DP-200 Certification Overview - [May 21, 2022] Latest DP-200 PDF Dumps
The Best Microsoft DP-200 Study Guides and Dumps of 2022
NEW QUESTION 137
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?
- A. sys.dm_pdw_waits
- B. sys.dm_pdw_request_steps
- C. sys.dm_pdw_exec_sessions
- D. sys.dm_pdw_nodes_tran_database_transactions
Answer: D
Explanation:
You can use Dynamic Management Views (DMVs) to monitor your workload including investigating query execution in SQL pool.
If your queries are failing or taking a long time to proceed, you can check and monitor if you have any transactions rolling back.
Example:
-- Monitor rollback
SELECT
SUM(CASE WHEN t.database_transaction_next_undo_lsn IS NOT NULL THEN 1 ELSE 0 END), t.pdw_node_id, nod.[type] FROM sys.dm_pdw_nodes_tran_database_transactions t JOIN sys.dm_pdw_nodes nod ON t.pdw_node_id = nod.pdw_node_id GROUP BY t.pdw_node_id, nod.[type] Reference:
https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-managemonitor# monitor-transaction-log-rollback
NEW QUESTION 138
You have an Azure data factory.
You need to ensure that pipeline-run data is retained for 120 days. The solution must ensure that you can query the data by using the Kusto query language.
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.
NOTE: More than one order of answer choices is correct. You will receive credit for any of the correct orders you select.
Answer:
Explanation:
Explanation
Step 1: Create an Azure Storage account that has a lifecycle policy
To automate common data management tasks, Microsoft created a solution based on Azure Data Factory. The service, Data Lifecycle Management, makes frequently accessed data available and archives or purges other data according to retention policies. Teams across the company use the service to reduce storage costs, improve app performance, and comply with data retention policies.
Step 2: Create a Log Analytics workspace that has Data Retention set to 120 days.
Data Factory stores pipeline-run data for only 45 days. Use Azure Monitor if you want to keep that data for a longer time. With Monitor, you can route diagnostic logs for analysis to multiple different targets, such as a Storage Account: Save your diagnostic logs to a storage account for auditing or manual inspection. You can use the diagnostic settings to specify the retention time in days.
Step 3: From Azure Portal, add a diagnostic setting.
Step 4: Send the data to a log Analytics workspace,
Event Hub: A pipeline that transfers events from services to Azure Data Explorer.
Keeping Azure Data Factory metrics and pipeline-run data.
Configure diagnostic settings and workspace.
Create or add diagnostic settings for your data factory.
* In the portal, go to Monitor. Select Settings > Diagnostic settings.
* Select the data factory for which you want to set a diagnostic setting.
* If no settings exist on the selected data factory, you're prompted to create a setting. Select Turn on diagnostics.
* Give your setting a name, select Send to Log Analytics, and then select a workspace from Log Analytics Workspace.
* Select Save.
Reference:
https://docs.microsoft.com/en-us/azure/data-factory/monitor-using-azure-monitor
NEW QUESTION 139
You need to mask tier 1 data. Which functions should you use? To answer, select the appropriate option in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
A: Default
Full masking according to the data types of the designated fields.
For string data types, use XXXX or fewer Xs if the size of the field is less than 4 characters (char, nchar, varchar, nvarchar, text, ntext).
B: email
C: Custom text
Custom StringMasking method which exposes the first and last letters and adds a custom padding string in the middle. prefix,[padding],suffix Tier 1 Database must implement data masking using the following masking logic:
References:
https://docs.microsoft.com/en-us/sql/relational-databases/security/dynamic-data-masking
NEW QUESTION 140
You need to ensure phone-based polling data upload reliability requirements are met. How should you configure monitoring? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: FileCapacity
FileCapacity is the amount of storage used by the storage account's File service in bytes.
Box 2: Avg
The aggregation type of the FileCapacity metric is Avg.
Scenario:
All services and processes must be resilient to a regional Azure outage.
All Azure services must be monitored by using Azure Monitor. On-premises SQL Server performance must be monitored.
References:
https://docs.microsoft.com/en-us/azure/azure-monitor/platform/metrics-supported
NEW QUESTION 141
You plan to create a new single database instance of Microsoft Azure SQL Database.
