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DP-300 dumps

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 Question #1 Topic 1 You have 20 Azure SQL databases provisioned by using the vCore purchasing model. You plan to create an Azure SQL Database elastic pool and add the 20 databases. Which three metrics should you use to size the elastic pool to meet the demands of your workload? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point. A. total size of all the databases B. geo-replication support C. number of concurrently peaking databases * peak CPU utilization per database D. maximum number of concurrent sessions for all the databases E. total number of databases * average CPU utilization per database Correct Answer: ACE  CE: Estimate the vCores needed for the pool as follows: For vCore-based purchasing model: MAX(<Total number of DBs X average vCore utilization per DB>, <Number of concurrently peaking DBs X Peak vCore utilization per DB) A: Estimate the storage space needed for the pool by adding the number of bytes needed for ...
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renewal of DP-300 exam questions

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  According to Microsoft SQL Server configuration best practices, what should you do to configure cach According to Microsoft SQL Server configuration best practices, what should you do to configure caching on volumes that host log files? Select only one answer. Enable read caching only. Enable write caching only. Enable read and write caching. Disable all caching. You plan to deploy Microsoft SQL Server 2019 to an Azure virtual machine that has eight CPUs and four disks. You expect that SQL Server will run tempdb heavy-workloads. You need to optimize the performance of tempdb. What should you do? Select only one answer. Store tempdb in eight files of the same size. Store tempdb in four files. Configure one of the files to have the size matching the amount of memory allocated to SQL Server. Enable trace flag 1117. Enable trace flag 1118. : You plan to implement SQL Server on an Azure virtual machine that has managed disks. You need to ensure that the virtual machine disks hosting t...
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Deterministic and Non -deterministics

  Deterministic and Non-deterministic Two approximate algorithms are offered for the approximate percentile functions: Non-deterministic: fastest method, whenever reproducibility is not required. This is the default method. Deterministic: slightly slower, but delivers deterministic results. Note that the differences will not be apparent with the small dataset in use here. REM Approximate median, NON DETERMINISTIC select approx_median(volume), approx_median(volume, 'ERROR_RATE' ) from approxt where state = 'CA' ; REM Approximate median, DETERMINISTIC select approx_median(volume deterministic), approx_median(volume deterministic, 'ERROR_RATE' ) from approxt where state = 'CA' ; REM Approximate percentile, DETERMINISTIC select approx_percentile( 0.1 deterministic) within group ( order by volume) from approxt where state = 'CA' ;
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