Assuming most of the updates update the same data, it might be. But what if updating the same data is rare? Wouldnt stm and sync between servers be an overhead as most of the time there wont be a conflict of the updates?
Sent from my self
On 10 Nov 2012, at 14:10, "Flávio W. Brasil" <fwbra...@gmail.com> wrote:
> Yes, it's faster. Optimistic locking with efficient memory usage scales very well.
> On Saturday, 10 de November de 2012 at 10:33, Konstantinos Kougios wrote:
>> are you sure that this is faster than managing the sync in the database/transaction level? What if you have 3 or 10 servers connecting with the same database?
>> On 09/11/12 12:33, Flávio W. Brasil wrote:
>>> Obs.: The test uses the great gfork framework to create multiple VMs.
>>> On Friday, 9 de November de 2012 at 10:10, Konstantinos Kougios wrote:
>>>> Flavio, thanks for the sample code. I'll have a better look later on but from a quick look I had, here is the question:
>>>> how does activate solve this issue when you have multiple application servers accessing 1 database (or a set of them) ?
>>>> On 09/11/12 11:53, Flávio W. Brasil wrote:
>>>>> On Friday, 9 de November de 2012 at 09:29, Tim Pigden wrote:
>>>>>> ah - but for me it's important that "website" is an immutable object and a case class. In that case would I not have to implement a secondary layer on top and we've conceptually just moved the problem from the database | application interface into a activate | rest-of-application interface?
>>>>>> On 9 November 2012 11:12, Flávio W. Brasil <fwbra...@gmail.com> wrote:
>>>>>>> Example on why Mapperdao has a veiled mutability:
>>>>>>> The Activate counterpart:
>>>>>>> Entity declaration is also much simpler using Activate:
>>>>>>> Than using Mapperdao:
>>>>>>> On Tuesday, 6 de November de 2012 at 20:32, Kostas kougios wrote:
>>>>>>>> Ok, to continue the discussion in this separate thread from https://groups.google.com/forum/?fromgroups=#!topic/scala-user/TNG6KG...
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