The database must only allow communication from the data engineer's workstation. You must connect directly to the instance by using Microsoft SQL Server Management Studio.
You need to create and configure the Database. Which three Azure PowerShell cmdlets should you use to develop the solution? To answer, move the appropriate cmdlets from the list of cmdlets to the answer area and arrange them in the correct order.
Answer:
Explanation:
Explanation
Step 1: New-AzureSqlServer
Create a server.
Step 2: New-AzureRmSqlServerFirewallRule
New-AzureRmSqlServerFirewallRule creates a firewall rule for a SQL Database server.
Can be used to create a server firewall rule that allows access from the specified IP range.
Step 3: New-AzureRmSqlDatabase
Example: Create a database on a specified server
PS C:\>New-AzureRmSqlDatabase -ResourceGroupName "ResourceGroup01" -ServerName "Server01"
-DatabaseName "Database01
References:
https://docs.microsoft.com/en-us/azure/sql-database/scripts/sql-database-create-and-configure-database-powersh
NEW QUESTION 142
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 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, Spark, 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 Databrick 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?
- A. No
- B. Yes
Answer: B
Explanation:
We need a High Concurrency cluster for the data engineers and the jobs.
Note:
Standard clusters are recommended for a single user. Standard can run workloads developed in any language:
Python, R, Scala, and SQL.
A high concurrency cluster is a managed cloud resource. The key benefits of high concurrency clusters are that they provide Apache Spark-native fine-grained sharing for maximum resource utilization and minimum query latencies.
References:
https://docs.azuredatabricks.net/clusters/configure.html
NEW QUESTION 143
Your company uses Azure SQL Database and Azure Blob storage.
All data at rest must be encrypted by using the company's own key. The solution must minimize administrative effort and the impact to applications which use the database.
You need to configure security.
What should you implement? To answer, select the appropriate option in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
References:
https://docs.microsoft.com/en-us/azure/sql-database/transparent-data-encryption-azure-sql
https://docs.microsoft.com/en-us/azure/storage/common/storage-service-encryption
NEW QUESTION 144
A company uses Microsoft Azure SQL Database to store sensitive company data. You encrypt the data and only allow access to specified users from specified locations.
You must monitor data usage, and data copied from the system to prevent data leakage.
You need to configure Azure SQL Database to email a specific user when data leakage occurs.
Which three 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.
Answer:
Explanation:
Explanation
NEW QUESTION 145
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 questions 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 need to configure data encryption for external applications.
Solution:
1. Access the Always Encrypted Wizard in SQL Server Management Studio
2. Select the column to be encrypted
3. Set the encryption type to Deterministic
4. Configure the master key to use the Azure Key Vault
5. Validate configuration results and deploy the solution
Does the solution meet the goal?
- A. No
- B. Yes
Answer: B
Explanation:
Explanation
We use the Azure Key Vault, not the Windows Certificate Store, to store the master key.
Note: The Master Key Configuration page is where you set up your CMK (Column Master Key) and select the key store provider where the CMK will be stored. Currently, you can store a CMK in the Windows certificate store, Azure Key Vault, or a hardware security module (HSM).
References:
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-always-encrypted-azure-key-vault
NEW QUESTION 146
A company plans to develop solutions to perform batch processing of multiple sets of geospatial data.
You need to implement the solutions.
Which Azure services should you use? To answer, select the appropriate configuration in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: HDInsight Tools for Visual Studio
Azure HDInsight Tools for Visual Studio Code is an extension in the Visual Studio Code Marketplace for developing Hive Interactive Query, Hive Batch Job and PySpark Job against Microsoft HDInsight.
Box 2: Hive View
You can use Apache Ambari Hive View with Apache Hadoop in HDInsight. The Hive View allows you to author, optimize, and run Hive queries from your web browser.
Box 3: HDInsight REST API
Azure HDInsight REST APIs are used to create and manage HDInsight resources through Azure Resource Manager.
