DP-300 Practice Question: Monitor, configure, and optimize database resources
You are optimizing an Azure SQL Database that uses the vCore purchasing model. The database is experiencing high RESOURCE_SEMAPHORE waits. You need to identify two actions that can reduce these waits. (Choose two.)
⚠ Common exam trap
The trap here is thinking that increasing MAXDOP or enabling read-scale out will reduce memory waits, when they either increase memory demand or do not address primary workload memory pressure.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Scale up to a higher service tier or compute size.
RESOURCE_SEMAPHORE waits indicate insufficient query workspace memory. Scaling up the compute size provides more memory for grants. Optimizing queries reduces the memory needed per query. Together, these actions lower the demand and increase the supply of memory grants, reducing waits. The other options either do not affect workspace memory or could worsen the situation.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Scale up to a higher service tier or compute size.
Why this is correct
Scaling up to a higher service tier or compute size increases the amount of memory available to the database, which directly increases the query workspace memory. This allows more queries to obtain memory grants, reducing RESOURCE_SEMAPHORE waits. This is a valid action to alleviate memory grant pressure.
- ✗
Increase the memory-optimized filegroup size.
Why it's wrong here
Memory-optimized filegroup is used for In-Memory OLTP tables, not for query workspace memory. RESOURCE_SEMAPHORE waits occur when queries cannot obtain workspace memory grants. Increasing the memory-optimized filegroup size does not affect the query workspace memory available to the database, so it would not reduce RESOURCE_SEMAPHORE waits.
- ✗
Enable read-scale out.
Why it's wrong here
Read-scale out directs read-only workloads to secondary replicas, but it does not increase the memory available on the primary for read-write workloads. RESOURCE_SEMAPHORE waits on the primary would not be reduced by offloading reads unless the read workload was the cause. However, the scenario does not specify read-only workload, so this is not a reliable action.
- ✗
Increase the maximum degree of parallelism (MAXDOP).
Why it's wrong here
Increasing MAXDOP allows queries to use more processors, but it also increases the memory grant required per query because each parallel thread may need memory. This can actually increase RESOURCE_SEMAPHORE waits by making each query request more memory. Therefore, it is not a recommended action to reduce these waits.
- ✓
Optimize queries to reduce their memory grant requirements.
Why this is correct
RESOURCE_SEMAPHORE waits happen when queries request more memory than available. By optimizing queries (e.g., adding indexes, rewriting queries, updating statistics), you can reduce the memory required for operations like sorts and hashes. This decreases the demand for memory grants, thus reducing waits. This is a direct and effective action.
Go deeper
Related to this question
Learn chapter
Overview of Azure Data Platform Options
Key term
Azure SQL Performance Tuning
Azure SQL Performance Tuning is the process of optimizing the speed and efficiency of queries and database operations in Microsoft Azure SQL Database or SQL Managed Instance to reduce latency and improve throughput.
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Last reviewed September 2026 · checked against the official Microsoft exam blueprint
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