Databricks Databricks Certified Data Engineer Professional Practice Exams
Last updated on Oct 22,2026- Exam Code: Databricks Certified Data Engineer Professional
- Exam Name: Databricks Certified Data Engineer Professional Exam
- Certification Provider: Databricks
- Latest update: Oct 22,2026
What is the first of a Databricks Python notebook when viewed in a text editor?
- A . %python
- B . % Databricks notebook source
- C . — Databricks notebook source
- D . //Databricks notebook source
A junior data engineer seeks to leverage Delta Lake’s Change Data Feed functionality to create a Type
1 table representing all of the values that have ever been valid for all rows in a bronze table created with the property delta.enableChangeDataFeed = true. They plan to execute the following code as a daily job:
Which statement describes the execution and results of running the above query multiple times?
- A . Each time the job is executed, newly updated records will be merged into the target table, overwriting previous values with the same primary keys.
- B . Each time the job is executed, the entire available history of inserted or updated records will be appended to the target table, resulting in many duplicate entries.
- C . Each time the job is executed, the target table will be overwritten using the entire history of inserted or updated records, giving the desired result.
- D . Each time the job is executed, the differences between the original and current versions are calculated; this may result in duplicate entries for some records.
- E . Each time the job is executed, only those records that have been inserted or updated since the last execution will be appended to the target table giving the desired result.
The data engineer team has been tasked with configured connections to an external database that does not have a supported native connector with Databricks. The external database already has data security configured by group membership. These groups map directly to user group already created in Databricks that represent various teams within the company.
A new login credential has been created for each group in the external database. The Databricks Utilities Secrets module will be used to make these credentials available to Databricks users.
Assuming that all the credentials are configured correctly on the external database and group membership is properly configured on Databricks, which statement describes how teams can be granted the minimum necessary access to using these credentials?
- A . ‘’Read’’ permissions should be set on a secret key mapped to those credentials that will be used by a given team.
- B . No additional configuration is necessary as long as all users are configured as administrators in the workspace where secrets have been added.
- C . “Read” permissions should be set on a secret scope containing only those credentials that will be used by a given team.
- D . “Manage” permission should be set on a secret scope containing only those credentials that will be used by a given team.
Which configuration parameter directly affects the size of a spark-partition upon ingestion of data into Spark?
- A . spark.sql.files.maxPartitionBytes
- B . spark.sql.autoBroadcastJoinThreshold
- C . spark.sql.files.openCostInBytes
- D . spark.sql.adaptive.coalescePartitions.minPartitionNum
- E . spark.sql.adaptive.advisoryPartitionSizeInBytes
All records from an Apache Kafka producer are being ingested into a single Delta Lake table with the following schema:
key BINARY, value BINARY, topic STRING, partition LONG, offset LONG, timestamp LONG
There are 5 unique topics being ingested. Only the "registration" topic contains Personal Identifiable Information (PII). The company wishes to restrict access to PII. The company also wishes to only retain records containing PII in this table for 14 days after initial ingestion. However, for non-PII information, it would like to retain these records indefinitely.
Which of the following solutions meets the requirements?
- A . All data should be deleted biweekly; Delta Lake’s time travel functionality should be leveraged to maintain a history of non-PII information.
- B . Data should be partitioned by the registration field, allowing ACLs and delete statements to be set for the PII directory.
- C . Because the value field is stored as binary data, this information is not considered PII and no special precautions should be taken.
- D . Separate object storage containers should be specified based on the partition field, allowing isolation at the storage level.
- E . Data should be partitioned by the topic field, allowing ACLs and delete statements to leverage partition boundaries.
In order to prevent accidental commits to production data, a senior data engineer has instituted a policy that all development work will reference clones of Delta Lake tables. After testing both deep and shallow clone, development tables are created using shallow clone.
A few weeks after initial table creation, the cloned versions of several tables implemented as Type 1 Slowly Changing Dimension (SCD) stop working. The transaction logs for the source tables show that vacuum was run the day before.
Why are the cloned tables no longer working?
- A . The data files compacted by vacuum are not tracked by the cloned metadata; running refresh on the cloned table will pull in recent changes.
- B . Because Type 1 changes overwrite existing records, Delta Lake cannot guarantee data consistency for cloned tables.
- C . The metadata created by the clone operation is referencing data files that were purged as invalid by the vacuum command
- D . Running vacuum automatically invalidates any shallow clones of a table; deep clone should always be used when a cloned table will be repeatedly queried.
A Delta Lake table representing metadata about content posts from users has the following schema:
user_id LONG, post_text STRING, post_id STRING, longitude FLOAT, latitude FLOAT, post_time TIMESTAMP, date DATE
This table is partitioned by the date column. A query is run with the following filter:
longitude < 20 & longitude > -20
Which statement describes how data will be filtered?
- A . Statistics in the Delta Log will be used to identify partitions that might Include files in the filtered
range. - B . No file skipping will occur because the optimizer does not know the relationship between the partition column and the longitude.
- C . The Delta Engine will use row-level statistics in the transaction log to identify the flies that meet the filter criteria.
- D . Statistics in the Delta Log will be used to identify data files that might include records in the filtered range.
- E . The Delta Engine will scan the parquet file footers to identify each row that meets the filter criteria.
When evaluating the Ganglia Metrics for a given cluster with 3 executor nodes, which indicator would signal proper utilization of the VM’s resources?
- A . The five Minute Load Average remains consistent/flat
- B . Bytes Received never exceeds 80 million bytes per second
- C . Network I/O never spikes
- D . Total Disk Space remains constant
- E . CPU Utilization is around 75%
A distributed team of data analysts share computing resources on an interactive cluster with autoscaling configured. In order to better manage costs and query throughput, the workspace administrator is hoping to evaluate whether cluster upscaling is caused by many concurrent users or resource-intensive queries.
In which location can one review the timeline for cluster resizing events?
- A . Workspace audit logs
- B . Driver’s log file
- C . Ganglia
- D . Cluster Event Log
- E . Executor’s log file
The view updates represents an incremental batch of all newly ingested data to be inserted or updated in the customers table.
The following logic is used to process these records.
Which statement describes this implementation?
- A . The customers table is implemented as a Type 3 table; old values are maintained as a new column alongside the current value.
- B . The customers table is implemented as a Type 2 table; old values are maintained but marked as no longer current and new values are inserted.
- C . The customers table is implemented as a Type 0 table; all writes are append only with no changes to existing values.
- D . The customers table is implemented as a Type 1 table; old values are overwritten by new values and no history is maintained.
- E . The customers table is implemented as a Type 2 table; old values are overwritten and new customers are appended.