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Databricks Certified Data Engineer Professional Sample Questions:

1. Review the following error traceback:
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Which statement describes the error being raised?

A) There is a type error because a column object cannot be multiplied.
B) There is a syntax error because the heartrate column is not correctly identified as a column.
C) There is a type error because a DataFrame object cannot be multiplied.
D) The code executed was PvSoark but was executed in a Scala notebook.
E) There is no column in the table named heartrateheartrateheartrate

2. The data engineer is using Spark's MEMORY_ONLY storage level. Which indicators should the data engineer look for in the spark UI's Storage tab to signal that a cached table is not performing optimally?

A) On Heap Memory Usage is within 75% of off Heap Memory usage
B) The RDD Block Name included the '' annotation signaling failure to cache
C) Size on Disk is> 0
D) The number of Cached Partitions> the number of Spark Partitions
E) Size on Disk is < Size in Memory

3. A data architect has designed a system in which two Structured Streaming jobs will concurrently write to a single bronze Delta table. Each job is subscribing to a different topic from an Apache Kafka source, but they will write data with the same schema. To keep the directory structure simple, a data engineer has decided to nest a checkpoint directory to be shared by both streams.
The proposed directory structure is displayed below:

Which statement describes whether this checkpoint directory structure is valid for the given scenario and why?

A) Yes; both of the streams can share a single checkpoint directory.
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B) Yes; Delta Lake supports infinite concurrent writers.
C) No; only one stream can write to a Delta Lake table.
D) No; Delta Lake manages streaming checkpoints in the transaction log.
E) No; each of the streams needs to have its own checkpoint directory.

4. A new data engineer notices that a critical field was omitted from an application that writes its Kafka source to Delta Lake. This happened even though the critical field was in the Kafka source.
That field was further missing from data written to dependent, long-term storage. The retention threshold on the Kafka service is seven days. The pipeline has been in production for three months.
Which describes how Delta Lake can help to avoid data loss of this nature in the future?

A) Ingestine all raw data and metadata from Kafka to a bronze Delta table creates a permanent, replayable history of the data state.Get Latest & Actual Certified-Data-Engineer-Professional Exam's Question and Answers from
B) Data can never be permanently dropped or deleted from Delta Lake, so data loss is not possible under any circumstance.
C) The Delta log and Structured Streaming checkpoints record the full history of the Kafka producer.
D) Delta Lake schema evolution can retroactively calculate the correct value for newly added fields, as long as the data was in the original source.
E) Delta Lake automatically checks that all fields present in the source data are included in the ingestion layer.

5. The data engineering team maintains the following code:
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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) 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.
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) 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.

Solutions: