QUICK AND EASIEST WAY OF GETTING DATABRICKS-CERTIFIED-DATA-ENGINEER-PROFESSIONAL DATABRICKS CERTIFIED DATA ENGINEER PROFESSIONAL EXAM CERTIFICATION EXAM

Quick and Easiest Way of Getting Databricks-Certified-Data-Engineer-Professional Databricks Certified Data Engineer Professional Exam Certification Exam

Quick and Easiest Way of Getting Databricks-Certified-Data-Engineer-Professional Databricks Certified Data Engineer Professional Exam Certification Exam

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Databricks Certified Data Engineer Professional Exam Sample Questions (Q97-Q102):

NEW QUESTION # 97
The data engineer is using Spark's MEMORY_ONLY storage level. Which indicators should the data engineer look for in the spark UI's Storage tab to signal that a cached table is not performing optimally?

  • A. The number of Cached Partitions> the number of Spark Partitions
  • B. The RDD Block Name included the '' annotation signaling failure to cache
  • C. Size on Disk is < Size in Memory
  • D. Size on Disk is> 0
  • E. On Heap Memory Usage is within 75% of off Heap Memory usage

Answer: D

Explanation:
When using Spark's MEMORY_ONLY storage level, the ideal scenario is that the data is fully cached in memory, and the Size on Disk should be 0 (indicating that the data is not spilled to disk). If the Size on Disk is greater than 0, it suggests that some data has been spilled to disk, which can lead to degraded performance as reading from disk is slower than reading from memory.


NEW QUESTION # 98
The data governance team is reviewing user for deleting records for compliance with GDPR. The following logic has been implemented to propagate deleted requests from the user_lookup table to the user aggregate table.

Assuming that user_id is a unique identifying key and that all users have requested deletion have been removed from the user_lookup table, which statement describes whether successfully executing the above logic guarantees that the records to be deleted from the user_aggregates table are no longer accessible and why?

  • A. No; the Delta Lake DELETE command only provides ACID guarantees when combined with the MERGE INTO command
  • B. Yes; Delta Lake ACID guarantees provide assurance that the DELETE command successed fully and permanently purged these records.
  • C. No; files containing deleted records may still be accessible with time travel until a BACUM command is used to remove invalidated data files.
  • D. Yes; the change data feed uses foreign keys to ensure delete consistency throughout the Lakehouse.
  • E. No; the change data feed only tracks inserts and updates not deleted records.

Answer: C

Explanation:
Get Latest & Actual Certified-Data-Engineer-Professional Exam's Question and Answers from Explanation:
The DELETE operation in Delta Lake is ACID compliant, which means that once the operation is successful, the records are logically removed from the table. However, the underlying files that contained these records may still exist and be accessible via time travel to older versions of the table. To ensure that these records are physically removed and compliance with GDPR is maintained, a VACUUM command should be used to clean up these data files after a certain retention period. The VACUUM command will remove the files from the storage layer, and after this, the records will no longer be accessible.


NEW QUESTION # 99
A junior data engineer on your team has implemented the following code block.

The view new_events contains a batch of records with the same schema as the events Delta table. The event_id field serves as a unique key for this table.
When this query is executed, what will happen with new records that have the same event_id as an existing record?

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

Answer: A

Explanation:
This is the correct answer because it describes what will happen with new records that have the same event_id as an existing record when the query is executed. The query uses the INSERT INTO command to append new records from the view new_events to the table events. However, the INSERT INTO command does not check for duplicate values in the primary key column (event_id) and does not perform any update or delete operations on existing records. Therefore, if there are new records that have the same event_id as an existing record, they will be ignored and not inserted into the table events.


NEW QUESTION # 100
Which statement describes Delta Lake optimized writes?

  • A. Optimized writes logical partitions instead of directory partitions partition boundaries are only Get Latest & Actual Certified-Data-Engineer-Professional Exam's Question and Answers from represented in metadata fewer small files are written.
  • B. An asynchronous job runs after the write completes to detect if files could be further compacted; yes, an OPTIMIZE job is executed toward a default of 1 GB.
  • C. A shuffle occurs prior to writing to try to group data together resulting in fewer files instead of each executor writing multiple files based on directory partitions.
  • D. Before a job cluster terminates, OPTIMIZE is executed on all tables modified during the most recent job.

Answer: C

Explanation:
Delta Lake optimized writes involve a shuffle operation before writing out data to the Delta table.
The shuffle operation groups data by partition keys, which can lead to a reduction in the number of output files and potentially larger files, instead of multiple smaller files. This approach can significantly reduce the total number of files in the table, improve read performance by reducing the metadata overhead, and optimize the table storage layout, especially for workloads with many small files.


NEW QUESTION # 101
The Databricks CLI is use to trigger a run of an existing job by passing the job_id parameter. The response that the job run request has been submitted successfully includes a filed run_id.
Get Latest & Actual Certified-Data-Engineer-Professional Exam's Question and Answers from Which statement describes what the number alongside this field represents?

  • A. The globally unique ID of the newly triggered run.
  • B. The total number of jobs that have been run in the workspace.
  • C. The job_id and number of times the job has been are concatenated and returned.
  • D. The job_id is returned in this field.
  • E. The number of times the job definition has been run in the workspace.

Answer: A

Explanation:
When triggering a job run using the Databricks CLI, the run_id field in the response represents a globally unique identifier for that particular run of the job. This run_id is distinct from the job_id.
While the job_id identifies the job definition and is constant across all runs of that job, the run_id is unique to each execution and is used to track and query the status of that specific job run within the Databricks environment. This distinction allows users to manage and reference individual executions of a job directly.


NEW QUESTION # 102
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