Databricks DATABRICKS-CERTIFIED-PROFESSIONAL-DATA-ENGINEER Online Practice Questions and Exam Preparation

Databricks DATABRICKS-CERTIFIED-PROFESSIONAL-DATA-ENGINEER Online Questions & Answers

• Question 21:

  Which distribution does Databricks support for installing custom Python code packages?

  A. sbt
  B. CRAN
  C. CRAM
  D. nom
  E. Wheels
  F. jars
  D. nom

• Question 22:

  A data engineer is configuring a pipeline that will potentially see late-arriving, duplicate records.

  In addition to de-duplicating records within the batch, which of the following approaches allows the data engineer to deduplicate data against previously processed records as it is inserted into a Delta table?

  A. Set the configuration delta.deduplicate = true.
  B. VACUUM the Delta table after each batch completes.
  C. Perform an insert-only merge with a matching condition on a unique key.
  D. Perform a full outer join on a unique key and overwrite existing data.
  E. Rely on Delta Lake schema enforcement to prevent duplicate records.
  C. Perform an insert-only merge with a matching condition on a unique key.

• Question 23:

  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 ofVACUUMcommands 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.
  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 24:

  A table named user_ltv is being used to create a view that will be used by data analysis on various teams. Users in the workspace are configured into groups, which are used for setting up data access using ACLs.

  The user_ltv table has the following schema:

  email STRING, age INT, ltv INT

  The following view definition is executed:

  CREATE VIEW user_ltv_no_minors AS SELECT email, age, ltv FROM user_ltv WHERE

  CASE

  WHEN is_member("auditing") THEN TRUE

  ELSE age >= 18

  END

  An analyze who is not a member of the auditing group executing the following query:

  SELECT * FROM user_ltv_no_minors

  Which result will be returned by this query?

  A. All columns will be displayed normally for those records that have an age greater than 18; records not meeting this condition will be omitted.
  B. All columns will be displayed normally for those records that have an age greater than 17; records not meeting this condition will be omitted.
  C. All age values less than 18 will be returned as null values all other columns will be returned with the values in user_ltv.
  D. All records from all columns will be displayed with the values in user_ltv.
  A. All columns will be displayed normally for those records that have an age greater than 18; records not meeting this condition will be omitted.

• Question 25:

  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. Databricks runs HDFS on cloud volume storage; as such, cloud virtual machines must be deployed in the region where the data is stored.
  B. 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.
  C. 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.
  D. 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.
  E. 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.
  C. 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.

• Question 26:

  The downstream consumers of a Delta Lake table have been complaining about data quality issues impacting performance in their applications. Specifically, they have complained that invalidlatitudeandlongitudevalues in theactivity_detailstable have been breaking their ability to use other geolocation processes.

  A junior engineer has written the following code to addCHECKconstraints to the Delta Lake table:

  

  A senior engineer has confirmed the above logic is correct and the valid ranges for latitude and longitude are provided, but the code fails when executed. Which statement explains the cause of this failure?

  A. Because another team uses this table to support a frequently running application, two- phase locking is preventing the operation from committing.
  B. The activity details table already exists; CHECK constraints can only be added during initial table creation.
  C. The activity details table already contains records that violate the constraints; all existing data must pass CHECK constraints in order to add them to an existing table.
  D. The activity details table already contains records; CHECK constraints can only be added prior to inserting values into a table.
  E. The current table schema does not contain the field valid coordinates; schema evolution will need to be enabled before altering the table to add a constraint.
  C. The activity details table already contains records that violate the constraints; all existing data must pass CHECK constraints in order to add them to an existing table.

• Question 27:

  A data architect has heard about lake's built-in versioning and time travel capabilities. For auditing purposes they have a requirement to maintain a full of all valid street addresses as they appear in the customers table.

  The architect is interested in implementing a Type 1 table, overwriting existing records with new values and relying on Delta Lake time travel to support long-term auditing. A data engineer on the project feels that a Type 2 table will provide

  better performance and scalability.

  Which piece of information is critical to this decision?

  A. Delta Lake time travel does not scale well in cost or latency to provide a long-term versioning solution.
  B. Delta Lake time travel cannot be used to query previous versions of these tables because Type 1 changes modify data files in place.
  C. Shallow clones can be combined with Type 1 tables to accelerate historic queries for long-term versioning.
  D. Data corruption can occur if a query fails in a partially completed state because Type 2 tables requires Setting multiple fields in a single update.
  A. Delta Lake time travel does not scale well in cost or latency to provide a long-term versioning solution.

• Question 28:

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

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

• Question 29:

  What statement is true regarding the retention of job run history?

  A. It is retained until you export or delete job run logs
  B. It is retained for 30 days, during which time you can deliver job run logs to DBFS or S3
  C. t is retained for 60 days, during which you can export notebook run results to HTML
  D. It is retained for 60 days, after which logs are archived
  E. It is retained for 90 days or until the run-id is re-used through custom run configuration
  C. t is retained for 60 days, during which you can export notebook run results to HTML

• Question 30:

  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.

  MERGE INTO customers

  USING (

  SELECT updates.customer_id as merge_ey, updates .*

  FROM updates

  UNION ALL

  SELECT NULL as merge_key, updates .*

  FROM updates JOIN customers

  ON updates.customer_id = customers.customer_id

  WHERE customers.current = true AND updates.address <> customers.address

  ) staged_updates

  ON customers.customer_id = mergekey

  WHEN MATCHED AND customers. current = true AND customers.address <> staged_updates.address THEN

  UPDATE SET current = false, end_date = staged_updates.effective_date

  WHEN NOT MATCHED THEN

  INSERT (customer_id, address, current, effective_date, end_date)

  VALUES (staged_updates.customer_id, staged_updates.address, true, staged_updates.effective_date, null)

  Which statement describes this implementation?

  A. The customers table is implemented as a Type 2 table; old values are overwritten and new customers are appended.
  B. The customers table is implemented as a Type 1 table; old values are overwritten by new values and no history is maintained.
  C. 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.
  D. The customers table is implemented as a Type 0 table; all writes are append only with no changes to existing values.
  C. 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.