> ## Documentation Index
> Fetch the complete documentation index at: https://docs.maia.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Run Notebook

export const ComponentMetadata = ({warehouses, unsupportedWarehouses = [], componentType, connectionInputs, connectionOutputs}) => {
  const allWarehouses = [...warehouses.map(w => ({
    name: w,
    supported: true
  })), ...unsupportedWarehouses.map(w => ({
    name: w,
    supported: false
  }))];
  return <div style={{
    background: 'var(--colors-background-light, #f9fafb)',
    border: '1px solid var(--colors-border-default, #e5e7eb)',
    borderRadius: '12px',
    padding: '20px 28px',
    marginBottom: '28px',
    boxShadow: '0 1px 4px rgba(0,0,0,0.10)'
  }}>
      <table style={{
    width: '100%',
    borderCollapse: 'collapse'
  }}>
        <tbody>
          <tr>
            <td style={{
    fontWeight: '600',
    paddingRight: '32px',
    paddingBottom: '14px',
    whiteSpace: 'nowrap',
    verticalAlign: 'middle',
    width: '180px'
  }}>Project Availability</td>
            <td style={{
    paddingBottom: '14px',
    verticalAlign: 'middle'
  }}>
              <div style={{
    display: 'flex',
    flexWrap: 'wrap',
    gap: '8px'
  }}>
                {allWarehouses.map((w, i) => <span key={i} style={{
    background: w.supported ? '#dcfce7' : '#fee2e2',
    color: w.supported ? '#15803d' : '#b91c1c',
    border: `1px solid ${w.supported ? '#bbf7d0' : '#fca5a5'}`,
    borderRadius: '9999px',
    padding: '3px 12px',
    fontSize: '0.85rem',
    fontWeight: '500',
    whiteSpace: 'nowrap'
  }}>
                    {w.name} {w.supported ? '✅' : '❌'}
                  </span>)}
              </div>
            </td>
          </tr>
          <tr>
            <td style={{
    fontWeight: '600',
    paddingRight: '32px',
    paddingBottom: '14px',
    whiteSpace: 'nowrap',
    verticalAlign: 'middle'
  }}>Component Type</td>
            <td style={{
    paddingBottom: '14px',
    verticalAlign: 'middle'
  }}>{componentType}</td>
          </tr>
          <tr>
            <td style={{
    fontWeight: '600',
    paddingRight: '32px',
    paddingBottom: '14px',
    whiteSpace: 'nowrap',
    verticalAlign: 'middle'
  }}>Connection Inputs</td>
            <td style={{
    paddingBottom: '14px',
    verticalAlign: 'middle'
  }}>{connectionInputs}</td>
          </tr>
          <tr>
            <td style={{
    fontWeight: '600',
    paddingRight: '32px',
    whiteSpace: 'nowrap',
    verticalAlign: 'middle'
  }}>Connection Outputs</td>
            <td style={{
    verticalAlign: 'middle'
  }}>{connectionOutputs}</td>
          </tr>
        </tbody>
      </table>
    </div>;
};

<ComponentMetadata warehouses={["Databricks"]} unsupportedWarehouses={["Snowflake", "Amazon Redshift", "BigQuery"]} componentType="Orchestration" connectionInputs="One" connectionOutputs="Unlimited" />

Use the Run Notebook component to execute a Databricks notebook from an orchestration pipeline. You might find this component useful if you wish to conflate ETL/ELT tasks with the subsequent analysis performed in your Databricks notebooks.

<Note>
  This component supports the use of pipeline and project variables. For more information, read [Project and pipeline variables](/docs/guides/variables).
</Note>

***

## Properties

<ResponseField name="Name" type="string" required>
  A human-readable name for the component.
</ResponseField>

{/* <!-- param-start:[clusterName] | warehouses: [databricks] --> */}

<ResponseField name="Cluster Name" type="drop-down" required>
  Select the [Databricks cluster](https://docs.databricks.com/clusters/index.html). The special value `[Environment Default]` uses the cluster defined in the active environment.
</ResponseField>

{/* <!-- param-start:[notebookPath] | warehouses: [databricks] --> */}

<ResponseField name="Notebook Path" type="string" required>
  The path to a [Databricks notebook](https://docs.databricks.com/notebooks/index.html). Search via a filepath string or browse the list of directories and notebooks based on the connected Workspace in the environment. Read [Copy notebook path (AWS)](https://docs.databricks.com/notebooks/notebooks-manage.html#copy-notebook-path) or [Copy notebook path (Azure)](https://learn.microsoft.com/en-gb/azure/databricks/notebooks/notebooks-manage#copy-notebook-path) to learn how to retrieve your notebook file path.
</ResponseField>

{/* <!-- param-start:[executionMode] | warehouses: [databricks] --> */}

<ResponseField name="Execution Mode" type="drop-down" required>
  * Asynchronous: Runs the task and sends a request to Databricks. The status of the task is ignored in terms of continuing the pipeline.
  * Synchronous: Runs the task and polls Databricks for a status update. The pipeline is delayed until Databricks has returned a status of `TERMINATED`. The results of which include `SUCCESS`, `FAILED`, `TIMEOUT`, or `CANCELLED`.

  The default is asynchronous.
</ResponseField>