- (Exam Topic 5)
You manage an enterprise data warehouse in Azure Synapse Analytics.
Users report slow performance when they run commonly used queries. Users do not report performance changes for infrequently used queries.
You need to monitor resource utilization to determine the source of the performance issues. Which metric should you monitor?
Correct Answer:
A
Tempdb is used to hold intermediate results during query execution. High utilization of the tempdb database can lead to slow query performance.
Note: If you have a query that is consuming a large amount of memory or have received an error message related to allocation of tempdb, it could be due to a very large CREATE TABLE AS SELECT (CTAS) or INSERT SELECT statement running that is failing in the final data movement operation.
Reference:
https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-managemonit
- (Exam Topic 5)
You have an Azure Stream Analytics job.
You need to ensure that the job has enough streaming units provisioned. You configure monitoring of the SU % Utilization metric.
Which two additional metrics should you monitor? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.
Correct Answer:
CD
To react to increased workloads and increase streaming units, consider setting an alert of 80% on the SU Utilization metric. Also, you can use watermark delay and backlogged events metrics to see if there is an impact.
Note: Backlogged Input Events: Number of input events that are backlogged. A non-zero value for this metric implies that your job isn't able to keep up with the number of incoming events. If this value is slowly increasing or consistently non-zero, you should scale out your job, by increasing the SUs.
Reference:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-monitoring
- (Exam Topic 5)
You plan to develop a dataset named Purchases by using Azure Databricks. Purchases will contain the following columns:
ProductID ItemPrice LineTotal Quantity StoreID Minute Month Hour Year Day
You need to store the data to support hourly incremental load pipelines that will vary for each StoreID. The solution must minimize storage costs.
How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Solution:
Graphical user interface, text, application Description automatically generated
Box 1: .partitionBy Example:
df.write.partitionBy("y","m","d") mode(SaveMode.Append) parquet("/data/hive/warehouse/db_name.db/" + tableName) Box 2: ("Year","Month","Day","Hour","StoreID")
Box 3: .parquet("/Purchases") Reference:
https://intellipaat.com/community/11744/how-to-partition-and-write-dataframe-in-spark-without-deleting-partiti
Does this meet the goal?
Correct Answer:
A
- (Exam Topic 5)
You have an Always On availability group deployed to Azure virtual machines. The availability group contains a database named DB1 and has two nodes named SQL1 and SQL2. SQL1 is the primary replica.
You need to initiate a full backup of DB1 on SQL2. Which statement should you run?
Correct Answer:
B
BACKUP DATABASE supports only copy-only full backups of databases, files, or filegroups when it's executed on secondary replicas. Copy-only backups don't impact the log chain or clear the differential bitmap.
Reference:
https://docs.microsoft.com/en-us/sql/database-engine/availability-groups/windows/active-secondaries-backup-on
- (Exam Topic 5)
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 SQL Server 2019 on an Azure virtual machine.
You are troubleshooting performance issues for a query in a SQL Server instance.
To gather more information, you query sys.dm_exec_requests and discover that the wait type is PAGELATCH_UP and the wait_resource is 2:3:905856.
You need to improve system performance.
Solution: You change the data file for the master database to autogrow by 10 percent. Does this meet the goal?
Correct Answer:
B
Reference:
https://docs.microsoft.com/en-US/troubleshoot/sql/performance/recommendations-reduce-allocation-contention
