DP-300 Questions and Answers

Azure HDInsight offers pre-made, monitoring dashboards in the form of solutions that can be used to monitor the workloads running on your clusters. There are solutions for Apache Spark, Hadoop, Apache Kafka, live long and process (LLAP), Apache HBase, and Apache Storm available in the Azure Marketplace.

Note: With Azure HDInsight you can set up Azure Monitor alerts that will trigger when the value of a metric or the results of a query meet certain conditions. You can condition on a query returning a record with a value that is greater than or less than a certain threshold, or even on the number of results returned by a query. For example, you could create an alert to send an email if a Spark job fails or if a Kafka disk usage becomes over 90 percent full.

To ensure that db1 is compatible with all the features and syntax of SQL Server 2012, you need to set the compatibility level of the database to 110, which is the compatibility level for SQL Server 20121. The compatibility level affects the behavior of certain Transact-SQL statements and features, and determines how the database engine interprets the SQL code2.

You can set the compatibility level of db1 by using the Azure portal or Transact-SQL statements. Here are the steps for both methods:

Using the Azure portal:

Go to the Azure portal and select your Azure SQL Database server that hosts db1.

Select the database db1 and click on Query Performance Insight in the left menu.

Click on Configure Query Store and select 110 from the Compatibility level dropdown list.

Click on Save to apply the change.

Using Transact-SQL statements:

Connect to db1 using SQL Server Management Studio, Azure Data Studio, or any other tool that supports Transact-SQL statements.

Open a new query window and run the following command: ALTER DATABASE db1 SET COMPATIBILITY_LEVEL = 110; GO

This command will set the compatibility level of db1 to 110, which is equivalent to SQL Server 2012.

These are the steps to set the compatibility level of db1 to 110. 

Box 1: SET AUTOMATIC_TUNING = AUTO

To enable automatic tuning on a single database via T-SQL, connect to the database and execute the following query:

ALTER DATABASE current SET AUTOMATIC_TUNING = AUTO

Setting automatic tuning to AUTO will apply Azure Defaults.

Box 2: SET AUTOMATIC_TUNING (FORCE_LAST_GOOD_PLAN = ON)

To configure individual automatic tuning options via T-SQL, connect to the database and execute the query such as this one:

ALTER DATABASE current SET AUTOMATIC_TUNING (FORCE_LAST_GOOD_PLAN = ON)

Setting the individual tuning option to ON will override any setting that database inherited and enable the tuning option. Setting it to OFF will also override any setting that database inherited and disable the tuning option.

Transparent data encryption (TDE) helps protect Azure SQL Database, Azure SQL Managed Instance, and Azure Synapse Analytics against the threat of malicious offline activity by encrypting data at rest.

Box 1: No

Just one failure within the 5-minute interval.

Box 2: No

Just two failures within the 5-minute interval.

Box 3: No

Just two failures within the 5-minute interval.

Yes

No

No

"Assigned Identity" and "Key id" https://learn.microsoft.com/en-us/powershell/module/az.sql/new-azsqlserver?view=azps-10.2.0#code-try-3

Scenario: The sales data, including the documents in JSON format, must be gathered as it arrives and analyzed online by using Azure Stream Analytics. The analytics process will perform aggregations that must be done continuously, without gaps, and without overlapping.

Tumbling window functions are used to segment a data stream into distinct time segments and perform a function against them, such as the example below. The key differentiators of a Tumbling window are that they repeat, do not overlap, and an event cannot belong to more than one tumbling window.

Scenario: Real-time processing must be monitored to ensure that workloads are sized properly based on actual usage patterns.

To monitor the performance of a database in Azure SQL Database and Azure SQL Managed Instance, start by monitoring the CPU and IO resources used by your workload relative to the level of database performance you chose in selecting a particular service tier and performance level.

Box 1: Hash

Scenario:

Ensure that queries joining and filtering sales transaction records based on product ID complete as quickly as possible.

A hash distributed table can deliver the highest query performance for joins and aggregations on large tables.

