Performance and RDBMS Tuning and Maintenance

Demantra is a Data Base resource intensive application.

- Evident from large implementations
- Large-scale implementations are global solutions across multiple regions or
  retailer oriented store-level solutions - Require very large demand data
  repositories storing billions of data points.

Common Demantra Performance issues
- Poor worksheet response times
- Longer Batch Engine run times
- Extended Simulation runs
- Prolonged Data loads
- Slow running user updates

These issues can be addressed by appropriate DB setup and tuning activities

Example 1.
This customer has been live on a Demantra VMI implementation and suddenly reported worksheet performance issues.

Sales_Data was ~32M records, non-partitioned

Highlights:
Analyze_Schema was not being run
Did a chained row count after Analyze_Schema – 48%
Recommended Rebuild_schema and worksheet performance improved 60% on average

 

Example 2.
This is a Demantra DM/PTP/DSM implementation. Just before UAT customer loaded full volume of Sales history,
Promotion and Settlement data and started experiencing serious worksheet performance issues.

MDP_Matrix=1.5M; Sales_Data=30M; Promotion_Data = 22M;

Highlights:
- CBO parameter changes
- Relocating null and empty columns in very large tables at the end of the row
- Sales_Data partitioning
- Reorder of Data by PK
- Worksheet specific Indexes

Performance Improvements reported:

Series Config Changes, 21%

GL Data Trim, 8%

Indexes, 2%

Reorder Data by PK, 32%

Worksheet Cache Refresh, 73%

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