Comments (2)
Reduced memory usage by discarding already saved normalized queries and keeping only the Int64 hash. See commit 547463a
Might not be enough for the cases where the queries are extremely volatile. One factor that might be driving the volatility is TVPs, where the number of values captured in the incoming workload is extremely varying and leads to masive INSERT...VALUES statements of different sizes, when it should be recording only the call to the TVP instead.
from workloadtools.
The memory leak was due to events queuing up in the listener, so I implemented a cache on disk to reduce memory consumption
from workloadtools.
Related Issues (20)
- FileWorkloadListener HOT 4
- Why would controller just stop? HOT 1
- Issue on my side with replay HOT 3
- WorkloadViewer: Unable to load data object reference not set to an instance of an object HOT 6
- Workload analysis does not work with case-sensitive collations
- Add to SqlWorkload the ability to start at a specific time and stop at a specific time
- Capture the workload Error HOT 16
- Connect to Azure using MFA
- Violation of PRIMARY KEY constraint 'PK_WorkloadDetails' HOT 2
- Uncaught Exception while creating XE Session on SQL 2022
- Azure SQL Server : Extended combine events for all databases in the Azure SQL Server.
- FileWorkloadListener very slow with large files HOT 22
- Application Name wrong on Replays HOT 1
- ExtendedEventsEventReader stops reading events
- WorkloadTools issue with Commvault Backups HOT 24
- ReplayConsumer not updating database HOT 2
- Attempt to make SqlWorkload.exe a service fails with 'Type cannot be instantiated' HOT 3
- Can WorkloadTools be used to stress test with a higher load than the recorded one? HOT 1
- ConvertWorkload - required trace columns HOT 1
- WorkloadFileWriterConsumer not capturing expected data HOT 3
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from workloadtools.