All Technologies Used
Motivation
The client approached Azati to streamline and optimize the process of extracting data from their general ledger, which involves handling large datasets from different sources, in order to improve performance and efficiency.
Main Challenges
Large volumes of data caused performance issues, including overloaded memory and inefficient query execution, which affected the system's ability to process and extract data quickly. Azati proposed optimizing the query design and improving the system's data handling capacity to ensure more efficient memory usage and faster query execution.
Poor query design and incorrect system statistics led to inefficient query execution plans, with the optimizer frequently opting for full table scans instead of utilizing indexes, causing delays and system bottlenecks. Azati suggested gathering accurate system statistics, including optimizing index usage and fine-tuning query design to allow the optimizer to select more efficient execution plans, significantly improving query performance.
Key Features
- Root Cause Analysis: Identified inefficiencies in query execution to understand the root cause of performance issues.
- Optimization of System Statistics: Improved performance by gathering and validating system statistics for the database.
- Improved Query Performance: Reduced query run time and improved system responsiveness by eliminating bottlenecks.
Our Approach
Project Impact
As a result of the optimization, the system's performance improved significantly, reducing the runtime of processes from an average of 3 hours to just 10-15 minutes. The number of direct path read events was halved, leading to faster data extraction and improved system efficiency.