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ADLS Datalake
ADLS Datalake
PROD
Available In
Feature List
Metadata
Data Profiler
Data Quality
Query Usage
Lineage
Column-level Lineage
Owners
dbt
Tags
Stored Procedures

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

Configure and schedule ADLS Datalake metadata and profiler workflows from the OpenMetadata UI:

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.

If, instead, you want to manage your workflows externally on your preferred orchestrator, you can check the following docs to run the Ingestion Framework anywhere.

Note: ADLS Datalake connector supports extracting metadata from file types JSON, CSV, TSV & Parquet.

To extract metadata from Azure ADLS (Storage Account - StorageV2), you will need an App Registration with the following permissions on the Storage Account:

  • Storage Blob Data Contributor
  • Storage Queue Data Contributor

We have support for Python versions 3.8-3.11

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

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.

  • Client ID : Client ID of the data storage account
  • Client Secret : Client Secret of the account
  • Tenant ID : Tenant ID under which the data storage account falls
  • Account Name : Account Name of the data Storage

The sourceConfig is defined here:

markDeletedTables: To flag tables as soft-deleted if they are not present anymore in the source system.

markDeletedStoredProcedures: Optional configuration to soft delete stored procedures in OpenMetadata if the source stored procedures are deleted. Also, if the stored procedures is deleted, all the associated entities like lineage, etc., with that stored procedures will be deleted.

includeTables: true or false, to ingest table data. Default is true.

includeViews: true or false, to ingest views definitions.

includeTags: Optional configuration to toggle the tags ingestion.

includeOwners: Set the 'Include Owners' toggle to control whether to include owners to the ingested entity if the owner email matches with a user stored in the OM server as part of metadata ingestion. If the ingested entity already exists and has an owner, the owner will not be overwritten.

includeStoredProcedures: Optional configuration to toggle the Stored Procedures ingestion.

includeDDL: Optional configuration to toggle the DDL Statements ingestion.

queryLogDuration: Configuration to tune how far we want to look back in query logs to process Stored Procedures results.

queryParsingTimeoutLimit: Configuration to set the timeout for parsing the query in seconds.

useFqnForFiltering: Regex will be applied on fully qualified name (e.g service_name.db_name.schema_name.table_name) instead of raw name (e.g. table_name).

databaseFilterPattern, schemaFilterPattern, tableFilterPattern: Note that the filter supports regex as include or exclude. You can find examples here

threads (beta): The number of threads to use when extracting the metadata using multithreading. Please take a look here before configuring this.

incremental (beta): Incremental Extraction configuration. Currently implemented for:

To send the metadata to OpenMetadata, it needs to be specified as type: metadata-rest.

The main property here is the openMetadataServerConfig, where you can define the host and security provider of your OpenMetadata installation.

Logger Level

You can specify the loggerLevel depending on your needs. If you are trying to troubleshoot an ingestion, running with DEBUG will give you far more traces for identifying issues.

JWT Token

JWT tokens will allow your clients to authenticate against the OpenMetadata server. To enable JWT Tokens, you will get more details here.

You can refer to the JWT Troubleshooting section link for any issues in your JWT configuration.

Store Service Connection

If set to true (default), we will store the sensitive information either encrypted via the Fernet Key in the database or externally, if you have configured any Secrets Manager.

If set to false, the service will be created, but the service connection information will only be used by the Ingestion Framework at runtime, and won't be sent to the OpenMetadata server.

Store Service Connection

If set to true (default), we will store the sensitive information either encrypted via the Fernet Key in the database or externally, if you have configured any Secrets Manager.

If set to false, the service will be created, but the service connection information will only be used by the Ingestion Framework at runtime, and won't be sent to the OpenMetadata server.

SSL Configuration

If you have added SSL to the OpenMetadata server, then you will need to handle the certificates when running the ingestion too. You can either set verifySSL to ignore, or have it as validate, which will require you to set the sslConfig.caCertificate with a local path where your ingestion runs that points to the server certificate file.

Find more information on how to troubleshoot SSL issues here.

filename.yaml

First, we will need to save the YAML file. Afterward, and with all requirements installed, we can run:

Note that from connector to connector, this recipe will always be the same. By updating the YAML configuration, you will be able to extract metadata from different sources.

You can learn more about how to ingest dbt models' definitions and their lineage here.