DATABRICKS-DEP Question 58

Community Discussion

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• Chose A0

  ,B,E - Correct answer s : A, B, E — `system.lakeflow.job_run_timeline` aggregates run history across every workspace in the same region into one queryable table, which the `listruns` endpoint cannot do since it is scoped to a single workspace per call.; `system.lakeflow.job_run_timeline` can be joined directly with `system.billing.usage` in ordinary SQL, whereas correlating REST API run objects with billing data requires the caller to write custom stitching logic.; Repeatedly polling `listruns` for a 90-day window requires paging through and re-fetching runs already retrieved on a prior poll, since the endpoint has no native cursor for returning only rows changed since the last call. A . The system table is designed to aggregate data across workspaces sharing the same metastore region, giving one queryable surface for the whole region, while the REST endpoint only ever returns runs for the single workspace it is called against. B . Because both are SQL tables in the same catalog, they can be joined directly with a standard SQL join, whereas combining REST API JSON responses with billing usage rows requires the caller to extract, normalize, and stitch the data together outside of SQL. C . Polling the endpoint on demand reflects a run's state as soon as it changes, while rows for a given run in the system table are documented to typically appear within about an hour rather than immediately. D . The retention relationship is reversed: the system table is documented to retain roughly 365 days of history, while the REST API is a live, point-in-time view of runs rather than a long-term, retention-guaranteed archive. E . The endpoint has no changed-since cursor, so a scheduled poll covering a rolling window has to re-request and re-filter runs it has already seen on earlier polls to detect what changed. F . The system table is documented to lag behind real-time state changes by up to about an hour, so it is not lower latency than a REST poll for any sub-minute polling schedule; the two approaches trade latency for aggregation and joinability in opposite directions.