免費下載DP-203考題 & DP-203熱門考題每個人都有自己的夢想，你夢想呢，是升職、是加薪或者等等。我的夢想的通過Microsoft的DP-203考試認證，我覺得有了這個認證，所有的問題都不是問題，不過想要通過這個認證是比較困難，不過不要緊，我選擇PDFExamDumps Microsoft的DP-203考試培訓資料，它可以幫助我實現我的夢想，如果也有IT夢，那就趕緊把它變成現實吧，選擇PDFExamDumps Microsoft的DP-203考試培訓資料，絕對信得過。 最新的 Microsoft Certified: Azure Data Engineer Associate DP-203 免費考試真題 (Q225-Q230):問題 #225
You have an Azure Synapse Analytics dedicated SQL pool.
You need to create a table named FactInternetSales that will be a large fact table in a dimensional model.
FactInternetSales will contain 100 million rows and two columns named SalesAmount and OrderQuantity.
Queries executed on FactInternetSales will aggregate the values in SalesAmount and OrderQuantity from the last year for a specific product. The solution must minimize the data size and query execution time.
How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point. 答案：
解題說明：
Explanation:
Box 1: (CLUSTERED COLUMNSTORE INDEX
CLUSTERED COLUMNSTORE INDEX
Columnstore indexes are the standard for storing and querying large data warehousing fact tables. This index uses column-based data storage and query processing to achieve gains up to 10 times the query performance in your data warehouse over traditional row-oriented storage. You can also achieve gains up to 10 times the data compression over the uncompressed data size. Beginning with SQL Server 2016 (13.x) SP1, columnstore indexes enable operational analytics: the ability to run performant real-time analytics on a transactional workload.
Note: Clustered columnstore index
A clustered columnstore index is the physical storage for the entire table.
To reduce fragmentation of the column segments and improve performance, the columnstore index might store some data temporarily into a clustered index called a deltastore and a B-tree list of IDs for deleted rows.
The deltastore operations are handled behind the scenes. To return the correct query results, the clustered columnstore index combines query results from both the columnstore and the deltastore.
Box 2: HASH([ProductKey])
A hash distributed table distributes rows based on the value in the distribution column. A hash distributed table is designed to achieve high performance for queries on large tables.
Choose a distribution column with data that distributes evenly
Reference: https://docs.microsoft.com/en-us ... re-indexes-overview https://docs.microsoft.com/en-us ... a-warehouse-tables- overview https://docs.microsoft.com/en-us ... a-warehouse-tables- distribute
問題 #226
You have an Azure Synapse Analytics dedicated SQL pool named SQL1 that contains a hash-distributed fact table named Table1.
You need to recreate Table1 and add a new distribution column. The solution must maximize the availability of data.
Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order. 答案：
解題說明：
Explanation:
問題 #227
You have an Azure Data Factory pipeline that has the activities shown in the following exhibit.
Use the drop-down menus to select the answer choice that completes each statement based on the information presented in the graphic.
NOTE: Each correct selection is worth one point. 答案：
解題說明：
Explanation
Box 1: succeed
Box 2: failed
Example:
Now let's say we have a pipeline with 3 activities, where Activity1 has a success path to Activity2 and a failure path to Activity3. If Activity1 fails and Activity3 succeeds, the pipeline will fail. The presence of the success path alongside the failure path changes the outcome reported by the pipeline, even though the activity executions from the pipeline are the same as the previous scenario.
Activity1 fails, Activity2 is skipped, and Activity3 succeeds. The pipeline reports failure.
Reference: https://datasavvy.me/2021/02/18/ ... -pipeline-outcomes/
問題 #228
You have an Azure Synapse Analytics dedicated SQL pool.
You need to create a table named FactInternetSales that will be a large fact table in a dimensional model. FactInternetSales will contain 100 million rows and two columns named SalesAmount and OrderQuantity. Queries executed on FactInternetSales will aggregate the values in SalesAmount and OrderQuantity from the last year for a specific product. The solution must minimize the data size and query execution time.
How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point. 答案：
解題說明：
Reference: https://docs.microsoft.com/en-us ... use-tables-overview https://docs.microsoft.com/en-us ... e-tables-distribute
問題 #229
You are implementing an Azure Stream Analytics solution to process event data from devices.
The devices output events when there is a fault and emit a repeat of the event every five seconds until the fault is resolved. The devices output a heartbeat event every five seconds after a previous event if there are no faults present.
A sample of the events is shown in the following table.
You need to calculate the uptime between the faults.
How should you complete the Stream Analytics SQL query? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point. 答案：
解題說明：
Reference: https://docs.microsoft.com/en-us ... re-stream-analytics https://docs.microsoft.com/en-us ... re-stream-analytics
