最新のMicrosoft DP-203のPDFと問題集で（2024）無料試験問題解答
あなたを合格させるMicrosoft Certified: Azure Data Engineer Associate DP-203試験問題集で2024年11月04日には335問あります
質問 # 83
You plan to create a real-time monitoring app that alerts users when a device travels more than 200 meters away from a designated location.
You need to design an Azure Stream Analytics job to process the data for the planned app. The solution must minimize the amount of code developed and the number of technologies used.
What should you include in the Stream Analytics job? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
正解：
解説：
Explanation
Diagram, table Description automatically generated
Input type: Stream
You can process real-time IoT data streams with Azure Stream Analytics.
Function: Geospatial
With built-in geospatial functions, you can use Azure Stream Analytics to build applications for scenarios such as fleet management, ride sharing, connected cars, and asset tracking.
Note: In a real-world scenario, you could have hundreds of these sensors generating events as a stream.
Ideally, a gateway device would run code to push these events to Azure Event Hubs or Azure IoT Hubs.
Reference:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-get-started-with-azure-stream-analytics
https://docs.microsoft.com/en-us/azure/stream-analytics/geospatial-scenarios
質問 # 84
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?
- A. schedule
- B. tumbling window
- C. on-demand
- D. event
正解：B
解説：
In case of pipeline failures, tumbling window trigger can retry the execution of the referenced pipeline automatically, using the same input parameters, without the user intervention. This can be specified using the property "retryPolicy" in the trigger definition.
Reference:
https://docs.microsoft.com/en-us/azure/data-factory/how-to-create-tumbling-window-trigger
質問 # 85
You have an Azure Storage account that generates 200,000 new files daily. The file names have a format of {YYYY}/{MM}/{DD}/{HH}/{CustomerID}.csv.
You need to design an Azure Data Factory solution that will load new data from the storage account to an Azure Data Lake once hourly. The solution must minimize load times and costs.
How should you configure the solution? To answer, select the appropriate options in the answer are a.
NOTE: Each correct selection is worth one point.
正解：
解説：
Reference:
https://docs.microsoft.com/en-us/stream-analytics-query/tumbling-window-azure-stream-analytics
質問 # 86
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.
正解：
解説：
Reference:
https://docs.microsoft.com/en-us/stream-analytics-query/session-window-azure-stream-analytics
https://docs.microsoft.com/en-us/stream-analytics-query/tumbling-window-azure-stream-analytics
質問 # 87
You need to implement an Azure Databricks cluster that automatically connects to Azure Data Lake Storage Gen2 by using Azure Active Directory (Azure AD) integration.
How should you configure the new cluster? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
正解：
解説：
Reference:
https://docs.azuredatabricks.net/spark/latest/data-sources/azure/adls-passthrough.html
質問 # 88
You have an Azure Data Factory instance named ADF1 and two Azure Synapse Analytics workspaces named WS1 and WS2.
ADF1 contains the following pipelines:
P1: Uses a copy activity to copy data from a nonpartitioned table in a dedicated SQL pool of WS1 to an Azure Data Lake Storage Gen2 account P2: Uses a copy activity to copy data from text-delimited files in an Azure Data Lake Storage Gen2 account to a nonpartitioned table in a dedicated SQL pool of WS2 You need to configure P1 and P2 to maximize parallelism and performance.
Which dataset settings should you configure for the copy activity if each pipeline? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
正解：
解説：
Explanation
Box 1: Set the Copy method to PolyBase
While SQL pool supports many loading methods including non-Polybase options such as BCP and SQL BulkCopy API, the fastest and most scalable way to load data is through PolyBase. PolyBase is a technology that accesses external data stored in Azure Blob storage or Azure Data Lake Store via the T-SQL language.
Box 2: Set the Copy method to Bulk insert
Polybase not possible for text files. Have to use Bulk insert.
Reference:
https://docs.microsoft.com/en-us/azure/synapse-analytics/sql/load-data-overview
質問 # 89
You have a data model that you plan to implement in a data warehouse in Azure Synapse Analytics as shown in the following exhibit.
All the dimension tables will be less than 2 GB after compression, and the fact table will be approximately 6 TB.
Which type of table should you use for each table? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
正解：
解説：
Explanation
質問 # 90
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 scenario, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have an Azure Storage account that contains 100 GB of files. The files contain text and numerical values. 75% of the rows contain description data that has an average length of 1.1 MB.
You plan to copy the data from the storage account to an Azure SQL data warehouse.
You need to prepare the files to ensure that the data copies quickly.
Solution: You modify the files to ensure that each row is more than 1 MB.
