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  • Exam Name: Databricks Certified Data Engineer Professional Exam
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Databricks-Certified-Professional-Data-Engineer Questions and Answers

Question # 1

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

1.[

2.{ "employeeId":1234

3."sales" : 10000},

4.

5.{ "employeeId":3232

6."sales" : 30000}

7.]

Calculate total sales made by all the employees?

Sample data with create table syntax for the data:

1.create or replace table sales as

2.select 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

7.select 2 as batchId ,

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

9. 'ARRAY>') as performance,

10. current_timestamp() as insertDate

A.

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

2.SELECT SUM (performance.sales) FROM CTE

B.

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

2.SELECT SUM (sales) FROM CTE

C.

1.select aggregate(flatten(collect_list(performance.sales)), 0, (x, y) -> x + y)

2.as total_sales from sales

D.

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

E.

1.select reduce(flatten(collect_list(performance:sales)), 0, (x, y) -> x + y)

2.as total_sales from sales

Question # 2

Which of the following technique can be used to implement fine-grained access control to rows and columns of the Delta table based on the user's access?

A.

Use Unity catalog to grant access to rows and columns

B.

Row and column access control lists

C.

Use dynamic view functions

D.

Data access control lists

E.

Dynamic Access control lists with Unity Catalog

Question # 3

Which of the following data workloads will utilize a Bronze table as its destination?

A.

A job that aggregates cleaned data to create standard summary statistics

B.

A job that queries aggregated data to publish key insights into a dashboard

C.

A job that ingests raw data from a streaming source into the Lakehouse

D.

A job that develops a feature set for a machine learning application

E.

A job that enriches data by parsing its timestamps into a human-readable format

Question # 4

You are working on IOT data where each device has 5 reading in an array collected in Celsius, you were asked to covert each individual reading from Celsius to Fahrenheit, fill in the blank with an appropriate function that can be used in this scenario.

Schema: deviceId INT, deviceTemp ARRAY

Databricks-Certified-Professional-Data-Engineer question answer

SELECT deviceId, __(deviceTempC,i-> (i * 9/5) + 32) as deviceTempF

FROM sensors

A.

APPLY

B.

MULTIPLY

C.

ARRAYEXPR

D.

TRANSFORM

E.

FORALL

Question # 5

The team has decided to take advantage of table properties to identify a business owner for each table, which of the following table DDL syntax allows you to populate a table property identifying the business owner of a table

CREATE TABLE inventory (id INT, units FLOAT)

A.

SET TBLPROPERTIES business_owner = 'supply chain'

CREATE TABLE inventory (id INT, units FLOAT)

B.

TBLPROPERTIES (business_owner = 'supply chain')

C.

CREATE TABLE inventory (id INT, units FLOAT)

SET (business_owner = ‘supply chain’)

D.

CREATE TABLE inventory (id INT, units FLOAT)

SET PROPERTY (business_owner = ‘supply chain’)

E.

CREATE TABLE inventory (id INT, units FLOAT)

SET TAG (business_owner = ‘supply chain’)

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