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Model Elasticsearch Data Using Azure Analysis Services
Leverage CData Connect Cloud to establish a connection between Azure Analysis Services and Elasticsearch, enabling the direct import of real-time Elasticsearch data.
Microsoft Azure Analysis Services (AAS) is a fully-managed platform-as-a-service (PaaS) offering that delivers enterprise-grade data models in the cloud. When combined with CData Connect Cloud, AAS facilitates immediate cloud-to-cloud access to Elasticsearch data for applications. This article outlines the process of connecting to Elasticsearch via Connect Cloud and importing Elasticsearch data into Visual Studio using an AAS extension.
CData Connect Cloud offers a seamless cloud-to-cloud interface tailored for Elasticsearch, enabling you to create live models of Elasticsearch data in Azure Analysis Services without the need to replicate data to a natively supported database. While constructing high-quality semantic data models for business reports and client applications, Azure Analysis Services formulates SQL queries to retrieve data. CData Connect Cloud is equipped with optimized data processing capabilities right from the start, directing all supported SQL operations, including filters and JOINs, directly to Elasticsearch. This leverages server-side processing for swift retrieval of the requested Elasticsearch data.
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
Prerequisites
Before you connect, you must first do the following:
- Connect a data source to your CData Connect Cloud account. Detailed steps are provided in the next section.
- Generate a Personal Access Token (PAT). Copy this down, as it acts as your password during authentication.
- Create a server in Azure Analysis Services to which you will deploy your data from CData Connect Cloud.
- Install and configure an On-Premise Gateway in your system. This will pull data from the source via CData Connect Cloud into the Azure Analysis Services project and deploy models to the server. Refer to the given link to find the detailed process.
Configure Elasticsearch Connectivity for AAS
Connectivity to Elasticsearch from Azure Analysis Services is made possible through CData Connect Cloud. To work with Elasticsearch data from Azure Analysis Services, we start by creating and configuring a Elasticsearch connection.
- Log into Connect Cloud, click Sources, and then click Add Connection
- Select "Elasticsearch" from the Add Connection panel
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Enter the necessary authentication properties to connect to Elasticsearch.
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.
- Click Create & Test
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Navigate to the Permissions tab in the Add Elasticsearch Connection page and update the User-based permissions.
Add a Personal Access Token
When connecting to Connect Cloud through the REST API, the OData API, or the Virtual SQL Server, a Personal Access Token (PAT) is used to authenticate the connection to Connect Cloud. It is best practice to create a separate PAT for each service to maintain granularity of access.
- Click on the Gear icon () at the top right of the Connect Cloud app to open the settings page.
- On the Settings page, go to the Access Tokens section and click Create PAT.
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Give the PAT a name and click Create.
- The personal access token is only visible at creation, so be sure to copy it and store it securely for future use.
With the connection configured and a PAT generated, you are ready to connect to Elasticsearch data from Visual Studio using Azure Analysis Services.
Connect to Elasticsearch in Visual Studio Using AAS
The steps below outline connecting to CData Connect Cloud from Azure Analysis Services to create a new Elasticsearch data source. You will need the Microsoft Analysis Services Project extension installed in Microsoft Visual Studio to continue.
- In Visual Studio, create a new project. Select Analysis Services Tabular Project. Click on Next.
- In the Configure your new project dialog box, enter a name for your project in the Project name field. Fill in the rest of the fields.
- Click on Create. The Tabular model designer dialog box opens. Select Workspace server and enter the address of your Azure Analysis Services server (for example, asazure://eastus.azure.windows.net/myAzureServer). Also, make sure to select the option SQL Server 2022 / Azure Analysis Services (1600) from the Compatibility level dropdown. Click on Test Connection to check if the connection details are correct. Click OK and sign in to your server.
- Now, click on OK to create the project. Your Visual Studio window should resemble the following screenshot:
- In the Tabular Model Explorer window of Visual Studio, right-click Data Sources and select Import From Data Source.
- In the Get Data window, select SQL Server database and click Connect. In the Server field, enter the Virtual SQL Server endpoint and the port separated by a comma: e.g., “tds.cdata.com, 14333”, and click on OK.
- Click on Database and enter the following information:
- User name: Enter your CData Connect Cloud username. This is displayed in the top-right corner of the CData Connect Cloud interface. For example, [email protected].
- Password: Enter the PAT you generated on the Settings page.
Click on Connect. If successful, the Navigator window will pop up.
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In the Navigator window, search and select the tables of your choice
- You should now see the Salesforce table populated with data in the preview section on the right panel.
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Click on Load to import the data.
Now that you have imported the Elasticsearch data into your data model, you are ready to deploy the project to Azure Analysis Services for use in business reports, client applications, and more.
Get CData Connect Cloud
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