Does this meet the goal?
- A. No
- B. Yes
正解：A
解説：
Explanation
Instead modify the files to ensure that each row is less than 1 MB.
References:
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/guidance-for-loading-data
質問 # 91
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 are a.
NOTE: Each correct selection is worth one point.
正解：
解説：
Reference:
https://docs.microsoft.com/en-us/stream-analytics-query/session-window-azure-stream-analytics
https://docs.microsoft.com/en-us/stream-analytics-query/tumbling-window-azure-stream-analytics
質問 # 92
The following code segment is used to create an Azure Databricks cluster.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
正解：
解説：
Reference:
https://adatis.co.uk/databricks-cluster-sizing/
https://docs.microsoft.com/en-us/azure/databricks/jobs
https://docs.databricks.com/administration-guide/capacity-planning/cmbp.html
https://docs.databricks.com/delta/index.html
質問 # 93
You have an Azure Data Factory pipeline named pipeline1 that is invoked by a tumbling window trigger named Trigger1. Trigger1 has a recurrence of 60 minutes.
You need to ensure that pipeline1 will execute only if the previous execution completes successfully.
How should you configure the self-dependency for Trigger1?
- A. offset: "01:00:00" size: "-01:00:00"
- B. offset: "-01:00:00" size: "01:00:00"
- C. offset: "01:00:00" size: "01:00:00"
- D. offset: "-00:01:00" size: "00:01:00"
正解：B
解説：
Explanation
Tumbling window self-dependency properties
In scenarios where the trigger shouldn't proceed to the next window until the preceding window is successfully completed, build a self-dependency. A self-dependency trigger that's dependent on the success of earlier runs of itself within the preceding hour will have the properties indicated in the following code.
Example code:
"name": "DemoSelfDependency",
"properties": {
"runtimeState": "Started",
"pipeline": {
"pipelineReference": {
"referenceName": "Demo",
"type": "PipelineReference"
}
},
"type": "TumblingWindowTrigger",
"typeProperties": {
"frequency": "Hour",
"interval": 1,
"startTime": "2018-10-04T00:00:00Z",
"delay": "00:01:00",
"maxConcurrency": 50,
"retryPolicy": {
"intervalInSeconds": 30
},
"dependsOn": [
{
"type": "SelfDependencyTumblingWindowTriggerReference",
"size": "01:00:00",
"offset": "-01:00:00"
}
]
}
}
}
Reference: https://docs.microsoft.com/en-us/azure/data-factory/tumbling-window-trigger-dependency
質問 # 94
You have an Azure Synapse Analytics dedicated SQL pool named Pool1. Pool1 contains a fact table named Tablet. Table1 contains sales data. Sixty-five million rows of data are added to Table1 monthly.
At the end of each month, you need to remove data that is older than 36 months. The solution must minimize how long it takes to remove the data.
How should you partition Table1, and how should you remove the old data? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
正解：
解説：
Explanation
質問 # 95
You plan to develop a dataset named Purchases by using Azure databricks Purchases will contain the following columns:
* ProductID
* ItemPrice
* lineTotal
* Quantity
* StorelD
* Minute
* Month
* Hour
* Year
* Day
You need to store the data to support hourly incremental load pipelines that will vary for each StoreID. the solution must minimize storage costs. How should you complete the rode? To answer, select the appropriate options In the answer are a.
NOTE: Each correct selection is worth one point.
正解：
解説：
Reference:
https://intellipaat.com/community/11744/how-to-partition-and-write-dataframe-in-spark-without-deleting-partitions-with-no-new-data
質問 # 96
You have an Azure Data Factory pipeline that has the activity 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.
正解：
解説：
質問 # 97
You have an Azure subscription that contains the resources shown in the following table.
You need to ensure that you can Spark notebooks in ws1. The solution must ensure secrets from kv1 by using UAMI1. What should you do? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
正解：
解説：
質問 # 98
You have an Azure subscription that contains an Azure Data Factory data pipeline named Pipeline1, a Log Analytics workspace named LA1, and a storage account named account1.
You need to retain pipeline-run data for 90 days. The solution must meet the following requirements:
* The pipeline-run data must be removed automatically after 90 days.
* Ongoing costs must be minimized.
Which two actions should you perform? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.
- A. Configure Pipeline1 to send logs to account1.
- B. From the Data Retention settings of LA1, set the data retention period to 90 days.
- C. Configure Pipeline1 to send logs to LA1.
- D. From the Diagnostic settings (classic) settings of account1. set the retention period to 90 days.