References:
https://visualstudiomagazine.com/articles/2019/01/25/vscode-hdinsight.aspx
https://docs.microsoft.com/en-us/azure/hdinsight/hadoop/apache-hadoop-use-hive-ambari-view
https://docs.microsoft.com/en-us/rest/api/hdinsight/
NEW QUESTION 147
Your company uses Microsoft Azure SQL Database configure with Elastic pool. You use Elastic Database jobs to run queries across all databases in the pod.
You need to analyze, troubleshoot, and report on components responsible for running Elastic Database jobs.
You need to determine the component responsible for running job service tasks.
Which components should you use for each Elastic pool job services task? To answer, drag the appropriate component to the correct task. Each component 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.
Answer:
Explanation:
Explanation
Execution results and diagnostics: Azure Storage
Job launcher and tracker: Job Service
Job metadata and state: Control database
The Job database is used for defining jobs and tracking the status and history of job executions. The Job database is also used to store agent metadata, logs, results, job definitions, and also contains many useful stored procedures, and other database objects, for creating, running, and managing jobs using T-SQL.
References:
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-job-automation-overview
NEW QUESTION 148
You have an Azure data factory.
You need to examine the pipeline failures from the last 60 days.
What should you use?
- A. the Activity log blade for the Data Factory resource
- B. the Resource health blade for the Data Factory resource
- C. Azure Monitor
- D. the Monitor & Manage app in Data Factory
Answer: C
Explanation:
Data Factory stores pipeline-run data for only 45 days. Use Azure Monitor if you want to keep that data for a longer time. With Monitor, you can route diagnostic logs for analysis to multiple different targets.
Reference:
https://docs.microsoft.com/en-us/azure/data-factory/monitor-using-azure-monitor
NEW QUESTION 149
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.
Answer:
Explanation:
Explanation
Box 1: Yes
You can now use a new extension of Azure Stream Analytics SQL to specify the number of partitions of a stream when reshuffling the data.
The outcome is a stream that has the same partition scheme. Please see below for an example:
WITH step1 AS (SELECT * FROM [input1] PARTITION BY DeviceID INTO 10),
step2 AS (SELECT * FROM [input2] PARTITION BY DeviceID INTO 10)
SELECT * INTO [output] FROM step1 PARTITION BY DeviceID UNION step2 PARTITION BY DeviceID Note: The new extension of Azure Stream Analytics SQL includes a keyword INTO that allows you to specify the number of partitions for a stream when performing reshuffling using a PARTITION BY statement.
Box 2: Yes
When joining two streams of data explicitly repartitioned, these streams must have the same partition key and partition count.
Box 3: Yes
10 partitions x six SUs = 60 SUs is fine.
Note: Remember, Streaming Unit (SU) count, which is the unit of scale for Azure Stream Analytics, must be adjusted so the number of physical resources available to the job can fit the partitioned flow. In general, six SUs is a good number to assign to each partition. In case there are insufficient resources assigned to the job, the system will only apply the repartition if it benefits the job.
Reference:
https://azure.microsoft.com/en-in/blog/maximize-throughput-with-repartitioning-in-azure-stream-analytics/
NEW QUESTION 150
You develop data engineering solutions for a company.
You need to deploy a Microsoft Azure Stream Analytics job for an IoT solution. The solution must:
* Minimize latency.
* Minimize bandwidth usage between the job and IoT device.
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.
Answer:
Explanation:
Explanation
NEW QUESTION 151
What should you include in the Data Factory pipeline for Race Central?
- A. a copy activity that uses a stored procedure as a source
- B. a delete activity that has logging enabled
- C. a filter activity that has a condition
- D. a copy activity that contains schema mappings
Answer: D
Explanation:
Scenario:
An Azure Data Factory pipeline must be used to move data from Cosmos DB to SQL Database for Race Central. If the data load takes longer than 20 minutes, configuration changes must be made to Data Factory.
The telemetry data is sent to a MongoDB database. A custom application then moves the data to databases in SQL Server 2017. The telemetry data in MongoDB has more than 500 attributes. The application changes the attribute names when the data is moved to SQL Server 2017.
You can copy data to or from Azure Cosmos DB (SQL API) by using Azure Data Factory pipeline.
