1. Reporting Services Proactive Maintenance
Grzegorz Stolecki
Reporting Services Proactive Maintenance

2. Sponsors

3. About me…
BI consultant, trainer SQL Server and Data Platform MVP since 2010 Data Community Poland Member

4. Agenda
Reporting Services Execution Log Anatomy How to transform Execution Log into useful piece of data for analysis… How to use Power BI and R to predict SSRS performance…

5. Proactive maintenance
Reactive – in case of an issue angry users send you s, call you… Proactive – in case of an issue you (angry) send s to users, call them and they think you are some kind of a god…

6. Reporting Services Logs
Execution Log Report Server Service Trace Log Report Server HTTP Log Configuration: ReportingServicesService.exe.config

7. Configuration
ExecutionLogLevel: Normal | Verbose

8. ExecutionLog3 view columns
RequestType
Interactive
Subscription
ItemAction
Render
Sort
BookmarkNavigation
DocumentNavigation
GetDocumentMap
FindString
Execute
RenderEdit

9. ExecutionLog3 view columns
Source
Live
Cache
Snapshot
History
AdHoc
Session
Rdce
TimeDataRetrieval
TimeProcessing
TimeRendering

10. Report parameters in the Execution Log
Stored in one text column Multiselect: more than one parameter value recorded Special characters encoded

11. ExecutionID
Identifies different activities during one report execution e.g.
Parameter value change
Interactive options: sorting, searching for a string, toggling report element visibility, document map navigating

12. How to transform ExecutionLog…
Add the index column (you will need it in the next task) Load parameters values into seperate table joined with the execution log table Add column with total time of execution (TimeDataRetrieval + TimeProcessing + TimeRendering) Seperate Render rows from the rest

13. How to analyze ? Standard Deviations Group reports with clustering
Execution count and times by:
Time period
Parameters values
Row count
Standard Deviations
Group reports with clustering
Use PCA (Principal Component Analysis) to reduce variables number

14. How to analyze ? Report selection for further analysis
High execution count
High row count
High variance of execution time
Periods with higher workload

15. How to analyze ? Report caching and snapshot usage
What phase does consume most of the execution time?
Data Retrieval  Processing  Rendering
Datasets execution analysis

16. How to analyze ?
Identify and decompose time series Workload peaks predicting Select reports for further, more detailed analysis

17. What tools to use ? Power BI Easily load and transform data
Fast exploratory analysis
R integration – use ready made controls or your own scripts

18. Thank You! Questions?