Memory usage in Google App Engine

I am a bit confused. I wrote a Java stand alone app and now I want to use GAE to deploy it on the web and on the way also to learn about GAE. In my application, I read data from file, store it in memory, process it, and then store the results in memory or file. I understand that now I need to store the results in the GAE's data store, which is fine. So I can run my program independently on my computer, then write the results to file, and then use GAE 开发者_运维知识库to upload all the results to the data store, and then users can query it. However, is there a way that I can transfer the entire process into the GAE application? so the application reads data from file, do the processing (use the memory on the application server and not my computer - needs at least 4GB of RAM), and then when it's done (might take 1-2 hours), writes everything to the GAE data store? (so it's an internal "offline" process that no users are involved).

I'm a bit confused since Google don't mention anything about memory quota.

Thanks!

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You will not be able to do your offline processing the way you are envisioning. There is a limit to how much memory your app can use, but that is not the main problem. All processing in app engine is done in request handlers. In other words, any action you want your app to do will be written as if it is handling a web request. Each of these handlers is limited to 30 seconds of running time. If your process tries to run longer, it will get shut down. App engine is optimized for serving web requests, not doing heavy computations.

All that being said, you may be able to break up your computational tasks into 30 second chunks and store intermediate results in the datastore or memcache. In that case you could use a cron job or task queue (both described in the app engine docs) to keep calling your processing handlers until the data crunching was done.

In summary, yes, it may be possible to do what you want, but it might not be worth the trouble. Look into other cloud solutions like Amazon's EC2 or Hadoop if you want to do computationally intensive things.