Column mapping applies when copying data from source to sink. By default, copy activity map source data to sink by column names. You can specify explicit mapping to customize the column mapping based on your need. More specifically, copy activity:
Read the data from source and determine the source schema
1. Use default column mapping to map columns by name, or apply explicit column mapping if specified.
2. Write the data to sink
3. Write the data to sink
Reference:
https://docs.microsoft.com/en-us/azure/data-factory/copy-activity-schema-and-type-mapping Manage and develop data processing Testlet 5 Case study Overview ADatum Corporation is a retailer that sells products through two sales channels: retail stores and a website.
Existing Environment
ADatum has one database server that has Microsoft SQL Server 2016 installed. The server hosts three mission-critical databases named SALESDB, DOCDB, and REPORTINGDB.
SALESDB collects data from the stored and the website.
DOCDB stored documents that connect to the sales data in SALESDB. The documents are stored in two different JSON formats based on the sales channel.
REPORTINGDB stores reporting data and contains server columnstore indexes. A daily process creates reporting data in REPORTINGDB from the data in SALESDB. The process is implemented as a SQL Server Integration Services (SSIS) package that runs a stored procedure from SALESDB.
Requirements
Planned Changes
ADatum plans to move the current data infrastructure to Azure. The new infrastructure has the following requirements:
* Migrate SALESDB and REPORTINGDB to an Azure SQL database.
* Migrate DOCDB to Azure Cosmos DB.
* The sales data including the documents in JSON format, must be gathered as it arrives and analyzed online by using Azure Stream Analytics. The analytic process will perform aggregations that must be done continuously, without gaps, and without overlapping.
* As they arrive, all the sales documents in JSON format must be transformed into one consistent format.
* Azure Data Factory will replace the SSIS process of copying the data from SALESDB to REPORTINGDB.
Technical Requirements
The new Azure data infrastructure must meet the following technical requirements:
* Data in SALESDB must encrypted by using Transparent Data Encryption (TDE). The encryption must use your own key.
* SALESDB must be restorable to any given minute within the past three weeks.
* Real-time processing must be monitored to ensure that workloads are sized properly based on actual usage patterns.
* Missing indexes must be created automatically for REPORTINGDB.
* Disk IO, CPU, and memory usage must be monitored for SALESDB.
NEW QUESTION 152
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 access key.
You plan to use PolyBase to load data into Azure SQL data warehouse.
You need to configure PolyBase to connect the data warehouse to the storage account.
Which three components should you create in sequence? To answer, move the appropriate components from the list of components to the answer are and arrange them in the correct order.
Answer:
Explanation:
Explanation
Step 1: a database scoped credential
To access your Data Lake Storage account, you will need to create a Database Master Key to encrypt your credential secret used in the next step. You then create a database scoped credential.
Step 2: an external data source
Create the external data source. Use the CREATE EXTERNAL DATA SOURCE command to store the location of the data. Provide the credential created in the previous step.
Step 3: an external file format
Configure data format: To import the data from Data Lake Storage, you need to specify the External File Format. This object defines how the files are written in Data Lake Storage.
References:
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-load-from-azure-data-lake-store
NEW QUESTION 153
You implement an event processing solution using Microsoft Azure Stream Analytics.
The solution must meet the following requirements:
*Ingest data from Blob storage
* Analyze data in real time
*Store processed data in Azure Cosmos DB
Which three 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.
Answer:
Explanation:
Explanation
Step 1: Configure Blob storage as input; select items with the TIMESTAMP BY clause The default timestamp of Blob storage events in Stream Analytics is the timestamp that the blob was last modified, which is BlobLastModifiedUtcTime. To process the data as a stream using a timestamp in the event payload, you must use the TIMESTAMP BY keyword.
Example:
The following is a TIMESTAMP BY example which uses the EntryTime column as the application time for events:
SELECT TollId, EntryTime AS VehicleEntryTime, LicensePlate, State, Make, Model, VehicleType, VehicleWeight, Toll, Tag FROM TollTagEntry TIMESTAMP BY EntryTime Step 2: Set up cosmos DB as the output Creating Cosmos DB as an output in Stream Analytics generates a prompt for information as seen below.
