VOOZH about

URL: https://www.cdata.com/kb/tech/elasticsearch-ado-ssas.rst

⇱ Build an OLAP Cube in SSAS from Elasticsearch Data

Build an OLAP Cube in SSAS from Elasticsearch Data

👁 Jerod Johnson
Jerod Johnson
Director, Technology Evangelism
Establish a connection to Elasticsearch data data from SQL Server Analysis Services, and use the Elasticsearch Data Provider to build OLAP cubes for use in analytics and reporting.

SQL Server Analysis Services (SSAS) serves as an analytical data engine employed in decision support and business analytics, offering high-level semantic data models for business reports and client applications like Power BI, Excel, Reporting Services reports, and various data visualization tools. When coupled with the CData ADO.NET Provider for Elasticsearch, you gain the capability to generate cubes from Elasticsearch data, facilitating more profound and efficient data analysis.

In this article, we will guide you through the process of developing and deploying a multi-dimensional model of Elasticsearch data by creating an Analysis Services project in Visual Studio. To proceed, ensure that you have an accessible SSAS instance and have installed the ADO.NET Provider.

About Elasticsearch Data Integration

Accessing and integrating live data from Elasticsearch has never been easier with CData. Customers rely on CData connectivity to:

  • Access both the SQL endpoints and REST endpoints, optimizing connectivity and offering more options when it comes to reading and writing Elasticsearch data.
  • Connect to virtually every Elasticsearch instance starting with v2.2 and Open Source Elasticsearch subscriptions.
  • Always receive a relevance score for the query results without explicitly requiring the SCORE() function, simplifying access from 3rd party tools and easily seeing how the query results rank in text relevance.
  • Search through multiple indices, relying on Elasticsearch to manage and process the query and results instead of the client machine.

Users frequently integrate Elasticsearch data with analytics tools such as Crystal Reports, Power BI, and Excel, and leverage our tools to enable a single, federated access layer to all of their data sources, including Elasticsearch.

For more information on CData's Elasticsearch solutions, check out our Knowledge Base article: CData Elasticsearch Driver Features & Differentiators.


Getting Started


Creating a Data Source for Elasticsearch

Start by creating a new Analysis Service Multidimensional and Data Mining Project in Visual Studio. Next, create a Data Source for Elasticsearch data in the project.

  1. In the Solution Explorer, right-click Data Source and select New Data Source.
  2. Opt to create a data source based on an existing or new connection and click New.
  3. In the Connection Manager, select CData ADO.NET Provider for Elasticsearch, enter the necessary connection properties, and click Next.

    Set the Server and Port connection properties to connect. To authenticate, set the User and Password properties, PKI (public key infrastructure) properties, or both. To use PKI, set the SSLClientCert, SSLClientCertType, SSLClientCertSubject, and SSLClientCertPassword properties.

    The data provider uses X-Pack Security for TLS/SSL and authentication. To connect over TLS/SSL, prefix the Server value with 'https://'. Note: TLS/SSL and client authentication must be enabled on X-Pack to use PKI.

    Once the data provider is connected, X-Pack will then perform user authentication and grant role permissions based on the realms you have configured.

    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.

    👁 Setting the Connection properties (Salesforce is shown.)
  4. Set the impersonation method to Inherit and click Next. 👁 Setting the impersonation method.
  5. Name the data source (CData Elasticsearch Source) and click Finish.

Creating a Data Source View

After you create the data source, create the data source view.

  1. In the Solution Explorer, right-click Data Source Views and select New Data Source View.
  2. Select the data source you just created (CData Elasticsearch Source) and click Next.
  3. Choose a foreign key match pattern that matches your underlying data source and click Next. 👁 Selecting the Foreign key match pattern.
  4. Select Elasticsearch tables to add to the view and click Next. 👁 Selecting Tables (Salesforce is shown).
  5. Name the view and click Finish

Based on the foreign key match scheme, relationships in the underlying data will be automatically detected. You can view (and edit) these relationships by double clicking Data Source View.

👁 Discovered relationships in the data source view (Salesforce is shown).

Note that adding a secondary data source to the Data Source View is not supported. When working with multiple data sources, SSAS requires both sources to support remote queries via OpenRowset which is unavailable in the ADO.NET Provider.

Creating a Cube for Elasticsearch

The last step before you can process the project and deploy Elasticsearch data to SSAS is creating the cubes.

  1. In the Solution Explorer, right-click Cubes and select New Cube
  2. Select "Use existing tables" and click Next.
  3. Select the tables that will be used for measure group tables and click Next. 👁 Selecting measure group tables (Salesforce is shown).
  4. Select the measures you want to include in the cube and click Next. 👁 Selecting measures (Salesforce is shown).
  5. Select the dimensions to be created, based on the available tables, and click Next. 👁 Selecting dimensions (Salesforce is shown).
  6. Review all of your selections and click Finish.

Process the Project

With the data source, data source view, and cube created, you are ready to deploy the cube to SSAS. To configure the target server and database, right-click the project and select properties. Navigate to deployment and configure the Server and Database properties in the Target section.

👁 Configuring the target server and database.

After configuring the target server and database, right-click the project and select Process. You may need to build and deploy the project as a part of this step. Once the project is built and deployed, click Run in the Process Database wizard.

Now you have an OLAP cube for Elasticsearch data in your SSAS instance, ready to be analyzed, reported, and viewed. Get started with a free, 30-day trial of the CData ADO.NET Provider for Elasticsearch.