Microsoft DP-600 Actual Free Exam Questions & Community Discussion
You have a Fabric warehouse that contains a table named SalesOrderDetail. SalesOrderDetail contains three columns named OrderQty, ProductID and SalesOrderlD. SalesOrderDetail contains one row per combination of SalesOrderlD and ProductID.
You need to calculate the proportion of the total quantity of each sales order represented by each product within the sales order.
Which T-SQL statement should you run?
You need to calculate the proportion of the total quantity of each sales order represented by each product within the sales order.
Which T-SQL statement should you run?
Correct Answer: B
Vote an answer
Explanation: Only visible for EduDump members. You can sign-up / login (it's free).
You have a Fabric workspace that uses the default Spark starter pool and runtime version 1,2.
You plan to read a CSV file named Sales.raw.csv in a lakehouse, select columns, and save the data as a Delta table to the managed area of the lakehouse. Sales_raw.csv contains 12 columns.
You have the following code.
For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point.
You plan to read a CSV file named Sales.raw.csv in a lakehouse, select columns, and save the data as a Delta table to the managed area of the lakehouse. Sales_raw.csv contains 12 columns.
You have the following code.
For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point.
Correct Answer:
Explanation:
The Spark engine will read only the ' SalesOrderNumber ' , ' OrderDate ' , ' CustomerName ' , ' UnitPrice ' columns from Sales_raw.csv. - Yes Removing the partition will reduce the execution time of the query. - No Adding inferSchema= ' true ' to the options will increase the execution time of the query. - Yes The code specifies the selection of certain columns, which means only those columns will be read into the DataFrame. Partitions in Spark are a way to optimize the execution of queries by organizing the data into parts that can be processed in parallel. Removing the partition could potentially increase the execution time because Spark would no longer be able to process the data in parallel efficiently. The inferSchema option allows Spark to automatically detect the column data types, which can increase the execution time of the initial read operation because it requires Spark to read through the data to infer the schema.
You have an Azure Data Lake Storage Gen2 account named storage! that contains a Parquet file named sales.
parquet.
You have a Fabric tenant that contains a workspace named Workspace1.
Using a notebook in Workspace1, you need to load the content of the file to the default lakehouse. The solution must ensure that the content will display automatically as a table named Sales in Lakehouse explorer.
How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
parquet.
You have a Fabric tenant that contains a workspace named Workspace1.
Using a notebook in Workspace1, you need to load the content of the file to the default lakehouse. The solution must ensure that the content will display automatically as a table named Sales in Lakehouse explorer.
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:
Step 1 - Read the Parquet file into a DataFrame
df = spark.read.parquet( " abfss://[email protected]/files/sales.parquet " ) This correctly loads the Parquet data into Spark.
Step 2 - Write into the Lakehouse as a managed table
If we want the result to be registered as a Lakehouse table and automatically appear in Lakehouse Explorer, we must:
Write the data in delta format (because Fabric Lakehouse tables are Delta tables ).
Save the table under the tables folder, not files .
So the correct code is:
df.write.mode( " overwrite " ). format ( " delta " ).saveAsTable( " tables/sales " ) Format: delta SaveAsTable Path: tables/sales References:
Lakehouse tables in Microsoft Fabric
Save DataFrame as Delta Table in Spark
# Answer Selection:
First dropdown # delta
Second dropdown # tables/sales
You have a Fabric tenant that contains a warehouse named Warehouse!. Warehousel contains two schemas name schemal and schema2 and a table named schemal.city.
You need to make a copy of schemal.city in schema2. The solution must minimize the copying of data.
Which T-SQL statement should you run?
You need to make a copy of schemal.city in schema2. The solution must minimize the copying of data.
Which T-SQL statement should you run?
Correct Answer: D
Vote an answer
Explanation: Only visible for EduDump members. You can sign-up / login (it's free).
You have a Fabric tenant that contains a new semantic model in OneLake.
