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Databricks Databricks-Certified-Professional-Data-Engineer Exam Overview:

Exam Component Description
Detail Information
Exam Cost $400 USD
Total Time 2 hours
Available Languages English
Passing Marks 70%
Exam Format Multiple Choice, True/False, and Lab-based
Prerequisites None
Validity 2 years

Databricks Certified Data Engineer Professional Exam Topics Breakdown

Domain Weight (%) Description
Data Engineering 40 Design, build, and maintain data pipelines
Data Analysis 30 Analyze data and enable machine learning
Advanced Topics 30 Advanced Spark optimization and production considerations

Few More Databricks-Certified-Professional-Data-Engineer Exact Exam Questions:

Question # 1

Each configuration below is identical to the extent that each cluster has 400 GB total of RAM, 160 total cores and only one Executor per VM. Given a job with at least one wide transformation, which of the following cluster configurations will result in maximum performance?

A. Total VMs; 1 • 400 GB per Executor • 160 Cores / Executor

B. • Total VMs: 8 • 50 GB per Executor • 20 Cores / Executor

C. Total VMs: 16 • 25 GB per Executor • 10 Cores/Executor

D. • Total VMs: 4 • 100 GB per Executor • 40 Cores/Executor

E. • Total VMs:2 • 200 GB per Executor • 80 Cores / Executor

Answer: B

Frequently Asked Questions

Databricks Databricks-Certified-Professional-Data-Engineer Sample Question Answers

Question # 1

The data governance team has instituted a requirement that all tables containing PersonalIdentifiable Information (PH) must be clearly annotated. This includes adding columncomments, table comments, and setting the custom table property"contains_pii" = true.The following SQL DDL statement is executed to create a new table: Which command allows manual confirmation that these three requirements have been met?

A. DESCRIBE EXTENDED dev.pii test
B. DESCRIBE DETAIL dev.pii test
C. SHOW TBLPROPERTIES dev.pii test
D. DESCRIBE HISTORY dev.pii test
E. SHOW TABLES dev

Question # 2

An upstream system is emitting change data capture (CDC) logs that are being written to acloud 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 aprimary key identified by the fieldpk_id.For auditing purposes, the data governance team wishes to maintain a full record of allvalues that have ever been valid in the source system. For analytical purposes, only themost recent value for each record needs to be recorded. The Databricks job to ingest theserecords occurs once per hour, but each individual record may have changed multiple timesover 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 byrunning 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 abronze table, then propagate all changes throughout the system.
C. Iterate through an ordered set of changes to the table, applying each in turn; rely onDelta Lake's versioning ability to create an audit log.
D. Use Delta Lake's change data feed to automatically process CDC data from an externalsystem, 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 deletethe most recent entry for each pk_id into a silver table to recreate the current table state.

Question # 3

Which configuration parameter directly affects the size of a spark-partition upon ingestionof 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

Question # 4

A production cluster has 3 executor nodes and uses the same virtual machine type for thedriver and executor.When evaluating the Ganglia Metrics for this cluster, which indicator would signal abottleneck caused by code executing on the driver?

A. The five Minute Load Average remains consistent/flat
B. Bytes Received never exceeds 80 million bytes per second
C. Total Disk Space remains constant
D. Network I/O never spikes
E. Overall cluster CPU utilization is around 25%

Question # 5

A junior data engineer on your team has implemented the following code block. The viewnew_eventscontains a batch of records with the same schema as theeventsDeltatable. Theevent_idfield serves as a unique key for this table.When this query is executed, what will happen with new records that have thesameevent_idas an existing record?

A. They are merged.
B. They are ignored.
C. They are updated.
D. They are inserted.
E. They are deleted.

Question # 6

A user new to Databricks is trying to troubleshoot long execution times for some pipelinelogic they are working on. Presently, the user is executing code cell-by-cell, usingdisplay()calls to confirm code is producing the logically correct results as new transformations areadded to an operation. To get a measure of average time to execute, the user is runningeach cell multiple times interactively.Which of the following adjustments will get a more accurate measure of how code is likelyto perform in production?

