
In this section, we provide guides and references to use the GCS Datalake connector.
Configure and schedule GCS Datalake metadata and profiler workflows from the OpenMetadata UI:
How to Run the Connector Externally
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.
Requirements
Note: GCS Datalake connector supports extracting metadata from file types JSON
, CSV
, TSV
& Parquet
.
Python Requirements
We have support for Python versions 3.8-3.11
If running OpenMetadata version greater than 0.13, you will need to install the Datalake ingestion for GCS
GCS installation
If version <0.13
You will be installing the requirements for GCS
Metadata Ingestion
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.
1. Define the YAML Config
This is a sample config for Datalake using GCS:
Source Configuration - Service Connection
gcpConfig:
- type: Credentials Type is the type of the account, for a service account the value of this field is
service_account
. To fetch this key, look for the value associated with thetype
key in the service account key file. - projectId: A project ID is a unique string used to differentiate your project from all others in Google Cloud. To fetch this key, look for the value associated with the
project_id
key in the service account key file. You can also pass multiple project id to ingest metadata from different BigQuery projects into one service. - privateKeyId: This is a unique identifier for the private key associated with the service account. To fetch this key, look for the value associated with the
private_key_id
key in the service account file. - privateKey: This is the private key associated with the service account that is used to authenticate and authorize access to BigQuery. To fetch this key, look for the value associated with the
private_key
key in the service account file. - clientEmail: This is the email address associated with the service account. To fetch this key, look for the value associated with the
client_email
key in the service account key file. - clientId: This is a unique identifier for the service account. To fetch this key, look for the value associated with the
client_id
key in the service account key file. - authUri: This is the URI for the authorization server. To fetch this key, look for the value associated with the
auth_uri
key in the service account key file. The default value to Auth URI is https://accounts.google.com/o/oauth2/auth. - tokenUri: The Google Cloud Token URI is a specific endpoint used to obtain an OAuth 2.0 access token from the Google Cloud IAM service. This token allows you to authenticate and access various Google Cloud resources and APIs that require authorization. To fetch this key, look for the value associated with the
token_uri
key in the service account credentials file. Default Value to Token URI is https://oauth2.googleapis.com/token. - authProviderX509CertUrl: This is the URL of the certificate that verifies the authenticity of the authorization server. To fetch this key, look for the value associated with the
auth_provider_x509_cert_url
key in the service account key file. The Default value for Auth Provider X509Cert URL is https://www.googleapis.com/oauth2/v1/certs - clientX509CertUrl: This is the URL of the certificate that verifies the authenticity of the service account. To fetch this key, look for the value associated with the
client_x509_cert_url
key in the service account key file.
- bucketName: name of the bucket in GCS
- Prefix: prefix in gcp bucket
Source Configuration - Source Config
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.
overrideMetadata (boolean): Set the 'Override Metadata' toggle to control whether to override the existing metadata in the OpenMetadata server with the metadata fetched from the source. If the toggle is set to true, the metadata fetched from the source will override the existing metadata in the OpenMetadata server. If the toggle is set to false, the metadata fetched from the source will not override the existing metadata in the OpenMetadata server. This is applicable for fields like description, tags, owner and displayName.
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.
databaseMetadataConfigType (string): Database Source Config Metadata Pipeline type.
incremental (beta): Incremental Extraction configuration. Currently implemented for:
Sink Configuration
To send the metadata to OpenMetadata, it needs to be specified as type: metadata-rest
.
Workflow Configuration
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.
ingestionPipelineFQN
Fully qualified name of ingestion pipeline, used to identify the current ingestion pipeline.
2. Run with the CLI
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.
dbt Integration
You can learn more about how to ingest dbt models' definitions and their lineage here.