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---
title: Run MariaDB Connector using the CLI
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slug: /connectors/database/mariadb/cli
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---
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# Run MariaDB using the metadata CLI
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< Table >
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| Stage | Metadata |Query Usage | Data Profiler | Data Quality | Lineage | DBT | Supported Versions |
|:------:|:------:|:-----------:|:-------------:|:------------:|:-------:|:---:|:------------------:|
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| PROD | ✅ | ❌ | ✅ | ✅ | Partially via Views | ❌ | -- |
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< / Table >
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< Table >
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| Lineage | Table-level | Column-level |
|:------:|:-----------:|:-------------:|
| Partially via Views | ✅ | ✅ |
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< / Table >
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In this section, we provide guides and references to use the MariaDB connector.
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Configure and schedule MariaDB metadata and profiler workflows from the OpenMetadata UI:
- [Requirements ](#requirements )
- [Metadata Ingestion ](#metadata-ingestion )
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- [Data Profiler ](#data-profiler )
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- [dbt Integration ](#dbt-integration )
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## Requirements
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< InlineCallout color = "violet-70" icon = "description" bold = "OpenMetadata 0.12 or later" href = "/deployment" >
To deploy OpenMetadata, check the < a href = "/deployment" > Deployment< / a > guides.
< / InlineCallout >
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.
### Python Requirements
To run the MariaDB ingestion, you will need to install:
```bash
pip3 install "openmetadata-ingestion[mariadb]"
```
## Metadata Ingestion
All connectors are defined as JSON Schemas.
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[Here ](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/entity/services/connections/database/mariaDBConnection.json )
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you can find the structure to create a connection to MariaDB.
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
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[JSON Schema ](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/metadataIngestion/workflow.json )
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### 1. Define the YAML Config
This is a sample config for MariaDB:
```yaml
source:
type: mariadb
serviceName: local_mariadb
serviceConnection:
config:
type: MariaDB
username: openmetadata_user
password: openmetadata_password
hostPort: localhost:5432
# databaseSchema: schema
sourceConfig:
config:
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type: DatabaseMetadata
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markDeletedTables: true
includeTables: true
includeViews: true
# includeTags: true
# databaseFilterPattern:
# includes:
# - database1
# - database2
# excludes:
# - database3
# - database4
# schemaFilterPattern:
# includes:
# - schema1
# - schema2
# excludes:
# - schema3
# - schema4
# tableFilterPattern:
# includes:
# - table1
# - table2
# excludes:
# - table3
# - table4
sink:
type: metadata-rest
config: {}
workflowConfig:
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# loggerLevel: DEBUG # DEBUG, INFO, WARN or ERROR
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openMetadataServerConfig:
hostPort: < OpenMetadata host and port >
authProvider: < OpenMetadata auth provider >
```
#### Source Configuration - Service Connection
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- **username**: Specify the User to connect to MariaDB. It should have enough privileges to read all the metadata.
- **password**: Password to connect to MariaDB.
- **hostPort**: Enter the fully qualified hostname and port number for your MariaDB deployment in the Host and Port field.
- **Connection Options (Optional)**: Enter the details for any additional connection options that can be sent to MariaDB during the connection. These details must be added as Key-Value pairs.
- **Connection Arguments (Optional)**: Enter the details for any additional connection arguments such as security or protocol configs that can be sent to MariaDB 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"`
- In case you authenticate with SSO using an external browser popup, then add the `authenticator` details in the Connection Arguments as a Key-Value pair as follows: `"authenticator" : "externalbrowser"`
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#### Source Configuration - Source Config
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The `sourceConfig` is defined [here ](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/metadataIngestion/databaseServiceMetadataPipeline.json ):
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- `markDeletedTables` : To flag tables as soft-deleted if they are not present anymore in the source system.
- `includeTables` : true or false, to ingest table data. Default is true.
- `includeViews` : true or false, to ingest views definitions.