Box 2: Round-robin

Scenario:

You plan to create a promotional table that will contain a promotion ID. The promotion ID will be associated to a specific product. The product will be identified by a product ID. The table will be approximately 5 GB.

A round-robin table is the most straightforward table to create and delivers fast performance when used as a staging table for loads. These are some scenarios where you should choose Round robin distribution:

When you cannot identify a single key to distribute your data.

If your data doesn’t frequently join with data from other tables.

When there are no obvious keys to join.

Scenario: Contoso requirements for the sales transaction dataset include:

Implement a surrogate key to account for changes to the retail store addresses.

A surrogate key on a table is a column with a unique identifier for each row. The key is not generated from the

table data. Data modelers like to create surrogate keys on their tables when they design data warehouse models. You can use the IDENTITY property to achieve this goal simply and effectively without affecting load performance.

The lifecycle management policy lets you:

Delete blobs, blob versions, and blob snapshots at the end of their lifecycles

To enable change data capture (CDC) for db1, you need to run the stored procedure sys.sp_cdc_enable_db in the database context. CDC is a feature that records activity on a database when tables and rows have been modified1. CDC can be used for various scenarios, such as data synchronization, auditing, or ETL processes2.

Here are the steps to enable CDC for db1:

Connect to db1 using SQL Server Management Studio, Azure Data Studio, or any other tool that supports Transact-SQL statements.

Open a new query window and run the following command: EXEC sys.sp_cdc_enable_db; GO

This command will enable CDC for the database and create the cdc schema, cdc user, metadata tables, and other system objects for the database3.

To verify that CDC is enabled for db1, you can query the is_cdc_enabled column in the sys.databases catalog view. The value should be 1 for db1.

These are the steps to enable CDC for db1

To configure high availability for dbl, you can use the failover groups feature of Azure SQL Database. Failover groups allow you to manage the replication and failover of a group of databases across different regions with the same connection strings1. You can choose all, or a subset of, user databases in a logical server to be replicated to another logical server in a different region. You can also specify the failover policy, such as manual or automatic, and the grace period for data loss.

Here are the steps to create a failover group for dbl:

Using the Azure portal:

Go to the Azure portal and select your Azure SQL Database server that hosts dbl.

Select Failover groups in the left menu and click on Add group.

Enter a name for the failover group and select a secondary region that is different from the primary region.

Click on Create a new server and enter the details for the secondary server, such as server name, admin login, password, and subscription.

Click on Select existing database(s) and choose dbl from the list of databases on the primary server.

Click on Configure failover policy and select the failover mode, grace period, and read-write failover endpoint mode according to your preferences.

Click on Create to create the failover group and start the replication of dbl to the secondary server.

Using PowerShell commands:

Install the Azure PowerShell module and log in with your Azure account.

Run the following command to create a new server in the secondary region: New-AzSqlServer -ResourceGroupName -ServerName -Location "" -SqlAdministratorCredentials $(New-Object -TypeName System.Management.Automation.PSCredential -ArgumentList "", $(ConvertTo-SecureString -String "" -AsPlainText -Force))

Run the following command to create a new failover group with dbl: New-AzSqlDatabaseFailoverGroup -ResourceGroupName -ServerName -PartnerResourceGroupName -PartnerServerName -FailoverGroupName -Database dbl -FailoverPolicy -GracePeriodWithDataLossHours -ReadWriteFailoverEndpoint ""

You can modify the parameters of the command according to your preferences, such as the failover policy, grace period, and read-write failover endpoint mode.

These are the steps to create a failover group for dbl

To configure a disaster recovery solution for db1, you can use the failover groups feature of Azure SQL Database. Failover groups allow you to manage the replication and failover of a group of databases across different regions with the same connection strings1. You can also use active geo-replication as an alternative, but you will need to update the connection strings manually after a failover2.

Here are the steps to create a failover group for db1 with the secondary server in the West US 3 region:

Using the Azure portal:

Go to the Azure portal and select your Azure SQL Database server that hosts db1.

