> ## Documentation Index
> Fetch the complete documentation index at: https://launchdarkly-preview.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Databricks Data Export

> This topic explains how to create and test a Databricks destination for Data Export.

> For the complete documentation index, see [llms.txt](/llms.txt). For the full documentation snapshot, see [llms-full.txt](/llms-full.txt).

<Note title="Data Export is an add-on feature">
  Data Export is available as an add-on to select plans. To learn more, [read about our pricing](https://launchdarkly.com/pricing/). To add Data Export to your plan, [contact Sales](https://launchdarkly.com/contact-sales/).
</Note>

## Overview

This topic explains how to create and test a Databricks destination for Data Export. Databricks is a cloud-based data processing and analysis platform that lets you work with large sets of data. By exporting your LaunchDarkly experiment data to the same Databricks warehouse as your other data, you can build custom reports in Databricks to answer product behavior questions.

## Prerequisites

To configure the Databricks Data Export integration, you must have the following prerequisites:

* You must have a [LaunchDarkly role](/home/account/roles) that allows you to [add and edit integrations](/home/account/roles/role-actions#integration-actions) and [add destinations](/home/account/roles/role-actions#destination-actions)

<Feature flag="docs-enable-non-commercial-content" match={"commercial"} fallbackValue={"commercial"}>\* You need to allow LaunchDarkly's data transfer service’s static IP address: `35.192.85.117`</Feature>

<Feature flag="docs-enable-non-commercial-content" match={"eu"} fallbackValue={"commercial"}>- You need to allow LaunchDarkly's data transfer service’s static IP address: `35.241.154.37`</Feature>

## Create a service principal

We recommended that you use a Databricks [Service principal](https://docs.databricks.com/aws/en/admin/users-groups/service-principals) to provide LaunchDarkly service access to your warehouse.

To create a new service principal, follow the Databricks instructions to [Add service principals to your account](https://docs.databricks.com/aws/en/admin/users-groups/manage-service-principals#-add-service-principals-to-your-account).

Ensure that the principal has **Workspace access** and **Databricks SQL access** entitlements. To learn how, read the Databricks documentation about [Access entitlements](https://docs.databricks.com/aws/en/security/auth/entitlements).

## Create a principal access token

Next, generate and provide an access token for the service principal. You can create an access token using the Databricks REST API. To learn how, read the Databricks [REST API documentation](https://docs.databricks.com/aws/en/dev-tools/auth/pat#use-the-databricks-rest-api-to-issue-personal-access-tokens).

You must provide specific values to the REST API. In the following example, set these values:

* Replace `databricks-instance` with your Databricks workspace URL. For example, `dbc-abcd1234-5678.cloud.databricks.com`.
* Replace `your-existing-access-token` with an existing valid PAT (string) that has permissions to create new tokens. Provide the values for these parameters:

<CodeGroup>
  ```bash title="API access token" theme={null}
      curl -X POST https://<databricks-instance>/api/2.0/token/create \
        -H "Authorization: Bearer <your-existing-access-token>" \
        -H "Content-Type: application/json" \
        -d '{
          "comment": "New PAT using DB API",
          "lifetime_seconds": <lifetime-of-pat-in-seconds>
        }'
  ```
</CodeGroup>

Omitting `lifetime_seconds` sets the lifetime to the maximum allowed by the workspace configuration.

You will provide the access token later when [setting up the integration](#configure-the-databricks-data-export-integration) in LaunchDarkly.

## Create a SQL warehouse

Now, follow the Databricks instructions to [Create a new SQL warehouse](https://docs.databricks.com/aws/en/compute/sql-warehouse/create).

Under [permissions](https://docs.databricks.com/aws/en/compute/sql-warehouse/create#manage-a-sql-warehouse), assign the **Can use** permission to the service principal you created above.

Under **Connection details**, find and save the **Server hostname** and **HTTP path** of the warehouse. You will need these when setting up the integration in LaunchDarkly.

## Give catalog and schema permissions

Then, give the service principal you created the appropriate permissions for your [destination catalog](https://docs.databricks.com/aws/en/catalogs/) and [destination schema](https://docs.databricks.com/aws/en/schemas/).

For your destination catalog, give the service principal the `USE CATALOG` permission.

For your destination schema, give the service principal the following grants:

* `USE SCHEMA`
* `APPLY TAG`
* `MODIFY`
* `READ VOLUME`
* `SELECT`
* `WRITE VOLUME`
* `CREATE MATERIALIZED VIEW`
* `CREATE TABLE`
* `CREATE VOLUME`Databricks selects "Unity Catalog" for metastore type by default. If your workspace uses the [legacy Hive metastore](https://docs.databricks.com/aws/en/data-governance/unity-catalog/hive-metastore), select it instead and provide the required S3 bucket details and access keys.

## Configure the Databricks Data Export integration

Finally, in LaunchDarkly, configure the Databricks Data Export integration.

To do this:

1. In LaunchDarkly, navigate to the [**Integrations**](https://app.launchdarkly.com/settings/integrations) page and find "Databricks Data Export."
2. Click **Add integration**. The "Create a destination" panel appears.
3. Give the integration a human-readable **Name**.
4. Select a **Project and environment** to export data from.
5. Enter the Databricks **Server hostname** you saved when you [created a SQL warehouse](#create-a-sql-warehouse).
6. Enter the **HTTP path** of your Databricks server you saved when you created a SQL warehouse.
7. Enter the **Databricks catalog**.
8. Enter the Databricks **Schema** name.
9. Enter the principal **Access token** you [created in a previous step](#create-a-principal-access-token).
10. Select a **Metastore** of "Unity Catalog" or "Hive."
11. Click **Test connection** to ensure your configuration is correct.
12. After reading the Integration Terms and Conditions, check the **I have read and agree to the Integration Terms and Conditions** checkbox.
13. Click **Save destination**. The new destination appears in the list of destinations.

Your Databricks Data Export integration is now complete.

To view the different event kinds for Databricks Data Export destinations, read [Warehouse Data Export schema reference](/integrations/data-export/warehouse-schema-reference).