正解：C、D
質問 # 99
You are responsible for providing access to an Azure Data Lake Storage Gen2 account.
Your user account has contributor access to the storage account, and you have the application ID and access key.
You plan to use PolyBase to load data into an enterprise data warehouse in Azure Synapse Analytics.
You need to configure PolyBase to connect the data warehouse to storage account.
Which three components should you create in sequence? To answer, move the appropriate components from the list of components to the answer area and arrange them in the correct order.
正解：
解説：
1 - a database scoped credential
2 - an external data source
3 - an external file format
質問 # 100
You have the following Azure Stream Analytics query.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
正解：
解説：
Reference:
https://azure.microsoft.com/en-in/blog/maximize-throughput-with-repartitioning-in-azure-stream-analytics/
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-streaming-unit-consumption
質問 # 101
You need to implement an Azure Synapse Analytics database object for storing the sales transactions data. The solution must meet the sales transaction dataset requirements.
What solution must meet the sales transaction dataset requirements.
What should you do? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
正解：
解説：
Explanation
Graphical user interface, text, application, table Description automatically generated
Box 1: Create table
Scenario: Load the sales transaction dataset to Azure Synapse Analytics Box 2: RANGE RIGHT FOR VALUES Scenario: Partition data that contains sales transaction records. Partitions must be designed to provide efficient loads by month. Boundary values must belong to the partition on the right.
RANGE RIGHT: Specifies the boundary value belongs to the partition on the right (higher values).
FOR VALUES ( boundary_value [,...n] ): Specifies the boundary values for the partition.
Scenario: Load the sales transaction dataset to Azure Synapse Analytics.
Contoso identifies the following requirements for the sales transaction dataset:
Partition data that contains sales transaction records. Partitions must be designed to provide efficient loads by month. Boundary values must belong to the partition on the right.
Ensure that queries joining and filtering sales transaction records based on product ID complete as quickly as possible.
Implement a surrogate key to account for changes to the retail store addresses.
Ensure that data storage costs and performance are predictable.
Minimize how long it takes to remove old records.
Reference:
https://docs.microsoft.com/en-us/sql/t-sql/statements/create-table-azure-sql-data-warehouse
質問 # 102
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 have an Azure Storage account that contains 100 GB of files. The files contain rows of text and numerical values. 75% of the rows contain description data that has an average length of 1.1 MB.
You plan to copy the data from the storage account to an enterprise data warehouse in Azure Synapse Analytics.
You need to prepare the files to ensure that the data copies quickly.
Solution: You copy the files to a table that has a columnstore index.
Does this meet the goal?
- A. No
- B. Yes
正解：A
解説：
Instead convert the files to compressed delimited text files.
Reference:
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/guidance-for-loading-data
質問 # 103
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 scenario, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have an Azure Storage account that contains 100 GB of files. The files contain text and numerical values. 75% of the rows contain description data that has an average length of 1.1 MB.
You plan to copy the data from the storage account to an Azure SQL data warehouse.
You need to prepare the files to ensure that the data copies quickly.
Solution: You modify the files to ensure that each row is less than 1 MB.
Does this meet the goal?
- A. Yes
- B. No
正解：A
解説：
When exporting data into an ORC File Format, you might get Java out-of-memory errors when there are large text columns. To work around this limitation, export only a subset of the columns.
References:
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/guidance-for-loading-data
質問 # 104
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マイクロソフトDP-203試験は、Azureプラットフォーム上のデータエンジニアリングにおいてキャリアを進めたいデータエンジニア、データアーキテクト、およびデータ専門家に適しています。この認定試験は、データエンジニアリング、データウェアハウジング、およびデータ分析の経験を持つ個人に最適です。この試験に合格することで、データ専門家は、Microsoft Azureサービスを使用してデータソリューションを設計および実装する能力を証明し、業界でのスキルと知識を認められることができます。
Microsoft DP-203：Microsoft Azure試験のデータエンジニアリングは、さまざまなAzureサービスを使用してデータソリューションを設計および実装するために必要なスキルと知識をテストするように設計されています。この試験は、データエンジニア、データアーキテクト、ビジネスインテリジェンス開発者と協力する専門家を対象としています。この試験は、Microsoft Certified：Azure Data Engineer Associate認定の一部です。
DP-203問題集はMicrosoft Certified: Azure Data Engineer Associate認証済み試験問題と解答：https://www.goshiken.com/Microsoft/DP-203-mondaishu.html
DP-203無料試験学習ガイド！（更新された335問あります)：https://drive.google.com/open?id=1UV1bhjyFxOTVH4zQWEitmFazfV4yv1d2