[Feb-2026] Download Real Databricks-Certified-Professional-Data-Engineer Exam Dumps for candidates 100% Free Dump Files [Q110-Q131]

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[Feb-2026] Download Real Databricks-Certified-Professional-Data-Engineer Exam Dumps for candidates. 100% Free Dump Files

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Databricks Certified Professional Data Engineer certification exam is designed for professionals who want to prove their expertise in designing, building, and maintaining data processing systems using Databricks. Databricks is a cloud-based data platform that provides a unified analytics engine for data processing, machine learning, and visualization. Databricks Certified Professional Data Engineer Exam certification exam tests the candidate’s knowledge and skills in various areas, including data engineering, data processing, data modeling, and data architecture.

NO.110 The data science team has created and logged a production using MLFlow. The model accepts a list of column names and returns a new column of type DOUBLE.
The following code correctly imports the production model, load the customer table containing the customer_id key column into a Dataframe, and defines the feature columns needed for the model.

Which code block will output DataFrame with the schema” customer_id LONG, predictions DOUBLE”?

Model, predict (df, columns)

Df, map (lambda k:midel (x [columns]) ,select (”customer_id predictions”)

Df. Select (”customer_id”.
Model (”columns) alias (”predictions”)

Df.apply(model, columns). Select (”customer_id, prediction”

NO.111 The Databricks CLI is used to trigger a run of an existing job by passing the job_id parameter. The response indicating the job run request was submitted successfully includes a field run_id. Which statement describes what the number alongside this field represents?

The job_id and number of times the job has been run are concatenated and returned.

The globally unique ID of the newly triggered run.

The job_id is returned in this field.

The number of times the job definition has been run in this workspace.

NO.112 When you drop an external DELTA table using the SQL Command DROP TABLE table_name, how does it impact metadata(delta log, history), and data stored in the storage?

Drops table from metastore, metadata(delta log, history)and data in storage

Drops table from metastore, data but keeps metadata(delta log, history) in storage

Drops table from metastore, metadata(delta log, history)but keeps the data in storage

Drops table from metastore, but keeps metadata(delta log, history)and data in storage

Drops table from metastore and data in storage but keeps metadata(delta log, history)

NO.113 When using the complete mode to write stream data, how does it impact the target table?

Entire stream waits for complete data to write

Stream must complete to write the data

Target table cannot be updated while stream is pending

Target table is overwritten for each batch

Delta commits transaction once the stream is stopped

NO.114 A table nameduser_ltvis 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.
Theuser_ltvtable 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?

Three columns will be returned, but one column will be named “redacted” and contain only null values.

Only the email and itv columns will be returned; the email column will contain all null values.

The email and ltv columns will be returned with the values in user itv.

The email, age. and ltv columns will be returned with the values in user ltv.

Only the email and ltv columns will be returned; the email column will contain the string
“REDACTED” in each row.

NO.115 Although the Databricks Utilities Secrets module provides tools to store sensitive credentials and avoid accidentally displaying them in plain text users should still be careful with which credentials are stored here and which users have access to using these secrets.
Which statement describes a limitation of Databricks Secrets?

Because the SHA256 hash is used to obfuscate stored secrets, reversing this hash will display the value in plain text.

Account administrators can see all secrets in plain text by loggingon to the Databricks Accounts console.

Secrets are stored in an administrators-only table within the Hive Metastore; database administrators have permission to query this table by default.

Iterating through a stored secret and printing each character will display secret contents in plain text.

The Databricks REST API can be used to list secrets in plain text if the personal access token has proper credentials.

NO.116 A Delta Lake table was created with the below query:

Realizing that the original query had a typographical error, the below code was executed:
ALTER TABLE prod.sales_by_stor RENAME TO prod.sales_by_store
Which result will occur after running the second command?

The table reference in the metastore is updated and no data is changed.

The table name change is recorded in the Delta transaction log.

All related files and metadata are dropped and recreated in a single ACID transaction.