Step 3: Create a query statement with the SELECT INTO statement.
References:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-define-inputs
NEW QUESTION 154
You have an Azure subscription that contains the resources shown in the following table.
All the resources have the default encryption settings.
- A. Enable Transparent Data Encryption (TDE) for synapsedb1.
- B. Enable Azure Storage encryption for storageaccount2.
- C. Enable Azure Storage encryption for storageaccount1.
- D. Enable encryption at rest for cosmosdb1.
Answer: B
NEW QUESTION 155
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 SQL database named DB1 that contains a table named Table1. Table1 has a field named Customer_ID that is varchar(22).
You need to implement masking for the Customer_ID field to meet the following requirements:
* The first two prefix characters must be exposed.
* The last four suffix characters must be exposed.
* All other characters must be masked.
Solution: You implement data masking and use a random number function mask.
Does this meet the goal?
- A. No
- B. Yes
Answer: A
Explanation:
Must use Custom Text data masking, which exposes the first and last characters and adds a custom padding string in the middle.
References:
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-dynamic-data-masking-get-started
NEW QUESTION 156
You have an enterprise data warehouse in Azure Synapse Analytics that contains a table named FactOnlineSales. The table contains data from the start of 2009 to the end of 2012.
You need to improve the performance of queries against FactOnlineSales by using table partitions. The solution must meet the following requirements:
* Create four partitions based on the order date.
* Ensure that each partition contains all the orders placed during a given calendar year.
How should you complete the T-SQL command? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Box 1: LEFT
RANGE LEFT: Specifies the boundary value belongs to the partition on the left (lower values). The default is LEFT.
Box 2: 20090101, 20100101, 20110101, 20120101
FOR VALUES ( boundary_value [,...n] ) specifies the boundary values for the partition. boundary_value is a constant expression.
Reference:
https://docs.microsoft.com/en-us/sql/t-sql/statements/create-table-azure-sql-data-warehouse
NEW QUESTION 157
You need to set up access to Azure SQL Database for Tier 7 and Tier 8 partners.
Which three actions should you perform in sequence? To answer, move the appropriate three actions from the list of actions to the answer area and arrange them in the correct order.
Answer:
Explanation:
Explanation:
Tier 7 and 8 data access is constrained to single endpoints managed by partners for access
Step 1: Set the Allow Azure Services to Access Server setting to Disabled
Set Allow access to Azure services to OFF for the most secure configuration.
By default, access through the SQL Database firewall is enabled for all Azure services, under Allow access to Azure services. Choose OFF to disable access for all Azure services.
Note: The firewall pane has an ON/OFF button that is labeled Allow access to Azure services. The ON setting allows communications from all Azure IP addresses and all Azure subnets. These Azure IPs or subnets might not be owned by you. This ON setting is probably more open than you want your SQL Database to be. The virtual network rule feature offers much finer granular control.
Step 2: In the Azure portal, create a server firewall rule
Set up SQL Database server firewall rules
Server-level IP firewall rules apply to all databases within the same SQL Database server.
To set up a server-level firewall rule:
* In Azure portal, select SQL databases from the left-hand menu, and select your database on the SQL databases page.
* On the Overview page, select Set server firewall. The Firewall settings page for the database server opens.
Step 3: Connect to the database and use Transact-SQL to create a database firewall rule
Database-level firewall rules can only be configured using Transact-SQL (T-SQL) statements, and only after you've configured a server-level firewall rule.
To setup a database-level firewall rule:
* Connect to the database, for example using SQL Server Management Studio.
* In Object Explorer, right-click the database and select New Query.
* In the query window, add this statement and modify the IP address to your public IP address:
* EXECUTE sp_set_database_firewall_rule N'Example DB Rule','0.0.0.4','0.0.0.4';
* On the toolbar, select Execute to create the firewall rule.
References:
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-security-tutorial
NEW QUESTION 158
You need to ensure that phone-based polling data can be analyzed in the PollingData database.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer are and arrange them in the correct order.
Answer:
Explanation:
Explanation:
Scenario:
All deployments must be performed by using Azure DevOps. Deployments must use templates used in multiple environments
No credentials or secrets should be used during deployments
NEW QUESTION 159
You develop data engineering solutions for a company.
