OpenMetadata/openmetadata-docs/content/v1.0.x/connectors/database/deltalake/index.md

---
title: DeltaLake
slug: /connectors/database/deltalake
---

# Deltalake

{% multiTablesWrapper %}

| Feature            | Status                       |
| :----------------- | :--------------------------- |
| Stage              | PROD                         |
| Metadata           | {% icon iconName="check" /%} |
| Query Usage        | {% icon iconName="cross" /%} |
| Data Profiler      | {% icon iconName="cross" /%} |
| Data Quality       | {% icon iconName="cross" /%} |
| Lineage            | Partially via Views          |
| DBT                | {% icon iconName="cross" /%} |
| Supported Versions | --                           |

| Feature      | Status                       |
| :----------- | :--------------------------- |
| Lineage      | Partially via Views          |
| Table-level  | {% icon iconName="check" /%} |
| Column-level | {% icon iconName="check" /%} |

{% /multiTablesWrapper %}


In this section, we provide guides and references to use the Deltalake connector.

Configure and schedule Deltalake metadata and profiler workflows from the OpenMetadata UI:

- [Requirements](#requirements)
- [Metadata Ingestion](#metadata-ingestion)
- [dbt Integration](/connectors/ingestion/workflows/dbt)

If you don't want to use the OpenMetadata Ingestion container to configure the workflows via the UI, then you can check
the following docs to connect using Airflow SDK or with the CLI.

{% tilesContainer %}

{% tile
    title="Ingest with Airflow"
    description="Configure the ingestion using Airflow SDK"
    link="/connectors/database/deltalake/airflow"
  / %}
{% tile
    title="Ingest with the CLI"
    description="Run a one-time ingestion using the metadata CLI"
    link="/connectors/database/deltalake/cli"
  / %}

{% /tilesContainer %}

## Requirements

{%inlineCallout icon="description" bold="OpenMetadata 0.12 or later" href="/deployment"%}
To deploy OpenMetadata, check the Deployment guides.
{%/inlineCallout%}

To run the Ingestion via the UI you'll need to use the OpenMetadata Ingestion Container, which comes shipped with
custom Airflow plugins to handle the workflow deployment.

## Metadata Ingestion

{% stepsContainer %}

{% step srNumber=1 %}

{% stepDescription title="1. Visit the Services Page" %}

The first step is ingesting the metadata from your sources. Under
Settings, you will find a Services link an external source system to
OpenMetadata. Once a service is created, it can be used to configure
metadata, usage, and profiler workflows.

To visit the Services page, select Services from the Settings menu.

{% /stepDescription %}

{% stepVisualInfo %}

{% image
src="/images/v1.0/connectors/visit-database-service-page.png"
alt="Visit Services Page"
caption="Find Databases option on left panel of the settings page" /%}

{% /stepVisualInfo %}

{% /step %}

{% step srNumber=2 %}

{% stepDescription title="2. Create a New Service" %}

Click on the 'Add New Service' button to start the Service creation.

{% /stepDescription %}

{% stepVisualInfo %}

{% image
src="/images/v1.0/connectors/create-database-service.png"
alt="Create a new service"
caption="Add a new Service from the Database Services page" /%}

{% /stepVisualInfo %}

{% /step %}

{% step srNumber=3 %}

{% stepDescription title="3. Select the Service Type" %}

Select Deltalake as the service type and click Next.

{% /stepDescription %}

{% stepVisualInfo %}

{% image
  src="/images/v1.0/connectors/deltalake/select-service.png"
  alt="Select Service"
  caption="Select your service from the list" /%}

{% /stepVisualInfo %}

{% /step %}

{% step srNumber=4 %}

{% stepDescription title="4. Name and Describe your Service" %}

Provide a name and description for your service as illustrated below.

#### Service Name

OpenMetadata uniquely identifies services by their Service Name. Provide
a name that distinguishes your deployment from other services, including
the other {connector} services that you might be ingesting metadata
from.

{% /stepDescription %}

{% stepVisualInfo %}

{% image
  src="/images/v1.0/connectors/deltalake/add-new-service.png"
  alt="Add New Service"
  caption="Provide a Name and description for your Service" /%}

{% /stepVisualInfo %}

{% /step %}


{% step srNumber=5 %}

{% stepDescription title="5. Configure the Service Connection" %}

In this step, we will configure the connection settings required for
this connector. Please follow the instructions below to ensure that
you've configured the connector to read from your deltalake service as
desired.

