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title | slug |
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DeltaLake | /connectors/database/deltalake |
{% connectorDetailsHeader name="DeltaLake" stage="PROD" platform="OpenMetadata" availableFeatures=["Metadata", "dbt"] unavailableFeatures=["Query Usage", "Data Profiler", "Data Quality", "Lineage", "Column-level Lineage", "Owners", "Tags", "Stored Procedures"] / %}
In this section, we provide guides and references to use the Deltalake connector.
Configure and schedule Deltalake metadata and profiler workflows from the OpenMetadata UI:
{% partial file="/v1.4/connectors/ingestion-modes-tiles.md" variables={yamlPath: "/connectors/database/deltalake/yaml"} /%}
Requirements
Deltalake requires to run with Python 3.8, 3.9 or 3.10. We do not yet support the Delta connector for Python 3.11
Metadata Ingestion
{% partial file="/v1.4/connectors/metadata-ingestion-ui.md" variables={ connector: "Deltalake", selectServicePath: "/images/v1.4/connectors/deltalake/select-service.png", addNewServicePath: "/images/v1.4/connectors/deltalake/add-new-service.png", serviceConnectionPath: "/images/v1.4/connectors/deltalake/service-connection.png", } /%}
{% stepsContainer %} {% extraContent parentTagName="stepsContainer" %}
Connection Details
- Metastore Host Port: Enter the Host & Port of Hive Metastore Service to configure the Spark Session. Either
of
metastoreHostPort
,metastoreDb
ormetastoreFilePath
is required. - Metastore File Path: Enter the file path to local Metastore in case Spark cluster is running locally. Either
of
metastoreHostPort
,metastoreDb
ormetastoreFilePath
is required. - Metastore DB: The JDBC connection to the underlying Hive metastore DB. Either
of
metastoreHostPort
,metastoreDb
ormetastoreFilePath
is required. - appName (Optional): Enter the app name of spark session.
- Connection Arguments (Optional): Key-Value pairs that will be used to pass extra
config
elements to the Spark Session builder.
We are internally running with pyspark
3.X and delta-lake
2.0.0. This means that we need to consider Spark configuration options for 3.X.
Metastore Host Port
When connecting to an External Metastore passing the parameter Metastore Host Port
, we will be preparing a Spark Session with the configuration
.config("hive.metastore.uris", "thrift://{connection.metastoreHostPort}")
Then, we will be using the catalog
functions from the Spark Session to pick up the metadata exposed by the Hive Metastore.
Metastore File Path
If instead we use a local file path that contains the metastore information (e.g., for local testing with the default metastore_db
directory), we will set
.config("spark.driver.extraJavaOptions", "-Dderby.system.home={connection.metastoreFilePath}")
To update the Derby
information. More information about this in a great SO thread.
- You can find all supported configurations here
- If you need further information regarding the Hive metastore, you can find it here, and in The Internals of Spark SQL book.
Metastore Database
You can also connect to the metastore by directly pointing to the Hive Metastore db, e.g., jdbc:mysql://localhost:3306/demo_hive
.
Here, we will need to inform all the common database settings (url, username, password), and the driver class name for JDBC metastore.
You will need to provide the driver to the ingestion image, and pass the classpath
which will be used in the Spark Configuration under spark.driver.extraClassPath
.
{% partial file="/v1.4/connectors/database/advanced-configuration.md" /%}
{% /extraContent %}
{% partial file="/v1.4/connectors/test-connection.md" /%}
{% partial file="/v1.4/connectors/database/configure-ingestion.md" /%}
{% partial file="/v1.4/connectors/ingestion-schedule-and-deploy.md" /%}
{% /stepsContainer %}
{% partial file="/v1.4/connectors/troubleshooting.md" /%}
{% partial file="/v1.4/connectors/database/related.md" /%}