DP-200-Topic2_在线真题试卷与模拟练习_DP-200-Topic2

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You develop a data ingestion process that will import data to an enterprise data warehouse in Azure Synapse Analytics. The data to be ingested resides in parquet files stored in an Azure Data Lake Gen 2 storage account.
You need to load the data from the Azure Data Lake Gen 2 storage account into the Data Warehouse.
Solution:
Create an external data source pointing to the Azure storage account
Create a workload group using the Azure storage account name as the pool name
Load the data using the INSERT`¦SELECT statement
Does the solution meet the goal?

You develop data engineering solutions for a company.

You must integrate the company's on-premises Microsoft SQL Server data with Microsoft Azure SQL Database. Data must be transformed incrementally.

You need to implement the data integration solution.

Which tool should you use to configure a pipeline to copy data?

You plan to create an Azure Databricks workspace that has a tiered structure. The workspace will contain the following three workloads:
✑ A workload for data engineers who will use Python and SQL
✑ A workload for jobs that will run notebooks that use Python, Scala, and SQL
✑ A workload that data scientists will use to perform ad hoc analysis in Scala and R
The enterprise architecture team at your company identifies the following standards for Databricks environments:
✑ The data engineers must share a cluster.
✑ The job cluster will be managed by using a request process whereby data scientists and data engineers provide packaged notebooks for deployment to the cluster.
✑ All the data scientists must be assigned their own cluster that terminates automatically after 120 minutes of inactivity. Currently, there are three data scientists.
You need to create the Databricks clusters for the workloads.
Solution: You create a Standard cluster for each data scientist, a High Concurrency cluster for the data engineers, and a Standard cluster for the jobs.
Does this meet the goal?

You plan to create an Azure Databricks workspace that has a tiered structure. The workspace will contain the following three workloads:
✑ A workload for data engineers who will use Python and SQL
✑ A workload for jobs that will run notebooks that use Python, Scala, and SQL
✑ A workload that data scientists will use to perform ad hoc analysis in Scala and R
The enterprise architecture team at your company identifies the following standards for Databricks environments:
✑ The data engineers must share a cluster.
✑ The job cluster will be managed by using a request process whereby data scientists and data engineers provide packaged notebooks for deployment to the cluster.
✑ All the data scientists must be assigned their own cluster that terminates automatically after 120 minutes of inactivity. Currently, there are three data scientists.
You need to create the Databricks clusters for the workloads.
Solution: You create a Standard cluster for each data scientist, a High Concurrency cluster for the data engineers, and a High Concurrency cluster for the jobs.
Does this meet the goal?

You plan to create an Azure Databricks workspace that has a tiered structure. The workspace will contain the following three workloads:
✑ A workload for data engineers who will use Python and SQL
✑ A workload for jobs that will run notebooks that use Python, Scala, and SQL
✑ A workload that data scientists will use to perform ad hoc analysis in Scala and R
The enterprise architecture team at your company identifies the following standards for Databricks environments:
✑ The data engineers must share a cluster.
✑ The job cluster will be managed by using a request process whereby data scientists and data engineers provide packaged notebooks for deployment to the cluster.
✑ All the data scientists must be assigned their own cluster that terminates automatically after 120 minutes of inactivity. Currently, there are three data scientists.
You need to create the Databricks clusters for the workloads.
Solution: You create a High Concurrency cluster for each data scientist, a High Concurrency cluster for the data engineers, and a Standard cluster for the jobs.
Does this meet the goal?

Each day, company plans to store hundreds of files in Azure Blob Storage and Azure Data Lake Storage. The company uses the parquet format.
You must develop a pipeline that meets the following requirements:
✑ Process data every six hours
✑ Offer interactive data analysis capabilities
✑ Offer the ability to process data using solid-state drive (SSD) caching
✑ Use Directed Acyclic Graph(DAG) processing mechanisms
✑ Provide support for REST API calls to monitor processes
✑ Provide native support for Python
✑ Integrate with Microsoft Power BI
You need to select the appropriate data technology to implement the pipeline.
Which data technology should you implement?

You develop a data ingestion process that will import data to an enterprise data warehouse in Azure Synapse Analytics. The data to be ingested resides in parquet files stored in an Azure Data Lake Gen 2 storage account.
You need to load the data from the Azure Data Lake Gen 2 storage account into the Data Warehouse.
Solution:
Create an external data source pointing to the Azure Data Lake Gen 2 storage account
Create an external file format and external table using the external data source
Load the data using the CREATE TABLE AS SELECT statement
Does the solution meet the goal?

