You have a Fabric tenant that contains a lakehouse named Lakehouse1. Lakehouse1 contains a table named Nyctaxi_raw. Nyctaxi_raw contains the following columns.

You create a Fabric notebook and attach it to lakehouse1.
You need to use PySpark code to transform the data. The solution must meet the following requirements:
* Add a column named pickupDate that will contain only the date portion of pickupDateTime.
* Filter the DataFrame to include only rows where fareAmount is a positive number that is less than 100.
How should you complete the code? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

Correct Answer:

Explanation:

* Add the pickupDate column: .withColumn("pickupDate", df["pickupDateTime"].cast("date"))
* Filter the DataFrame: .filter("fareAmount > 0 AND fareAmount < 100")
In PySpark, you can add a new column to a DataFrame using the .withColumn method, where the first argument is the new column name and the second argument is the expression to generate the content of the new column. Here, we use the .cast("date") function to extract only the date part from a timestamp. To filter the DataFrame, you use the .filter method with a condition that selects rows where fareAmount is greater than 0 and less than 100, thus ensuring only positive values less than 100 are included.

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You have a Fabric tenant that contains a workspace named Workspace1. Workspace1 contains a lakehouse named I.H1 and a warehouse named DW1. I.H1 contains a table named signindata that is in the dho schema.
You need to create a stored procedure in DW1 that deduplicates the data in the signindata table.
How should you complete the T-SQL statement? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Correct Answer:

Explanation:

Scenario Recap
Fabric tenant # Workspace1
Contains:
Lakehouse LH1 (with table signindata in schema dho )
Warehouse DW1
Task: Create a stored procedure in DW1 that deduplicates rows in signindata .
Step 1: Stored procedure structure
In T-SQL, stored procedures begin with:
AS
BEGIN
-- logic
END
So the correct option for the first blank is BEGIN .
BEGIN DISTRIBUTED TRANSACTION is not needed because we are not spanning multiple servers or needing distributed transactions.
SET is not the right way to start the logic block.
Step 2: Deduplication logic
To remove duplicates from signindata , the query should return unique rows .
The simplest way is:
SELECT DISTINCT PersonID, FirstName, LastName
FROM dho.signindata;
Thus the correct choice for the second blank is DISTINCT .
GROUP BY could also deduplicate but is less efficient here since no aggregation is requested.
TOP 100 PERCENT WITH TIES is irrelevant.
Step 3: Final T-SQL stored procedure
CREATE PROCEDURE dbo.usp_GetPerson
AS
BEGIN
SELECT DISTINCT PersonID, FirstName, LastName
FROM dho.signindata;
EN D ;
Why this is correct
BEGIN # correct stored procedure structure.
DISTINCT # ensures deduplication of rows from signindata .
References
CREATE PROCEDURE (Transact-SQL)
DISTINCT (Transact-SQL)

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You have a Fabric workspace named Workspace1 and a warehouse named Warehouse1. Workspace1 contains a user named User1. User1 is assigned the Viewer role for Workspace1.
You need to ensure that User1 can share Warehouse1 with other users. The solution must follow the principle of least privilege.
Which role should you assign to User1?

• A.Contributor for Workspace1
• B.Member for Workspace1
• C.Admin for Workspace1
• D.db.owner for Warehouse1

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You have a Fabric eventhouse that contains a KQL database. The database contains a table named TaxiData that stores the following data.

You need to create a column named FirstPickupDateTime that will contain the first value of each hour from tpep_pickup_datetime partitioned by payment_type.
NOTE: Each correct selection is worth one point.

Correct Answer:

Explanation:

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You have a Fabric tenant that contains a warehouse named Warehouse1. Warehouse1 contains two schemas name schema1 and schema2 and a table named schema1.city.
You need to make a copy of schema1.city in schema2. The solution must minimize the copying of data.
Which T-SQL statement should you run?

• A.INSERT INTO schema2.city SELECT * FROM schema1.city;
• B.SELECT * INTO schema2.city FROM schema1.city;
• C.CREATE TABLE schema2.city AS CLONE OF schema1.city;
• D.CREATE TABLE schema2.city AS SELECT * FROM schema1.city;

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