- `databaseFilterPattern` , `schemaFilterPattern` , `tableFilternPattern` : Note that the they support regex as include or exclude. E.g.,
```yaml
tableFilterPattern:
includes:
- users
- type_test
```
#### 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.
For a simple, local installation using our docker containers, this looks like:
```yaml
workflowConfig:
openMetadataServerConfig:
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hostPort: 'http://localhost:8585/api'
authProvider: openmetadata
securityConfig:
jwtToken: '{bot_jwt_token}'
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```
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We support different security providers. You can find their definitions [here ](https://github.com/open-metadata/OpenMetadata/tree/main/openmetadata-spec/src/main/resources/json/schema/security/client ).
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You can find the different implementation of the ingestion below.
< Collapse title = "Configure SSO in the Ingestion Workflows" >
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### Openmetadata JWT Auth
```yaml
workflowConfig:
openMetadataServerConfig:
hostPort: 'http://localhost:8585/api'
authProvider: openmetadata
securityConfig:
jwtToken: '{bot_jwt_token}'
```
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### Auth0 SSO
```yaml
workflowConfig:
openMetadataServerConfig:
hostPort: 'http://localhost:8585/api'
authProvider: auth0
securityConfig:
clientId: '{your_client_id}'
secretKey: '{your_client_secret}'
domain: '{your_domain}'
```
### Azure SSO
```yaml
workflowConfig:
openMetadataServerConfig:
hostPort: 'http://localhost:8585/api'
authProvider: azure
securityConfig:
clientSecret: '{your_client_secret}'
authority: '{your_authority_url}'
clientId: '{your_client_id}'
scopes:
- your_scopes
```
### Custom OIDC SSO
```yaml
workflowConfig:
openMetadataServerConfig:
hostPort: 'http://localhost:8585/api'
authProvider: custom-oidc
securityConfig:
clientId: '{your_client_id}'
secretKey: '{your_client_secret}'
domain: '{your_domain}'
```
### Google SSO
```yaml
workflowConfig:
openMetadataServerConfig:
hostPort: 'http://localhost:8585/api'
authProvider: google
securityConfig:
secretKey: '{path-to-json-creds}'
```
### Okta SSO
```yaml
workflowConfig:
openMetadataServerConfig:
hostPort: http://localhost:8585/api
authProvider: okta
securityConfig:
clientId: "{CLIENT_ID - SPA APP}"
orgURL: "{ISSUER_URL}/v1/token"
privateKey: "{public/private keypair}"
email: "{email}"
scopes:
- token
```
### Amazon Cognito SSO
The ingestion can be configured by [Enabling JWT Tokens ](https://docs.open-metadata.org/deployment/security/enable-jwt-tokens )
```yaml
workflowConfig:
openMetadataServerConfig:
hostPort: 'http://localhost:8585/api'
authProvider: auth0
securityConfig:
clientId: '{your_client_id}'
secretKey: '{your_client_secret}'
domain: '{your_domain}'
```
### OneLogin SSO
Which uses Custom OIDC for the ingestion
```yaml
workflowConfig:
openMetadataServerConfig:
hostPort: 'http://localhost:8585/api'
authProvider: custom-oidc
securityConfig:
clientId: '{your_client_id}'
secretKey: '{your_client_secret}'
domain: '{your_domain}'
```
### KeyCloak SSO
Which uses Custom OIDC for the ingestion
```yaml
workflowConfig:
openMetadataServerConfig:
hostPort: 'http://localhost:8585/api'
authProvider: custom-oidc
securityConfig:
clientId: '{your_client_id}'
secretKey: '{your_client_secret}'
domain: '{your_domain}'
```
< / Collapse >
### 2. Run with the CLI
First, we will need to save the YAML file. Afterward, and with all requirements installed, we can run:
```bash
metadata ingest -c < path-to-yaml >
```
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.
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## Data Profiler
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The Data Profiler workflow will be using the `orm-profiler` processor.
While the `serviceConnection` will still be the same to reach the source system, the `sourceConfig` will be
updated from previous configurations.
