> ## Documentation Index > Fetch the complete documentation index at: https://docs.open-metadata.org/llms.txt > Use this file to discover all available pages before exploring further. # Run the Databend Connector Externally > Use YAML to configure Databend database connections with metadata ingestion, profiling, and data quality. ![Databend](https://docs.open-metadata.org/public/images/connectors/databend.webp) # Databend BETA This section provides guides and references for the Databend connector. Configure Databend metadata workflows externally with YAML: * [Requirements](#requirements) * [Metadata Ingestion](#metadata-ingestion) * [Data Profiler](#data-profiler) * [Data Quality](#data-quality) ## How to Run the Connector Externally 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. If, instead, you want to manage your workflows externally on your preferred orchestrator, you can check the following docs to run the Ingestion Framework **anywhere**. > **[External Schedulers](https://docs.open-metadata.org/v2.1.x-SNAPSHOT/deployment/ingestion.md)** > > Get more information about running the Ingestion Framework Externally ## Requirements OpenMetadata connects to the Databend HTTP query service with a SQLAlchemy driver, using a username and password. The connecting user must be able to read the system and `information_schema` metadata, and to read the databases and tables you want to ingest. ### Entity Mapping OpenMetadata ingests only the Databend `default` catalog. Databend objects map to OpenMetadata entities as follows: | Databend | OpenMetadata | | - | - | | Catalog (`default`) | Database | | Database | Schema | | Tables and views | Tables | ### Profiler and Data Quality Running the profiler workflow, data quality tests, or data diff requires `SELECT` on the tables and schemas being profiled or tested. For more information, see [Profiler Workflow](https://docs.open-metadata.org/v2.1.x-SNAPSHOT/how-to-guides/data-quality-observability/profiler/profiler-workflow.md) and [Data Quality](https://docs.open-metadata.org/v2.1.x-SNAPSHOT/how-to-guides/data-quality-observability/quality.md). ### Python Requirements Use Python 3.10 or later. Python 3.12 is recommended, because it is what the OpenMetadata 2.0 ingestion images use. To confirm the supported range for your release, check the `Requires-Python` metadata of that release’s `openmetadata-ingestion` package. To run the Databend ingestion, install: ```bash theme={null} pip3 install "openmetadata-ingestion[databend]" ``` ## Metadata Ingestion All connectors are defined as JSON Schemas. See the [Databend connection JSON Schema](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/entity/services/connections/database/databendConnection.json) for the full set of properties. To create and run a metadata ingestion workflow, create a YAML configuration. The configuration connects to the source, processes entities if needed, and reaches 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 Use the following YAML configuration as a starting point. #### Source Configuration Configure the source type and service name for your Databend connector. #### Username **username**: Username to connect to Databend. The user must be able to read system and `information_schema` metadata. #### Password **password**: Password to connect to Databend. #### Host Port **hostPort**: Host and port of the Databend HTTP query service. The default self-hosted port is `8000`. #### Database Schema and Connection Options **databaseSchema**: Optional Databend database to ingest. It is also used as the initial database of the connection. When omitted, the connection starts in the `default` database and OpenMetadata scans all accessible Databend databases as schemas. **connectionOptions**: Additional options appended to the Databend connection URL. For a non-TLS HTTP endpoint, such as the default self-hosted port `8000`, set `sslmode` to `disable`. For a TLS endpoint, set `sslmode` to `enable`. #### 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. * **markDeletedStoredProcedures**: Optional configuration to soft delete stored procedures in OpenMetadata if the source stored procedures are deleted. Also, if the stored procedure is deleted, all the associated entities like lineage, etc., with that stored procedure will be deleted. * **markDeletedSchemas**: Optional configuration to soft delete schemas stored in OpenMetadata if the source schema is deleted. Setting this flag to true will only keep filtered schemas and delete any other schemas that do not match schemaFilterPattern or do not exist at source. * **markDeletedDatabases**: Additional optional configuration for soft deletion, providing a granular option to select which particular entities should be deleted. * **includeTables**: Set to `true` or `false` to ingest table data. Default is `true`. * **includeViews**: Set to `true` or `false` to ingest view definitions. * **includeTags**: Optional configuration to toggle the tags ingestion. * **includeOwners**: Set the **Include Owners** toggle to control whether to include owners to the ingested entity if the owner email matches with a user stored in the OM server as part of metadata ingestion. If the ingested entity already exists and has an owner, the owner will not be overwritten. * **ownerConfig**: