Import Presto Data Using Azure Data Factory



Use CData Connect Cloud to connect to Presto Data from Azure Data Factory and import live Presto data.

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

CData Connect Cloud offers a cloud-to-cloud interface tailored for Presto, granting you the ability to access live data from Presto 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 Cloud seamlessly channels all supported SQL operations, including filters and JOINs, directly to Presto. This harnesses server-side processing to expedite the retrieval of the desired Presto data.

About Presto Data Integration

Accessing and integrating live data from Trino and Presto SQL engines has never been easier with CData. Customers rely on CData connectivity to:

  • Access data from Trino v345 and above (formerly PrestoSQL) and Presto v0.242 and above (formerly PrestoDB)
  • Read and write access all of the data underlying your Trino or Presto instances
  • Optimized query generation for maximum throughput.

Presto and Trino allow users to access a variety of underlying data sources through a single endpoint. When paired with CData connectivity, users get pure, SQL-92 access to their instances, allowing them to integrate business data with a data warehouse or easily access live data directly from their preferred tools, like Power BI and Tableau.

In many cases, CData's live connectivity surpasses the native import functionality available in tools. One customer was unable to effectively use Power BI due to the size of the datasets needed for reporting. When the company implemented the CData Power BI Connector for Presto they were able to generate reports in real-time using the DirectQuery connection mode.


Getting Started


Configure Presto Connectivity for ADF

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

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

  1. Log into Connect Cloud, click Connections and click Add Connection
  2. Select "Presto" from the Add Connection panel
  3. Enter the necessary authentication properties to connect to Presto.

    Set the Server and Port connection properties to connect, in addition to any authentication properties that may be required.

    To enable TLS/SSL, set UseSSL to true.

    Authenticating with LDAP

    In order to authenticate with LDAP, set the following connection properties:

    • AuthScheme: Set this to LDAP.
    • User: The username being authenticated with in LDAP.
    • Password: The password associated with the User you are authenticating against LDAP with.

    Authenticating with Kerberos

    In order to authenticate with KERBEROS, set the following connection properties:

    • AuthScheme: Set this to KERBEROS.
    • KerberosKDC: The Kerberos Key Distribution Center (KDC) service used to authenticate the user.
    • KerberosRealm: The Kerberos Realm used to authenticate the user with.
    • KerberosSPN: The Service Principal Name for the Kerberos Domain Controller.
    • KerberosKeytabFile: The Keytab file containing your pairs of Kerberos principals and encrypted keys.
    • User: The user who is authenticating to Kerberos.
    • Password: The password used to authenticate to Kerberos.
  4. Click Create & Test
  5. Navigate to the Permissions tab in the Add Presto Connection page and update the User-based permissions.

Add a Personal Access Token

If you are connecting from a service, application, platform, or framework that does not support OAuth authentication, you can create a Personal Access Token (PAT) to use for authentication. Best practices would dictate that you create a separate PAT for each service, to maintain granularity of access.

  1. Click on your username at the top right of the Connect Cloud app and click User Profile.
  2. On the User Profile page, scroll down to the Personal Access Tokens section and click Create PAT.
  3. Give your PAT a name and click Create.
  4. 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, you are ready to connect to Presto data from Azure Data Factory.

Access Live Presto Data in Azure Data Factory

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

  1. Login to Azure Data Factory.
  2. If you have not yet created a Data Factory, Click New -> Dataset.
  3. 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.
  4. 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 Cloud data source you want to connect to (for example, Presto1).
    • 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 - select Password (not Azure Key Vault) and enter the PAT you generated on the Settings page.
    • Click Create.
  5. 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.
  6. After creating the linked service, the following screen should appear:
  7. Click preview data to see the imported Presto table.
  8. You can now use this dataset when creating data flows in Azure Data Factory.

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