### 1. Define the YAML Config
This is a sample config for the profiler:
```yaml
source:
type: mariadb
serviceName: local_mariadb
serviceConnection:
config:
type: MariaDB
username: openmetadata_user
password: openmetadata_password
hostPort: localhost:5432
# databaseSchema: schema
sourceConfig:
config:
type: Profiler
# generateSampleData: true
# profileSample: 85
# threadCount: 5 (default)
# databaseFilterPattern:
# includes:
# - database1
# - database2
# excludes:
# - database3
# - database4
# schemaFilterPattern:
# includes:
# - schema1
# - schema2
# excludes:
# - schema3
# - schema4
# tableFilterPattern:
# includes:
# - table1
# - table2
# excludes:
# - table3
# - table4
processor:
type: orm-profiler
config: {} # Remove braces if adding properties
# tableConfig:
# - fullyQualifiedName: < table fqn >
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# profileSample: < number between 0 and 99 > # default will be 100 if omitted
# profileQuery: < query to use for sampling data for the profiler >
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# columnConfig:
# excludeColumns:
# - < column name >
# includeColumns:
# - columnName: < column name >
# - metrics:
# - MEAN
# - MEDIAN
# - ...
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# partitionConfig:
# enablePartitioning: < set to true to use partitioning >
# partitionColumnName: < partition column name . Must be a timestamp or datetime / date field type >
# partitionInterval: < partition interval >
# partitionIntervalUnit: < YEAR , MONTH , DAY , HOUR >
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sink:
type: metadata-rest
config: {}
workflowConfig:
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# loggerLevel: DEBUG # DEBUG, INFO, WARN or ERROR
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openMetadataServerConfig:
hostPort: < OpenMetadata host and port >
authProvider: < OpenMetadata auth provider >
```
#### Source Configuration
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- You can find all the definitions and types for the `serviceConnection` [here ](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/entity/services/connections/database/mariaDBConnection.json ).
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- The `sourceConfig` is defined [here ](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/metadataIngestion/databaseServiceProfilerPipeline.json ).
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Note that the filter patterns support regex as includes or excludes. E.g.,
```yaml
tableFilterPattern:
includes:
- *users$
```
#### Processor
Choose the `orm-profiler` . Its config can also be updated to define tests from the YAML itself instead of the UI:
```yaml
processor:
type: orm-profiler
config:
tableConfig:
- fullyQualifiedName: < table fqn >
profileSample: < number between 0 and 99 >
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partitionConfig:
partitionField: < field to use as a partition field >
partitionQueryDuration: < for date / datetime partitioning based set the offset from today >
partitionValues: < values to uses as a predicate for the query >
profileQuery: < query to use for sampling data for the profiler >
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columnConfig:
excludeColumns:
- < column name >
includeColumns:
- columnName: < column name >
- metrics:
- MEAN
- MEDIAN
- ...
```
`tableConfig` allows you to set up some configuration at the table level.
All the properties are optional. `metrics` should be one of the metrics listed [here ](https://docs.open-metadata.org/openmetadata/ingestion/workflows/profiler/metrics )
#### Workflow Configuration
The same as the metadata ingestion.
### 2. Run with the CLI
After saving the YAML config, we will run the command the same way we did for the metadata ingestion:
```bash
metadata profile -c < path-to-yaml >
```
Note how instead of running `ingest` , we are using the `profile` command to select the Profiler workflow.
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## SSL Configuration
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In order to integrate SSL in the Metadata Ingestion Config, the user will have to add the SSL config under connectionArguments which is placed in the source.
```yaml
---
source:
type: mariadb
serviceName: "< service name > "
serviceConnection:
config:
type: MariaDB
username: < username >
password: < password >
hostPort: < hostPort >
...
...
connectionArguments:
ssl:
ssl_ca: /path/to/client-ssl/ca.pem,
ssl_cert: /path/to/client-ssl/client-cert.pem
ssl_key: /path/to/client-ssl/client-key.pem
#ssl_disabled: True #boolean
#ssl_verify_cert: True #boolean
#ssl_verify_identity: True #boolean
```
- **ssl**: A dict of arguments which contains:
- **ssl_ca**: Path to the file that contains a PEM-formatted CA certificate.
- **ssl_cert**: Path to the file that contains a PEM-formatted client certificate.
- **ssl_disabled**: A boolean value that disables usage of TLS.
- **ssl_key**: Path to the file that contains a PEM-formatted private key for the client certificate.
- **ssl_verify_cert**: Set to true to check the server certificate's validity.
- **ssl_verify_identity**: Set to true to check the server's identity.
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## dbt Integration
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You can learn more about how to ingest dbt models' definitions and their lineage [here ](/connectors/ingestion/workflows/dbt ).