2 - datastore query is expensive but memcache works great, so cache frequently accessed data
3 - i make sure that whenever i put() any data, i immediately set Memcache, and before making any get() from datastore, I try get Memcache first, this should not cause issues.
My question for point #2 is in the line of the need to perform data migration actually.
Let's say you have a bug on your code in a way that the data stored currently are wrong and you need to fix them up by performing a batch update. Would that hurt you in terms of cost? How would you handle such situation?
Or let's just say that your user profile data model needs to be re-jiggered to support a new feature (adding columns, changing current columns, etc).
it depends on how big your data is, but every query operation, every fetch, every write operation it charged. http://code.google.com/appengine/docs/billing.html has details on how many read/write datastore API calls are made per operation. if u have to write in a new column for thousands of entries, then it will cost a bit, $0.10/100k operations, one re-write has 7 operations + incoming/outgoing bandwidth cost + instance usage cost will apply, it is hard to estimate actual cost.
Comments
1 - gramfeed is paid, http://code.google.com/appengine/docs/billing.html is correct, dont know what the other one is, i think that $9/month in minimun fee, i go past it anyway.
2 - datastore query is expensive but memcache works great, so cache frequently accessed data
3 - i make sure that whenever i put() any data, i immediately set Memcache, and before making any get() from datastore, I try get Memcache first, this should not cause issues.
Thank you for the reply!
My question for point #2 is in the line of the need to perform data migration actually.
Let's say you have a bug on your code in a way that the data stored currently are wrong and you need to fix them up by performing a batch update. Would that hurt you in terms of cost? How would you handle such situation?
Or let's just say that your user profile data model needs to be re-jiggered to support a new feature (adding columns, changing current columns, etc).
it depends on how big your data is, but every query operation, every fetch, every write operation it charged. http://code.google.com/appengine/docs/billing.html has details on how many read/write datastore API calls are made per operation. if u have to write in a new column for thousands of entries, then it will cost a bit, $0.10/100k operations, one re-write has 7 operations + incoming/outgoing bandwidth cost + instance usage cost will apply, it is hard to estimate actual cost.