On Wednesday, 4 September 2013 12:37:33 UTC+8, Brian Craft wrote:
>
>
>
> On Tuesday, September 3, 2013 9:14:30 PM UTC-7, Mikera wrote:
>>
>> On Wednesday, 4 September 2013 10:00:42 UTC+8, Brian Craft wrote:
>>
>>> I'm loading data files of about 1-2G, which are composed of a bunch of
>>> numeric data blocks. I need to store the data blocks w/o storing
>>> duplicates. They arrive as vectors of floats, and are stored as primitive
>>> byte arrays.
>>>
>>> I first tried memoizing the function that saves a block (returning an
>>> id), with the core memoize function. This failed because every block became
>>> a different key in the memoization, regardless of the content. It looks
>>> like clojure treats variables referencing primitive arrays as equal only if
>>> they refer to the same array. Note:
>>>
>>> cavm.core=> ({[1 2 3] "foo"} [1 2 3])
>>> "foo"
>>> cavm.core=> ({(float-array [1 2 3]) "foo"} (float-array [1 2 3]))
>>> nil
>>> cavm.core=> (let [a (float-array [1 2 3])] ({a "foo"} a))
>>> "foo"
>>>
>>>
>>>
>>> I next tried memoizing over the vector of floats, however performance
>>> became pathologically slow, and the process threw an OOM. I'm guessing this
>>> is due to the memory requirements of a clojure vector of floats vs. a
>>> primitive array of bytes holding the same data. Is there an easy way to
>>> compare the storage requirements?
>>>
>>> Any suggestions on how better to handle this?
>>>
>>
>> You may want to use the :ndarray-float array implementation in the latest
>> version of core.matrix.
>>
>> This is effectively a wrapper over a raw Java float array: so your
>> storage requirement should be close to the size of the raw byte data
>> (assuming the data blocks are large enough that the size of the wrapper is
>> negligible)
>>
>
> Ah, interesting.
>
> > *matrix-implementation*
> :vectorz
> > ({(matrix [1 2 3 4]) "foo"} (matrix [1 2 3 4]))
> "foo"
>
> I don't otherwise need core.matrix at this point in the loader, but this
> is convenient. Why does that work?
>
That works because Vectorz (the underlying Java lib) has a sane
implementation of .equals and .hashCode. It's pretty fast as well, though
it is still O(n) since it doesn't do hashcode caching.
Note that the :vectorz implementation uses 8-byte doubles rather than
4-byte floats though - so if you really need single precision to keep the
overall memory usage down then it might not be the best choice. I
personally never use 4-byte floats because the numerical errors soon become
problematic, but YMMV.
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