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Databricks Certified Data Engineer Professional Sample Questions:

1. A data engineer is reviewing the PySpark code to copy a part of the production dataset to the sandbox environment, and needs to be sure that no PII(Personally Identifiable Information) data is being copied. After checking the sales table, the data engineer notices that it has user emails as the only PII data included as well as being the only column to identify the user.
from pyspark.sql import functions as F

Which anonymised code should be used to achieve the required outcome?

A) df.withColumn ("user_email", F.sha2 ("user_email"))
B) df.withColumn ("user_email", F.regexp_replace ("user_eamail", "@*", "@anonymized.com"))
C) df.withColumn ("hashed_email", sha2 ("user_email"))
D) df.withColumn ("user_emai", F.expr("uuid()"))

2. A platform team is creating a standardized template for Databricks Asset Bundles to support CI/CD. The template must specify defaults for artifacts, workspace root paths, and a run identity, while allowing a "dev" target to be the default and override specific paths. How should the team use databricks.yml to satisfy these requirements?

A) Use deployment, builds, context, identity, and environments; set dev as default environment and override paths under builds.
B) Use project, packages, environment, identity, and stages; set dev as default stage and override workspace under environment.
C) Use roots, modules, profiles, actor, and targets; where profiles contain workspace and artifacts defaults and actor sets run identity.
D) Use bundle, artifacts, workspace, run_as, and targets at the top level; set one target with default:true and override workspace paths or artifacts under that target.

3. Which statement describes integration testing?

A) Requires manual intervention
B) Validates behavior of individual elements of your application
C) Validates interactions between subsystems of your application
D) Validates an application use case
E) Requires an automated testing framework

4. An upstream system is emitting change data capture (CDC) logs that are being written to a cloud object storage directory. Each record in the log indicates the change type (insert, update, or delete) and the values for each field after the change. The source table has a primary key identified by the field pk_id.
For analytical purposes, only the most recent value for each record needs to be recorded in the target Delta Lake table in the Lakehouse. The Databricks job to ingest these records occurs once per hour, but each individual record may have changed multiple times over the course of an hour.
Which solution meets these requirements?

A) Use Delta Lake's change data feed to automatically process CDC data from an external system, propagating all changes to all dependent tables in the Lakehouse.
B) Iterate through an ordered set of changes to the table, applying each in turn to create the current state of the table, (insert, update, delete), timestamp of change, and the values.
C) Deduplicate records in each batch by pk_id and overwrite the target table.
D) Use MERGE INTO to insert, update, or delete the most recent entry for each pk_id into a table, then propagate all changes throughout the system.

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

Solutions: