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Databricks Databricks-Certified-Professional-Data-Engineer Dumps Questions Answers

Databricks-Certified-Professional-Data-Engineer exam

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Databricks Certified Data Engineer Professional Exam

Last Update May 30, 2023
Total Questions : 222

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Last Update May 30, 2023
Total Questions : 222

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Databricks Certified Data Engineer Professional Exam Questions and Answers

Questions 1

Which of the following operations are not supported on a streaming dataset view?




SELECT sum(unitssold) FROM streaming_view


SELECT max(unitssold) FROM streaming_view


SELECT id, sum(unitssold) FROM streaming_view GROUP BY id ORDER BY id


SELECT id, count(*) FROM streaming_view GROUP BY id


SELECT * FROM streadming_view ORDER BY id

Questions 2

You have written a notebook to generate a summary data set for reporting, Notebook was scheduled using the job cluster, but you realized it takes 8 minutes to start the cluster, what feature can be used to start the cluster in a timely fashion so your job can run immediatley?



Setup an additional job to run ahead of the actual job so the cluster is running second job starts


Use the Databricks cluster pools feature to reduce the startup time


Use Databricks Premium edition instead of Databricks standard edition


Pin the cluster in the cluster UI page so it is always available to the jobs


Disable auto termination so the cluster is always running

Questions 3

You are trying to calculate total sales made by all the employees by parsing a complex struct data type that stores employee and sales data, how would you approach this in SQL

Table definition,

batchId INT, performance ARRAY>, in-sertDate TIMESTAMP

Sample data of performance column


2.{ "employeeId":1234

3."sales" : 10000},


5.{ "employeeId":3232

6."sales" : 30000}


Calculate total sales made by all the employees?

Sample data with create table syntax for the data:

1.create or replace table sales as 1 as batchId ,

3.from_json('[{ "employeeId":1234,"sales" : 10000 },{ "employeeId":3232,"sales" : 30000 }]',

4. 'ARRAY>') as performance,

5. current_timestamp() as insertDate

6.union all 2 as batchId ,

8. from_json('[{ "employeeId":1235,"sales" : 10500 },{ "employeeId":3233,"sales" : 32000 }]',

9. 'ARRAY>') as performance,

10. current_timestamp() as insertDate



1.WITH CTE as (SELECT EXPLODE (performance) FROM table_name)

2.SELECT SUM (performance.sales) FROM CTE


1.WITH CTE as (SELECT FLATTEN (performance) FROM table_name)


C. aggregate(flatten(collect_list(performance.sales)), 0, (x, y) -> x + y) total_sales from sales


SELECT SUM(SLICE (performance, sales)) FROM employee

E. reduce(flatten(collect_list(performance:sales)), 0, (x, y) -> x + y) total_sales from sales

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