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Databricks Certified-Data-Engineer-Professional Exam Syllabus Topics:

Databricks Certified Data Engineer Professional Sample Questions:

Question 1

A large company seeks to implement a near real-time solution involving hundreds of pipelines with parallel updates of many tables with extremely high volume and high velocity data.
Which of the following solutions would you implement to achieve this requirement?

A. Configure Databricks to save all data to attached SSD volumes instead of object storage, increasing file I/O significantly.
B. Partition ingestion tables by a small time duration to allow for many data files to be written in parallel.
C. Store all tables in a single database to ensure that the Databricks Catalyst Metastore can load balance overall throughput.
D. Use Databricks High Concurrency clusters, which leverage optimized cloud storage connections to maximize data throughput.
E. Isolate Delta Lake tables in their own storage containers to avoid API limits imposed by cloud vendors.

Question 2

A junior data engineer has configured a workload that posts the following JSON to the Databricks REST API endpoint 2.0/jobs/create.

Assuming that all configurations and referenced resources are available, which statement describes the result of executing this workload three times?

A. The logic defined in the referenced notebook will be executed three times on the referenced existing all purpose cluster.
B. One new job named "Ingest new data" will be defined in the workspace, but it will not be executed.
C. Three new jobs named "Ingest new data" will be defined in the workspace, and they will each run once daily.
D. Three new jobs named "Ingest new data" will be defined in the workspace, but no jobs will be executed.
E. The logic defined in the referenced notebook will be executed three times on new clusters with the configurations of the provided cluster ID.

Question 3

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

Question 4

A task orchestrator has been configured to run two hourly tasks. First, an outside system writes Parquet data to a directory mounted at /mnt/raw_orders/. After this data is written, a Databricks job containing the following code is executed:

Assume that the fields customer_id and order_id serve as a composite key to uniquely identify each order, and that the time field indicates when the record was queued in the source system.
If the upstream system is known to occasionally enqueue duplicate entries for a single order hours apart, which statement is correct?

A. Duplicate records arriving more than 2 hours apart will be dropped, but duplicates that arrive in the same batch may both be written to the orders table.
B. All records will be held in the state store for 2 hours before being deduplicated and committed to the orders table.
C. The orders table will contain only the most recent 2 hours of records and no duplicates will be present.
D. The orders table will not contain duplicates, but records arriving more than 2 hours late will be ignored and missing from the table.
E. Duplicate records enqueued more than 2 hours apart may be retained and the orders table may contain duplicate records with the same customer_id and order_id.

Question 5

A junior member of the data engineering team is exploring the language interoperability of Databricks notebooks. The intended outcome of the below code is to register a view of all sales that occurred in countries on the continent of Africa that appear in the geo_lookup table.
Before executing the code, running SHOW TABLES on the current database indicates the database contains only two tables: geo_lookup and sales.

Which statement correctly describes the outcome of executing these command cells in order in an interactive notebook?

A. Both commands will fail. No new variables, tables, or views will be created.
B. Cmd 1 will succeed. Cmd 2 will search all accessible databases for a table or view named countries af: if this entity exists, Cmd 2 will succeed.
C. Both commands will succeed. Executing show tables will show that countries at and sales at have been registered as views.
D. Cmd 1 will succeed and Cmd 2 will fail, countries at will be a Python variable representing a PySpark DataFrame.
E. Cmd 1 will succeed and Cmd 2 will fail, countries at will be a Python variable containing a list of strings.

Solutions: