OpenMetadata/openmetadata-docs/content/v1.1.0/connectors/database/mysql/cli.md

title	slug
Run MySQL Connector using the CLI	/connectors/database/mysql/cli

Run MySQL using the metadata CLI

{% multiTablesWrapper %}

Feature	Status
Stage	PROD
Metadata	{% icon iconName="check" /%}
Query Usage	{% icon iconName="cross" /%}
Data Profiler	{% icon iconName="check" /%}
Data Quality	{% icon iconName="check" /%}
Lineage	Partially via Views
DBT	{% icon iconName="cross" /%}
Supported Versions	MySQL >= 8.0.0

Feature	Status
Lineage	Partially via Views
Table-level	{% icon iconName="check" /%}
Column-level	{% icon iconName="check" /%}

{% /multiTablesWrapper %}

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

Configure and schedule MySQL metadata and profiler workflows from the OpenMetadata UI:

• Requirements
• Metadata Ingestion
• Data Profiler
• dbt Integration

Requirements

{%inlineCallout icon="description" bold="OpenMetadata 0.12 or later" href="/deployment"%} To deploy OpenMetadata, check the Deployment 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 MySQL ingestion, you will need to install:

pip3 install "openmetadata-ingestion[mysql]"

Metadata Ingestion

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

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 MySQL:

{% codePreview %}

{% codeInfoContainer %}

Source Configuration - Service Connection

{% codeInfo srNumber=1 %}

username: Specify the User to connect to MySQL. It should have enough privileges to read all the metadata.

{% /codeInfo %}

{% codeInfo srNumber=2 %}

authType: Choose from basic auth and IAM based auth.

Basic Auth

password: Password comes under Basic Auth type.

{% /codeInfo %}

{% codeInfo srNumber=3 %}

IAM BASED Auth

• awsAccessKeyId & awsSecretAccessKey: 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.

awsSessionToken: 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.

awsRegion: 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.

endPointURL: 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.

profileName: 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.

assumeRoleArn: 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.

assumeRoleSessionName: 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.

assumeRoleSourceIdentity: 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.

{% /codeInfo %}

{% codeInfo srNumber=4 %}

Host and Port: Enter the fully qualified hostname and port number for your MySQL 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 %}

Source Configuration - Source Config

{% codeInfo srNumber=8 %}

The sourceConfig is defined here:

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 filter supports regex as include or exclude. You can find examples here

{% /codeInfo %}

Sink Configuration

{% codeInfo srNumber=9 %}

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

{% /codeInfo %}

{% partial file="workflow-config.md" /%}

Advanced Configuration

{% codeInfo srNumber=6 %}

Connection Options (Optional): Enter the details for any additional connection options that can be sent to Athena 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 Athena 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: mysql
  serviceName: <service name>
  serviceConnection:
    config:
      type: Mysql

      username: <username>

      authType: 
            password: <password>

      authType: 
            awsConfig:
                  awsAccessKeyId: access key id
                  awsSecretAccessKey: access secret key
                  awsRegion: aws region name

      hostPort: <hostPort>

      databaseSchema: schema

      # connectionOptions:
      #   key: value

      # connectionArguments:
      #   key: value

  sourceConfig:
    config:
      type: DatabaseMetadata
      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: {}

{% partial file="workflow-config-yaml.md" /%}

{% /codeBlock %}

{% /codePreview %}

2. Run with the CLI

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

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.

Data Profiler

The Data Profiler workflow will be using the orm-profiler processor.

After running a Metadata Ingestion workflow, we can run Data Profiler workflow. While the serviceName will be the same to that was used in Metadata Ingestion, so the ingestion bot can get the serviceConnection details from the server.

1. Define the YAML Config

This is a sample config for the profiler:

{% codePreview %}

{% codeInfoContainer %}

{% codeInfo srNumber=15 %}

Source Configuration - Source Config

You can find all the definitions and types for the sourceConfig here.

generateSampleData: Option to turn on/off generating sample data.