You use a Fabric notebook to read the data into a Spark DataFrame.
You need to evaluate the data to calculate the min, max, mean, and standard deviation values for all the string and numeric columns.
Solution: You use the following PySpark expression:
df.show()
Does this meet the goal?
You use a Fabric notebook to read the data into a Spark DataFrame.
You need to evaluate the data to calculate the min, max, mean, and standard deviation values for all the string and numeric columns.
Solution: You use the following PySpark expression:
df.show()
Does this meet the goal?
Correct Answer: B
Vote an answer
Explanation: Only visible for EduDump members. You can sign-up / login (it's free).
You have a data warehouse that contains a table named Stage. Customers. Stage-Customers contains all the customer record updates from a customer relationship management (CRM) system. There can be multiple updates per customer You need to write a T-SQL query that will return the customer ID, name, postal code, and the last updated time of the most recent row for each customer ID.
How should you complete the code? To answer, select the appropriate options in the answer area, NOTE Each correct selection is worth one point.
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:
In the ROW_NUMBER() function, choose OVER (PARTITION BY CustomerID ORDER BY LastUpdated DESC) .
In the WHERE clause, choose WHERE X = 1 .
To select the most recent row for each customer ID, you use the ROW_NUMBER() window function partitioned by CustomerID and ordered by LastUpdated in descending order. This will assign a row number of 1 to the most recent update for each customer. By selecting rows where the row number ( X ) is 1, you get the latest update per customer.
References =
Use the OVER clause to aggregate data per partition
Use window functions
You have a Fabric tenant that contains a warehouse named WH1. You run the following T-SQL query against WH1.
For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point.
For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point.
Correct Answer:
Explanation:
We are analyzing the query:
SELECT e.[WWI Employee ID],
e.Employee,
e.[Preferred Name],
gdr.[WWI Employee ID] AS [Direct Report ID],
gdr.Employee AS [Direct Report]
FROM Dimension.Employee AS e
OUTER APPLY Dimension.GetDirectReports(e.[Employee Key]) AS gdr;
Key concepts:
APPLY operator : Used to join a table with a table-valued function .
OUTER APPLY ensures all rows from the left (Employee) are returned, even if the function returns no rows (similar to LEFT JOIN).
Table-valued function (TVF) : Returns a set of rows (unlike scalar functions, which return a single value).
The function executes once per row from the left table, not once for the whole query.
Evaluating each statement:
" Dimension.GetDirectReports is a scalar T-SQL function. "
No # It must be a table-valued function , because OUTER APPLY requires a table expression.
" The Dimension.GetDirectReports function will run only once when the query runs. " No # With APPLY , the function runs for each row of Dimension.Employee .
" The output rows will include at least one row for each row in the Dimension.Employee table. " Yes # Because of OUTER APPLY , every employee row is included, even if there are no direct reports (in that case, the columns from gdr will be NULL).
Scalar function # No
Runs once per query # No
At least one row per Employee # Yes
References:
APPLY operator in T-SQL
Table-valued functions
You have a Fabric tenant that contains a workspace named Workspace^ Workspacel is assigned to a Fabric capacity.
You need to recommend a solution to provide users with the ability to create and publish custom Direct Lake semantic models by using external tools. The solution must follow the principle of least privilege.
Which three actions in the Fabric Admin portal should you include in the recommendation? Each correct answer presents part of the solution.
NOTE: Each correct answer is worth one point.
You need to recommend a solution to provide users with the ability to create and publish custom Direct Lake semantic models by using external tools. The solution must follow the principle of least privilege.
Which three actions in the Fabric Admin portal should you include in the recommendation? Each correct answer presents part of the solution.
NOTE: Each correct answer is worth one point.
Correct Answer: B,C,D
Vote an answer
Explanation: Only visible for EduDump members. You can sign-up / login (it's free).
Which type of data store should you recommend in the AnalyticsPOC workspace?
Correct Answer: C
Vote an answer
0
0
0
10