Advanced, hierarchical configuration for assigning owners to databases, schemas, and tables during ingestion, with per-entity mappings and inheritance. For more information, see [Hierarchical Owner Configuration](https://docs.open-metadata.org/connectors/ingestion/workflows/metadata/hierarchical-owner-configuration.md). * **includeStoredProcedures**: Optional configuration to toggle the Stored Procedures ingestion. * **includeDDL**: Optional configuration to toggle the DDL Statements ingestion. * **overrideMetadata** *(boolean)*: Set the **Override Metadata** toggle to control whether to override the existing metadata in the OpenMetadata server with the metadata fetched from the source. If the toggle is set to true, the metadata fetched from the source will override the existing metadata in the OpenMetadata server. If the toggle is set to false, the metadata fetched from the source will not override the existing metadata in the OpenMetadata server. This is applicable for fields like description, tags, owner, and displayName. * **queryLogDuration**: Configuration to tune how far we want to look back in query logs to process Stored Procedures results. * **queryParsingTimeoutLimit**: Configuration to set the timeout for parsing the query in seconds. * **useFqnForFiltering**: Regex will be applied on the fully qualified name (for example, `service_name.db_name.schema_name.table_name`) instead of the raw name (for example, `table_name`). * **databaseFilterPattern**, **schemaFilterPattern**: Note that the filter supports regex as include or exclude. You can find examples [here](https://docs.open-metadata.org/connectors/ingestion/workflows/metadata/filter-patterns/database.md). * **tableFilterPattern**: Note that the filter supports regex as include or exclude. You can find examples [here](https://docs.open-metadata.org/connectors/ingestion/workflows/metadata/filter-patterns/table.md). * **threads (beta)**: The number of threads to use when extracting the metadata using multithreading. * **databaseMetadataConfigType** *(string)*: Database Source Config Metadata Pipeline type. * **incremental (beta)**: Incremental Extraction configuration. Currently implemented for [BigQuery](https://docs.open-metadata.org/connectors/ingestion/workflows/metadata/incremental-extraction/bigquery.md), [Redshift](https://docs.open-metadata.org/connectors/ingestion/workflows/metadata/incremental-extraction/redshift.md), and [Snowflake](https://docs.open-metadata.org/connectors/ingestion/workflows/metadata/incremental-extraction/snowflake.md). #### Sink Configuration To send the metadata to OpenMetadata, it needs to be specified as `type: metadata-rest`. #### Workflow Configuration The main property here is `openMetadataServerConfig`, where you can define the host and security provider of your OpenMetadata installation. * **loggerLevel**: Specify the logger level depending on your needs. If you are troubleshooting an ingestion, use `DEBUG` for more detailed traces. * **JWT token**: JWT tokens allow clients to authenticate against the OpenMetadata server. See [Enable JWT Tokens](https://docs.open-metadata.org/deployment/security/enable-jwt-tokens.md) and [JWT Troubleshooting](https://docs.open-metadata.org/deployment/security/jwt-troubleshooting.md) for more information. * **storeServiceConnection**: If set to `true` (default), sensitive information is stored encrypted with the Fernet Key or externally if you have configured a [Secrets Manager](https://docs.open-metadata.org/deployment/secrets-manager.md). If set to `false`, the service is created, but the service connection information is only used by the Ingestion Framework at runtime and is not sent to the OpenMetadata server. * **SSL configuration**: If you have added SSL to the [OpenMetadata server](https://docs.open-metadata.org/deployment/security/enable-ssl.md), configure the certificates for ingestion. Set `verifySSL` to `ignore`, or set it to `validate` and provide `sslConfig.caCertificate` with a local path to the server certificate. See [SSL Troubleshooting](https://docs.open-metadata.org/deployment/security/enable-ssl/ssl-troubleshooting.md) for more information. * **ingestionPipelineFQN**: Fully qualified name of the ingestion pipeline, used to identify the current ingestion pipeline. databend\_config.yaml Copy full code ```yaml theme={null} source: type: databend serviceName: local_databend serviceConnection: config: type: Databend username: # REQUIRED password: # REQUIRED hostPort: # REQUIRED - format: host:port (default port 8000) # databaseSchema: # connectionOptions: # sslmode: disable # disable for non-TLS HTTP (port 8000), enable for TLS ``` ```yaml theme={null} sourceConfig: config: type: DatabaseMetadata markDeletedTables: true markDeletedStoredProcedures: true markDeletedSchemas: true markDeletedDatabases: true includeTables: true includeViews: true # includeTags: true # includeOwners: false # ownerConfig: # default: data-platform-team # database: # database1: owner1 # databaseSchema: # database1.schema1: owner1 # table: # database1.schema1.table1: owner1 # enableInheritance: true # includeStoredProcedures: true # includeDDL: true # overrideMetadata: false # queryLogDuration: 1 # queryParsingTimeoutLimit: 300 # useFqnForFiltering: false # threads: 1 # databaseMetadataConfigType: () # incremental: # enabled: true # lookbackDays: 7 # safetyMarginDays: 1 # databaseFilterPattern: # includes: # - database1 # - database2 # excludes: # - database3 # - database4 # schemaFilterPattern: # includes: # - schema1 # - schema2 # excludes: # - schema3 # - schema4 # tableFilterPattern: # includes: # - users # - type_test # excludes: # - table3 # - table4 ``` ```yaml theme={null} sink: type: metadata-rest config: {} ``` ```yaml theme={null} workflowConfig: loggerLevel: INFO # DEBUG, INFO, WARNING or ERROR openMetadataServerConfig: hostPort: "http://localhost:8585/api" authProvider: openmetadata securityConfig: jwtToken: "{bot_jwt_token}" ## Store the service Connection information storeServiceConnection: true # false ## Secrets Manager Configuration # secretsManagerProvider: aws, azure or noop # secretsManagerLoader: airflow or env ## If SSL, fill the following # verifySSL: validate # or ignore # sslConfig: # caCertificate: /local/path/to/certificate # ingestionPipelineFQN: . ## e.g., "my_redshift.metadata" ``` ### 2. Run with the CLI First, we will need to save the YAML file. Afterward, and with all requirements installed, we can run: ```bash theme={null} 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. ## Data Profiler The Data Profiler workflow will be using the `orm-profiler` processor. After running a Metadata Ingestion workflow, we can run the 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: #### Source Configuration Configure the source type and service name for your profiler workflow. #### Profiler Config Type **type**: Set to `Profiler` for data profiling ingestion. #### Profile Sample Config **profileSampleConfig**: How much data the profiler and tests run on. * **sampleConfigType**: `DYNAMIC` (default) resolves the sample size at runtime from the table's row count. `STATIC` uses a fixed size you set yourself. * **config**: the settings for the chosen type. With `DYNAMIC`, `smartSampling: true` applies the built-in tiers. Set it to `false` and provide `thresholds` to define your own. With `STATIC`, set `profileSample`, and optionally `profileSampleType` and `samplingMethodType`. #### Thread Count **threadCount**: Number of threads to use during metric computations. #### Timeout Seconds **timeoutSeconds**: Profiler Timeout in Seconds. #### Database Filter Pattern **databaseFilterPattern**: Regex to only fetch databases that matches the pattern. #### Schema Filter Pattern **schemaFilterPattern**: Regex to only fetch tables or databases that matches the pattern. #### Table Filter Pattern **tableFilterPattern**: Regex to only fetch tables or databases that matches the pattern. #### 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 including: * Profile sample settings per table * Custom profile queries * Column-level configuration (include/exclude columns, specific metrics) * Partition configuration for large tables #### Sink Configuration To send the metadata to OpenMetadata, it needs to be specified as `type: metadata-rest`. \{connector}\_profiler.yaml Copy full code ```yaml theme={null} source: type: databend serviceName: databend sourceConfig: config: type: Profiler # profileSampleConfig: # sampleConfigType: DYNAMIC # DYNAMIC (default) or STATIC # config: # smartSampling: true # threadCount: 5 # timeoutSeconds: 43200 # databaseFilterPattern: # includes: # - database1 # - database2 # excludes: # - database3 # schemaFilterPattern: # includes: # - schema1 # - schema2 # excludes: # - schema3 # tableFilterPattern: # includes: # - table1 # - table2 # excludes: # - table3 processor: type: orm-profiler config: {} # Remove braces if adding properties # tableConfig: # - fullyQualifiedName: # profileSampleConfig: # sampleConfigType: STATIC # omit entirely to inherit dynamic sampling # config: # profileSample: # profileQuery: # columnConfig: # excludeColumns: # - # includeColumns: # - columnName: # - metrics: # - MEAN # - MEDIAN # - ... # partitionConfig: # enablePartitioning: # partitionColumnName: # partitionIntervalType: # Pick one of the variation shown below # ----'TIME-UNIT' or 'INGESTION-TIME'------- # partitionInterval: # partitionIntervalUnit: # ------------'INTEGER-RANGE'--------------- # partitionIntegerRangeStart: # partitionIntegerRangeEnd: # -----------'COLUMN-VALUE'---------------- # partitionValues: # - # - sink: type: metadata-rest config: {} ``` * You can learn more about how to configure and run the Profiler Workflow to extract Profiler data and execute the Data Quality from [here](https://docs.open-metadata.org/how-to-guides/data-quality-observability/profiler/profiler-workflow.md) ### 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 theme={null} metadata profile -c ``` Note now instead of running `ingest`, we are using the `profile` command to select the Profiler workflow. > **[Data Profiler](https://docs.open-metadata.org/v2.1.x-SNAPSHOT/how-to-guides/data-quality-observability/profiler/profiler-workflow.md)** > > Find more information about the Data Profiler here ## Auto Classification The Auto Classification workflow will be using the `orm-profiler` processor. After running a Metadata Ingestion workflow, we can run the Auto Classification 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 Auto Classification Workflow: #### Source Configuration