Select Failover groups in the left menu and click on Add group.

Enter a name for the failover group and select West US 3 as the secondary region.

Click on Create a new server and enter the details for the secondary server, such as server name, admin login, password, and subscription.

Click on Select existing database(s) and choose db1 from the list of databases on the primary server.

Click on Configure failover policy and select the failover mode, grace period, and read-write failover endpoint mode according to your preferences.

Click on Create to create the failover group and start the replication of db1 to the secondary server.

Using PowerShell commands:

Install the Azure PowerShell module and log in with your Azure account.

Run the following command to create a new server in the West US 3 region: New-AzSqlServer -ResourceGroupName -ServerName -Location "West US 3" -SqlAdministratorCredentials $(New-Object -TypeName System.Management.Automation.PSCredential -ArgumentList "", $(ConvertTo-SecureString -String "" -AsPlainText -Force))

Run the following command to create a new failover group with db1: New-AzSqlDatabaseFailoverGroup -ResourceGroupName -ServerName -PartnerResourceGroupName -PartnerServerName -FailoverGroupName -Database db1 -FailoverPolicy Manual -GracePeriodWithDataLossHours 1 -ReadWriteFailoverEndpoint "Enabled"

You can modify the parameters of the command according to your preferences, such as the failover policy, grace period, and read-write failover endpoint mode.

These are the steps to create a failover group for db1 with the secondary server in the West US 3 region.

SalesSQLDb1 experiences performance issues that are likely due to out-of-date statistics and frequent blocking queries.

A: Use sys.dm_pdw_nodes_tran_locks instead of sys.dm_tran_locks from Azure Synapse Analytics (SQL Data Warehouse) or Parallel Data Warehouse.

E: Example:

The following query will show blocking information.

SELECT

t1.resource_type,

t1.resource_database_id,

t1.resource_associated_entity_id,

t1.request_mode,

t1.request_session_id,

t2.blocking_session_id

FROM sys.dm_tran_locks as t1

INNER JOIN sys.dm_os_waiting_tasks as t2

ON t1.lock_owner_address = t2.resource_address;

Note: Depending on the system you’re working with you can access these wait statistics from one of three locations:

sys.dm_os_wait_stats: for SQL Server

sys.dm_db_wait_stats: for Azure SQL Database

sys.dm_pdw_nodes_os_wait_stats: for Azure SQL Data Warehouse

Automating Azure SQL DB index and statistics maintenance using Azure Automation:

1. Create Azure automation account (Step 1)

2. Import SQLServer module (Step 2)

3. Add Credentials to access SQL DB

This will use secure way to hold login name and password that will be used to access Azure SQL DB

4. Add a runbook to run the maintenance (Step 3)

Steps: 1. Click on "runbooks" at the left panel and then click "add a runbook"

2. Choose "create a new runbook" and then give it a name and choose "Powershell" as the type of the runbook and then click on "create"

5. Schedule task (Step 4)

Steps:1. Click on Schedules2. Click on "Add a schedule" and follow the instructions to choose existing schedule or create a new schedule.

Scenario: Business Requirements

Litware identifies business requirements include: meet an SLA of 99.99% availability for all Azure deployments.

Box 1: Cloud witness

If you have a Failover Cluster deployment, where all nodes can reach the internet (by extension of Azure), it is recommended that you configure a Cloud Witness as your quorum witness resource.

Box 2: Azure Basic Load Balancer

Microsoft guarantees that a Load Balanced Endpoint using Azure Standard Load Balancer, serving two or more Healthy Virtual Machine Instances, will be available 99.99% of the time.

Note: There are two main options for setting up your listener: external (public) or internal. The external (public) listener uses an internet facing load balancer and is associated with a public Virtual IP (VIP) that is accessible over the internet. An internal listener uses an internal load balancer and only supports clients within the same Virtual Network.

Scenario: SalesSQLDb1 uses database firewall rules and contained database users.

