An upstream system has been configured to pass the date for a given batch of data to the Databricks Jobs API as a parameter. The notebook to be scheduled will use this parameter to load data with the following code: df = spark.read.format("parquet").load(f"/mnt/source/(date)")Which code block should be used to create the date Python variable used in the above code block?

E- dbutils.widgets.text("date", "null")date = dbutils.widgets.get("date")

The Databricks workspace administrator has configured interactive clusters for each of the data engineering groups. To control costs, clusters are set to terminate after 30 minutes of inactivity. Each user should be able to execute workloads against their assigned clusters at any time of the day.Assuming users have been added to a workspace but not granted any permissions, which of the following describes the minimal permissions a user would need to start and attach to an already configured cluster.

D- "Can Restart" privileges on the required cluster

When scheduling Structured Streaming jobs for production, which configuration automatically recovers from query failures and keeps costs low?

D- Cluster: New Job Cluster;Retries: Unlimited;Maximum Concurrent Runs: 1

The data engineering team has configured a Databricks SQL query and alert to monitor the values in a Delta Lake table. The recent_sensor_recordings table contains an identifying sensor_id alongside the timestamp and temperature for the most recent 5 minutes of recordings.The below query is used to create the alert:The query is set to refresh each minute and always completes in less than 10 seconds. The alert is set to trigger when mean (temperature) > 120. Notifications are triggered to be sent at most every 1 minute.If this alert raises notifications for 3 consecutive minutes and then stops, which statement must be true?

E- The average temperature recordings for at least one sensor exceeded 120 on three consecutive executions of the query

A junior developer complains that the code in their notebook isn't producing the correct results in the development environment. A shared screenshot reveals that while they're using a notebook versioned with Databricks Repos, they're using a personal branch that contains old logic. The desired branch named dev-2.3.9 is not available from the branch selection dropdown.Which approach will allow this developer to review the current logic for this notebook?

B- Use Repos to pull changes from the remote Git repository and select the dev-2.3.9 branch.

The security team is exploring whether the Databricks secrets module can be used to securely connect to an external database.After initially testing the code with all credentials as plain strings, they upload the database password to the Databricks secrets scope and configure the proper permissions for the currently active user.They then modify the code as follows (leaving all other variables unchanged):pythonpassword = dbutils.secrets.get(scope="db_creds", key="jdbc_password")print(password) df = ( spark .read .format("jdbc") .option("url", connection) .option("dbtable", tablename) .option("user", username) .option("password", password))What will happen when this code is executed?

E- The connection to the external table will succeed; the string "REDACTED" will be printed.

The data science team has created and logged a production model using MLflow. The following code correctly imports and applies the production model to output the predictions as a new DataFrame named preds with the schema:customer_id LONG, predictions DOUBLE, date DATEfrom pyspark.sql.functions import current_date model = mlflow.pyfunc.spark_udf(spark, model_uri="models:/churn/prod")df = spark.table("customers")columns = ["account_age", "time_since_last_seen", "app_rating"] preds = ( df.select( "customer_id", model(*columns).alias("predictions"), current_date().alias("date") ))The data science team would like the predictions saved to a Delta Lake table, with the ability to compare all predictions across time. Churn predictions will be made at most once per day.Which code block accomplishes this task while minimizing potential compute costs?

A- preds.write.mode("append").saveAsTable("churn_preds")

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:( spark.read .format("parquet") .load(f"/mnt/raw_orders/{date}") .dropDuplicates(["customer_id", "order_id"]) .write .mode("append") .saveAsTable("orders"))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?

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

A junior member of the data engineering team is exploring the language interoperability of Databricks notebooks. The intended outcome of the code below is to register a view of all sales that occurred in countries on the continent of Africa, as listed in the geo_lookup table.Before executing the code, running SHOW TABLES on the current database confirms that the database contains only two tables: geo_lookup and sales.❖ Cmd 1 — Python Cell:pythoncountries_af = [x[0] for x in spark.table("geo_lookup").filter("continent = 'AF'").select("country").collect()]❖ Cmd 2 — SQL Cell:sqlCREATE VIEW sales_af ASSELECT *FROM salesWHERE city IN countries_af AND continent = "AF"

E- Cmd 1 will succeed and Cmd 2 will fail. countries_af will be a Python variable containing a list of strings.

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 FLOATTo find all the records from within the Arctic Circle, you execute a query with the below filter: latitude > 66.3Which statement describes how the Delta engine identifies which files to load?

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

Certified Data Engineer Professional Exam Questions

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Preparing for the Certified Data Engineer Professional exam requires a thorough understanding of various concepts and practical skills related to data engineering. This practice exam, featuring 323 real questions, offers candidates an invaluable opportunity to familiarize themselves with the exam format and question style. By engaging with these practice questions, you can assess your grasp of critical topics, identify areas that may need further review, and gauge your readiness for the actual certification exam.

