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Databricks Certified Data Engineer Professional Exam Sample Questions (Q89-Q94):

NEW QUESTION # 89
Which of the following technologies can be used to identify key areas of text when parsing Spark Driver log4j output?

* A. Scala Datasets
* B. Regex
* C. Julia
* D. C++
* E. pyspsark.ml.feature
Answer: B

Explanation:
Regex, or regular expressions, are a powerful way of matching patterns in text. They can be used Get Latest & Actual Certified-Data-Engineer-Professional Exam's Question and Answers from to identify key areas of text when parsing Spark Driver log4j output, such as the log level, the timestamp, the thread name, the class name, the method name, and the message. Regex can be applied in various languages and frameworks, such as Scala, Python, Java, Spark SQL, and Databricks notebooks.

NEW QUESTION # 90
A Delta Lake table representing metadata about content from user has the following schema:
Based on the above schema, which column is a good candidate for partitioning the Delta Table?

* A. Date
* B. Post_id
* C. Post_time
* D. latitude
* E. User_id
Answer: A

Explanation:
Partitioning a Delta Lake table improves query performance by organizing data into partitions based on the values of a column. In the given schema, the date column is a good candidate for partitioning for several reasons:
Time-Based Queries: If queries frequently filter or group by date, partitioning by the date column can significantly improve performance by limiting the amount of data scanned. Granularity: The date column likely has a granularity that leads to a reasonable number of partitions (not too many and not too few). This balance is important for optimizing both read and write performance.
Data Skew: Other columns like post_id or user_id might lead to uneven partition sizes (data skew), which can negatively impact performance.
Get Latest & Actual Certified-Data-Engineer-Professional Exam's Question and Answers from Partitioning by post_time could also be considered, but typically date is preferred due to its more manageable granularity.

NEW QUESTION # 91
Assuming that the Databricks CLI has been installed and configured correctly, which Databricks CLI command can be used to upload a custom Python Wheel to object storage mounted with the DBFS for use with a production job?

* A. workspace
* B. configure
* C. jobs
* D. fs
* E. libraries
Answer: D

Explanation:
https://docs.databricks.com/en/archive/dev-tools/cli/dbfs-cli.html

NEW QUESTION # 92
The data architect has mandated that all tables in the Lakehouse should be configured as external (also known as "unmanaged") Delta Lake tables.
Which approach will ensure that this requirement is met?

* A. When the workspace is being configured, make sure that external cloud object storage has been mounted.
* B. When tables are created, make sure that the EXTERNAL keyword is used in the CREATE TABLE statement.
* C. When a database is being created, make sure that the LOCATION keyword is used.
* D. When configuring an external data warehouse for all table storage, leverage Databricks for all ELT.
* E. When data is saved to a table, make sure that a full file path is specified alongside the Delta format.
Answer: B

Explanation:
Get Latest & Actual Certified-Data-Engineer-Professional Exam's Question and Answers from To create an external or unmanaged Delta Lake table, you need to use the EXTERNAL keyword in the CREATE TABLE statement. This indicates that the table is not managed by the catalog and the data files are not deleted when the table is dropped. You also need to provide a LOCATION clause to specify the path where the data files are stored.
For example:
CREATE EXTERNAL TABLE events ( date DATE, eventId STRING, eventType STRING, data STRING) USING DELTA LOCATION `/mnt/delta/events'; This creates an external Delta Lake table named events that references the data files in the
`/mnt/delta/events' path. If you drop this table, the data files will remain intact and you can recreate the table with the same statement.

NEW QUESTION # 93
A table is registered with the following code:
Get Latest & Actual Certified-Data-Engineer-Professional Exam's Question and Answers from

Both users and orders are Delta Lake tables. Which statement describes the results of querying recent_orders?

* A. 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.
* B. All logic will execute when the table is defined and store the result of joining tables to the DBFS; this stored data will be returned when the table is queried.
* C. The versions of each source table will be stored in the table transaction log; query results will be saved to DBFS with each query.
* 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. 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.
Answer: B

Explanation:
Table is created and data of join will be stored on DBFS and it will be returned on query time.

NEW QUESTION # 94
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