to SQL (Built-In) on the Loading Knowledge Module tab. 👁 SQL-based access to Google Search enables you to use standard database-to-database knowledge modules.
    

You can then run the mapping to load Google Search results into Oracle.