Visualize REST Data in TIBCO Spotfire through OData



Integrate REST data into dashboards in TIBCO Spotfire.

OData is a major protocol enabling real-time communication among cloud-based, mobile, and other online applications. The CData API Server, when paired with the ADO.NET Provider for REST, provides REST data (or data from 200+ other ADO.NET Providers) to OData consumers like TIBCO Spotfire. This article shows how to use the API Server and Spotfire's built-in support for OData to access REST data in real time.

Set Up the API Server

Follow the steps below to begin producing secure REST OData services:

Deploy

The API Server runs on your own server. On Windows, you can deploy using the stand-alone server or IIS. On a Java servlet container, drop in the API Server WAR file. See the help documentation for more information and how-tos.

The API Server is also easy to deploy on Microsoft Azure, Amazon EC2, and Heroku.

Connect to REST

After you deploy the API Server and the ADO.NET Provider for REST, provide authentication values and other connection properties needed to connect to REST by clicking Settings -> Connections and adding a new connection in the API Server administration console.

See the Getting Started chapter in the data provider documentation to authenticate to your data source: The data provider models REST APIs as bidirectional database tables and XML/JSON files as read-only views (local files, files stored on popular cloud services, and FTP servers). The major authentication schemes are supported, including HTTP Basic, Digest, NTLM, OAuth, and FTP. See the Getting Started chapter in the data provider documentation for authentication guides.

After setting the URI and providing any authentication values, set Format to "XML" or "JSON" and set DataModel to more closely match the data representation to the structure of your data.

The DataModel property is the controlling property over how your data is represented into tables and toggles the following basic configurations.

  • Document (default): Model a top-level, document view of your REST data. The data provider returns nested elements as aggregates of data.
  • FlattenedDocuments: Implicitly join nested documents and their parents into a single table.
  • Relational: Return individual, related tables from hierarchical data. The tables contain a primary key and a foreign key that links to the parent document.

See the Modeling REST Data chapter for more information on configuring the relational representation. You will also find the sample data used in the following examples. The data includes entries for people, the cars they own, and various maintenance services performed on those cars.

When you configure the connection, you may also want to set the Max Rows connection property. This will limit the number of rows returned, which is especially helpful for improving performance when designing reports and visualizations.

You can then choose the REST entities you want to allow the API Server access to by clicking Settings -> Resources.

Authorize API Server Users

After determining the OData services you want to produce, authorize users by clicking Settings -> Users. The API Server uses authtoken-based authentication and supports the major authentication schemes. Access can also be restricted based on IP address; by default only connections to the local machine are allowed. You can authenticate as well as encrypt connections with SSL.

Create Data Visualizations on External REST Data

  1. Open Spotfire and click Add Data Tables -> OData.
  2. In the OData Connection dialog, enter the following information:
    • Service URL: Enter the API Server's OData endpoint. For example: http://localhost:8032/api.rsc
    • Authentication Method: Select Username and Password.
    • Username: Enter the username of an API Server user. You can create API users on the Security tab of the administration console.
    • Password: Enter the authtoken of an API Server user.
  3. Select the tables and columns you want to add to the dashboard. This example uses people.
  4. If you want to work with the live data, click the Keep Data Table External option. This option enables your dashboards to reflect changes to the data in real time.

    If you want to load the data into memory and process the data locally, click the Import Data Table option. This option is better for offline use or if a slow network connection is making your dashboard less interactive.

  5. After adding tables, the Recommended Visualizations wizard is displayed. When you select a table, Spotfire uses the column data types to detect number, time, and category columns. This example uses [ personal.name.last ] in the Numbers section and [ personal.name.first ] in the Categories section.

After adding several visualizations in the Recommended Visualizations wizard, you can make other modifications to the dashboard. For example, you can apply a filter: After clicking the Filter button, the available filters for each query are displayed in the Filters pane.

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CData API Server