Will that end up being cheaper than the following? Put a new entity in the datastore for each vote - Kind: "Vote", ID: Auto generated, Vote for: "Item S" Have a task queue query all the votes and delete them then write the count of votes to a global object.
Cost = 1 datastore read + 1 datastore write + some fairly minor task processing per vote. On Sep 29, 1:47 pm, Peter Dev <[email protected]> wrote: > Price: > - with backends lets say 3 B2 machines = 350USD/Month > - UrlFetch Data Sent/Received 0,15USD/GB > > Limit: > - URL Fetch Daily Limit 46,000,000 calls > this can be a problem...but I see it is possible to request an > increase > > Write data parallel in DB: Task Queue with rate every 30second could > be a solution > (check timestamps in cache and write in DB) > > RESET counters = empty cache in Backends & reset counter of object in > DB > > Backends cache = HashMap with shared counter values > or > counter values without sharding > (just increment value in java hashmap is fast enough) > > With backends we don’t need sharding I think....what do you think? Thx. -- 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.