A. Scala is the only language that can be accurately tested using interactive notebooks; because the best performance is achieved by using Scala code compiled to JARs. all PySpark and Spark SQL logic should be refactored.
B. The only way to meaningfully troubleshoot code execution times in developmentnotebooks Is to use production-sized data and production-sized clusters with Run Allexecution.
C. Production code development should only be done using an IDE; executing codeagainst a local build of open source Spark and Delta Lake will provide the most accuratebenchmarks for how code will perform in production.
D. Calling display () forces a job to trigger, while many transformations will only add to thelogical query plan; because of caching, repeated execution of the same logic does notprovide meaningful results.
E. The Jobs Ul should be leveraged to occasionally run the notebook as a job and trackexecution time during incremental code development because Photon can only be enabledon clusters launched for scheduled jobs.

Question # 7

The viewupdatesrepresents an incremental batch of all newly ingested data to be inserted or updated in thecustomerstable. 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 anew column alongside the current value.
B. The customers table is implemented as a Type 2 table; old values are maintained butmarked 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 withno changes to existing values.
D. The customers table is implemented as a Type 1 table; old values are overwritten bynew values and no history is maintained.
E. The customers table is implemented as a Type 2 table; old values are overwritten andnew customers are appended.

Question # 8

Although the Databricks Utilities Secrets module provides tools to store sensitivecredentials and avoid accidentally displaying them in plain text users should still be carefulwith which credentials are stored here and which users have access to using these secrets.Which statement describes a limitation of Databricks Secrets?

A. Because the SHA256 hash is used to obfuscate stored secrets, reversing this hash will display the value in plain text.
B. Account administrators can see all secrets in plain text by loggingon to the DatabricksAccounts console.
C. Secrets are stored in an administrators-only table within the Hive Metastore; databaseadministrators have permission to query this table by default.
D. Iterating through a stored secret and printing each character will display secret contentsin plain text.
E. The Databricks REST API can be used to list secrets in plain text if the personal accesstoken has proper credentials.

Question # 9

Where in the Spark UI can one diagnose a performance problem induced by not leveragingpredicate push-down?

A. In the Executor's log file, by grippingfor "predicate push-down"
B. In the Stage's Detail screen, in the Completed Stages table, by noting the size of dataread from the Input column
C. In the Storage Detail screen, by noting which RDDs are not stored on disk
D. In the Delta Lake transaction log. by noting the column statistics
E. In the Query Detail screen, by interpreting the Physical Plan

Question # 10

Which of the following is true of Delta Lake and the Lakehouse?

A. Because Parquet compresses data row by row. strings will only be compressed when acharacter is repeated multiple times.
B. Delta Lake automatically collects statistics on the first 32 columns of each table whichare leveraged in data skipping based on query filters.
C. Views in the Lakehouse maintain a valid cache of the most recent versions of sourcetables at all times.
D. Primary and foreign key constraints can be leveraged to ensure duplicate values arenever entered into a dimension table.
E. Z-order can only be applied to numeric values stored in Delta Lake tables

Question # 11

A Delta Lake table representing metadata about content posts from users has the followingschema:user_id LONG, post_text STRING, post_id STRING, longitude FLOAT, latitude FLOAT,post_time TIMESTAMP, date DATEThis table is partitioned by the date column. A query is run with the following filter:longitude < 20 & longitude > -20Which statement describes how data will be filtered?

A. Statistics in the Delta Log will be used to identify partitions that might Include files in thefiltered range.
B. No file skipping will occur because the optimizer does not know the relationship betweenthe partition column and the longitude.
C. The Delta Engine will use row-level statistics in the transaction log to identify the fliesthat meet the filter criteria.
D. Statistics in the Delta Log will be used to identify data files that might include records inthe filtered range.
E. The Delta Engine will scan the parquet file footers to identify each row that meets thefilter criteria.

Question # 12

The data science team has created and logged a production model using MLflow. Thefollowing code correctly imports and applies the production model to output the predictionsas a new DataFrame namedpredswith the schema "customer_id LONG, predictionsDOUBLE, date DATE". The data science team would like predictions saved to a Delta Lake table with the ability tocompare 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. Option A
B. Option B
C. Option C
D. Option D
E. Option E

Question # 13

Which REST API call can be used to review the notebooks configured to run as tasks in amulti-task job?

A. /jobs/runs/list
B. /jobs/runs/get-output
C. /jobs/runs/get
D. /jobs/get
E. /jobs/list

Question # 14

A data architect has designed a system in which two Structured Streaming jobs willconcurrently write to a single bronze Delta table. Each job is subscribing to a different topicfrom an Apache Kafka source, but they will write data with the same schema. To keep thedirectory structure simple, a data engineer has decided to nest a checkpoint directory to beshared by both streams.The proposed directory structure is displayed below: Which statement describes whether this checkpoint directory structure is valid for the givenscenario and why?

A. No; Delta Lake manages streaming checkpoints in the transaction log.
B. Yes; both of the streams can share a single checkpoint directory.
C. No; only one stream can write to a Delta Lake table.
D. Yes; Delta Lake supports infinite concurrent writers.
E. No; each of the streams needs to have its own checkpoint directory.

Question # 15

The data engineering team maintains a table of aggregate statistics through batch nightlyupdates. This includes total sales for the previous day alongside totals and averages for avariety of time periods including the 7 previous days, year-to-date, and quarter-to-date.This table is namedstore_saies_summaryand the schema is as follows: The tabledaily_store_salescontains all the information needed to updatestore_sales_summary. The schema for this table is:store_id INT, sales_date DATE, total_sales FLOATIfdaily_store_salesis implemented as a Type 1 table and thetotal_salescolumn might beadjusted after manual data auditing, which approach is the safest to generate accuratereports in thestore_sales_summarytable?

A. Implement the appropriate aggregate logic as a batch read against the daily_store_salestable and overwrite the store_sales_summary table with each Update.
B. Implement the appropriate aggregate logic as a batch read against the daily_store_salestable and append new rows nightly to the store_sales_summary table.
C. Implement the appropriate aggregate logic as a batch read against the daily_store_salestable and use upsert logic to update results in the store_sales_summary table.
D. Implement the appropriate aggregate logic as a Structured Streaming read against the daily_store_sales table and use upsert logic to update results in the store_sales_summarytable.
E. Use Structured Streaming to subscribe to the change data feed for daily_store_salesand apply changes to the aggregates in the store_sales_summary table with each update.

Question # 16

A Databricks job has been configured with 3 tasks, each of which is a Databricks notebook.Task A does not depend on other tasks. Tasks B and C run in parallel, with each having aserial dependency on task A.If tasks A and B complete successfully but task C fails during a scheduled run, whichstatement describes the resulting state?

A. All logic expressed in the notebook associated with tasks A and B will have beensuccessfully completed; some operations in task C may have completed successfully.
B. All logic expressed in the notebook associated with tasks A and B will have beensuccessfully completed; any changes made in task C will be rolled back due to task failure.
C. All logic expressed in the notebook associated with task A will have been successfullycompleted; tasks B and C will not commit any changes because of stage failure.
D. Because all tasks are managed as a dependency graph, no changes will be committedto the Lakehouse until ail tasks have successfully been completed.
E. Unless all tasks complete successfully, no changes will be committed to the Lakehouse;because task C failed, all commits will be rolled back automatically.

Question # 17

A junior data engineer has configured a workload that posts the following JSON to theDatabricks REST API endpoint2.0/jobs/create. Assuming that all configurations and referenced resources are available, which statementdescribes the result of executing this workload three times?

