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ETL SQL Analysis Services in Oracle Data Integrator

This article shows how to transfer SQL Analysis Services data into a data warehouse using Oracle Data Integrator.

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

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

This article walks through a JDBC-based ETL -- SQL Analysis Services to Oracle. After reverse engineering a data model of SQL Analysis Services 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 SQL Analysis Services data. After reverse engineering, you can query real-time SQL Analysis Services data and create mappings based on SQL Analysis Services 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 SSAS.
    • Technology: Select Generic SQL.
    • Logical Schema: Enter SSAS.
    • Context: Select Global.
  3. On the Data Server screen of the resulting dialog, enter the following information:
    • Name: Enter SSAS.
    • Driver List: Select Oracle JDBC Driver.
    • Driver: Enter cdata.jdbc.ssas.SSASDriver
    • URL: Enter the JDBC URL containing the connection string.

      To connect, provide authentication and set the Url property to a valid SQL Server Analysis Services endpoint. You can connect to SQL Server Analysis Services instances hosted over HTTP with XMLA access. See the Microsoft documentation to configure HTTP access to SQL Server Analysis Services.

      To secure connections and authenticate, set the corresponding connection properties, below. The data provider supports the major authentication schemes, including HTTP and Windows, as well as SSL/TLS.

      • HTTP Authentication

        Set AuthScheme to "Basic" or "Digest" and set User and Password. Specify other authentication values in CustomHeaders.

      • Windows (NTLM)

        Set the Windows User and Password and set AuthScheme to "NTLM".

      • Kerberos and Kerberos Delegation

        To authenticate with Kerberos, set AuthScheme to NEGOTIATE. To use Kerberos delegation, set AuthScheme to KERBEROSDELEGATION. If needed, provide the User, Password, and KerberosSPN. By default, the data provider attempts to communicate with the SPN at the specified Url.

      • SSL/TLS:

        By default, the data provider attempts to negotiate SSL/TLS by checking the server's certificate against the system's trusted certificate store. To specify another certificate, see the SSLServerCert property for the available formats.

      You can then access any cube as a relational table: When you connect the data provider retrieves SSAS metadata and dynamically updates the table schemas. Instead of retrieving metadata every connection, you can set the CacheLocation property to automatically cache to a simple file-based store.

      See the Getting Started section of the CData documentation, under Retrieving Analysis Services Data, to execute SQL-92 queries to the cubes.

      Built-in Connection String Designer

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

      java -jar cdata.jdbc.ssas.jar

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

      Below is a typical connection string:

      jdbc:ssas:User=myuseraccount;Password=mypassword;URL=http://localhost/OLAP/msmdpump.dll;
  4. On the Physical Schema screen, enter the following information:
    • Schema (Schema): Enter SSAS.
    • Schema (Work Schema): Enter SSAS.
  5. In the opened model click Reverse Engineer to retrieve the metadata for SQL Analysis Services tables.

Edit and Save SQL Analysis Services Data

After reverse engineering you can now work with SQL Analysis Services data in ODI. To edit and save SQL Analysis Services 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 SQL Analysis Services. You will load Adventure_Works 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 Adventure_Works table in SQL Analysis Services: CREATE TABLE ODI_DEMO.TRG_ADVENTURE_WORKS (SALES_AMOUNT NUMBER(20,0),Fiscal_Year 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_ADVENTURE_WORKS 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_ADVENTURE_WORKS table from the Sales Administration model onto the mapping.
  7. Drag the Adventure_Works table from the SQL Analysis Services 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 ADVENTURE_WORKS_AP in TARGET_GROUP.
  10. In the ADVENTURE_WORKS_AP properties, select LKM SQL to SQL (Built-In) on the Loading Knowledge Module tab.

You can then run the mapping to load SQL Analysis Services data into Oracle.