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The Microsoft DP-300 exam measures the capability of the candidates to complete certain technical tasks, such as querying performance, planning and implementing the High Availability & Disaster Recovery environment, and optimizing & monitoring operational resources. The highlights of these topics are as follows:
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Monitoring of database configuration
The configuration of database autogrowth
Reviewing options for database configuration
Database free space reports
Using T-SQL for restoration and backups
Performing database backups and transaction log backups
Restoring user databases
Always On Availability Groups and preparing databases for them
System health assessment
Utilizing DBCC for database consistency checks
The use of DMVs for examining health of servers and databases
Management of authorization and authentication
Handling security principals and certificates
The configuration of permissions
NEW QUESTION # 168
You plan to create a table in an Azure Synapse Analytics dedicated SQL pool.
Data in the table will be retained for five years. Once a year, data that is older than five years will be deleted.
You need to ensure that the data is distributed evenly across partitions. The solutions must minimize the amount of time required to delete old data.
How should you complete the Transact-SQL statement? To answer, drag the appropriate values to the correct targets. Each value 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:
Reference:
https://docs.microsoft.com/en-us/sql/t-sql/statements/create-table-azure-sql-data-warehouse
https://docs.microsoft.com/en-us/azure/synapse-analytics/sql/best-practices-dedicated-sql-pool
NEW QUESTION # 169**
You are performing exploratory analysis of bus fare data in an Azure Data Lake Storage Gen2 account by using an Azure Synapse Analytics serverless SQL pool.
You execute the Transact-SQL query 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.
Answer: **
Explanation:
Explanation
Graphical user interface, table Description automatically generated
Box 1: CSV files that have file named beginning with "tripdata2020"
Box 2: a header
FIRSTROW = 'firstrow'
Specifies the number of the first row to load. The default is 1 and indicates the first row in the specified data file. The row numbers are determined by counting the row terminators. FIRSTROW is 1-based.
Reference:
https://docs.microsoft.com/en-us/azure/synapse-analytics/sql/develop-openrowset
NEW QUESTION # 170**
DRAG DROP
Your company analyzes images from security cameras and sends alerts to security teams that respond to unusual activity. The solution uses Azure Databricks.
You need to send Apache Spark level events, Spark Structured Streaming metrics, and application metrics to Azure Monitor.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions in the answer area and arrange them in the correct order.
Select and Place:
Answer: **
Explanation:
Section: [none]
Explanation:
Send application metrics using Dropwizard.
Spark uses a configurable metrics system based on the Dropwizard Metrics Library.
To send application metrics from Azure Databricks application code to Azure Monitor, follow these steps:
Step 1: Configure your Azure Databricks cluster to use the Databricksmonitoring library.
Prerequisite: Configure your Azure Databricks cluster to use the monitoring library.
Step 2: Build the spark-listeners-loganalytics-1.0-SNAPSHOT.jar JAR file Step 3: Create Dropwizard counters in your application code Create Dropwizard gauges or counters in your application code
NEW QUESTION # 171**
HOTSPOT
You are building an Azure Stream Analytics job to retrieve game data.
You need to ensure that the job returns the highest scoring record for each five-minute time interval of each game.
How should you complete the Stream Analytics query? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Hot Area:
Answer: **
Explanation:
Section: [none]
Explanation:
Box 1: TopOne() OVER(PARTITION BY Game ORDER BY Score Desc)
TopOne returns the top-rank record, where rank defines the ranking position of the event in the window according to the specified ordering. Ordering/ranking is based on event columns and can be specified in ORDER BY clause.
Analytic Function Syntax:
TopOne() OVER ([<PARTITION BY clause>] ORDER BY (<column name> [ASC |DESC])+ <LIMIT DURATION clause> [<WHEN clause>]) Box 2: Tumbling(minute 5) 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.
Reference:
https://docs.microsoft.com/en-us/stream-analytics-query/topone-azure-stream-analytics
https://github.com/MicrosoftDocs/azure-docs/blob/master/articles/stream-analytics/stream-analytics-window- functions.md
NEW QUESTION # 172**
You need to recommend a configuration for ManufacturingSQLDb1 after the migration to Azure. The solution must meet the business requirements.
What should you include in the recommendation? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer: **
Explanation:
Reference:
https://technet.microsoft.com/windows-server-docs/failover-clustering/deploy-cloud-witness
https://azure.microsoft.com/en-us/support/legal/sla/load-balancer/v1_0/
NEW QUESTION # 173
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