Thank you very much,

Matthieu, your answer is very helpful. The complex logic and semantic aspect might be the big issues for MapReduce.  Actor model is flexible for logic and semantic.

In my opinion, the processing of mapreduce is still very fast ,since it handles a block, while stream may need to compute a event every time or cache in memory for a while.
Maybe the speed is not the main problem.

Thank you for the link, Kaiser.

Dingyu Yang

2012/10/17 Kaiser Md. Nahiduzzaman <>
Good question and good answer! While Matthieu has already answered
this question, the following review of MapReduce online might also be


On Tue, Oct 16, 2012 at 8:08 AM, Matthieu Morel <> wrote:
> Hi,
> S4 is inspired by the actor model: it is not a strict implementation, but
> provides asynchronous event based processing, state encapsulation, safe
> messaging and location transparency.
> It also incorporates data partitioning, as in MapReduce.
> AFAIK, MapReduce Online extends Hadoop with continuous micro batching but
> still retains some blocking behaviour, disk I/O, and tradeoffs coming from
> adapting a platform originally optimized for large batch processing.
> In contrast, the main objective of S4 is to provide a generic platform for
> low latency data processing. You can define arbitrarily complex graphs of
> PEs, everything is processed in memory, in a stateful manner (if needed),
> and there is typically no disk I/O.
> Hope this helps,
> Matthieu
> On 10/16/12 7:49 AM, ԣ wrote:
>> Hello, all,
>> S4 is using actor model to implement real-time processing.
>> Each PE is regarded as a actor and messages communicate between actors.
>> While I read the paper "Mapreduce Online", it also supports pipeline
>> online processing and near real-time and stream publish results.
>> Therefore, I am really interested in Where is the actor model in S4, and
>> What it can do but MapRduce cannot?
>> Thank you !
>> Dingyu Yang