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

Databricks Certified Data Engineer Professional Sample Questions:

1. A data engineer is using Lakeflow Declarative Pipeline to propagate row deletions from a source bronze table (user_bronze) to a target silver table (user_silver). The engineer wants deletions in user_bronze to automatically delete corresponding rows in user_silver during pipeline execution.
Which configuration ensures deletions in the bronze table are propagated to the silver table?

A) Enable Change Data Feed (CDF) on user_bronze, read its CDF stream, and use apply_changes() with apply_as_deletes=True for user_silver.
B) Use apply_changes without CDF and filter rows where _soft_deleted is true.
C) Enable CDF on user_silver, read its transaction log, and use MERGE to sync deletions.
D) Configure VACUUM on user_bronze to delete files, then rebuild user_silver from scratch.

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) Size on Disk is < Size in Memory
E) The number of Cached Partitions> the number of Spark Partitions

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

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

4. The data architect has mandated that all tables in the Lakehouse should be configured as external (also known as "unmanaged") Delta Lake tables.
Which approach will ensure that this requirement is met?

A) When tables are created, make sure that the EXTERNAL keyword is used in the CREATE TABLE statement.
B) When a database is being created, make sure that the LOCATION keyword is used.
C) When the workspace is being configured, make sure that external cloud object storage has been mounted.
D) When configuring an external data warehouse for all table storage, leverage Databricks for all ELT.
E) When data is saved to a table, make sure that a full file path is specified alongside the Delta format.

5. A platform engineer is creating catalogs and schemas for the development team to use.
The engineer has created an initial catalog, catalog_A, and initial schema, schema_A. The engineer has also granted USE CATALOG, USE SCHEMA, and CREATE TABLE to the development team so that the engineer can begin populating the schema with new tables.
Despite being owner of the catalog and schema, the engineer noticed that they do not have access to the underlying tables in Schema_A.
What explains the engineer's lack of access to the underlying tables?

A) Permissions explicitly given by the table creator are the only way the Platform Engineer could access the underlying tables in their schema.
B) The platform engineer needs to execute a REFRESH statement as the table permissions did not automatically update for owners.
C) The owner of the schema does not automatically have permission to tables within the schema, but can grant them to themselves at any point.
D) Users granted with USE CATALOG can modify the owner's permissions to downstream tables.

Solutions: