Good point Robert, I'm not sure if it's just the datastore. My users wind up getting a 500 error on requests that just read data, usually even if the datastore has issues, you can still read from it.
I'd be comfortable using memcache, but I'd want to ensure it had the same data integrity as the datastore (or something close anyhow). The nice thing about the datastore is that there is optimistic locking, so I know when there's contention. Currently, our users collectively modify data at about the same time (like 7-12 updates in a single second from several users), it's pretty important that I keep them in order, so I currently have my writes wrapped in a datastore transaction with a loop that runs about 5 times or until the transaction succeeds. Has anyone managed that type of contention in the memcache? If so, I'd love to hear some techniques that can ensure no update tramples a previous concurrent update. I've submitted inquiries to the billing and CPU request form, but haven't heard back. Does it usually take longer than 24 hours to hear back from the app-engine support team? Thanks -- You received this message because you are subscribed to the Google Groups "Google App Engine for Java" group. To post to this group, send email to [email protected]. To unsubscribe from this group, send email to [email protected]. For more options, visit this group at http://groups.google.com/group/google-appengine-java?hl=en.
