Hey folks, I’m working on a project using Python 2.7 Google App Engine SDK. I need to deal with huge text files (over 2GB) and I’m wondering if App Engine can handle reading and writing these monsters to Google Drive or Cloud Storage.
I’m planning to grab about a million rows from the Datastore (or maybe NDB) and save them as a text file. It’s basically network relationship data, like this:
Node1 -> Node2
Node2 -> Node3
Node1 -> Node4
I’m thinking I might need to use task queues or cron jobs for this. After processing, I’ll have another file with scores for each node pair, which I’ll need to write back to the database.
What kind of issues should I watch out for? Any tips or tricks you can share? Thanks!
yo, i’ve done similar stuff. app engine can handle it, but u gotta be smart. use cloud storage, not drive. split ur work into chunks w/ task queues. watch out for timeouts n memory limits. streaming data helps. keep an eye on quotas too. good luck with ur project!
I have worked on similar projects where we managed massive file operations on App Engine using Cloud Storage. In my experience, it is much more reliable to use Cloud Storage because it was designed for heavy data and streaming, unlike Google Drive. I addressed potential issues by breaking the workload into smaller tasks using task queues, which helped avoid timeouts and memory problems. The streaming capabilities of the client library allowed for writing data in chunks. Also, careful monitoring of quotas and planning for the 60-second request limit were essential to ensure smooth processing.
Having tackled similar challenges, I can confirm App Engine’s capability to handle large-scale file operations when coupled with Cloud Storage. Key to success is implementing a robust chunking strategy. Break your million-row dataset into manageable segments, processing each via separate task queue jobs. This approach mitigates timeout risks and memory constraints.
For file writes, leverage Cloud Storage’s resumable upload feature. It’s particularly useful for your 2GB+ files, allowing recovery from network interruptions. When reading, consider using the Cloud Storage JSON API for improved performance.
Regarding database operations, batch your writes to minimize Datastore API calls. Monitor your quota usage closely, especially for high-frequency operations. Lastly, ensure your app is designed to handle potential failures gracefully, implementing appropriate retry logic where necessary.