OpenMetadata/openmetadata-docs/content/v1.4.x/connectors/database/deltalake/yaml.md

title	slug
Run the Delta Lake Connector Externally	/connectors/database/deltalake/yaml

{% connectorDetailsHeader name="DeltaLake" stage="PROD" platform="OpenMetadata" availableFeatures=["Metadata", "dbt"] unavailableFeatures=["Query Usage", "Data Profiler", "Data Quality", "Lineage", "Column-level Lineage", "Owners", "Tags", "Stored Procedures"] / %}

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
• Metadata Ingestion
• dbt Integration

{% partial file="/v1.4/connectors/external-ingestion-deployment.md" /%}

Requirements

Deltalake requires to run with Python 3.8, 3.9 or 3.10. We do not yet support the Delta connector for Python 3.11

Python Requirements

{% partial file="/v1.4/connectors/python-requirements.md" /%}

To run the Deltalake ingestion, you will need to install:

pip3 install "openmetadata-ingestion[deltalake]"

Metadata Ingestion

All connectors are defined as JSON Schemas. Here you can find the structure to create a connection to Deltalake.

In order to create and run a Metadata Ingestion workflow, we will follow the steps to create a YAML configuration able to connect to the source, process the Entities if needed, and reach the OpenMetadata server.

The workflow is modeled around the following JSON Schema

1. Define the YAML Config

This is a sample config for Deltalake:

{% codePreview %}

{% codeInfoContainer %}

Source Configuration - Service Connection

{% codeInfo srNumber=1 %}

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.

• You can find all supported configurations here
• If you need further information regarding the Hive metastore, you can find it here, and in The Internals of Spark SQL book.

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 spark.driver.extraClassPath.

{% /codeInfo %}

{% partial file="/v1.4/connectors/yaml/database/source-config-def.md" /%}

{% partial file="/v1.4/connectors/yaml/ingestion-sink-def.md" /%}

{% partial file="/v1.4/connectors/yaml/workflow-config-def.md" /%}

Advanced Configuration

{% codeInfo srNumber=2 %}

Connection Options (Optional): Enter the details for any additional connection options that can be sent to database during the connection. These details must be added as Key-Value pairs.

{% /codeInfo %}

{% codeInfo srNumber=3 %}

Connection Arguments (Optional): Enter the details for any additional connection arguments such as security or protocol configs that can be sent to database during the connection. These details must be added as Key-Value pairs.

• In case you are using Single-Sign-On (SSO) for authentication, add the authenticator details in the Connection Arguments as a Key-Value pair as follows: "authenticator" : "sso_login_url"

{% /codeInfo %}

{% /codeInfoContainer %}

{% codeBlock fileName="filename.yaml" %}

source:
  type: deltalake
  serviceName: "<service name>"
  serviceConnection:
    config:
      type: DeltaLake

      metastoreConnection:
        # Pick only of the three
        ## 1. Hive Service Thrift Connection
        metastoreHostPort: "<metastore host port>"
        ## 2. Hive Metastore db connection
        # metastoreDb: jdbc:mysql://localhost:3306/demo_hive
        # username: username
        # password: password
        # driverName: org.mariadb.jdbc.Driver
        # jdbcDriverClassPath: /some/path/
        ## 3. Local file for Testing
        # metastoreFilePath: "<path_to_metastore>/metastore_db"
      appName: MyApp

      # connectionOptions:
      #   key: value

      # connectionArguments:
      #   key: value

{% partial file="/v1.4/connectors/yaml/database/source-config.md" /%}

{% partial file="/v1.4/connectors/yaml/ingestion-sink.md" /%}

{% partial file="/v1.4/connectors/yaml/workflow-config.md" /%}

{% /codeBlock %}

{% /codePreview %}

{% partial file="/v1.4/connectors/yaml/ingestion-cli.md" /%}

dbt Integration

{% tilesContainer %}

{% 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 %}