Aaron, thanks for chiming in.

I'm doing what you said, i.e. all data for a single object (which is quite
lean with about 100 attributes 10 bytes each) just goes into a single
column, as opposed to the previous version of my application, which had all
attributes of each small object mapped to individual columns.

So yes, I perhaps considered having 100 objects in a single column but that
is suboptimal for many reasons (hard to add object later).

My reference to OOP was this -- if I was sticking with the original design,
it could have been advantageous to have OOP since statistically it's likely
that requests for objects are often serial, e.g. often people don't query
for just one object with id=123, but for a series like id=[123..145]. If I
bunch these into rows containing 100 objects each, that promises some
efficiency right there, as I read one row as opposed to say 50.




aaron morton wrote:
> 
> I'd collapse all the data for a single object into a single column, not
> sure about storing 100 objects in a single column though. 
> 
> Have you considered any concurrency issues ? e.g. multiple threads /
> processes wanting to update different objects in the same group of 100? 
> 
> Dont understand your reference to the OOP in the context of a reading 100
> columns from a row. 
> 
> Aaron
> 
>  
> On 19 Mar 2011, at 16:22, buddhasystem wrote:
> 
> > As I'm working on this further, I want to understand this:
> > 
> > Is it advantageous to flatten data in blocks (strings) each
> containing a
> > series of objects, if I know that a serial object read is often
> likely, but
> > don't want to resort to OPP? I worked out the optimal granularity, it
> seems.
> > Is it better to read a serialized single column with 100 objects than
> a row
> > consisting of a hundred columns each modeling an object?
> > 
> > --
> > View this message in context:
> http://cassandra-user-incubator-apache-org.3065146.n2.nabble.com/Reading-whole-row-vs-a-range-of-columns-pycassa-tp6186518p6186782.html
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> archive at Nabble.com.
> 


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