Wetu Importer - Optimize Sync Performance for Large Data Imports

[ashleyshaw]

Wetu Importer - Optimize Sync Performance for Large Data Imports

Overview

Syncing large datasets from Wetu through the Wetu Importer can be time-consuming and sometimes leads to failed syncs due to timeouts or high server load. This results in a poor user experience, especially for businesses handling large volumes of data.

Problem

• Slow Performance: Syncing large datasets takes too long, which can delay updates and reduce efficiency.
• Sync Failures: Imports may fail entirely when processing large amounts of data due to timeouts or resource limits.

Proposed Solution

• Batch Processing: Implement batch processing for large data imports to break down the sync into smaller, more manageable chunks. This approach will:

  • Reduce the load on the server by syncing data in smaller batches.
  • Improve overall reliability by minimizing the risk of timeouts or server overloads.
  • Allow users to monitor the progress of the sync, making it easier to identify and troubleshoot potential issues.

  Example:

  • Instead of attempting to sync all tour data at once, the importer could process 100 entries at a time until the full dataset has been imported.

Alternatives Considered

• Running Imports During Off-Peak Hours: While this reduces the load on servers during high-traffic periods, it is not a reliable solution for all users and doesn’t directly address the performance issues during sync.

Benefits

• Improved Performance: By breaking the import process into batches, the system can handle large datasets more efficiently without impacting server performance.
• Fewer Failures: Reducing the strain on the server will lead to fewer failed syncs, minimizing the need for manual re-syncs or troubleshooting.
• Better User Experience: Faster, more reliable imports will enhance the overall usability of the Wetu Importer, especially for businesses handling large volumes of data.

Additional Context

Batch processing is a widely-used method