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title | slug |
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Run DynamoDB Connector using the CLI | /connectors/database/dynamodb/cli |
Run DynamoDB using the metadata CLI
In this section, we provide guides and references to use the DynamoDB connector.
Configure and schedule DynamoDB metadata and profiler workflows from the OpenMetadata UI:
Requirements
To deploy OpenMetadata, check the Deployment guides.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 DynamoDB ingestion, you will need to install:
pip3 install "openmetadata-ingestion[dynamodb]"
Metadata Ingestion
All connectors are defined as JSON Schemas. Here you can find the structure to create a connection to DynamoDB.
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 DynamoDB:
source:
type: bigquery
serviceName: "<service name>"
serviceConnection:
config:
type: BigQuery
credentials:
gcsConfig:
type: My Type
projectId: project ID
privateKeyId: us-east-2
privateKey: |
-----BEGIN PRIVATE KEY-----
Super secret key
-----END PRIVATE KEY-----
clientEmail: client@mail.com
clientId: 1234
# authUri: https://accounts.google.com/o/oauth2/auth (default)
# tokenUri: https://oauth2.googleapis.com/token (default)
# authProviderX509CertUrl: https://www.googleapis.com/oauth2/v1/certs (default)
clientX509CertUrl: https://cert.url
sourceConfig:
config:
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
# For dbt, choose one of Cloud, Local, HTTP, S3 or GCS configurations
# dbtConfigSource:
# # For cloud
# dbtCloudAuthToken: token
# dbtCloudAccountId: ID
# # For Local
# dbtCatalogFilePath: path-to-catalog.json
# dbtManifestFilePath: path-to-manifest.json
# # For HTTP
# dbtCatalogHttpPath: http://path-to-catalog.json
# dbtManifestHttpPath: http://path-to-manifest.json
# # For S3
# dbtSecurityConfig: # These are modeled after all AWS credentials
# awsAccessKeyId: KEY
# awsSecretAccessKey: SECRET
# awsRegion: us-east-2
# dbtPrefixConfig:
# dbtBucketName: bucket
# dbtObjectPrefix: "dbt/"
# # For GCS
# dbtSecurityConfig: # These are modeled after all GCS credentials
# type: My Type
# projectId: project ID
# privateKeyId: us-east-2
# privateKey: |
# -----BEGIN PRIVATE KEY-----
# Super secret key
# -----END PRIVATE KEY-----
# clientEmail: client@mail.com
# clientId: 1234
# authUri: https://accounts.google.com/o/oauth2/auth (default)
# tokenUri: https://oauth2.googleapis.com/token (default)
# authProviderX509CertUrl: https://www.googleapis.com/oauth2/v1/certs (default)
# clientX509CertUrl: https://cert.url (URI)
# dbtPrefixConfig:
# dbtBucketName: bucket
# dbtObjectPrefix: "dbt/"
sink:
type: metadata-rest
config: {}
workflowConfig:
# loggerLevel: DEBUG # DEBUG, INFO, WARN or ERROR
openMetadataServerConfig:
hostPort: "<OpenMetadata host and port>"
authProvider: "<OpenMetadata auth provider>"
Source Configuration - Service Connection
- awsAccessKeyId: Enter your secure access key ID for your DynamoDB connection. The specified key ID should be authorized to read all databases you want to include in the metadata ingestion workflow.
- awsSecretAccessKey: Enter the Secret Access Key (the passcode key pair to the key ID from above).
- awsRegion: Enter the location of the amazon cluster that your data and account are associated with.
- awsSessionToken: The AWS session token is an optional parameter. If you want, enter the details of your temporary session token.
- endPointURL: Your DynamoDB connector will automatically determine the AWS DynamoDB endpoint URL based on the region. You may override this behavior by entering a value to the endpoint URL.
- Connection Options (Optional): Enter the details for any additional connection options that can be sent to DynamoDB 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 DynamoDB 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"
- In case you are using Single-Sign-On (SSO) for authentication, add the
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.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.,
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:
workflowConfig:
openMetadataServerConfig:
hostPort: 'http://localhost:8585/api'
authProvider: openmetadata
securityConfig:
jwtToken: '{bot_jwt_token}'
We support different security providers. You can find their definitions here. You can find the different implementation of the ingestion below.
Openmetadata JWT Auth
workflowConfig:
openMetadataServerConfig:
hostPort: 'http://localhost:8585/api'
authProvider: openmetadata
securityConfig:
jwtToken: '{bot_jwt_token}'
Auth0 SSO
workflowConfig:
openMetadataServerConfig:
hostPort: 'http://localhost:8585/api'
authProvider: auth0
securityConfig:
clientId: '{your_client_id}'
secretKey: '{your_client_secret}'
domain: '{your_domain}'
Azure SSO
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
workflowConfig:
openMetadataServerConfig:
hostPort: 'http://localhost:8585/api'
authProvider: custom-oidc
securityConfig:
clientId: '{your_client_id}'
secretKey: '{your_client_secret}'
domain: '{your_domain}'
Google SSO
workflowConfig:
openMetadataServerConfig:
hostPort: 'http://localhost:8585/api'
authProvider: google
securityConfig:
secretKey: '{path-to-json-creds}'
Okta SSO
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
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
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
workflowConfig:
openMetadataServerConfig:
hostPort: 'http://localhost:8585/api'
authProvider: custom-oidc
securityConfig:
clientId: '{your_client_id}'
secretKey: '{your_client_secret}'
domain: '{your_domain}'
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.
dbt Integration
You can learn more about how to ingest dbt models' definitions and their lineage here.