--- title: Run Snowflake Connector using the CLI slug: /connectors/database/snowflake/cli --- # Run Snowflake using the metadata CLI | Stage | Metadata |Query Usage | Data Profiler | Data Quality | Lineage | DBT | Supported Versions | |:------:|:------:|:-----------:|:-------------:|:------------:|:-------:|:---:|:------------------:| | PROD | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | -- |
| Lineage | Table-level | Column-level | |:------:|:-----------:|:-------------:| | ✅ | ✅ | ✅ |
In this section, we provide guides and references to use the Snowflake connector. Configure and schedule Snowflake metadata and profiler workflows from the OpenMetadata UI: - [Requirements](#requirements) - [Metadata Ingestion](#metadata-ingestion) - [Query Usage](#query-usage) - [Data Profiler](#data-profiler) - [Lineage](#lineage) - [dbt Integration](#dbt-integration) ## 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 Snowflake ingestion, you will need to install: ```bash pip3 install "openmetadata-ingestion[snowflake]" ``` If you want to run the Usage Connector, you'll also need to install: ```bash pip3 install "openmetadata-ingestion[snowflake-usage]" ``` To ingest basic metadata snowflake user must have the following priviledges: - `USAGE` Privilege on Warehouse - `USAGE` Privilege on Database - `USAGE` Privilege on Schema - `SELECT` Privilege on Tables ```sql -- Create New Role CREATE ROLE NEW_ROLE; -- Create New User CREATE USER NEW_USER DEFAULT_ROLE=NEW_ROLE PASSWORD='PASSWORD'; -- Grant role to user GRANT ROLE NEW_ROLE TO USER NEW_USER; -- Grant USAGE Privilege on Warehouse to New Role GRANT USAGE ON WAREHOUSE WAREHOUSE_NAME TO ROLE NEW_ROLE; -- Grant USAGE Privilege on Database to New Role GRANT USAGE ON DATABASE TEST_DB TO ROLE NEW_ROLE; -- Grant USAGE Privilege on required Schemas to New Role GRANT USAGE ON SCHEMA TEST_SCHEMA TO ROLE NEW_ROLE; -- Grant SELECT Privilege on required tables & views to New Role GRANT SELECT ON ALL TABLES IN SCHEMA TEST_SCHEMA TO ROLE NEW_ROLE; GRANT SELECT ON ALL VIEWS IN SCHEMA TEST_SCHEMA TO ROLE NEW_ROLE; ``` While running the usage workflow, Openmetadata fetches the query logs by querying `snowflake.account_usage.query_history` table. For this the snowflake user should be granted the `ACCOUNTADMIN` role or a role granted IMPORTED PRIVILEGES on the database `SNOWFLAKE`. ```sql -- Grant IMPORTED PRIVILEGES on all Schemas of SNOWFLAKE DB to New Role GRANT IMPORTED PRIVILEGES ON ALL SCHEMAS IN DATABASE SNOWFLAKE TO ROLE NEW_ROLE; ``` If ingesting tags, the user should also have permissions to query `snowflake.account_usage.tag_references`.For this the snowflake user should be granted the `ACCOUNTADMIN` role or a role granted IMPORTED PRIVILEGES on the database ```sql -- Grant IMPORTED PRIVILEGES on all Schemas of SNOWFLAKE DB to New Role GRANT IMPORTED PRIVILEGES ON ALL SCHEMAS IN DATABASE SNOWFLAKE TO ROLE NEW_ROLE; ``` You can find more information about the `account_usage` schema [here](https://docs.snowflake.com/en/sql-reference/account-usage.html). ## Metadata Ingestion All connectors are defined as JSON Schemas. [Here](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/entity/services/connections/database/snowflakeConnection.json) you can find the structure to create a connection to Snowflake. 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](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/metadataIngestion/workflow.json) ### 1. Define the YAML Config This is a sample config for Snowflake: ```yaml source: type: snowflake serviceName: serviceConnection: config: type: Snowflake username: password: warehouse: account: # database: includeTempTables: false # hostPort: account.region.service.snowflakecomputing.com # privateKey: | # # <...> # snowflakePrivatekeyPassphrase: # role: 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: {} workflowConfig: # loggerLevel: DEBUG # DEBUG, INFO, WARN or ERROR openMetadataServerConfig: hostPort: "" authProvider: "" ``` #### Source Configuration - Service Connection - **username**: Specify the User to connect to Snowflake. It should have enough privileges to read all the metadata. - **password**: Password to connect to Snowflake. - **account**: Enter the details for the Snowflake Account. - **role**: Enter the details of the Snowflake Account Role. This is an optional detail. - **warehouse**: Warehouse name. - **database**: The database of the data source is an optional parameter, if you would like to restrict the metadata reading to a single database. If left blank, OpenMetadata ingestion attempts to scan all the databases. - **privateKey**: Connection to Snowflake instance via Private Key instead of a Password. - The multi-line key needs to be correctly formatted in YAML so a literal block scalar which retains new lines is recommended (`|`). - **includeTempTables**: Optional configuration for ingestion of TRANSIENT and TEMPORARY tables, By default, it will skip the TRANSIENT and TEMPORARY tables. - **snowflakePrivatekeyPassphrase**: Snowflake Passphrase Key