A transactions table has been liquid clustered on the columns product_id, user_id, and event_date. Which operation lacks support for cluster on write?

• A. spark.write.format('delta').mode('append')
• B. spark.writestream.format('delta').mode('append')
• C. CTAS and RTAS statements
• D. INSERT INTO operations

A CHECK constraint has been successfully added to the Delta table named activity_details using the following logic:

A batch job is attempting to insert new records to the table, including a record where latitude =
45.50 and longitude = 212.67.
Which statement describes the outcome of this batch insert?

• A. The write will insert all records except those that violate the table constraints; the violating records will be reported in a warning log.
• B. The write will fail completely because of the constraint violation and no records will be inserted into the target table.
• C. The write will include all records in the target table; any violations will be indicated in the boolean column named valid_coordinates.
• D. The write will fail when the violating record is reached; any records previously processed will be recorded to the target table.
• E. The write will insert all records except those that violate the table constraints; the violating records will be recorded to a quarantine table.

Each configuration below is identical to the extent that each cluster has 400 GB total of RAM 160 total cores and only one Executor per VM.
Given an extremely long-running job for which completion must be guaranteed, which cluster configuration will be able to guarantee completion of the job in light of one or more VM failures?

• A. - Total VMs: 2
  - 200 GB per Executor
  - 80 Cores / Executor
• B. - Total VMs: 1
  - 400 GB per Executor
  - 160 Cores/Executor
• C. - Total VMs: 8
  - 50 GB per Executor
  - 20 Cores / Executor
• D. - Total VMs: 16
  - 25 GB per Executor
  - 10 Cores / Executor
• E. - Total VMs: 4
  - 100 GB per Executor
  - 40 Cores / Executor

The data engineering team maintains the following code:

Assuming that this code produces logically correct results and the data in the source tables has been de-duplicated and validated, which statement describes what will occur when this code is executed?

• A. An incremental job will leverage information in the state store to identify unjoined rows in the source tables and write these rows to the enriched_iteinized_orders_by_account table.
• B. An incremental job will detect if new rows have been written to any of the source tables; if new rows are detected, all results will be recalculated and used to overwrite the enriched_itemized_orders_by_account table.
• C. The enriched_itemized_orders_by_account table will be overwritten using the current valid version of data in each of the three tables referenced in the join logic.
• D. No computation will occur until enriched_itemized_orders_by_account is queried; upon query materialization, results will be calculated using the current valid version of data in each of the three tables referenced in the join logic.
• E. A batch job will update the enriched_itemized_orders_by_account table, replacing only those rows that have different values than the current version of the table, using accountID as the primary key.

A data team's Structured Streaming job is configured to calculate running aggregates for item sales to update a downstream marketing dashboard. The marketing team has introduced a new field to track the number of times this promotion code is used for each item. A junior data engineer suggests updating the existing query as follows: Note that proposed changes are in bold.
Original query:

Proposed query:

Which step must also be completed to put the proposed query into production?

• A. Register the data in the "/item_agg" directory to the Hive metastore
• B. Specify a new checkpointlocation
• C. Increase the shuffle partitions to account for additional aggregates
• D. Remove .option (mergeSchema', true') from the streaming write
• E. Run REFRESH TABLE delta, /item_agg'