Microsoft Data Engineering on Microsoft Azure - DP-203 Exam Practice Test
You have an Azure subscription.
You plan to build a data warehouse in an Azure Synapse Analytics dedicated SQL pool named pool1 that will contain staging tables and a dimensional model. Pool1 will contain the following tables.
You need to design the table storage for pool1. The solution must meet the following requirements:
Maximize the performance of data loading operations to Staging.WebSessions.
Minimize query times for reporting queries against the dimensional model.
Which type of table distribution should you use for each table? To answer, drag the appropriate table distribution types to the correct tables. Each table distribution type may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
You plan to build a data warehouse in an Azure Synapse Analytics dedicated SQL pool named pool1 that will contain staging tables and a dimensional model. Pool1 will contain the following tables.
You need to design the table storage for pool1. The solution must meet the following requirements:
Maximize the performance of data loading operations to Staging.WebSessions.
Minimize query times for reporting queries against the dimensional model.
Which type of table distribution should you use for each table? To answer, drag the appropriate table distribution types to the correct tables. Each table distribution type may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Correct Answer:
Explanation:
Box 1: Replicated
The best table storage option for a small table is to replicate it across all the Compute nodes.
Box 2: Hash
Hash-distribution improves query performance on large fact tables.
Box 3: Round-robin
Round-robin distribution is useful for improving loading speed.
Reference: https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse- tables-distribute
You have two Azure Blob Storage accounts named account1 and account2?
You plan to create an Azure Data Factory pipeline that will use scheduled intervals to replicate newly created or modified blobs from account1 to account?
You need to recommend a solution to implement the pipeline. The solution must meet the following requirements:
* Ensure that the pipeline only copies blobs that were created of modified since the most recent replication event.
* Minimize the effort to create the pipeline.
What should you recommend?
You plan to create an Azure Data Factory pipeline that will use scheduled intervals to replicate newly created or modified blobs from account1 to account?
You need to recommend a solution to implement the pipeline. The solution must meet the following requirements:
* Ensure that the pipeline only copies blobs that were created of modified since the most recent replication event.
* Minimize the effort to create the pipeline.
What should you recommend?
Correct Answer: A
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You are designing an Azure Stream Analytics solution that will analyze Twitter data.
You need to count the tweets in each 10-second window. The solution must ensure that each tweet is counted only once.
Solution: You use a hopping window that uses a hop size of 10 seconds and a window size of 10 seconds.
Does this meet the goal?
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You are designing an Azure Stream Analytics solution that will analyze Twitter data.
You need to count the tweets in each 10-second window. The solution must ensure that each tweet is counted only once.
Solution: You use a hopping window that uses a hop size of 10 seconds and a window size of 10 seconds.
Does this meet the goal?
Correct Answer: B
Explanation: Only visible for ExamsLabs members. You can sign-up / login (it's free).
You are implementing Azure Stream Analytics windowing functions.
Which windowing function should you use for each requirement? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Which windowing function should you use for each requirement? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Correct Answer:
You are processing streaming data from vehicles that pass through a toll booth.
You need to use Azure Stream Analytics to return the license plate, vehicle make, and hour the last vehicle passed during each 10-minute window.
How should you complete the query? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
You need to use Azure Stream Analytics to return the license plate, vehicle make, and hour the last vehicle passed during each 10-minute window.
How should you complete the query? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Correct Answer:
Explanation:
Box 1: MAX
The first step on the query finds the maximum time stamp in 10-minute windows, that is the time stamp of the last event for that window. The second step joins the results of the first query with the original stream to find the event that match the last time stamps in each window.
Query:
WITH LastInWindow AS
(
SELECT
MAX(Time) AS LastEventTime
FROM
Input TIMESTAMP BY Time
GROUP BY
TumblingWindow(minute, 10)
)
SELECT
Input.License_plate,
Input.Make,
Input.Time
FROM
Input TIMESTAMP BY Time
INNER JOIN LastInWindow
ON DATEDIFF(minute, Input, LastInWindow) BETWEEN 0 AND 10
AND Input.Time = LastInWindow.LastEventTime
Box 2: TumblingWindow
Tumbling windows are a series of fixed-sized, non-overlapping and contiguous time intervals.