The table reference in the metastore is updated and all data files are moved.

A new Delta transaction log Is created for the renamed table.

NO.117 A junior data engineer has manually configured a series of jobs using the Databricks Jobs UI. Upon reviewing their work, the engineer realizes that they are listed as the “Owner” for each job. They attempt to transfer
“Owner” privileges to the “DevOps” group, but cannot successfully accomplish this task.
Which statement explains what is preventing this privilege transfer?

Databricks jobs must have exactly one owner; “Owner” privileges cannot be assigned to a group.

The creator of a Databricks job will always have “Owner” privileges; this configuration cannot be changed.

Other than the default “admins” group, only individual users can be granted privileges on jobs.

A user can only transfer job ownership to a group if they are also a member of that group.

Only workspace administrators can grant “Owner” privileges to a group.

NO.118 Which of the statement is correct about the cluster pools?

Cluster pools allow you to perform load balancing

Cluster pools allow you to create a cluster

Cluster pools allow you to save time when starting a new cluster

Cluster pools are used to share resources among multiple teams

Cluster pools allow you to have all the nodes in the cluster from single physical server rack

NO.119 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?

Each time the job is executed, newly updated records will be merged into the target table, overwriting previous values with the same primary keys.

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.

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.

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.

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.

NO.120 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?

Statistics in the Delta Log will be used to identify partitions that might Include files in the filtered range.

No file skipping will occur because the optimizer does not know the relationship between the partition column and the longitude.

The Delta Engine will use row-level statistics in the transaction log to identify the flies that meet the filter criteria.

Statistics in the Delta Log will be used to identify data files that might include records in the filtered range.

The Delta Engine will scan the parquet file footers to identify each row that meets the filter criteria.

NO.121 A Spark job is taking longer than expected. Using the Spark UI, a data engineer notes that the Min, Median, and Max Durations for tasks in a particular stage show the minimum and median time to complete a task as roughly the same, but the max duration for a task to be roughly 100 times as long as the minimum.
Which situation is causing increased duration of the overall job?

Task queueing resulting from improper thread pool assignment.

Spill resulting from attached volume storage being too small.

Network latency due to some cluster nodes being in different regions from the source data

Skew caused by more data being assigned to a subset of spark-partitions.

Credential validation errors while pulling data from an external system.

NO.122 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?

The customers table is implemented as a Type 3 table; old values are maintained as a new column alongside the current value.

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.

The customers table is implemented as a Type 0 table; all writes are append only with no changes to existing values.

The customers table is implemented as a Type 1 table; old values are overwritten by new values and no history is maintained.

The customers table is implemented as a Type 2 table; old values are overwritten and new customers are appended.

NO.123 A data engineer wants to ingest a large collection of image files (JPEG and PNG) from cloud object storage into a Unity Catalog-managed table for analysis and visualization.
Which two configurations and practices are recommended to incrementally ingest these images into the table? (Choose 2 answers)

Move files to a volume and read with SQL editor.

Use Auto Loader and set cloudFiles.format to “BINARYFILE”.

Use Auto Loader and set cloudFiles.format to “TEXT”.

Use Auto Loader and set cloudFiles.format to “IMAGE”.

Use the pathGlobFilter option to select only image files (e.g., “*.jpg,*.png”).

NO.124 A junior data engineer has manually configured a series of jobs using the Databricks Jobs UI. Upon reviewing their work, the engineer realizes that they are listed as the “Owner” for each job. They attempt to transfer
“Owner” privileges to the “DevOps” group, but cannot successfully accomplish this task.
Which statement explains what is preventing this privilege transfer?

Databricks jobs must have exactly one owner; “Owner” privileges cannot be assigned to a group.

The creator of a Databricks job will always have “Owner” privileges; this configuration cannot be changed.

Other than the default “admins” group, only individual users can be granted privileges on jobs.

A user can only transfer job ownership to a group if they are also a member of that group.

Only workspace administrators can grant “Owner” privileges to a group.