The practice exam allows you to simulate the test-taking experience, which can help reduce anxiety and improve time management skills. More importantly, it highlights your strengths and weaknesses, enabling you to create a focused study plan tailored to your needs. The exposure to real questions not only reinforces learning but also enhances your problem-solving abilities under exam conditions. Taking this practice exam is a strategic step towards achieving certification and advancing your career as a data engineer. Utilize this resource effectively to ensure you are well-equipped for success on exam day.

Per page:

Welcome to the Certified Data Engineer Professional exam questions and answers page. Here, you will find a curated collection of 323 real practice questions designed to help you prepare effectively for your certification exam. This repository serves as a practical resource for understanding the types of questions you may encounter, as well as the concepts and skills necessary for success in the field of data engineering. By working through these questions, you can assess your knowledge, identify areas for improvement, and build confidence before tackling the actual exam.

To make the most of this resource, review each question carefully and take note of any topics where you feel less confident. Use the provided answers and explanations to deepen your understanding of the concepts involved. Additionally, simulate exam conditions by setting a timer and answering questions in a single sitting to improve your time management skills.

How to pass the Certified Data Engineer Professional exam:

1. **Active Learning**: Engage with the material actively—rather than just reading, try to explain concepts in your own words or teach them to someone else.

2. **Consistent Study Schedule**: Establish a regular study routine. Dedicate specific hours each week to focus on different topics and practice questions, ensuring steady progress over time.

3. **Hands-On Experience**: If possible, gain practical experience with relevant tools and technologies. Working on real projects can reinforce your understanding and provide valuable context for the exam concepts.

Question 11 Single Choice

The data engineering team has configured a job to process customer requests to be forgotten (have their data deleted). All user data that needs to be deleted is stored in Delta Lake tables using default table settings.

The team has decided to process all deletions from the previous week as a batch job at 1am each Sunday. The total duration of this job is less than one hour. Every Monday at 3am, a batch job executes a series of VACUUM commands on all Delta Lake tables throughout the organization.

The compliance officer has recently learned about Delta Lake's time travel functionality. They are concerned that this might allow continued access to deleted data.

Assuming all delete logic is correctly implemented, which statement correctly addresses this concern?

A- Because the VACUUM command permanently deletes all files containing deleted records, deleted records may be accessible with time travel for around 24 hours.

B- Because the default data retention threshold is 24 hours, data files containing deleted records will be retained until the VACUUM job is run the following day.

C- Because Delta Lake time travel provides full access to the entire history of a table, deleted records can always be recreated by users with full admin privileges.

D- Because Delta Lake's delete statements have ACID guarantees, deleted records will be permanently purged from all storage systems as soon as a delete job completes.

E- Because the default data retention threshold is 7 days, data files containing deleted records will be retained until the VACUUM job is run 8 days later.

Question 12 Single Choice

A junior data engineer has configured a workload that posts the following JSON to the Databricks REST API endpoint 2.0/jobs/create:

json
{
 "name": "Ingest new data",
 "existing_cluster_id": "6015-954420-peace720",
 "notebook_task": {
 "notebook_path": "/Prod/ingest.py"
 }
}

Assuming that all configurations and referenced resources are available, which statement correctly describes the result of executing this API request three times?

Question 13 Single Choice

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 auditing purposes, the data governance team wishes to maintain a full record of all values that have ever been valid in the source system. For analytical purposes, only the most recent value for each record needs to be recorded. 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- Create a separate history table for each pk_id resolve the current state of the table by running a union all filtering the history tables for the most recent state.

B- Use MERGE INTO to insert, update, or delete the most recent entry for each pk_id into a bronze table, then propagate all changes throughout the system.

C- Iterate through an ordered set of changes to the table, applying each in turn; rely on Delta Lake's versioning ability to create an audit log.

D- 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.

E- Ingest all log information into a bronze table; use MERGE INTO to insert, update, or delete the most recent entry for each pk_id into a silver table to recreate the current table state.

Question 14 Single Choice

An hourly batch job is configured to ingest data files from a cloud object storage container, where each batch represents all records produced by the source system in a given hour. The batch job to process these records into the Lakehouse is sufficiently delayed to ensure no late-arriving data is missed.

The user_id field represents a unique key for the data, which has the following schema:

sql
user_id BIGINT,
username STRING,
user_utc STRING,
user_region STRING,
last_login BIGINT,
auto_pay BOOLEAN,
last_updated BIGINT

New records are all ingested into a table named account_history which maintains a full record of all data in the same schema as the source.
The next table in the system is named account_current and is implemented as a Type 1 table, representing the most recent value for each unique user_id.

Assuming there are millions of user accounts and tens of thousands of records processed hourly, which implementation can be used to efficiently update the described account_current table as part of each hourly batch job?

A- Use Auto Loader to subscribe to new files in the account_history directory; configure a Structured Streaming trigger once job to batch update newly detected files into the account_current table.

B- Overwrite the account_current table with each batch using the results of a query against the account_history table grouping by user_id and filtering for the max value of last_updated.

C- Filter records in account_history using the last_updated field and the most recent hour processed, as well as the max last_login by user_id write a merge statement to update or insert the most recent value for each user_id.

D- Use Delta Lake version history to get the difference between the latest version of account_history and one version prior, then write these records to account_current.