You develop a data ingestion process that will import data to an enterprise data warehouse in Azure Synapse Analytics. The data to be ingested resides in parquet files stored in an Azure Data Lake Gen 2 storage account.
You need to load the data from the Azure Data Lake Gen 2 storage account into the Data Warehouse.
Solution:
Create a remote service binding pointing to the Azure Data Lake Gen 2 storage account
Create an external file format and external table using the external data source
Load the data using the CREATE TABLE AS SELECT statement
Does the solution meet the goal?

You develop a data ingestion process that will import data to an enterprise data warehouse in Azure Synapse Analytics. The data to be ingested resides in parquet files stored in an Azure Data Lake Gen 2 storage account.
You need to load the data from the Azure Data Lake Gen 2 storage account into the Data Warehouse.
Solution:
Create an external data source pointing to the Azure storage account
Create a workload group using the Azure storage account name as the pool name
Load the data using the CREATE TABLE AS SELECT statement
Does the solution meet the goal?

You need to develop a pipeline for processing data. The pipeline must meet the following requirements:
✑ Scale up and down resources for cost reduction
✑ Use an in-memory data processing engine to speed up ETL and machine learning operations.
✑ Use streaming capabilities
✑ Provide the ability to code in SQL, Python, Scala, and R
Integrate workspace collaboration with Git
What should you use?

You are developing a solution that will use Azure Stream Analytics. The solution will accept an Azure Blob storage file named Customers. The file will contain both in-store and online customer details. The online customers will provide a mailing address.
You have a file in Blob storage named LocationIncomes that contains median incomes based on location. The file rarely changes.
You need to use an address to look up a median income based on location. You must output the data to Azure SQL Database for immediate use and to Azure
Data Lake Storage Gen2 for long-term retention.
Solution: You implement a Stream Analytics job that has one streaming input, one query, and two outputs.
Does this meet the goal?

You plan to create an Azure Databricks workspace that has a tiered structure. The workspace will contain the following three workloads:
✑ A workload for data engineers who will use Python and SQL
✑ A workload for jobs that will run notebooks that use Python, Scala, and SQL
✑ A workload that data scientists will use to perform ad hoc analysis in Scala and R
The enterprise architecture team at your company identifies the following standards for Databricks environments:
✑ The data engineers must share a cluster.
✑ The job cluster will be managed by using a request process whereby data scientists and data engineers provide packaged notebooks for deployment to the cluster.
✑ All the data scientists must be assigned their own cluster that terminates automatically after 120 minutes of inactivity. Currently, there are three data scientists.
You need to create the Databricks clusters for the workloads.
Solution: You create a Standard cluster for each data scientist, a Standard cluster for the data engineers, and a High Concurrency cluster for the jobs.
Does this meet the goal?

You develop a data ingestion process that will import data to an enterprise data warehouse in Azure Synapse Analytics. The data to be ingested resides in parquet files stored in an Azure Data Lake Gen 2 storage account.
You need to load the data from the Azure Data Lake Gen 2 storage account into the Data Warehouse.
Solution:
Use Azure Data Factory to convert the parquet files to CSV files
Create an external data source pointing to the Azure Data Lake Gen 2 storage account
Create an external file format and external table using the external data source
Load the data using the CREATE TABLE AS SELECT statement
Does the solution meet the goal?

You need to implement complex stateful business logic within an Azure Stream Analytics service.
Which type of function should you create in the Stream Analytics topology?

You have an Azure virtual machine that has Microsoft SQL Server installed. The database on the virtual machine contains a table named Table1.
You need to copy the data from Table1 to an Azure Data Lake Storage Gen2 account by using an Azure Data Factory V2 copy activity.
Which type of integration runtime should you use?

You are developing a solution that will use Azure Stream Analytics. The solution will accept an Azure Blob storage file named Customers. The file will contain both in-store and online customer details. The online customers will provide a mailing address.
You have a file in Blob storage named LocationIncomes that contains median incomes based on location. The file rarely changes.
You need to use an address to look up a median income based on location. You must output the data to Azure SQL Database for immediate use and to Azure
Data Lake Storage Gen2 for long-term retention.
Solution: You implement a Stream Analytics job that has two streaming inputs, one query, and two outputs.
Does this meet the goal?

You are creating a new notebook in Azure Databricks that will support R as the primary language but will also support Scala and SQL.
Which switch should you use to switch between languages?

You have an Azure Stream Analytics job that receives clickstream data from an Azure event hub.
You need to define a query in the Stream Analytics job. The query must meet the following requirements:
✑ Count the number of clicks within each 10-second window based on the country of a visitor.
✑ Ensure that each click is NOT counted more than once.
How should you define the query?

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