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title | slug |
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Run the Doris Connector Externally | /connectors/database/doris/yaml |
{% connectorDetailsHeader name="Doris" stage="PROD" platform="OpenMetadata" availableFeatures=["Metadata", "Data Profiler", "Data Quality"] unavailableFeatures=["Query Usage", "Lineage", "Column-level Lineage", "Owners", "Tags", "Stored Procedures", "dbt"] / %}
In this section, we provide guides and references to use the Doris connector.
Configure and schedule Doris metadata and profiler workflows from the OpenMetadata UI:
{% partial file="/v1.5/connectors/external-ingestion-deployment.md" /%}
Requirements
Metadata: Doris >= 1.2.0, Data Profiler: Doris >= 2.0.2
Python Requirements
{% partial file="/v1.5/connectors/python-requirements.md" /%}
To run the Doris ingestion, you will need to install:
pip3 install "openmetadata-ingestion[doris]"
Metadata Ingestion
All connectors are defined as JSON Schemas. Here you can find the structure to create a connection to Doris.
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 Doris:
{% codePreview %}
{% codeInfoContainer %}
Source Configuration - Service Connection
{% codeInfo srNumber=1 %}
username: Specify the User to connect to Doris. It should have enough privileges to read all the metadata.
{% /codeInfo %}
{% codeInfo srNumber=2 %}
{% codeInfo srNumber=2 %}
password: Password to connect to Doris.
{% /codeInfo %}
{% codeInfo srNumber=4 %}
Host and Port: Enter the fully qualified hostname and port number for your Doris deployment in the Host and Port field.
{% /codeInfo %}
{% codeInfo srNumber=5 %}
databaseSchema: databaseSchema of the data source. This is optional parameter, if you would like to restrict the metadata reading to a single databaseSchema. When left blank, OpenMetadata Ingestion attempts to scan all the databaseSchema.
{% /codeInfo %}
{% partial file="/v1.5/connectors/yaml/database/source-config-def.md" /%}
{% partial file="/v1.5/connectors/yaml/ingestion-sink-def.md" /%}
{% partial file="/v1.5/connectors/yaml/workflow-config-def.md" /%}
Advanced Configuration
{% codeInfo srNumber=6 %}
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=7 %}
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: doris
serviceName: <service name>
serviceConnection:
config:
type: Doris
username: <username>
password: <password>
hostPort: <hostPort>
databaseSchema: schema
# connectionOptions:
# key: value
# connectionArguments:
# key: value
{% partial file="/v1.5/connectors/yaml/database/source-config.md" /%}
{% partial file="/v1.5/connectors/yaml/ingestion-sink.md" /%}
{% partial file="/v1.5/connectors/yaml/workflow-config.md" /%}
{% /codeBlock %}
{% /codePreview %}
{% partial file="/v1.5/connectors/yaml/ingestion-cli.md" /%}
{% partial file="/v1.5/connectors/yaml/data-profiler.md" variables={connector: "doris"} /%}
{% partial file="/v1.5/connectors/yaml/data-quality.md" /%}
Securing Doris Connection with SSL in OpenMetadata
To establish secure connections between OpenMetadata and Doris, navigate to the Advanced Config section. Here, you can provide the CA certificate used for SSL validation by specifying the caCertificate
. Alternatively, if both client and server require mutual authentication, you'll need to use all three parameters: ssl_key
, ssl_cert
, and ssl_ca
. In this case, ssl_cert
is used for the client’s SSL certificate, ssl_key
for the private key associated with the SSL certificate, and ssl_ca
for the CA certificate to validate the server’s certificate.
sslConfig:
caCertificate: "/path/to/ca_certificate"
sslCertificate: "/path/to/your/ssl_cert"
sslKey: "/path/to/your/ssl_key"
Lineage
You can learn more about how to ingest lineage here.
dbt Integration
You can learn more about how to ingest dbt models' definitions and their lineage here.