used with and encrypted Private Key. - **Connection Options (Optional)**: Enter the details for any additional connection options that can be sent to Snowflake 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 Snowflake 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"` #### Source Configuration - Source Config The `sourceConfig` is defined [here](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/metadataIngestion/databaseServiceMetadataPipeline.json): - `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: hostPort: 'http://localhost:8585/api' authProvider: openmetadata securityConfig: jwtToken: '{bot_jwt_token}' ``` 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). You can find the different implementation of the ingestion below. ### Openmetadata JWT Auth ```yaml workflowConfig: openMetadataServerConfig: hostPort: 'http://localhost:8585/api' authProvider: openmetadata securityConfig: jwtToken: '{bot_jwt_token}' ``` ### 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}' ``` ### 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 ``` 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. ## Query Usage To ingest the Query Usage, the `serviceConnection` configuration will remain the same. However, the `sourceConfig` is now modeled after this JSON Schema. ### 1. Define the YAML Config This is a sample config for Snowflake Usage: ```yaml source: type: snowflake-usage serviceName: "" serviceConnection: config: type: Snowflake username: password: warehouse: account: # database: # hostPort: account.region.service.snowflakecomputing.com # privateKey: # snowflakePrivatekeyPassphrase: # role: sourceConfig: config: # Number of days to look back queryLogDuration: 7 # This is a directory that will be DELETED after the usage runs stageFileLocation: # resultLimit: 1000 # If instead of getting the query logs from the database we want to pass a file with the queries # queryLogFilePath: path-to-file processor: type: query-parser config: {} stage: type: table-usage config: filename: "/tmp/snowflake_usage" bulkSink: type: metadata-usage config: filename: "/tmp/snowflake_usage" workflowConfig: # loggerLevel: DEBUG # DEBUG, INFO, WARN or ERROR openMetadataServerConfig: hostPort: "" authProvider: "" ``` #### Source Configuration - Service Connection 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/bigQueryConnection.json). They are the same as metadata ingestion. #### Source Configuration - Source Config The `sourceConfig` is defined [here](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/metadataIngestion/databaseServiceQueryUsagePipeline.json). - `queryLogDuration`: Configuration to tune how far we want to look back in query logs to process usage data. - `resultLimit`: Configuration to set the limit for query logs #### Processor, Stage and Bulk Sink To specify where the staging files will be located. Note that the location is a directory that will be cleaned at the end of the ingestion. #### Workflow Configuration The same as the metadata ingestion. ### 2. Run with the CLI There is an extra requirement to run the Usage pipelines. You will need to install: ```bash pip3 install --upgrade 'openmetadata-ingestion[snowflake-usage]' ``` After saving the YAML config, we will run the command the same way we did for the metadata ingestion: ```bash metadata ingest -c ``` ## Data Profiler 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: snowflake serviceName: "" serviceConnection: config: type: Snowflake username: password: warehouse: account: # database: # hostPort: account.region.service.snowflakecomputing.com # privateKey: # snowflakePrivatekeyPassphrase: # role: 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: # profileSample: # default will be 100 if omitted # profileQuery: # columnConfig: # excludeColumns: # - # includeColumns: # - columnName: # - metrics: # - MEAN # - MEDIAN # - ... # partitionConfig: # enablePartitioning: # partitionColumnName: # partitionInterval: # partitionIntervalUnit: sink: type: metadata-rest config: {} workflowConfig: # loggerLevel: DEBUG # DEBUG, INFO, WARN or ERROR openMetadataServerConfig: hostPort: "" authProvider: "" ``` #### Source Configuration - 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/snowflakeConnection.json). - The `sourceConfig` is defined [here](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/metadataIngestion/databaseServiceProfilerPipeline.json). 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:
profileSample: partitionConfig: partitionField: partitionQueryDuration: partitionValues: profileQuery: columnConfig: excludeColumns: - includeColumns: - columnName: - 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 ``` Note how instead of running `ingest`, we are using the `profile` command to select the Profiler workflow. ## Lineage You can learn more about how to ingest lineage [here](/connectors/ingestion/workflows/lineage). ## dbt Integration You can learn more about how to ingest dbt models' definitions and their lineage [here](/connectors/ingestion/workflows/dbt).