{% /stepDescription %}

{% stepVisualInfo %}

{% image
  src="/images/v1.0/connectors/deltalake/service-connection.png"
  alt="Configure service connection"
  caption="Configure the service connection by filling the form" /%}

{% /stepVisualInfo %}

{% /step %}

{% extraContent parentTagName="stepsContainer" %}

#### Connection Options

- **Metastore Host Port**: Enter the Host & Port of Hive Metastore Service to configure the Spark Session. Either
  of `metastoreHostPort`, `metastoreDb` or `metastoreFilePath` is required.
- **Metastore File Path**: Enter the file path to local Metastore in case Spark cluster is running locally. Either
  of `metastoreHostPort`, `metastoreDb` or `metastoreFilePath` is required.
- **Metastore DB**: The JDBC connection to the underlying Hive metastore DB. Either
  of `metastoreHostPort`, `metastoreDb` or `metastoreFilePath` is required.
- **appName (Optional)**: Enter the app name of spark session.
- **Connection Arguments (Optional)**: Key-Value pairs that will be used to pass extra `config` elements to the Spark Session builder.

We are internally running with `pyspark` 3.X and `delta-lake` 2.0.0. This means that we need to consider Spark configuration options for 3.X.

##### Metastore Host Port

When connecting to an External Metastore passing the parameter `Metastore Host Port`, we will be preparing a Spark Session with the configuration

```
.config("hive.metastore.uris", "thrift://{connection.metastoreHostPort}") 
```

Then, we will be using the `catalog` functions from the Spark Session to pick up the metadata exposed by the Hive Metastore.

##### Metastore File Path

If instead we use a local file path that contains the metastore information (e.g., for local testing with the default `metastore_db` directory), we will set

```
.config("spark.driver.extraJavaOptions", "-Dderby.system.home={connection.metastoreFilePath}") 
```

To update the `Derby` information. More information about this in a great [SO thread](https://stackoverflow.com/questions/38377188/how-to-get-rid-of-derby-log-metastore-db-from-spark-shell).

- You can find all supported configurations [here](https://spark.apache.org/docs/latest/configuration.html)
- If you need further information regarding the Hive metastore, you can find it [here](https://spark.apache.org/docs/3.0.0-preview/sql-data-sources-hive-tables.html),
  and in The Internals of Spark SQL [book](https://jaceklaskowski.gitbooks.io/mastering-spark-sql/content/spark-sql-hive-metastore.html).

##### Metastore Database

You can also connect to the metastore by directly pointing to the Hive Metastore db, e.g., `jdbc:mysql://localhost:3306/demo_hive`.

Here, we will need to inform all the common database settings (url, username, password), and the driver class name for JDBC metastore.

You will need to provide the driver to the ingestion image, and pass the `classpath` which will be used in the Spark Configuration under `sparks.driver.extraClassPath`.

{% /extraContent %}

{% step srNumber=6 %}

{% stepDescription title="6. Test the Connection" %}

Once the credentials have been added, click on `Test Connection` and Save
the changes.

{% /stepDescription %}

{% stepVisualInfo %}

{% image
  src="/images/v1.0/connectors/test-connection.png"
  alt="Test Connection"
  caption="Test the connection and save the Service" /%}

{% /stepVisualInfo %}

{% /step %}

{% step srNumber=7 %}

{% stepDescription title="7. Configure Metadata Ingestion" %}

In this step we will configure the metadata ingestion pipeline,
Please follow the instructions below

{% /stepDescription %}

{% stepVisualInfo %}

{% image
src="/images/v1.0/connectors/configure-metadata-ingestion-database.png"
alt="Configure Metadata Ingestion"
caption="Configure Metadata Ingestion Page" /%}

