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Ingest data from Smartsheet

Beta

This feature is in Beta. Workspace admins can control access to this feature from the Previews page. See Manage Databricks previews.

Learn how to create a managed Smartsheet ingestion pipeline using Databricks Lakeflow Connect.

Requirements​

  • To create an ingestion pipeline, you must first meet the following requirements:

    • Your workspace must be enabled for Unity Catalog.

    • Serverless compute must be enabled for your workspace. See Serverless compute requirements.

    • If you plan to create a new connection: You must have CREATE CONNECTION privileges on the metastore. See Manage privileges in Unity Catalog.

      If the connector supports UI-based pipeline authoring, an admin can create the connection and the pipeline at the same time by completing the steps on this page. However, if the users who create pipelines use API-based pipeline authoring or are non-admin users, an admin must first create the connection in Catalog Explorer. See Connect to managed ingestion sources.

    • If you plan to use an existing connection: You must have USE CONNECTION privileges or ALL PRIVILEGES on the connection object.

    • You must have USE CATALOG privileges on the target catalog.

    • You must have USE SCHEMA and CREATE TABLE privileges on an existing schema or CREATE SCHEMA privileges on the target catalog.

  • To ingest from Smartsheet, you must first complete the steps in Configure OAuth for Smartsheet ingestion.

Create an ingestion pipeline​

Each source object (sheet or report) is ingested into a streaming table. For a list of supported source object types, see Supported source object types.

  1. In the sidebar of the Databricks workspace, click Data Ingestion.
  2. On the Add data page, under Databricks connectors, click Smartsheet.
  3. On the Connection page of the ingestion wizard, select the connection that stores your Smartsheet access credentials. If you have the CREATE CONNECTION privilege on the metastore, you can click Plus icon. Create connection to create a new connection with the authentication details in Configure OAuth for Smartsheet ingestion.
  4. Click Next.
  5. On the Ingestion setup page, enter a name for the pipeline.
  6. Select a catalog and a schema to write event logs to. If you have USE CATALOG and CREATE SCHEMA privileges on the catalog, you can click Plus icon. Create schema in the drop-down menu to create a new schema.
  7. Click Create pipeline and continue.
  8. On the Source page, select the sheets or reports to ingest.
  9. Click Save and continue.
  10. On the Destination page, select a catalog and a schema to load data into. If you have USE CATALOG and CREATE SCHEMA privileges on the catalog, you can click Plus icon. Create schema in the drop-down menu to create a new schema.
  11. Click Save and continue.
  12. (Optional) On the Schedules and notifications page, click Plus icon. Create schedule. Set the frequency to refresh the destination tables.
  13. (Optional) Click Plus icon. Add notification to set email notifications for pipeline operation success or failure, then click Save and run pipeline.

Examples​

Use these examples to configure your pipeline.

Ingest a single source object​

The source_schema is always "default" for Smartsheet. The source_table is the 16-digit sheet or report ID, which you can find in the Smartsheet URL or sheet properties.

The following pipeline definition file ingests a single Smartsheet sheet:

YAML
variables:
  dest_catalog:
    default: main
  dest_schema:
    default: ingest_destination_schema

resources:
  pipelines:
    pipeline_smartsheet:
      name: smartsheet_pipeline
      catalog: ${var.dest_catalog}
      schema: ${var.dest_schema}
      ingestion_definition:
        connection_name: <smartsheet-connection>
        objects:
          - table:
              source_schema: default
              source_table: '7483920174635241'
              destination_catalog: ${var.dest_catalog}
              destination_schema: ${var.dest_schema}

Ingest multiple source objects​

The following pipeline definition file ingests multiple sheets or reports:

YAML
variables:
  dest_catalog:
    default: main
  dest_schema:
    default: ingest_destination_schema

resources:
  pipelines:
    pipeline_smartsheet:
      name: smartsheet_pipeline
      catalog: ${var.dest_catalog}
      schema: ${var.dest_schema}
      ingestion_definition:
        connection_name: <smartsheet-connection>
        objects:
          - table:
              source_schema: default
              source_table: '7483920174635241'
              destination_catalog: ${var.dest_catalog}
              destination_schema: ${var.dest_schema}
          - table:
              source_schema: default
              source_table: '3219847562038416'
              destination_catalog: ${var.dest_catalog}
              destination_schema: ${var.dest_schema}

Use connector and table options​

Use connector_options and table_configuration to control schema enforcement, column selection, and row filtering.

The following pipeline definition file ingests a sheet with column exclusion and row filtering:

YAML
variables:
  dest_catalog:
    default: main
  dest_schema:
    default: hr_data

resources:
  pipelines:
    pipeline_smartsheet:
      name: smartsheet_pipeline
      catalog: ${var.dest_catalog}
      schema: ${var.dest_schema}
      ingestion_definition:
        connection_name: <smartsheet-connection>
        connector_options:
          enforce_schema: false
        objects:
          - table:
              source_schema: default
              source_table: '7483920174635241'
              destination_catalog: ${var.dest_catalog}
              destination_schema: ${var.dest_schema}
              destination_table: employee_roster
              table_configuration:
                exclude_columns:
                  - Employee Name
                  - Status
                row_filter: "row_number <= 10 OR Department != 'Engineering'"

Bundle job definition file​

The following is an example job definition file for use with Declarative Automation Bundles. The job runs every day, exactly one day from the last run.

YAML
resources:
  jobs:
    smartsheet_dab_job:
      name: smartsheet_dab_job

      trigger:
        periodic:
          interval: 1
          unit: DAYS

      email_notifications:
        on_failure:
          - <email-address>

      tasks:
        - task_key: refresh_pipeline
          pipeline_task:
            pipeline_id: ${resources.pipelines.pipeline_smartsheet.id}

Common patterns​

For advanced pipeline configurations, see Common patterns for managed ingestion pipelines.

Next steps​

Start, schedule, and set alerts on your pipeline. See Common pipeline maintenance tasks.

Additional resources​

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