You have an Azure Synapse workspace named MyWorkspace that contains an Apache Spark database named mytestdb.
You run the following command in an Azure Synapse Analytics Spark pool in MyWorkspace.
CREATE TABLE mytestdb.myParquetTable(
EmployeeID int,
EmployeeName string,
EmployeeStartDate date)
USING Parquet -
You then use Spark to insert a row into mytestdb.myParquetTable. The row contains the following data.
 
One minute later, you execute the following query from a serverless SQL pool in MyWorkspace.
SELECT EmployeeID -
FROM mytestdb.dbo.myParquetTable
WHERE EmployeeName = 'Alice';
What will be returned by the query?

A. 24

B. an error

C. a null value










 

Suggested Answer: A

Once a database has been created by a Spark job, you can create tables in it with Spark that use Parquet as the storage format. Table names will be converted to lower case and need to be queried using the lower case name. These tables will immediately become available for querying by any of the Azure Synapse workspace Spark pools. They can also be used from any of the Spark jobs subject to permissions.
Note: For external tables, since they are synchronized to serverless SQL pool asynchronously, there will be a delay until they appear.
Reference:
https://docs.microsoft.com/en-us/azure/synapse-analytics/metadata/table

This question is in DP-203 Data Engineering on Microsoft Azure Exam
For getting Microsoft Certified: Azure Data Engineer Associate Certificate


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