A project requires an in-memory batch data processing solution.
You need to provision an HDInsight cluster for batch processing of data on Microsoft Azure.
How should you complete the PowerShell segment? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: New-AzStorageContainer
# Example: Create a blob container. This holds the default data store for the cluster.
New-AzStorageContainer `
-Name $clusterName `
-Context $defaultStorageContext
$sparkConfig = New-Object "System.Collections.Generic.Dictionary``2[System.String,System.String]"
$sparkConfig.Add("spark", "2.3")
Box 2: Spark
Spark provides primitives for in-memory cluster computing. A Spark job can load and cache data into memory and query it repeatedly. In-memory computing is much faster than disk-based applications than disk-based applications, such as Hadoop, which shares data through Hadoop distributed file system (HDFS).
Box 3: New-AzureRMHDInsightCluster
# Create the HDInsight cluster. Example:
New-AzHDInsightCluster `
-ResourceGroupName $resourceGroupName `
-ClusterName $clusterName `
-Location $location `
-ClusterSizeInNodes $clusterSizeInNodes `
-ClusterType $"Spark" `
-OSType "Linux" `
Box 4: Spark
HDInsight is a managed Hadoop service. Use it deploy and manage Hadoop clusters in Azure. For batch processing, you can use Spark, Hive, Hive LLAP, MapReduce.
References:
https://docs.microsoft.com/bs-latn-ba/azure/hdinsight/spark/apache-spark-jupyter-spark-sql-use-powershell
https://docs.microsoft.com/bs-latn-ba/azure/hdinsight/spark/apache-spark-overview
NEW QUESTION 160
A company plans to use Platform-as-a-Service (PaaS) to create the new data pipeline process. The process must meet the following requirements.
Ingest:
*Access multiple data sources
*Provide the ability to orchestrate workflow
*Provide the capability to run SQL Server Integration Services packages.
Store:
*Optimize storage for big data workloads.
*Provide encryption of data at rest.
*Operate with no size limits.
Prepare and Train:
*Provide a fully-managed and interactive workspace for exploration and visualization.
*Provide the ability to program in R, SQL, Python, Scala, and Java.
*Provide seamless user authentication with Azure Active Directory.
Model & Serve:
*Implement native columnar storage.
*Support for the SQL language
*Provide support for structured streaming.
You need to build the data integration pipeline.
Which technologies should you use? To answer, select the appropriate options in the answer area.
Answer:
Explanation:
Ingest: Azure Data Factory
Azure Data Factory pipelines can execute SSIS packages.
In Azure, the following services and tools will meet the core requirements for pipeline orchestration, control flow, and data movement: Azure Data Factory, Oozie on HDInsight, and SQL Server Integration Services (SSIS).
Store: Data Lake Storage
Data Lake Storage Gen1 provides unlimited storage.
Note: Data at rest includes information that resides in persistent storage on physical media, in any digital format. Microsoft Azure offers a variety of data storage solutions to meet different needs, including file, disk, blob, and table storage. Microsoft also provides encryption to protect Azure SQL Database, Azure Cosmos DB, and Azure Data Lake.
Prepare and Train: Azure Databricks
Azure Databricks provides enterprise-grade Azure security, including Azure Active Directory integration.
With Azure Databricks, you can set up your Apache Spark environment in minutes, autoscale and collaborate on shared projects in an interactive workspace. Azure Databricks supports Python, Scala, R, Java and SQL, as well as data science frameworks and libraries including TensorFlow, PyTorch and scikit-learn.
Model and Serve: SQL Data Warehouse
SQL Data Warehouse stores data into relational tables with columnar storage.
Azure SQL Data Warehouse connector now offers efficient and scalable structured streaming write support for SQL Data Warehouse. Access SQL Data Warehouse from Azure Databricks using the SQL Data Warehouse connector.
References:
https://docs.microsoft.com/bs-latn-ba/azure/architecture/data-guide/technology-choices/pipeline-orchestration-da
https://docs.microsoft.com/en-us/azure/azure-databricks/what-is-azure-databricks
NEW QUESTION 161
......
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