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Integrate Live HCL Domino Data into Amazon SageMaker Canvas with RDS



Use CData Connect Cloud to connect to HCL Domino from Amazon RDS connector in Amazon SageMaker Canvas and build custom models using live HCL Domino data.

Amazon SageMaker Canvas is a no-code machine learning platform that lets you generate predictions, prepare data, and build models without writing code. When paired with CData Connect Cloud, you get instant, cloud-to-cloud access to HCL Domino data for building custom machine-learning models, predicting customer churn, generating texts, building chatbots, and more. This article shows how to connect to Connect Cloud from Amazon SageMaker Canvas using the RDS connector and integrate live HCL Domino data into your ML model deployments.

CData Connect Cloud provides a pure SQL, cloud-to-cloud interface for HCL Domino, allowing you to easily integrate with live HCL Domino data in Amazon SageMaker Canvas — without replicating the data. CData Connect Cloud looks exactly like a SQL Server database to Amazon SageMaker Canvas and uses optimized data processing out of the box to push all supported SQL operations (filters, JOINs, etc) directly to HCL Domino, leveraging server-side processing to quickly return HCL Domino data.

Configure HCL Domino Connectivity for Amazon SageMaker Canvas

Connectivity to HCL Domino from Amazon SageMaker Canvas is made possible through CData Connect Cloud. To work with HCL Domino data from Amazon SageMaker Canvas, we start by creating and configuring a HCL Domino connection.

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

    Prerequisites

    The connector requires the Proton component to be installed. Normally, Proton is distributed as part of the AppDev pack. See the HCL documentation for instructions on acquiring and installing Proton or the AppDev pack.

    Once the Proton service is installed and running, you will also need to create a user account and download its Internet certificate. This certificate can be used to set the connector certificate connection properties.

    Authenticating to Domino

    • Server: The name or IP address of the server running Domino with the Proton service.
    • Port: The port number that the Proton service is listening on.
    • Database: The name of the database file, including the .nsf extension.
    • SSLClientCertType: This must match the format of the certificate file. Typically this will be either PEMKEY_FILE for .pem certificates or PFXFILE for .pfx certificates.
    • SSLClientCert: The path to the certificate file.
    • SSLServerCert: This can be set to (*) if you trust the server. This is usually the case, but if you want to perform SSL validation, you may provide a certificate or thumbprint instead. See the documentation for SSLServerCert for details.

    Additional Server Configuration

    The connector supports querying Domino views if any are defined. Before views can be queried by the connector they must be registered with the design catalog.

    Please refer to the Catalog Administration section of the AppDev pack documentation for details on how to do this.

  4. Click Create & Test.
  5. Navigate to the Permissions tab in the Add HCL Domino 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 HCL Domino data from Amazon SageMaker Canvas.

Connecting to CData Connect Cloud from Amazon SageMaker Canvas

With the connection in CData Connect Cloud configured, you are ready to integrate live HCL Domino data into Amazon SageMaker Canvas using its RDS connector.

  1. Select a domain and user profile in Amazon SageMaker Canvas and click on "Open Canvas".
  2. Once the Canvas application opens, navigate to the left panel, and select "My models".
  3. Click on "Create new model" in the My models screen.
  4. Specify a Model name in Create new model window and select a Problem type. Click on "Create".
  5. Once the model version gets created, click on "Create dataset" in the Select dataset tab.
  6. In the Create a tabular dataset window, add a "Dataset name" and click on "Create".
  7. Click on the "Data Source" drop-down and search for or navigate to the RDS connector and click on " Add Connection".
  8. In the Add a new RDS connection window, set the following properties:

    • Connection Name: a relevant connection name
    • Set Engine type to sqlserver-web
    • Set Port to 14333
    • Set Address as tds.cdata.com
    • Set Username to a Connect Cloud user (e.g. [email protected])
    • Set Password to the PAT for the above user
    • Set Database name the HCL Domino connection (e.g., Domino1)
  9. Click on "Create connection".

Integrating HCL Domino Data into Amazon SageMaker Canvas

With the connection to Connect Cloud configured in the RDS, you are ready to integrate live HCL Domino data into your Amazon SageMaker Canvas dataset.

  1. In the tabular dataset created in RDS with HCL Domino data, search for the HCL Domino connection configured on Connect Cloud in the search bar or from the list of connections.
  2. Select the table of your choice from HCL Domino, drag and drop it into the canvas on the right.
  3. You can create workflows by joining any number of tables from the HCL Domino connection (as shown below). Click on "Create dataset".
  4. Once the dataset is created, click on "Select dataset" to build your model.
  5. Perform analysis, generate prediction, and deploy the model.

At this point, you have access to live HCL Domino data in Amazon SageMaker that you can utilize to build custom ML models to generate predictive business insights and grow your organization.

SQL Access to HCL Domino Data from Cloud Applications

Now you have a direct connection to live HCL Domino data from Amazon SageMaker Canvas. You can create more connections, datasets, and predictive models to drive business — all without replicating HCL Domino data.

To get real-time data access to 100+ SaaS, Big Data, and NoSQL sources directly from your cloud applications, see the CData Connect Cloud.