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Databricks Certified Data Engineer Professional Sample Questions:

1. 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) 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.
B) 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.
C) 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.
D) 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.
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.

2. A data engineer us ingesting JSON files from cloud object storage using Databricks Auto Loader.
The source folder may occasionally receive large files of data, which risks overwhelming the stream. To ensure predictable micro-batch sizes, the team wants to throttle ingestion based on the volume of data scanned at 1 GB, regardless of the number of files. Which Auto Loader configuration should the data engineer used to achieve this?

A) Configure cloudFiles.maxBytesPerTrigger with 1 GB to place a limit.
B) Configure cloudFiles.maxFilesPerTrigger and estimate the average file size to approximate a size-based throttle of 1 GB.
C) Configure cloudFiles.maxSizePerTrigger with 1 GB to place a limit.
D) Configure cloudFiles.maxPartitionBytes with 1GB to limit data in each partition.

3. Which statement describes a key benefit of an end-to-end test?

A) It pinpoint errors in the building blocks of your application.
B) It provides testing coverage for all code paths and branches.
C) It closely simulates real world usage of your application.
D) It makes it easier to automate your test suite

4. A data engineer is using Auto Loader to read incoming JSON data as it arrives. They have configured Auto Loader to quarantine invalid JSON records but notice that over time, some records are being quarantined even though they are well-formed JSON.
The code snippet is:
df = (spark.readStream
.format("cloudFiles")
.option("cloudFiles.format", "json")
.option("badRecordsPath", "/tmp/somewhere/badRecordsPath")
.schema("a int, b int")
.load("/Volumes/catalog/schema/raw_data/"))
What is the cause of the missing data?

A) The engineer forgot to set the option "cloudFiles.quarantineMode" = "rescue".
B) The badRecordsPath location is accumulating many small files.
C) At some point, the upstream data provider switched everything to multi-line JSON.
D) The source data is valid JSON but does not conform to the defined schema in some way.

5. Spill occurs as a result of executing various wide transformations. However, diagnosing spill requires one to proactively look for key indicators.
Where in the Spark UI are two of the primary indicators that a partition is spilling to disk?

A) Query's detail screen and Job's detail screen
B) Driver's and Executor's log files
C) Executor's detail screen and Executor's log files
D) Stage's detail screen and Executor's log files
E) Stage's detail screen and Query's detail screen

Solutions: