Databricks Certified Professional Data Engineer - Databricks-Certified-Professional-Data-Engineer FREE EXAM DUMPS QUESTIONS & ANSWERS]

Question 1

A data engineering team has a time-consuming data ingestion job with three data sources. Each notebook takes about one hour to load new data. One day, the job fails because a notebook update introduced a new required configuration parameter. The team must quickly fix the issue and load the latest data from the failing source.
Which action should the team take?

A. Repair the run with the new parameter. B. Share the analysis with the failing notebook owner so that they can fix it quickly. C. Repair the run with the new parameter, and update the task by adding the missing task parameter. D. Update the task by adding the missing task parameter, and manually run the job.

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Correct Answer: C Vote an answer

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Question 2

Which statement describes Delta Lake Auto Compaction?

A. Before a Jobs cluster terminates, optimize is executed on all tables modified during the most recent job. B. An asynchronous job runs after the write completes to detect if files could be further compacted; if yes, an optimize job is executed toward a default of 128 MB. C. Data is queued in a messaging bus instead of committing data directly to memory; all data is committed from the messaging bus in one batch once the job is complete. D. An asynchronous job runs after the write completes to detect if files could be further compacted; if yes, an optimize job is executed toward a default of 1 GB. E. Optimized writes use logical partitions instead of directory partitions; because partition boundaries are only represented in metadata, fewer small files are written.

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Correct Answer: B Vote an answer

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Question 3

A data engineer is performing a join operating to combine values from a static userlookup table with a streaming DataFrame streamingDF.
Which code block attempts to perform an invalid stream-static join?

A. userLookup.join(streamingDF, [ " user_id " ], how= " right " ) B. streamingDF.join(userLookup, [ " user_id"], how= " left " ) C. userLookup.join(streamingDF, [ " userid " ], how= " inner " ) D. streamingDF.join(userLookup, [ " user_id " ], how= " outer " ) E. streamingDF.join(userLookup, [ " userid " ], how= " inner " )

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Question 4

A data engineer manages a production Lakeflow Declarative Pipeline that processes customer transaction data. The pipeline includes several data quality expectations such as transaction_amount > 0 and customer_id IS NOT NULL. These expectations are defined using the EXPECT clause in SQL.
The engineer aims to monitor the pipeline's data quality by analyzing the number of records that passed or failed each expectation during the latest pipeline update. The Lakeflow Declarative Pipelines event logs are stored in a Delta table named event_log_table.
For the most recent pipeline update, determine a programmatically appropriate approach to extract information like the name of each expectation, associated dataset, count of records that passed the expectation, and count of records that failed the expectation.
Which method retrieves the desired data quality metrics from the Lakeflow Declarative Pipelines event log?

A. Access the event_log_table, filter for events where event_type = ' expectation_result ' , and extract the expectation metrics from the details field. B. Use the Lakeflow Declarative Pipelines UI to navigate to the specific pipeline, select the dataset, and view the Data Quality tab to manually retrieve the expectation metrics. C. Access the event_log_table, filter for events where event_type = ' flow_progress ' , and parse details.
flow_progress.data_quality.expectations field to extract the required metrics. D. Query the event_log_table for events with event_type = ' data_quality ' and directly select the passed_records and failed_records fields.

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Question 5

A Delta Lake table with Change Data Feed (CDF) enabled 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. Modify the overwrite logic to include a field populated by calling current_timestamp() as data are being written; use this field to identify records written on a particular date. C. 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. D. 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.

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Correct Answer: D Vote an answer

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Question 6

The security team is exploring whether or not the Databricks secrets module can be leveraged for connecting to an external database.
After testing the code with all Python variables being defined with strings, they upload the password to the secrets module and configure the correct permissions for the currently active user. They then modify their code to the following (leaving all other variables unchanged).

Which statement describes what will happen when the above code is executed?

A. The connection to the external table will fail; the string " redacted " will be printed. B. The connection to the external table will succeed; the string " redacted " will be printed. C. An interactive input box will appear in the notebook; if the right password is provided, the connection will succeed and the password will be printed in plain text. D. An interactive input box will appear in the notebook; if the right password is provided, the connection will succeed and the encoded password will be saved to DBFS. E. The connection to the external table will succeed; the string value of password will be printed in plain text.

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Correct Answer: B Vote an answer

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Question 7

A small company based in the United States has recently contracted a consulting firm in India to implement several new data engineering pipelines to power artificial intelligence applications. All the company ' s data is stored in regional cloud storage in the United States.
The workspace administrator at the company is uncertain about where the Databricks workspace used by the contractors should be deployed.
Assuming that all data governance considerations are accounted for, which statement accurately informs this decision?

A. Cross-region reads and writes can incur significant costs and latency; whenever possible, compute should be deployed in the same region the data is stored. B. Databricks runs HDFS on cloud volume storage; as such, cloud virtual machines must be deployed in the region where the data is stored. C. Databricks workspaces do not rely on any regional infrastructure; as such, the decision should be made based upon what is most convenient for the workspace administrator. D. Databricks notebooks send all executable code from the user ' s browser to virtual machines over the open internet; whenever possible, choosing a workspace region near the end users is the most secure. E. Databricks leverages user workstations as the driver during interactive development; as such, users should always use a workspace deployed in a region they are physically near.

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Question 8

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?

A. The average temperature recordings for at least one sensor exceeded 120 on three consecutive executions of the query B. The total average temperature across all sensors exceeded 120 on three consecutive executions of the query C. The source query failed to update properly for three consecutive minutes and then restarted D. The maximum temperature recording for at least one sensor exceeded 120 on three consecutive executions of the query E. The recent_sensor_recordings table was unresponsive for three consecutive runs of the query

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Question 9

A departing platform owner currently holds ownership of multiple catalogs and controls storage credentials and external locations. A data engineer has been asked to ensure continuity: transfer catalog ownership to the platform team group, delegate ongoing privilege management, and retain the ability to receive and share data via Delta Sharing.
Which role must be in place to perform these actions across the metastore?

A. Metastore Admin, because metastore admins can transfer ownership and manage privileges across all metastore objects, including shares and recipients. B. Catalog Owner, because catalog owners can transfer any object in any catalog in the metastore. C. Workspace Admin, because workspace admins can transfer ownership of any Unity Catalog object. D. Account Admin, because account admins can only create metastores but cannot change ownership of catalogs.

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Question 10

A data engineer has created a transactions Delta table on Databricks that should be used by the analytics team.
The analytics team wants to use the table with another tool that requires Apache Iceberg format.
What should the data engineer do?

A. Require the analytics team to use a tool that supports Delta table. B. Create an Iceberg copy of the transactions Delta table which can be used by the analytics team. C. Enable uniform on the transactions table to ' iceberg ' so that the table can be read as an Iceberg table. D. Convert the transactions Delta table to Iceberg and enable uniform so that the table can be read as a Delta table.

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Correct Answer: D Vote an answer

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Question 11

The data engineering team maintains the following code:

Assuming that this code produces logically correct results and the data in the source table has been de- duplicated and validated, which statement describes what will occur when this code is executed?

A. The gold_customer_lifetime_sales_summary table will be overwritten by aggregated values calculated from all records in the silver_customer_sales table as a batch job. B. An incremental job will leverage running information in the state store to update aggregate values in the gold_customer_lifetime_sales_summary table. C. The silver_customer_sales table will be overwritten by aggregated values calculated from all records in the gold_customer_lifetime_sales_summary table as a batch job. D. An incremental job will detect if new rows have been written to the silver_customer_sales table; if new rows are detected, all aggregates will be recalculated and used to overwrite the gold_customer_lifetime_sales_summary table. E. A batch job will update the gold_customer_lifetime_sales_summary table, replacing only those rows that have different values than the current version of the table, using customer_id as the primary key.

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Question 12

A data engineering team needs to implement a tagging system for their tables as part of an automated ETL process, and needs to apply tags programmatically to tables in Unity Catalog.
Which SQL command adds tags to a table programmatically?

A. ALTER TABLE table_name SET TAGS ( ' key1 ' = ' value1 ' , ' key2 ' = ' value2 ' ); B. SET TAGS FOR table_name AS ( ' key1 ' = ' value1 ' , ' key2 ' = ' value2 ' ); C. COMMENT ON TABLE table_name TAGS ( ' key1 ' = ' value1 ' , ' key2 ' = ' value2 ' ); D. APPLY TAGS ON table_name VALUES ( ' key1 ' = ' value1 ' , ' key2 ' = ' value2 ' );

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Question 13

A junior data engineer is migrating a workload from a relational database system to the Databricks Lakehouse. The source system uses a star schema, leveraging foreign key constrains and multi-table inserts to validate records on write.
Which consideration will impact the decisions made by the engineer while migrating this workload?

A. All Delta Lake transactions are ACID compliance against a single table, and Databricks does not enforce foreign key constraints. B. Committing to multiple tables simultaneously requires taking out multiple table locks and can lead to a state of deadlock. C. Foreign keys must reference a primary key field; multi-table inserts must leverage Delta Lake ' s upsert functionality. D. Databricks only allows foreign key constraints on hashed identifiers, which avoid collisions in highly- parallel writes.

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Question 14

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?

A. 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. B. 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. C. Each write to the orders table will only contain unique records, and only those records without duplicates in the target table will be written. D. Each write to the orders table will run deduplication over the union of new and existing records, ensuring no duplicate records are present. E. Each write to the orders table will only contain unique records, but newly written records may have duplicates already present in the target table.

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Correct Answer: E Vote an answer

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