NO.125 A Databricks SQL dashboard has been configured to monitor the total number of records present in a collection of Delta Lake tables using the following query pattern:
SELECT COUNT (*) FROM table –
Which of the following describes how results are generated each time the dashboard is updated?

The total count of rows is calculated by scanning all data files

The total count of rows will be returned from cached results unless REFRESH is run

The total count of records is calculated from the Delta transaction logs

The total count of records is calculated from the parquet file metadata

The total count of records is calculated from the Hive metastore

NO.126 Which statement describes the correct use of pyspark.sql.functions.broadcast?

It marks a column as having low enough cardinality to properly map distinct values to available partitions, allowing a broadcast join.

It marks a column as small enough to store in memory on all executors, allowing a broadcast join.

It caches a copy of the indicated table on attached storage volumes for all active clusters within a Databricks workspace.

It marks a DataFrame as small enough to store in memory on all executors, allowing a broadcast join.

It caches a copy of the indicated table on all nodes in the cluster for use in all future queries during the cluster lifetime.

NO.127 Which of the following scenarios is the best fit for AUTO LOADER?

Efficiently process new data incrementally from cloud object storage

Efficiently move data incrementally from one delta table to another delta table

Incrementally process new data from streaming data sources like Kafka into delta lake

Incrementally process new data from relational databases like MySQL

Efficiently copy data from one data lake location to another data lake location

NO.128 Which of the statements are correct about lakehouse?

Lakehouse only supports Machine learning workloads and Data warehouses support BI workloads

Lakehouse only supports end-to-end streaming workloads and Data warehouses support Batch workloads

Lakehouse does not support ACID

In Lakehouse Storage and compute are coupled

Lakehouse supports schema enforcement and evolution

NO.129 An upstream source writes Parquet data as hourly batches to directories named with the current date. A nightly batch job runs the following code to ingest all data from the previous day as indicated by the date variable:

Assume that the fields customer_id and order_id serve as a composite key to uniquely identify each order.
If the upstream system is known to occasionally produce duplicate entries for a single order hours apart, which statement is correct?

Each write to the orders table will only contain unique records, and only those records without duplicates in the target table will be written.

Each write to the orders table will only contain unique records, but newly written records may have duplicates already present in the target table.

Each write to the orders table will only contain unique records; if existing records with the same key are present in the target table, these records will be overwritten.

Each write to the orders table will only contain unique records; if existing records with the same key are present in the target table, the operation will tail.

Each write to the orders table will run deduplication over the union of new and existing records, ensuring no duplicate records are present.

NO.130 A Delta table of weather records is partitioned by date and has the below schema:
date DATE, device_id INT, temp FLOAT, latitude FLOAT, longitude FLOAT
To find all the records from within the Arctic Circle, you execute a query with the below filter:
latitude > 66.3
Which statement describes how the Delta engine identifies which files to load?

All records are cached to an operational database and then the filter is applied

The Parquet file footers are scanned for min and max statistics for the latitude column

All records are cached to attached storage and then the filter is applied

The Delta log is scanned for min and max statistics for the latitude column

The Hive metastore is scanned for min and max statistics for the latitude column

NO.131 A developer has successfully configured credential for Databricks Repos and cloned a remote Git repository. Hey don not have privileges to make changes to the main branch, which is the only branch currently visible in their workspace.
Use Response to pull changes from the remote Git repository commit and push changes to a branch that appeared as a changes were pulled.

Use Repos to merge all differences and make a pull request back to the remote repository.

Use repos to merge all difference and make a pull request back to the remote repository.

Use Repos to create a new branch commit all changes and push changes to the remote Git repertory.

Use repos to create a fork of the remote repository commit all changes and make a pull request on the source repository

Databricks Certified Professional Data Engineer certification exam is a highly sought-after certification in the data engineering industry. It is designed to test the skills and knowledge of data engineers who work with Databricks, a cloud-based platform that helps organizations manage large amounts of data and perform advanced analytics.

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