Starting with Wave 2022.15 release of SAP Analytics Cloud we introduce the “Backend Query Analysis”
- Data is well-prepared
- Story is well-performing
We focus in this blogpost on the latter. To design a well-performing story it is helpful for the developer to get immediate feedback about each widgets performance. The importance of this feedback is proportional to the complexity of the Story design as it is getting more difficult to maintain the overview.
Among other scenarios, there are three performance factors that you should be aware of:
- Performance of the client
- Performance of the network
- Performance of the widgets
While client and network performance are addressed in the SAP Analytics Cloud Performance Benchmark, SAC is considered by some people as a blackbox in regards to the widget’s performance. We acknowledged the need to provide additional information in SAC, to help the designers to understand how the widget design affects the query performance and how they can reach the most efficient implementation. This information about the widget’s query runtime in the backend system was missing. This is something that we introduce now by and by, the information of the query performance itself.
First we show widgets that have a backend runtime of more than one second and show what has been reported by the backend system as potential factors that might contribute to that runtime.
Content Overview
The query analysis will be available if:
- the query runtime in the backed system was greater than 1s
- the Story is in edit mode
- Classic Mode
- Table
- Value Driver Tree (VDT)
- Optimized Design Mode
- Chart
- Table
- VDT
The query analysis is accessible via:
- Classic Design Mode
- Table: Context Menu/ Show Performance Analysis
- VDT: Context Menu/ Show Performance Analysis
- Optimized Design Mode
- Chart: Context Menu/ Applied to Chart/ Errors and Warnings
- Table: Context Menu/ Show Performance Analysis (design will be adopted according to chart)
- VDT: Context Menu/ Show Performance Analysis (design will be adopted according to chart)
- Table feature:
- warning icon at the table
Scope
- Identify SAC Stories and Analytic Applications that have the highest performance impact in the backend system
- Analyze Backend Runtime Distribution of problematic scenarios
- Use Performance Analysis Tool for workflow analysis of these problematic scenarios and identify time consuming Widgets
- Identify most used Stories and Analytic Applications
- Analyze workflows of problematic scenarios
- Identify problematic widgets within these workflows
- Use Model SAC_PERFORMANCE_E2E (Files/ System/ Common/ SAC Content) to analyze Entry Page and navigation within problematic Story to be able to redesign and optimize
Examples
- Hana / MDS
- BW / InA
- Many Calculations resulting in 30s query processing time
Outlook
- More information for InA and additional SAP Notes and recommendations for how to improve performance in dialogue
- More information for MDS and additional SAP Notes and recommendations for how to improve performance in dialogue
- Consideration of additional information for planning specific details
- Widget Analysis as next step of query analysis adding client and network information to the dialogue
Prerequisite SAP Notes
- SAP BusinessWarehouse 3228409 – INA: performance analysis metrics as part of the InA response