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final class atoti_directquery_databricks.ConnectionConfig

Config to connect to a Databricks database.

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Example

>>> import os
>>> from atoti_directquery_databricks import ConnectionConfig
>>> connection_config = ConnectionConfig(
...     url="jdbc:databricks://"
...     + os.environ["DATABRICKS_SERVER_HOSTNAME"]
...     + "/default;"
...     + "transportMode=http;"
...     + "ssl=1;"
...     + "httpPath="
...     + os.environ["DATABRICKS_HTTP_PATH_SQL_WAREHOUSE"]
...     + ";"
...     + "AuthMech=3;"
...     + "UID=token;",
...     password=os.environ["DATABRICKS_AUTH_TOKEN"],
... )
>>> external_database = session.connect_to_external_database(connection_config)

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array_long_agg_function_name : str | None = None

The name (if different from the default) of the UDAF performing atoti.agg.long() on native arrays.
Deprecated: Deprecated since version 0.9.14: Spark UDAFs API is not recommended by Databricks, use array conversion instead.

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array_short_agg_function_name : str | None = None

The name (if different from the default) of the UDAF performing atoti.agg.short() on native arrays.
Deprecated: Deprecated since version 0.9.14: Spark UDAFs API is not recommended by Databricks, use array conversion instead.

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array_sum_agg_function_name : str | None = None

The name (if different from the default) of the UDAF performing atoti.agg.sum() on native arrays.
Deprecated: Deprecated since version 0.9.14: Spark UDAFs API is not recommended by Databricks, use array conversion instead.

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array_sum_product_agg_function_name : str | None = None

The name (if different from the default) of the UDAF performing atoti.agg.sum_product() on native arrays.
Deprecated: Deprecated since version 0.9.14: Spark UDAFs API is not recommended by Databricks, use array conversion instead.

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auto_multi_column_array_conversion : AutoMultiColumnArrayConversion | None = None

When not None, multi-column array conversion will be performed automatically.

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column_clustered_queries : ‘all’ | ‘feeding’ = ‘feeding’

Control which queries will use clustering columns.

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feeding_query_timeout : Duration = datetime.timedelta(seconds=3600)

Timeout for queries performed on the external database during feeding phases. The feeding phases are:

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feeding_url : str | None = None

When not None, this JDBC connection string will be used instead of url for the feeding phases.

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lookup_mode : ‘allow’ | ‘warn’ | ‘deny’ = ‘warn’

Whether lookup queries on the external database are allowed. Lookup can be very slow and expensive as the database may not enforce primary keys.

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max_sub_queries : Annotated[int, Field(gt=0)] = 500

Maximum number of sub queries performed when splitting a query into multi-step queries.

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password : str | None = None

The password to connect to the database. Passing it in this separate attribute prevents it from being logged alongside the connection string. If None, a password is expected to be present in url.

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query_timeout : Duration = datetime.timedelta(seconds=300)

Timeout for queries performed on the external database outside feeding phases.

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time_travel : Literal[False, ‘lax’, ‘strict’] = ‘strict’

How to use Databricks’ time travel feature. Databricks does not support time travel with views, so the options are:
  • False: tables and views are queried on the latest state of the database.
  • "lax": tables are queried with time travel but views are queried without it.
  • "strict": tables are queried with time travel and querying a view raises an error.

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url : str

The JDBC connection string.