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Databricks Certified Data Engineer Professional Sample Questions:
1. Although the Databricks Utilities Secrets module provides tools to store sensitive credentials and avoid accidentally displaying them in plain text users should still be careful with which credentials are stored here and which users have access to using these secrets.
Which statement describes a limitation of Databricks Secrets?
A) Iterating through a stored secret and printing each character will display secret contents in plain text.
B) Because the SHA256 hash is used to obfuscate stored secrets, reversing this hash will display Get Latest & Actual Certified-Data-Engineer-Professional Exam's Question and Answers from the value in plain text.
C) Secrets are stored in an administrators-only table within the Hive Metastore; database administrators have permission to query this table by default.
D) The Databricks REST API can be used to list secrets in plain text if the personal access token has proper credentials.
E) Account administrators can see all secrets in plain text by logging on to the Databricks Accounts console.
2. A data ingestion task requires a one-TB JSON dataset to be written out to Parquet with a target Get Latest & Actual Certified-Data-Engineer-Professional Exam's Question and Answers from part- file size of 512 MB. Because Parquet is being used instead of Delta Lake, built-in file-sizing features such as Auto-Optimize & Auto-Compaction cannot be used.
Which strategy will yield the best performance without shuffling data?
A) Ingest the data, execute the narrow transformations, repartition to 2,048 partitions (1TB*
1024*1024/512), and then write to parquet.
B) Set spark.sql.files.maxPartitionBytes to 512 MB, ingest the data, execute the narrow transformations, and then write to parquet.
C) Set spark.sql.adaptive.advisoryPartitionSizeInBytes to 512 MB bytes, ingest the data, execute the narrow transformations, coalesce to 2,048 partitions (1TB*1024*1024/512), and then write to parquet.
D) Set spark.sql.shuffle.partitions to 512, ingest the data, execute the narrow transformations, and then write to parquet.
E) Set spark.sql.shuffle.partitions to 2,048 partitions (1TB*1024*1024/512), ingest the data, execute the narrow transformations, optimize the data by sorting it (which automatically repartitions the data), and then write to parquet.
3. Review the following error traceback:
Get Latest & Actual Certified-Data-Engineer-Professional Exam's Question and Answers from
Which statement describes the error being raised?
A) There is no column in the table named heartrateheartrateheartrate
B) There is a type error because a column object cannot be multiplied.
C) There is a type error because a DataFrame object cannot be multiplied.
D) The code executed was PvSoark but was executed in a Scala notebook.
E) There is a syntax error because the heartrate column is not correctly identified as a column.
4. What is the first of a Databricks Python notebook when viewed in a text editor?
A) %python
B) // Databricks notebook source
C) # Databricks notebook source
D) -- Databricks notebook source
E) # MAGIC %python
5. 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 change data feed only tracks inserts and updates not deleted records.
B) Yes; Delta Lake ACID guarantees provide assurance that the DELETE command successed fully and permanently purged these records.
C) No; the Delta Lake DELETE command only provides ACID guarantees when combined with the MERGE INTO command
D) No; files containing deleted records may still be accessible with time travel until a BACUM command is used to remove invalidated data files.
E) Yes; the change data feed uses foreign keys to ensure delete consistency throughout the Lakehouse.
Solutions:
Question # 1 Answer: D | Question # 2 Answer: E | Question # 3 Answer: A | Question # 4 Answer: C | Question # 5 Answer: D |

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