[R-SIG-Finance] R + HDF5 + Pytables
manojsw at gmail.com
Tue May 18 05:56:06 CEST 2010
Daniel - that's interesting feedback.
Jeff: I did a quick search on indexing packages and it seems its still
in development stages - looks very promising thou. I am more than
happy to test it out and give feedback/suggestions.
Hopefully we could do a comparision/benchmarking of few different
alternatives (including commercial tools like kdb).
2010/5/18 Daniel Cegiełka <daniel.cegielka at gmail.com>:
> Hi Monoj
> I tested hdf5 with R and in my opinion there is no sense to use it
> with xts/zoo for tick data.
> If you will work with R, then much better is to store xts objects (or
> R objects) directly on the disk (it's simpler, faster and better way).
> Check (Jeff Ryan) packages:
> RBerkeley: https://r-forge.r-project.org/projects/rberkeley/
> indexing: http://r-forge.r-project.org/projects/indexing/
> example for RBerkeley:
> bdb <- db_create()
> db_open(bdb,file='blotter.db') # load db_file from disc
> # and some quary
> If you need ultra fast solution, you must try Jeff's indexing package ;)
> 2010/5/17 Manoj <manojsw at gmail.com>
>> Dear All,
>> I have created a HDF5 file using Python + Pytables. The HDF5
>> file stores tick-data and as such is quite huge in size. I am planning
>> to use R/zoo/xts combination for analytics. The tricky bit is that I
>> am unable to find a good wrapper to access/query the HDF5 created by
>> Pytables (keeping intact all the nice features such as indices etc of
>> HDF5 file) . The hdf5 library in R wouldn't help given the size of
>> the file.
>> One (crude) option is to query data using Python/Pytables, write
>> to an output file and invoke R for analytics. The question is - could
>> this task be done in a more efficient fashion? Is there a good
>> HDF5/Pytables wrapper that could help me do the task completely within
>> Any tips/suggestions would be greatly appreciated.
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