A. Three new jobs named "Ingest new data" will be defined in the workspace, and they willeach run once daily.
B. The logic defined in the referenced notebook will be executed three times on newclusters with the configurations of the provided cluster ID.
C. Three new jobs named "Ingest new data" will be defined in the workspace, but no jobswill be executed.
D. One new job named "Ingest new data" will be defined in the workspace, but it will not beexecuted.
E. The logic defined in the referenced notebook will be executed three times on thereferenced existing all purpose cluster.

Question # 18

A table is registered with the following code: Bothusersandordersare Delta Lake tables. Which statement describes the results of queryingrecent_orders?

A. All logic will execute at query time and return the result of joining the valid versions of the source tables at the time the query finishes.
B. All logic will execute when the table is definedand store the result of joiningtables to the DBFS; this stored data will be returned when the table is queried.
C. Results will be computed and cached when the table is defined; these cached results will incrementally update as new records are inserted into source tables.
D. All logic will execute at query time and return the result of joining the valid versions of the source tables at the time the query began.
E. The versions of each source table will be stored in the table transaction log; query results will be saved to DBFS with each query.

Question # 19

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_storeWhich result will occur after running the second command?

A. The table reference in the metastore is updated and no data is changed.
B. The table name change is recorded in the Delta transaction log.
C. All related files and metadata are dropped and recreated in a single ACID transaction.
D. The table reference in the metastore is updated and all data files are moved.
E. A new Delta transaction log Is created for the renamed table.

Question # 20

A junior data engineer has been asked to develop a streaming data pipeline with a groupedaggregation using DataFramedf. The pipeline needs to calculate the average humidity andaverage temperature for each non-overlapping five-minute interval. Events are recordedonce per minute per device.Streaming DataFramedfhas the following schema:"device_id INT, event_time TIMESTAMP, temp FLOAT, humidity FLOAT"Code block: Choose the response that correctly fills in the blank within the code block to complete thistask.

A. to_interval("event_time", "5 minutes").alias("time")
B. window("event_time", "5 minutes").alias("time")
C. "event_time"
D. window("event_time", "10 minutes").alias("time")
E. lag("event_time", "10 minutes").alias("time")

Question # 21

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

A. Each microbatch of a stream-static join will use the most recent version of the staticDelta table as of each microbatch.
B. Each microbatch of a stream-static join will use the most recent version of the staticDelta table as of the job's initialization.
C. The checkpoint directory will be used to track state information for the unique keyspresent in the join.
D. Stream-static joins cannot use static Delta tables because of consistency issues.
E. The checkpoint directory will be used to track updates to the static Delta table.

Question # 22

The DevOps team has configured a production workload as a collection of notebooksscheduled to run daily using the Jobs UI. A new data engineering hire is onboarding to theteam and has requested access to one of these notebooks to review the production logic.What are the maximum notebook permissions that can be granted to the user withoutallowing accidental changes to production code or data?

A. Can Manage
B. Can Edit
C. No permissions
D. Can Read
E. Can Run

Question # 23

Which Python variable contains a list of directories to be searched when trying to locaterequired modules?

A. importlib.resource path
B. ,sys.path
C. os-path
D. pypi.path
E. pylib.source

Question # 24

A data engineer, User A, has promoted a new pipeline to production by using the RESTAPI to programmatically create several jobs. A DevOps engineer, User B, has configuredan external orchestration tool to trigger job runs through the REST API. Both usersauthorized the REST API calls using their personal access tokens.Which statement describes the contents of the workspace audit logs concerning theseevents?

A. Because the REST API was used for job creation and triggering runs, a ServicePrincipal will be automatically used to identity these events.
B. Because User B last configured the jobs, their identity will be associated with both thejob creation events and the job run events.
C. Because these events are managed separately, User A will have their identityassociated with the job creation events and User B will have their identity associated withthe job run events.
D. Because the REST API was used for job creation and triggering runs, user identity willnot be captured in the audit logs.
E. Because User A created the jobs, their identity will be associated with both the jobcreation events and the job run events.

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