E- Filter records in account_history using the last_updated field and the most recent hour processed, making sure to deduplicate on username; write a merge statement to update or insert the most recent value for each username.

Question 15 Single Choice

A table in the Lakehouse named customer_churn_params is used in churn prediction by the machine learning team. The table contains information about customers derived from a number of upstream sources. Currently, the data engineering team populates this table nightly by overwriting the table with the current valid values derived from upstream data sources.

The churn prediction model used by the ML team is fairly stable in production. The team is only interested in making predictions on records that have changed in the past 24 hours.

Which approach would simplify the identification of these changed records?

A- Apply the churn model to all rows in the customer_churn_params table, but implement logic to perform an upsert into the predictions table that ignores rows where predictions have not changed.

B- Convert the batch job to a Structured Streaming job using the complete output mode; configure a Structured Streaming job to read from the customer_churn_params table and incrementally predict against the churn model.

C- Calculate the difference between the previous model predictions and the current customer_churn_params on a key identifying unique customers before making new predictions; only make predictions on those customers not in the previous predictions.

D- Modify the overwrite logic to include a field populated by calling spark.sql.functions.current_timestamp() as data are being written; use this field to identify records written on a particular date.

E- Replace the current overwrite logic with a merge statement to modify only those records that have changed; write logic to make predictions on the changed records identified by the change data feed.

Question 16 Single Choice

A table is registered with the following SQL code:

sql
CREATE TABLE recent_orders AS (
 SELECT 
 a.user_id, 
 a.email, 
 b.order_id, 
 b.order_date 
 FROM (
 SELECT user_id, email
 FROM users
 ) a
 INNER JOIN (
 SELECT user_id, order_id, order_date
 FROM orders
 WHERE order_date >= (current_date() - 7)
 ) b
 ON a.user_id = b.user_id
);

Both users and orders are Delta Lake tables.

Which statement best describes the results of querying recent_orders?

Question 17 Single Choice

A production workload incrementally applies updates from an external Change Data Capture feed to a Delta Lake table as an always-on Structured Stream job. When data was initially migrated for this table, OPTIMIZE was executed and most data files were resized to 1 GB. Auto Optimize and Auto Compaction were both turned on for the streaming production job. Recent review of data files shows that most data files are under 64 MB, although each partition in the table contains at least 1 GB of data and the total table size is over 10 TB.

Which of the following likely explains these smaller file sizes?

Question 18 Single Choice

Which statement regarding stream-static joins and static Delta tables is correct?

Question 19 Single Choice

A junior data engineer has been asked to develop a streaming data pipeline with a grouped aggregation using DataFrame df. The pipeline needs to calculate the average humidity and average temperature for each non-overlapping five-minute interval. Events are recorded once per minute per device.

The schema for the streaming DataFrame df is as follows:

plaintext
"device_id INT, event_time TIMESTAMP, temp FLOAT, humidity FLOAT"

Code block:

python
df.withWatermark("event_time", "10 minutes")
 .groupBy(
 # Fill in the blank here to complete the task
 "device_id"
 )
 .agg(
 avg("temp").alias("avg_temp"),
 avg("humidity").alias("avg_humidity")
 )
 .writeStream
 .format("delta")
 .saveAsTable("sensor_avg")

Choose the response that correctly fills in the blank within the code block to complete this task.

Question 20 Single Choice

A data engineer has decided to nest a checkpoint directory to be shared by both streams. The proposed directory structure is displayed below:

sql
/bronze
 ├── checkpoint
 ├── delta_log
 ├── year_week=2020_01
 ├── year_week=2020_02

Which statement describes whether this checkpoint directory structure is valid for the given scenario and why?

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Frequently Asked Questions

How realistic are the practice questions for the Certified Data Engineer Professional exam?

The practice questions closely mirror the style and complexity of the real exam, helping you familiarize yourself with the types of scenarios you may encounter.

How should I use the practice exam questions to prepare for the certification?

Use the practice questions to identify your strengths and weaknesses, focusing on areas where you feel less confident, and review explanations for both correct and incorrect answers.

How many practice questions should I complete before taking the real exam?

While there is no definitive number, aim to complete as many practice questions as possible, ideally all 323, to gain comprehensive exposure to the exam content.

Can I track my progress while taking the practice exam questions?

Yes, most practice exam platforms provide tools to track your progress and performance, helping you understand which topics need more review.

Is it beneficial to retake the practice questions multiple times?

Retaking practice questions can reinforce learning and help to ensure you retain the material, especially on questions you initially found challenging.

Certified Data Engineer Professional Exam Questions

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Question 11 Single Choice

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Question 12 Single Choice

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Question 13 Single Choice

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Question 14 Single Choice

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Question 15 Single Choice

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Question 16 Single Choice

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Question 17 Single Choice

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Question 18 Single Choice

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Question 19 Single Choice

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Certified Data Engineer Professional Exam Questions

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Question 11 Single Choice

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Question 12 Single Choice

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Question 13 Single Choice

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Question 14 Single Choice

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Question 15 Single Choice

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Question 16 Single Choice

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Question 18 Single Choice

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