OpenMetadata/openmetadata-docs/content/v1.6.x-SNAPSHOT/connectors/database/deltalake/index.md

title	slug
DeltaLake	/connectors/database/deltalake

{% 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="/v1.5/connectors/ingestion-modes-tiles.md" variables={yamlPath: "/connectors/database/deltalake/yaml"} /%}

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

The DeltaLake connector is able to extract the information from a metastore or directly from the storage.

If extracting directly from the storage, some extra requirements are needed depending on the storage

S3 Permissions

To execute metadata extraction AWS account should have enough access to fetch required data. The Bucket Policy in AWS requires at least these permissions:

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Effect": "Allow",
            "Action": [
                "s3:GetObject",
                "s3:ListBucket"
            ],
            "Resource": [
                "arn:aws:s3:::<my bucket>",
                "arn:aws:s3:::<my bucket>/*"
            ]
        }
    ]
}

Metadata Ingestion

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Connection Details For MetastoreConfig

• 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.

Connection Details for StorageConfig - S3

• AWS Access Key ID & AWS Secret Access Key: When you interact with AWS, you specify your AWS security credentials to verify who you are and whether you have permission to access the resources that you are requesting. AWS uses the security credentials to authenticate and authorize your requests (docs).

Access keys consist of two parts: An access key ID (for example, AKIAIOSFODNN7EXAMPLE), and a secret access key (for example, wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY).

You must use both the access key ID and secret access key together to authenticate your requests.

You can find further information on how to manage your access keys here.

• AWS Region: Each AWS Region is a separate geographic area in which AWS clusters data centers (docs).

As AWS can have instances in multiple regions, we need to know the region the service you want reach belongs to.

Note that the AWS Region is the only required parameter when configuring a connection. When connecting to the services programmatically, there are different ways in which we can extract and use the rest of AWS configurations.

You can find further information about configuring your credentials here.

• AWS Session Token (optional): If you are using temporary credentials to access your services, you will need to inform the AWS Access Key ID and AWS Secrets Access Key. Also, these will include an AWS Session Token.

You can find more information on Using temporary credentials with AWS resources.

• Endpoint URL (optional): To connect programmatically to an AWS service, you use an endpoint. An endpoint is the URL of the entry point for an AWS web service. The AWS SDKs and the AWS Command Line Interface (AWS CLI) automatically use the default endpoint for each service in an AWS Region. But you can specify an alternate endpoint for your API requests.

Find more information on AWS service endpoints.

• Profile Name: A named profile is a collection of settings and credentials that you can apply to a AWS CLI command. When you specify a profile to run a command, the settings and credentials are used to run that command. Multiple named profiles can be stored in the config and credentials files.

You can inform this field if you'd like to use a profile other than default.

Find here more information about Named profiles for the AWS CLI.

• Assume Role Arn: Typically, you use AssumeRole within your account or for cross-account access. In this field you'll set the ARN (Amazon Resource Name) of the policy of the other account.

A user who wants to access a role in a different account must also have permissions that are delegated from the account administrator. The administrator must attach a policy that allows the user to call AssumeRole for the ARN of the role in the other account.

This is a required field if you'd like to AssumeRole.

Find more information on AssumeRole.

• Assume Role Session Name: An identifier for the assumed role session. Use the role session name to uniquely identify a session when the same role is assumed by different principals or for different reasons.

By default, we'll use the name OpenMetadataSession.

Find more information about the Role Session Name.

• Assume Role Source Identity: The source identity specified by the principal that is calling the AssumeRole operation. You can use source identity information in AWS CloudTrail logs to determine who took actions with a role.

Find more information about Source Identity.

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{% /extraContent %}

{% partial file="/v1.5/connectors/test-connection.md" /%}

{% partial file="/v1.5/connectors/database/configure-ingestion.md" /%}

{% partial file="/v1.5/connectors/ingestion-schedule-and-deploy.md" /%}

{% /stepsContainer %}

{% partial file="/v1.5/connectors/troubleshooting.md" /%}

{% partial file="/v1.5/connectors/database/related.md" /%}