DATABRICKS-DEP Question 76

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• Chose A0

  ,B,C - Correct answer s : A, B, C — Databricks can automatically change the clustering keys as the observed query workload shifts, without requiring the table to be dropped and recreated.; Databricks can automatically change the clustering keys as the query workload shifts over time, without ever dropping and recreating the underlying table.; `OPTIMIZE` reclusters only the data that needs it incrementally, instead of requiring a full table rewrite every time new clickstream events are appended. A . This is accurate: `CLUSTER BY AUTO` lets Databricks pick and revise clustering keys based on observed query history as access patterns evolve, without a table rebuild. B . This is accurate: without fixed partition directories, concurrent writers are not funneled into contention over a small set of `event_type` folders the way rigid partitioning would force. C . This is accurate: standard `OPTIMIZE` on a liquid-clustered table only rewrites data that needs reclustering, rather than rewriting the whole table on every run like a full Z-Order pass would. D . This overstates the guarantee; liquid clustering improves data skipping through better file organization, but it does not guarantee single-file reads for every filtered query. E . This is backwards; `CLUSTER BY AUTO` relies on Databricks continuously analyzing query history to decide whether and how to adjust clustering keys over time. F . Z-Order statistics are only maintained within each partition, so the optimizer cannot use them to skip data across `event_type` partition boundaries, limiting global data skipping.