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

Databricks Certified Data Engineer Professional Sample Questions:

1. A data team is working to optimize an existing large, fast-growing table 'orders' with high cardinality columns, which experiences significant data skew and requires frequent concurrent writes. The team notice that the columns 'user_id', 'event_timestamp' and 'product_id' are heavily used in analytical queries and filters, although those keys may be subject to change in the future due to different business requirements. Which partitioning strategy should the team choose to optimize the table for immediate data skipping, incremental management over time, and flexibility?

A) Z-order the table with OPTIMIZE orders ZORDER BY (user_id, product_id, event_timestamp)
B) Partition the table with: ALTER TABLE orders PARTITION BY user_id, product_id, event_timestamp
C) Use z-order after partitiing the table: OPTIMIZE orders ZORDER BY (user_id, product_id) WHERE event_timestamp = current date () - 1 DAY
D) Cluster the table with: ALTER TABLE orders CLUSTER BY user_id, product_id, event_timestamp

2. A table named user_ltv is being used to create a view that will be used by data analysts on various teams. Users in the workspace are configured into groups, which are used for setting up data access using ACLs.
The user_ltv table has the following schema:
email STRING, age INT, ltv INT
The following view definition is executed:

An analyst who is not a member of the marketing group executes the following query:
SELECT * FROM email_ltv
Which statement describes the results returned by this query?

A) Only the email and ltv columns will be returned; the email column will contain the string
"REDACTED" in each row.
B) Three columns will be returned, but one column will be named "redacted" and contain only null values.
C) Only the email and itv columns will be returned; the email column will contain all null values.
D) The email and ltv columns will be returned with the values in user itv.
E) The email, age. and ltv columns will be returned with the values in user ltv.

3. Which statement describes Delta Lake Auto Compaction?

A) Data is queued in a messaging bus instead of committing data directly to memory; all data is committed from the messaging bus in one batch once the job is complete.
B) Optimized writes use logical partitions instead of directory partitions; because partition boundaries are only represented in metadata, fewer small files are written.
C) An asynchronous job runs after the write completes to detect if files could be further compacted; if yes, an optimize job is executed toward a default of 1 GB.
D) Before a Jobs cluster terminates, optimize is executed on all tables modified during the most recent job.
E) An asynchronous job runs after the write completes to detect if files could be further compacted; if yes, an optimize job is executed toward a default of 128 MB.

4. Which statement describes the correct use of pyspark.sql.functions.broadcast?

A) It marks a column as small enough to store in memory on all executors, allowing a broadcast join.
B) It caches a copy of the indicated table on all nodes in the cluster for use in all future queries during the cluster lifetime.
C) It marks a column as having low enough cardinality to properly map distinct values to available partitions, allowing a broadcast join.
D) It caches a copy of the indicated table on attached storage volumes for all active clusters within a Databricks workspace.
E) It marks a DataFrame as small enough to store in memory on all executors, allowing a broadcast join.

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

Solutions: