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Databricks Certified Data Engineer Professional Sample Questions:

1. Which Python variable contains a list of directories to be searched when trying to locate required modules?

A) sys.path
B) os.path
C) pypi.path
D) pylib.source
E) importlib.resource path

2. A data engineer needs to create an application that will collect information about the latest job run including the repair history. How should the data engineer format the request?

A) Call/api/2.1/jobs/runs/get with the run_id and include_history parameters
B) Call/api/2.1/jobs/runs/get with the job_id and include_history parameters
C) Call/api/2.1/jobs/runs/list with the job_id and include_history parameters
D) Call/api/2.1/jobs/runs/list with the run_id and include_history parameters

3. The data science team has requested assistance in accelerating queries on free form text from user reviews. The data is currently stored in Parquet with the below schema:
item_id INT, user_id INT, review_id INT, rating FLOAT, review STRING
The review column contains the full text of the review left by the user. Specifically, the data science team is looking to identify if any of 30 key words exist in this field.
A junior data engineer suggests converting this data to Delta Lake will improve query performance.
Which response to the junior data engineer's suggestion is correct?

A) ZORDER ON review will need to be run to see performance gains.
B) Delta Lake statistics are not optimized for free text fields with high cardinality.
C) The Delta log creates a term matrix for free text fields to support selective filtering.
D) Text data cannot be stored with Delta Lake.
E) Delta Lake statistics are only collected on the first 4 columns in a table.

4. Which of the following is true of Delta Lake and the Lakehouse?

A) Z-order can only be applied to numeric values stored in Delta Lake tables
B) Views in the Lakehouse maintain a valid cache of the most recent versions of source tables at all times.
C) Delta Lake automatically collects statistics on the first 32 columns of each table which are leveraged in data skipping based on query filters.
D) Because Parquet compresses data row by row. strings will only be compressed when a character is repeated multiple times.
E) Primary and foreign key constraints can be leveraged to ensure duplicate values are never entered into a dimension table.

5. A company stores account transactions in a Delta Lake table. The company needs to apply frequent account-level correlations (e.g., UPDATE statements) but wants to avoid rewriting entire Parquet files for each change to reduce file churn and improve write performance. Which Delta Lake feature should they enable?

A) Enable automatic file compaction on writes
B) Partition the Delta table by account_id
C) Enable change data feed on the Delta table
D) Enable deletion vectors on the Delta table

Solutions: