MetaScore calculation is slow for older blockchain accounts

[advaita-saha]

Describe the bug
For very old account metascore calculation becomes very slow, as

Expected behavior
It should be fast.

PS - you can use multi-process to make it fast, or can come up with your own solution

[AK4266]

Hey, can you assign me this issue. I would like to work on this under GSSoC'23

[advaita-saha]

Hey, can you assign me this issue. I would like to work on this under GSSoC'23

Sure,
Do let me know your approach.
If I find your approach good enough will assign you the issue

[AK4266]

Sure, I will start working on this, and I'll let you know as soon as I get the idea...

[shahkushal38]

any update @AK4266 ??

[AishwaryaSatpute1]

I'm here to suggest some alternative approaches that may help improve the speed and efficiency of MetaScore calculation for these accounts.

Data Segmentation: Instead of processing the entire blockchain account data at once, consider segmenting the data based on time intervals or specific blocks. By breaking down the calculation into smaller chunks, you can distribute the workload and reduce the processing time for each segment.

Historical Snapshot: Create a periodic snapshot of older blockchain accounts and their associated data. Instead of recalculating the MetaScore from scratch every time, use the latest snapshot as a starting point and apply incremental updates based on subsequent changes. This approach can significantly reduce the computational overhead for older accounts.

Parallel Processing: Explore the possibility of parallelizing the MetaScore calculation process by utilizing multiple computing resources. By dividing the workload among multiple threads or machines, you can expedite the calculation for older accounts. However, ensure proper synchronization and data consistency to avoid any conflicts.

Algorithmic Optimization: Review the existing MetaScore calculation algorithm and look for opportunities to optimize its efficiency. Consider employing more efficient data structures, algorithmic techniques (such as dynamic programming or memoization), or leveraging pre-calculated values to speed up the calculation process.

Caching Mechanism: Implement a caching mechanism to store previously calculated MetaScores for older accounts. This way, you can retrieve the precalculated values instead of recomputing them. Ensure the cache is efficiently managed and refreshed whenever relevant changes occur to maintain accuracy.

Prioritization Strategy: Analyze the importance and frequency of MetaScore calculations for different accounts. Prioritize the calculation process based on account activity or relevance to ensure that accounts requiring immediate attention receive faster processing.

Please guide on which one you feels more suitable for this project ???? Soon I'll update you with pseudo Algorithm.