Box 1: DTU

Scenario:

The 30 new databases must scale automatically.

Once all requirements are met, minimize costs whenever possible.

You can configure resources for the pool based either on the DTU-based purchasing model or the vCore-based purchasing model.

In short, for simplicity, the DTU model has an advantage. Plus, if you’re just getting started with Azure SQL Database, the DTU model offers more options at the lower end of performance, so you can get started at a lower price point than with vCore.

Box 2: An Azure SQL database elastic pool

Azure SQL Database elastic pools are a simple, cost-effective solution for managing and scaling multiple databases that have varying and unpredictable usage demands. The databases in an elastic pool are on a single server and share a set number of resources at a set price. Elastic pools in Azure SQL Database enable SaaS developers to optimize the price performance for a group of databases within a prescribed budget while delivering performance elasticity for each database.

Scenario: Authenticate database users by using Active Directory credentials.

The configuration steps include the following procedures to configure and use Azure Active Directory authentication.

Create and populate Azure AD.

Optional: Associate or change the active directory that is currently associated with your Azure Subscription.

Create an Azure Active Directory administrator. (Step 1)

Configure your client computers.

Create contained database users in your database mapped to Azure AD identities. (Step 2)

Connect to your database by using Azure AD identities. (Step 3)

Azure Database Migration service

Box 1: Premium 4-VCore

Scenario: Migrate the SERVER1 databases to the Azure SQL Database platform.

Minimize downtime during the migration of the SERVER1 databases.

Premimum 4-vCore is for large or business critical workloads. It supports online migrations, offline migrations, and faster migration speeds.

Box 1: The server, the elastic pool, and the database

Senario:

SalesSQLDb1 is in an elastic pool named SalesSQLDb1Pool.

Litware technical requirements include: all SQL Server and Azure SQL Database metrics related to CPU and storage usage and limits must be analyzed by using Azure built-in functionality.

Box 2: Azure Event hubs

Scenario: Migrate ManufacturingSQLDb1 to the Azure virtual machine platform.

Event hubs are able to handle custom metrics.

Scenario: Authenticate database users by using Active Directory credentials.

(Create a new Azure SQL database named ResearchDB1 on a logical server named ResearchSrv01.)

Authenticate the user in SQL Database or SQL Data Warehouse based on an Azure Active Directory user:

CREATE USER [Fritz@contoso.com] FROM EXTERNAL PROVIDER;

There are CPU and Data I/O spikes for the PaaS prototype. Business Critical 4-vCore is needed.

Scenario: In the event of an Azure regional outage, ensure that the customers can access the PaaS solution with minimal downtime. The solution must provide automatic failover.

The auto-failover groups feature allows you to manage the replication and failover of a group of databases on a server or all databases in a managed instance to another region. It is a declarative abstraction on top of the existing active geo-replication feature, designed to simplify deployment and management of geo-replicated databases at scale. You can initiate failover manually or you can delegate it to the Azure service based on a user-defined policy.

The latter option allows you to automatically recover multiple related databases in a secondary region after a catastrophic failure or other unplanned event that results in full or partial loss of the SQL Database or SQL Managed Instance availability in the primary region.

Box 1: Yes

DBAGroup1 is member of the Contributor role.

The Contributor role grants full access to manage all resources, but does not allow you to assign roles in Azure RBAC, manage assignments in Azure Blueprints, or share image galleries.

Box 2: No

Box 3: Yes

DBAGroup2 is member of the SQL DB Contributor role.

The SQL DB Contributor role lets you manage SQL databases, but not access to them. Also, you can't manage their security-related policies or their parent SQL servers. As a member of this role you can create and manage SQL databases.

Scenario: Use a single dashboard to review security and audit data for all the PaaS databases.

With dashboards can bring together operational data that is most important to IT across all your Azure resources, including telemetry from Azure Log Analytics.

Note: Auditing for Azure SQL Database and Azure Synapse Analytics tracks database events and writes them to an audit log in your Azure storage account, Log Analytics workspace, or Event Hubs.