Import Elasticsearch Data Using Azure Data Factory

Dibyendu Datta
Lead Technology Evangelist

Use CData Connect AI to connect to Elasticsearch Data from Azure Data Factory and import live Elasticsearch data.

Microsoft Azure Data Factory (ADF) is a completely managed, serverless data integration service. When combined with CData Connect AI, ADF enables immediate cloud-to-cloud access to Elasticsearch data within data flows. This article outlines the process of connecting to Elasticsearch through Connect AI and accessing Elasticsearch data within ADF.

CData Connect AI offers a cloud-to-cloud interface tailored for Elasticsearch, granting you the ability to access live data from Elasticsearch data within Azure Data Factory without the need for data replication to a natively supported database. Equipped with optimized data processing capabilities by default, CData Connect AI seamlessly channels all supported SQL operations, including filters and JOINs, directly to Elasticsearch. This harnesses server-side processing to expedite the retrieval of the desired 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

Configure Elasticsearch Connectivity for ADF

Connectivity to Elasticsearch from Azure Data Factory is made possible through CData Connect AI. To work with Elasticsearch data from Azure Data Factory, we start by creating and configuring a Elasticsearch connection.

CData Connect AI uses a straightforward, point-and-click interface to connect to data sources.

Log into Connect AI, click Sources, and then click Add Connection

👁 Adding a Connection

Select "Elasticsearch" from the Add Connection panel

👁 Selecting a data source

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.
👁 Configuring a connection (Salesforce is shown)
Click Save & Test
Navigate to the Permissions tab in the Add Elasticsearch Connection page and update the User-based permissions. 👁 Updating permissions

Add a Personal Access Token

When connecting to Connect AI 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 AI. 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 AI app to open the settings page.
On the Settings page, go to the Access Tokens section and click Create PAT.
Give the PAT a name and click Create. 👁 Creating a new PAT
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 Azure Data Factory.

Access Live Elasticsearch Data in Azure Data Factory

To establish a connection from Azure Data Factory to the CData Connect AI Virtual SQL Server API, follow these steps.

👁 Logging in to ADF

If you have not yet created a Data Factory, Click New -> Dataset.

👁 Creating new data factory

In the search bar, enter SQL Server and select it when it appears. On the following screen, enter a name for the server. In the Linked service field, select New.

👁 Selecting SQL Server

Enter the connection settings.
- Name - enter a name of your choice.
- Server name - enter the Virtual SQL Server endpoint and port separated by a comma: tds.cdata.com,14333
- Database name - enter the Connection Name of the CData Connect AI data source you want to connect to (for example, Elasticsearch1).
- User Name - enter your CData Connect AI username. This is displayed in the top-right corner of the CData Connect AI interface. For example, [email protected].
- Password - select Password (not Azure Key Vault) and enter the PAT you generated on the Settings page.
- Click Create.

👁 Configuring new linked service

In Set properties, set the Name, choose the Linked service we just created, select a Table name from those available, and Import schema from connection/store. Click OK.