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extension towards paralell map / reduce that maps eventually #42
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Well, seems too theoretical for me. |
real life workload. when you need to increase the throughput of a sysytem you run many of them in parallel. this is what Spark & Storm do in slight different fundamental ways. the way reactive framework operate is a DAG. a single node acts as a computational node. |
Regarding multi-server/load-distribution scenarios, the only thing currently planned is consistent hashing. |
P.S. The next step in that direction is adding server-side event filters/listeners. |
looking forward to playing with it and seeing where i can push it. |
this is a nice dataflow reactive system.
i was wondering ig this project intends to allow parallelization of a single datanode in th dag to be say 100 dag nodes of the same type. then each one receives a slice of the data on the bus and then converges.
its a logical next step i feel to use the power of crdt because you dont have to conform to map reduce i think anymore because the results can join over time .
bacon.js has a similar approach as swarm (not the same) but has formalized the map reduce without crdt.
https://github.com/baconjs/bacon.js
the two joined would be potent !!
can you have a look and see if you see what i see. i would like to converge the two and put a formal dsl that is serialisable perhaps with a web ide on top
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