[Hdf-forum] writing data as fast as possible

Fri Jan 15 06:30:30 EST 2010

Hi Dimitris, 

Thanks for your suggestion. 
I'll look into the VFL possibility. A disadvantage I see is that you
have to make it known, so common tools won't recognize it. I guess it is
not  possible to load it dynamically. In principle it should be possible
by storing the driver name and use it as the name of the shared library.

Does using a specific VFL mean that all data are written through that
VFL and that it is not possible to store the meta data in the 'normal'
way and only store the bulk data through that VFL? 
Preferably I would like to bypass HDF5 entirely when writing (apart
from telling the VFL) and use that VFL when reading. In that way I can
write as I like and still use tools like h5view to look at the data
(provided the VFL can be loaded dynamically).  

As I said writing happens in parallel, so each disk has to part of the
job. But we would like to keep the amount of resources needed to a
minimum, for which optimal write performance is needed. Reading is less
of an issue. 

Cheers, 
Ger

>>> Dimitris Servis <servisster at gmail.com> 1/15/2010 11:47 AM >>>
Ger

couldn't you use the multi VFL driver? In any case, the nGB/sec rate
will not be sustainable by any hard drive today in the market right?
Even if you buffer in SSDs still the disk write speed is your bottleneck
rather than hdf5...

HTH

-- dimitris

2010/1/15 Ger van Diepen <diepen at astron.nl>

We have an instrument generating several GBytes/second.
We would like to dump these data as fast as possible to disk (of
course
in a parallel way), preferably with O_DIRECT to bypass the OS file
cache
and to avoid seeks to maintain meta data.
Yet, it would be nice if these data can be seen as an HDF5 dataset.

My question is if it possible to do something like this. Either that
HDF5 has the option to write data in this way or through some
mechanism
that HDF5 can treat such an external file as HDF5 data, possibly by
dynamically loading a shared library that knows how to interpret the
data.

I'm asking this because we have the impression that something like an
extendible dataset does not give us the performance/robustness we
need.
In case of a crash we would like to lose as few data as possible,
which
means that a regular flush has to be done which might kill
performance.
I guess that without a flush the indices are only written at the end,
so
the data cannot be found in case of a crash.

Cheers,
Ger van Diepen

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