{% /codeInfo %}

{% codeInfo srNumber=16 %}

profileSample: Percentage of data or no. of rows we want to execute the profiler and tests on.

{% /codeInfo %}

{% codeInfo srNumber=17 %}

threadCount: Number of threads to use during metric computations.

{% /codeInfo %}

{% codeInfo srNumber=18 %}

processPiiSensitive: Optional configuration to automatically tag columns that might contain sensitive information.

{% /codeInfo %}

{% codeInfo srNumber=19 %}

confidence: Set the Confidence value for which you want the column to be marked

{% /codeInfo %}

{% codeInfo srNumber=20 %}

timeoutSeconds: Profiler Timeout in Seconds

{% /codeInfo %}

{% codeInfo srNumber=21 %}

databaseFilterPattern: Regex to only fetch databases that matches the pattern.

{% /codeInfo %}

{% codeInfo srNumber=22 %}

schemaFilterPattern: Regex to only fetch tables or databases that matches the pattern.

{% /codeInfo %}

{% codeInfo srNumber=23 %}

tableFilterPattern: Regex to only fetch tables or databases that matches the pattern.

{% /codeInfo %}

{% codeInfo srNumber=24 %}

Processor Configuration

Choose the orm-profiler. Its config can also be updated to define tests from the YAML itself instead of the UI:

tableConfig: tableConfig allows you to set up some configuration at the table level. {% /codeInfo %}

{% codeInfo srNumber=25 %}

Sink Configuration

To send the metadata to OpenMetadata, it needs to be specified as type: metadata-rest. {% /codeInfo %}

{% codeInfo srNumber=26 %}

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:

{% /codeInfo %}

{% /codeInfoContainer %}

{% codeBlock fileName="filename.yaml" %}

source:
  type: mysql
  serviceName: <service name>
  sourceConfig:
    config:
      type: Profiler

      generateSampleData: true

      # profileSample: 85

      # threadCount: 5

      processPiiSensitive: false

      # confidence: 80

      # timeoutSeconds: 43200

      # 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>
    #     profileSample: <number between 0 and 99> # default 

    #     profileSample: <number between 0 and 99> # default will be 100 if omitted
    #     profileQuery: <query to use for sampling data for the profiler>
    #     columnConfig:
    #       excludeColumns:
    #         - <column name>
    #       includeColumns:
    #         - columnName: <column name>
    #         - metrics:
    #           - MEAN
    #           - MEDIAN
    #           - ...
    #     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>

sink:
  type: metadata-rest
  config: {}

workflowConfig:
  # loggerLevel: DEBUG  # DEBUG, INFO, WARN or ERROR
  openMetadataServerConfig:
    hostPort: <OpenMetadata host and port>
    authProvider: <OpenMetadata auth provider>

{% /codeBlock %}

{% /codePreview %}

• You can learn more about how to configure and run the Profiler Workflow to extract Profiler data and execute the Data Quality from here

2. Run with the CLI

After saving the YAML config, we will run the command the same way we did for the metadata ingestion:

metadata profile -c <path-to-yaml>

Note how instead of running ingest, we are using the profile command to select the Profiler workflow.

SSL Configuration

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.

{% codePreview %}

{% codeInfoContainer %}

{% codeInfo srNumber=27 %}

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.

{% /codeInfo %}

{% /codeInfoContainer %}

{% codeBlock fileName="filename.yaml" %}

source:
  type: mysql
  serviceName: "<service name>"
  serviceConnection:
    config:
      type: Mysql
      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

{% /codeBlock %} {% /codePreview %}

dbt Integration

{% tilesContainer %}

{% tile icon="mediation" title="dbt Integration" description="Learn more about how to ingest dbt models' definitions and their lineage." link="/connectors/ingestion/workflows/dbt" /%}

{% /tilesContainer %}

Related

{% tilesContainer %}

{% tile title="Ingest with Airflow" description="Configure the ingestion using Airflow SDK" link="/connectors/database/mysql/airflow" / %}

{% /tilesContainer %}