This documentation is for the unstable version of GoodData, currrently in development.
For stable version, go to the latest stable version of this article.

AI Lake

Drive AI Lake long-running operations from the SDK. Today the surface covers the actions needed by aggregate-aware logical data models — most notably the ANALYZE TABLE refresh that pre-aggregation workflows rely on so the cost-based optimizer picks up new statistics.

The AI Lake API uses long-running operations: an action returns immediately with an operation_id, and the client polls until the operation reaches a terminal status (succeeded or failed).

Action Methods

Operation Methods

Example 

from gooddata_sdk import GoodDataSdk

sdk = GoodDataSdk.create(host="https://demo.gooddata.com", token="<token>")

# Refresh CBO statistics for a single table after a bulk load.
operation_id = sdk.catalog_ai_lake.analyze_statistics(
    instance_id="warehouse-prod",
    table_names=["agg_orders_country_daily"],
)

# Block until the operation finishes; raises CatalogAILakeOperationError
# on failure and TimeoutError if it doesn't finish in time.
op = sdk.catalog_ai_lake.wait_for_operation(operation_id, timeout_s=600.0)
assert op.is_succeeded
analyze_statistics