[erlang-questions] Help creating distributed server cache

David Fox <>
Fri Dec 7 19:52:38 CET 2012


I did not know about the Chicago group. Thanks for the heads up, I'll 
make sure to look into it :)

On 12/6/2012 17:26, Garrett Smith wrote:
> On Thu, Dec 6, 2012 at 5:01 PM, David Fox <> wrote:
>> Hi Garret, thanks for the response.
>>
>> I have not yet finished implementing the API; I'm still in the design phase
>> figuring out how everything should be hooked up.
> Right. though I think you can start to build actual pieces (i.e.
> compiling/running code) based on what's the most obvious to you, even
> if it's just super stupidly simple. It will give you a basis for
> iteration, which will further you help your understanding. You may
> find yourself spending almost no time designing :)
>
>> Totally agree on not limiting yourself to options this early on, I'm just
>> asking for some help and opinions on some problems I saw in potential
>> implementations :)
>>
>> David Fox
>> m: 630 930 9219
>> Chicago
> Ah, I'm also in Chicago. Do you know about the Chicago Erlang User Group:
>
> http://www.meetup.com/ErlangChicago/
>
> We haven't met the last few months, but I'd like to do an informal
> meetup before years end!
>
>> On 12/6/2012 16:34, Garrett Smith wrote:
>>> Hi David,
>>>
>>> On Thu, Dec 6, 2012 at 9:43 PM, David Fox <> wrote:
>>>> I'm currently developing a gaming server which stores player information
>>>> that can be accessed from any of our games via a REST API.
>>>>
>>>> So far I've thought of two ways to structure and cache player data:
>>>>
>>>> 1. When a client requests data on a player, spawn 1 player process. This
>>>> process handles: all subsequent requests from clients for this player,
>>>> retrieving the player data from the DB when created and periodically
>>>> updating the DB with any new data from clients. If the player is not
>>>> requested by another client within... say 30 minutes, the player process
>>>> will terminate.
>>>>
>>>> 2. Just keep previously requested data in a distributed LRU cache (e.g.,
>>>> memcached, redis, mnesia)
>>>>
>>>> Out of the two, I prefer #1 since it would allow me to separate the
>>>> functionality of different "data types" (e.g., player data, game data).
>>>>
>>>> There are just 2 problems with doing it this way that I'd like your
>>>> thoughts
>>>> and help with:
>>>> I. I would have to implement some sort of "LRU process cache" so I could
>>>> terminate processes to free memory for new ones.
>>>> II. If a load balancer connects a client to node #1, but the process for
>>>> the
>>>> requested player is on node #2, how can the player process on node #2
>>>> send
>>>> the data to the socket opened for the client on node #1. Is it possible
>>>> to
>>>> somehow send an socket across nodes? The reason I ask, is that I'd like
>>>> to
>>>> prevent sending big messages across nodes.
>>> It's tough to answer high level "approach" style questions, especially
>>> without some hands on work (tinkering) to help you understand the
>>> problem.
>>>
>>> Limiting yourself to either/or options at this stage might also be
>>> premature.
>>>
>>> Do you have a first pass at the public API for this service?
>>>
>>> If you have an idea of the functions that could define the interface,
>>> you can ask, for each unimplemented function:
>>>
>>> - Can I make this side-effect free -- i.e. calling the function
>>> doesn't change state or otherwise tamper with the universe?
>>>
>>> - Does the function read from or write to long running state?
>>>
>>> Side effect free functions are easy, which is why you try to solve
>>> problems using them exclusively whenever possible.
>>>
>>> For long running state, you can use a simple gen_server to implement
>>> state initialization and mutation. If you have questions about what I
>>> mean here, you'll need to bone up on gen_server, or alternatively look
>>> at e2 services (see http://e2project.org) as they're simpler to write.
>>>
>>> Once you have something very basic working, see if you're done! It
>>> might just work for you as is, at least for the short term. If it
>>> doesn't work, address the specific problem. E.g. if your problem is "I
>>> loose my state when the VM crahses," you'll need to implement
>>> persistence in some fashion.
>>>
>>> Questions at that level are much easier to answer :)
>>>
>>> Garrett
>>




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