Configure the source type and service name for your auto classification workflow. #### Auto Classification Config Type **type**: Set to `AutoClassification` for automatic PII tagging. #### Store Sample Data **storeSampleData**: Option to turn on/off storing sample data. If enabled, we will ingest sample data for each table. #### Enable Auto Classification **enableAutoClassification**: Optional configuration to automatically tag columns that might contain sensitive information. #### Confidence **confidence**: Set the Confidence value for which you want the column to be tagged as PII. Confidence value ranges from 0 to 100. A higher number will yield less false positives but more false negatives. A lower number will yield more false positives but less false negatives. #### Database Filter Pattern **databaseFilterPattern**: Regex to only fetch databases that matches the pattern. #### Schema Filter Pattern **schemaFilterPattern**: Regex to only fetch tables or databases that matches the pattern. #### Table Filter Pattern **tableFilterPattern**: Regex to only fetch tables or databases that matches the pattern. #### 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. #### Sink Configuration To send the metadata to OpenMetadata, it needs to be specified as `type: metadata-rest`. \{connector}\_auto\_classification.yaml Copy full code ```yaml theme={null} source: type: databend serviceName: databend sourceConfig: config: type: AutoClassification # storeSampleData: true # enableAutoClassification: true # confidence: 80 # databaseFilterPattern: # includes: # - database1 # - database2 # excludes: # - database3 # schemaFilterPattern: # includes: # - schema1 # - schema2 # excludes: # - schema3 # tableFilterPattern: # includes: # - table1 # - table2 # excludes: # - table3 processor: type: orm-profiler config: {} sink: type: metadata-rest config: {} ``` ### 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 theme={null} metadata classify -c ``` > [!TIP] > > Now instead of running `ingest`, we are using the `classify` command to select the Auto Classification workflow. ## Data Quality ### Adding Data Quality Test Cases from yaml config When creating a JSON config for a test workflow the source configuration is very simple. ```yaml theme={null} source: type: TestSuite serviceName: sourceConfig: config: type: TestSuite entityFullyQualifiedName: ``` The only sections you need to modify here are the `serviceName` (this name needs to be unique) and `entityFullyQualifiedName` (the entity for which we'll be executing tests against) keys. Once you have defined your source configuration you'll need to define te processor configuration. ```yaml theme={null} processor: type: "orm-test-runner" config: forceUpdate: testCases: - name: testDefinitionName: columnValueLengthsToBeBetween columnName: parameterValues: - name: minLength value: 10 - name: maxLength value: 25 - name: testDefinitionName: tableRowCountToEqual parameterValues: - name: value value: 10 ``` The processor type should be set to ` "orm-test-runner"`. For accepted test definition names and parameter value names refer to the [tests page](https://docs.open-metadata.org/how-to-guides/data-quality-observability/quality/tests-yaml.md). > [!TIP] > > Note that while you can define tests directly in this YAML configuration, running the > workflow will execute ALL THE TESTS present in the table, regardless of what you are defining in the YAML. > > This makes it easy for any user to contribute tests via the UI, while maintaining the test execution external. You can keep your YAML config as simple as follows if the table already has tests. ```yaml theme={null} processor: type: "orm-test-runner" config: {} ``` ### Key reference: * `forceUpdate`: if the test case exists (base on the test case name) for the entity, implements the strategy to follow when running the test (i.e. whether or not to update parameters) * `testCases`: list of test cases to add to the entity referenced. Note that we will execute all the tests present in the Table. * `name`: test case name * `testDefinitionName`: test definition * `columnName`: only applies to column test. The name of the column to run the test against * `parameterValues`: parameter values of the test The `sink` and `workflowConfig` will have the same settings as the ingestion and profiler workflow. ### Full `yaml` config example ```yaml theme={null} source: type: TestSuite serviceName: MyAwesomeTestSuite sourceConfig: config: type: TestSuite entityFullyQualifiedName: MySQL.default.openmetadata_db.tag_usage # testCases: ["run_only_this_test_case"] # Optional, if not provided all tests will be executed processor: type: "orm-test-runner" config: forceUpdate: false testCases: - name: column_value_length_tagFQN testDefinitionName: columnValueLengthsToBeBetween columnName: tagFQN parameterValues: - name: minLength value: 10 - name: maxLength value: 25 - name: table_row_count_test testDefinitionName: tableRowCountToEqual parameterValues: - name: value value: 10 sink: type: metadata-rest config: {} workflowConfig: openMetadataServerConfig: hostPort: authProvider: ``` ### How to Run Tests To run the tests from the CLI execute the following command ``` metadata test -c /path/to/my/config.yaml ``` This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.