Also last time I checked dataflow in contrib was dead, Cascalog, datomic 
and to some extent core.logic fill this niche 

Ronen

On Tuesday, August 21, 2012 3:55:46 AM UTC+3, ronen wrote:
>
> Terabyte size and chain of dependent tasks might hint toward 
> Cascalog<https://github.com/nathanmarz/cascalog/wiki> this assumes that 
> your doing batch job processing (on top of hadoop) 
>
> If you need a more soft real time datalog based query then I would check 
> datomic <http://www.datomic.com/> although from your description is 
> sounds less so.
>
> Ronen
>
> On Tuesday, August 21, 2012 3:14:23 AM UTC+3, Leif wrote:
>>
>> +1.  I know of a couple tools in python for this purpose that are called 
>> "workflow management systems."   It would be good to know if there is a 
>> robust one in clojure.
>>
>> On Monday, August 20, 2012 12:18:54 AM UTC-4, matt hoffman wrote:
>>>
>>> I have a problem that I'm trying to figure out how to tackle. I'm new to 
>>> Clojure, but I'm interested, and perhaps this will be my excuse to give it 
>>> a try. Any of the following answers would help:
>>> "What you're describing really sounds like X"
>>> "You could think of that problem like this, instead"
>>> "You may want to search for term 'Y'...it sounds related" (I imagine I'm 
>>> probably describing some well-established domain...I just don't know the 
>>> right terms to search for)
>>>
>>> So, the problem:
>>> I have an app that is in production doing some fairly complex 
>>> calculations on large-ish (terabyte-range) amounts of data.  The 
>>> calculations are expressed as chains of dependent tasks, where each tasks 
>>> can have a number of inputs and outputs. But the code has become hard to 
>>> maintain, full of accidental complexity and very difficult for newer 
>>> developers to understand. So, I'm trying to find the right abstractions to 
>>> put in place to keep things simple. 
>>> One of the sources of complexity is the intermingling of code involving 
>>> loading data, dividing up data to be executed in parallel, processing data, 
>>> persisting data, and handling the execution flow on an individual datum 
>>> (configuring pipelines of components,etc.) I'd like to keep the functions 
>>> pure and push the other concerns off to a framework -- and, ideally, not 
>>> have to write that framework. 
>>>
>>> So I think my problem statement is this: 
>>> I'd like to be able to define functions that specify, somehow, what 
>>> input they want, and perhaps what output they produce. Then I'd like to 
>>> push the concern of how those inputs are calculated -- loaded from a db, 
>>> calculated from source data -- off on some other party. 
>>>
>>> For example, if I define a function that requires "foo", and I call that 
>>> function without providing "foo", I'd like for _something_ to step in and 
>>> say, "Ok, you require foo. I have this function over here that produces 
>>> foo. Let me call that for you, then hand you the output."  Perhaps instead 
>>> of a framework that transparently looks up and executes that function and 
>>> provides a Future for the result, perhaps I can explicitly build a 
>>> dependency graph up-front containing all the functions required to produce 
>>> the end result, and then execute them all in order... I think the effect is 
>>> the same. 
>>>
>>> From a bit of searching I've done today, dataflow programming like 
>>> clojure.contrib.dataflow sounds like it might be close to what I'm looking 
>>> for, but I'd love to hear ideas.   Am I describing something that already 
>>> exists?  Would this actually be simpler than it seems using some clever 
>>> macros? Are there some keywords I should search for to get started?  Or 
>>> perhaps I'm coming at this problem wrong, and I should think about it a 
>>> different way...
>>>
>>>

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