{% /stepVisualInfo %}

{% /step %}

{% extraContent parentTagName="stepsContainer" %}

#### Metadata Ingestion Options

- **Name**: This field refers to the name of ingestion pipeline, you can customize the name or use the generated name.
- **Database Filter Pattern (Optional)**: Use to database filter patterns to control whether or not to include database as part of metadata ingestion.
  - **Include**: Explicitly include databases by adding a list of comma-separated regular expressions to the Include field. OpenMetadata will include all databases with names matching one or more of the supplied regular expressions. All other databases will be excluded.
  - **Exclude**: Explicitly exclude databases by adding a list of comma-separated regular expressions to the Exclude field. OpenMetadata will exclude all databases with names matching one or more of the supplied regular expressions. All other databases will be included.
- **Schema Filter Pattern (Optional)**: Use to schema filter patterns to control whether or not to include schemas as part of metadata ingestion.
  - **Include**: Explicitly include schemas by adding a list of comma-separated regular expressions to the Include field. OpenMetadata will include all schemas with names matching one or more of the supplied regular expressions. All other schemas will be excluded.
  - **Exclude**: Explicitly exclude schemas by adding a list of comma-separated regular expressions to the Exclude field. OpenMetadata will exclude all schemas with names matching one or more of the supplied regular expressions. All other schemas will be included.
- **Table Filter Pattern (Optional)**: Use to table filter patterns to control whether or not to include tables as part of metadata ingestion.
  - **Include**: Explicitly include tables by adding a list of comma-separated regular expressions to the Include field. OpenMetadata will include all tables with names matching one or more of the supplied regular expressions. All other tables will be excluded.
  - **Exclude**: Explicitly exclude tables by adding a list of comma-separated regular expressions to the Exclude field. OpenMetadata will exclude all tables with names matching one or more of the supplied regular expressions. All other tables will be included.
- **Include views (toggle)**: Set the Include views toggle to control whether or not to include views as part of metadata ingestion.
- **Include tags (toggle)**: Set the 'Include Tags' toggle to control whether to include tags as part of metadata ingestion.
- **Enable Debug Log (toggle)**: Set the Enable Debug Log toggle to set the default log level to debug, these logs can be viewed later in Airflow.

- **Mark Deleted Tables (toggle)**: Set the Mark Deleted Tables toggle to flag tables as soft-deleted if they are not present anymore in the source system.
- **Mark Deleted Tables from Filter Only (toggle)**: Set the Mark Deleted Tables from Filter Only toggle to flag tables as soft-deleted if they are not present anymore within the filtered schema or database only. This flag is useful when you have more than one ingestion pipelines. For example if you have a schema

{% /extraContent %}

{% step srNumber=8 %}

{% stepDescription title="8. Schedule the Ingestion and Deploy" %}

Scheduling can be set up at an hourly, daily, weekly, or manual cadence. The
timezone is in UTC. Select a Start Date to schedule for ingestion. It is
optional to add an End Date.

Review your configuration settings. If they match what you intended,
click Deploy to create the service and schedule metadata ingestion.

If something doesn't look right, click the Back button to return to the
appropriate step and change the settings as needed.

After configuring the workflow, you can click on Deploy to create the
pipeline.

{% /stepDescription %}

{% stepVisualInfo %}

{% image
src="/images/v1.0/connectors/schedule.png"
alt="Schedule the Workflow"
caption="Schedule the Ingestion Pipeline and Deploy" /%}

{% /stepVisualInfo %}

{% /step %}

{% step srNumber=9 %}

{% stepDescription title="9. View the Ingestion Pipeline" %}

Once the workflow has been successfully deployed, you can view the
Ingestion Pipeline running from the Service Page.

{% /stepDescription %}

{% stepVisualInfo %}

{% image
src="/images/v1.0/connectors/view-ingestion-pipeline.png"
alt="View Ingestion Pipeline"
caption="View the Ingestion Pipeline from the Service Page" /%}

{% /stepVisualInfo %}

{% /step %}

{% /stepsContainer %}

## Troubleshooting

 ### Workflow Deployment Error

If there were any errors during the workflow deployment process, the
Ingestion Pipeline Entity will still be created, but no workflow will be
present in the Ingestion container.

- You can then edit the Ingestion Pipeline and Deploy it again.

- From the Connection tab, you can also Edit the Service if needed.

{% image
src="/images/v1.0/connectors/workflow-deployment-error.png"
alt="Workflow Deployment Error"
caption="Edit and Deploy the Ingestion Pipeline" /%}

## Related

{% tilesContainer %}

{% tile
  title="Profiler Workflow"
  description="Learn more about how to configure the Data Profiler from the UI."
  link="/connectors/ingestion/workflows/profiler" /%}

{% tile
  title="Data Quality Workflow"
  description="Learn more about how to configure the Data Quality tests from the UI."
  link="/connectors/ingestion/workflows/data-quality" /%}

{% tile
  icon="mediation"
  title="dbt Integration"
  description="Learn more about how to ingest dbt models' definitions and their lineage."
  link="/connectors/ingestion/workflows/dbt" /%}

{% /tilesContainer %}