Box 3: DATEDIFF
DATEDIFF is a date-specific function that compares and returns the time difference between two DateTime fields, for more information, refer to date functions.
Reference:
https://docs.microsoft.com/en-us/stream-analytics-query/tumbling-window-azure-stream-analytics
You have an Azure Synapse Analytics dedicated SQL pool named Pool1 and an Azure Data Lake Storage Gen2 account named Account1.
You plan to access the files in Account1 by using an external table.
You need to create a data source in Pool1 that you can reference when you create the external table.
How should you complete the Transact-SQL statement? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
You plan to access the files in Account1 by using an external table.
You need to create a data source in Pool1 that you can reference when you create the external table.
How should you complete the Transact-SQL statement? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Correct Answer:
Explanation:
Box 1: blob
The following example creates an external data source for Azure Data Lake Gen2 CREATE EXTERNAL DATA SOURCE YellowTaxi WITH ( LOCATION = 'https://azureopendatastorage.blob.core.windows.net/nyctlc/yellow/', TYPE = HADOOP) Box 2: HADOOP Reference:
https://docs.microsoft.com/en-us/azure/synapse-analytics/sql/develop-tables-external-tables
You have a SQL pool in Azure Synapse.
You discover that some queries fail or take a long time to complete.
You need to monitor for transactions that have rolled back.
Which dynamic management view should you query?
You discover that some queries fail or take a long time to complete.
You need to monitor for transactions that have rolled back.
Which dynamic management view should you query?
Correct Answer: A
Explanation: Only visible for ExamsLabs members. You can sign-up / login (it's free).
You are incrementally loading data into fact tables in an Azure Synapse Analytics dedicated SQL pool.
Each batch of incoming data is staged before being loaded into the fact tables. | You need to ensure that the incoming data is staged as quickly as possible. | How should you configure the staging tables? To answer, select the appropriate options in the answer area.
Each batch of incoming data is staged before being loaded into the fact tables. | You need to ensure that the incoming data is staged as quickly as possible. | How should you configure the staging tables? To answer, select the appropriate options in the answer area.
Correct Answer:
Explanation:
Round-robin distribution is recommended for staging tables because it distributes data evenly across all the distributions without requiring a hash column. This can improve the speed of data loading and avoid data skew. Heap tables are recommended for staging tables because they do not have any indexes or partitions that can slow down the data loading process. Heap tables are also easier to truncate and reload than clustered index or columnstore index tables.
You have an Azure subscription that contains an Azure Cosmos DB database. Azure Synapse Link is implemented on the database. You configure a full fidelity schema for the analytical store. You perform the following actions:
How many columns will the analytical store contain?
How many columns will the analytical store contain?
Correct Answer: C
You have an Azure Synapse Analytics Apache Spark pool named Pool1.
You plan to load JSON files from an Azure Data Lake Storage Gen2 container into the tables in Pool1. The structure and data types vary by file.
You need to load the files into the tables. The solution must maintain the source data types.
What should you do?
You plan to load JSON files from an Azure Data Lake Storage Gen2 container into the tables in Pool1. The structure and data types vary by file.
You need to load the files into the tables. The solution must maintain the source data types.
What should you do?
Correct Answer: C
Explanation: Only visible for ExamsLabs members. You can sign-up / login (it's free).
You have an Azure Data Factory pipeline that performs an incremental load of source data to an Azure Data Lake Storage Gen2 account.
Data to be loaded is identified by a column named LastUpdatedDate in the source table.
You plan to execute the pipeline every four hours.
You need to ensure that the pipeline execution meets the following requirements:
Automatically retries the execution when the pipeline run fails due to concurrency or throttling limits.
Supports backfilling existing data in the table.
Which type of trigger should you use?
Data to be loaded is identified by a column named LastUpdatedDate in the source table.
You plan to execute the pipeline every four hours.
You need to ensure that the pipeline execution meets the following requirements:
Automatically retries the execution when the pipeline run fails due to concurrency or throttling limits.
Supports backfilling existing data in the table.
Which type of trigger should you use?
Correct Answer: B
Explanation: Only visible for ExamsLabs members. You can sign-up / login (it's free).