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

Databricks Certified Data Engineer Professional Sample Questions:

1. A view is registered with the following code:

Both users and orders are Delta Lake tables.
Which statement describes the results of querying recent_orders?

A) All logic will execute at query time and return the result of joining the valid versions of the source tables at the time the query finishes.
B) All logic will execute when the view is defined and store the result of joining tables to the DBFS; this stored data will be returned when the view is queried.
C) All logic will execute at query time and return the result of joining the valid versions of the source tables at the time the query began.
D) Results will be computed and cached when the view is defined; these cached results will incrementally update as new records are inserted into source tables.

2. A data engineer is developing a Lakeflow Declarative Pipeline (LDP) using a Databricks notebook directly connected to their pipeline. After adding new table definitions and transformation logic in their notebook, they want to check for any syntax errors in the pipeline code without actually processing data or running the pipeline. How should the data engineer perform this syntax check?

A) Disconnect the notebook from the pipeline and reconnect it to a compute cluster to access code validation features.
B) Switch to a workspace file instead of a notebook to access validation and diagnostics tools.
C) Use the "Validate" option in the notebook to check for syntax errors.
D) Open the web terminal from the notebook and run a shell command to validate the pipeline code.

3. The data engineering team maintains the following code:

Assuming that this code produces logically correct results and the data in the source table has been de-duplicated and validated, which statement describes what will occur when this code is executed?

A) The gold_customer_lifetime_sales_summary table will be overwritten by aggregated values calculated from all records in the silver_customer_sales table as a batch job.
B) The silver_customer_sales table will be overwritten by aggregated values calculated from all records in the gold_customer_lifetime_sales_summary table as a batch job.
C) A batch job will update the gold_customer_lifetime_sales_summary table, replacing only those rows that have different values than the current version of the table, using customer_id as the primary key.
D) An incremental job will detect if new rows have been written to the silver_customer_sales table; if new rows are detected, all aggregates will be recalculated and used to overwrite the gold_customer_lifetime_sales_summary table.
E) An incremental job will leverage running information in the state store to update aggregate values in the gold_customer_lifetime_sales_summary table.

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

5. A data engineer is masking a column containing email addresses. The goal is to produce output strings of identical length for all rows, while generating different outputs for different email values.
Which SQL function should be used to achieve this?

A) mask(email, '?')
B) sha1(email)
C) sha2(email, 0)
D) hash(email)

Solutions: