How we optimized expiry date updates for 1 million records?

When working with large datasets, even small operations can become slow and unpredictable. Recently, we faced a timeout issue while updating expiry dates in a system that handles around 1 million records. This blog explains the problem we encountered, how we diagnosed it, and the solution we implemented using GridGain Distributed Cache.

The Problem

We started noticing timeout errors whenever the expiry dates were being updated for large datasets.The job was supposed to finish quickly, but instead, it kept failing due to the enormous amount of data — almost 1 million records.

This made it clear that our existing update process was not optimized for high-volume operations.

 Approach: Reproducing the Issue

To understand the bottleneck better, we replicated the scenario by creating 1 million test records.
This helped us observe the exact point where the system slowed down and why the timeout occurred.

During debugging, we identified that the real issue lay in the way data was being fetched and updated sequentially. The system simply wasn’t designed to handle this load efficiently.

Solution: Optimizing With GridGain Distributed Cache

To solve this, we introduced GridGain Distributed Cache, which allows distributed processing across multiple nodes.

Here’s what we achieved:

•  Optimized the update flow, reducing heavy sequential operations
  
•  Improved performance by using distributed computing
  
•  Eliminated timeout errors, even with large datasets
  
•  Ensured that updates now complete well within acceptable limits
  

 Key Technologies Used

• Event Debugging
  
• GridGain
  
• Distributed Cache
  
• Large Dataset Handling
  
• Application Performance Optimization
  

Conclusion

This experience highlighted how important it is to understand system bottlenecks, especially when dealing with large datasets.
By using GridGain Distributed Cache, we transformed a failing process into a fast and reliable one.
It was a challenging task, but also a rewarding one — both in terms of learning and delivering a successful solution.