Trying out additional example files

This is really neat, and I’m excited to try things out with some additional HDF files!

I realize the goal is to flesh out the specification and this is not a general conversion tool yet, but it seems like working with more HDF files out in the wild might bring things to light.

Some initial questions/suggestions:

1. How to write out the .zchunkstore? seems things are setup currently to just output logging info
2. Add chunk info output to logger (maybe dtype and MB too?) lggr.debug(f'_ARRAY_CHUNKS = {h5obj.chunks}')
3. Could be useful to first check input file is valid H5. this is easy for a local file, not sure about remote:

        if not h5py.is_hdf5(f):
            raise ValueError('Not an hdf5 file')

What isn’t supported? https://github.com/intake/fsspec-reference-maker/blob/bf41138add53b0201e583aa40840cd4fa5fb907b/fsspec_reference_maker/hdf.py#L103-L106

The first file I tried to generate .zchunkstore with ran into the above, code and traceback below:

def ATL06_remote():
    return hdf2zarr.run(
        's3://its-live-data.jpl.nasa.gov/icesat2/alt06/rel003/ATL06_20181230162257_00340206_003_01.h5',
        mode='rb', anon=False, requester_pays=True,
        default_fill_cache=False, default_cache_type='none'
    )

DEBUG:h5-to-zarr:translator:Group: /gt1l/land_ice_segments
DEBUG:h5-to-zarr:translator:Dataset: /gt1l/land_ice_segments/atl06_quality_summary
Traceback (most recent call last):
  File "h5py/h5o.pyx", line 302, in h5py.h5o.cb_obj_simple
  File "/Users/scott/miniconda3/envs/fsspec-ref/lib/python3.8/site-packages/h5py/_hl/group.py", line 591, in proxy
    return func(name, self[name])
  File "/Users/scott/GitHub/fsspec-reference-maker/fsspec_reference_maker/hdf.py", line 105, in translator
    raise RuntimeError(
RuntimeError: /gt1l/land_ice_segments/atl06_quality_summary uses unsupported HDF5 filters

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "./test.py", line 45, in <module>
    ATL06_remote()
  File "./test.py", line 15, in ATL06_remote
    return hdf2zarr.run(
  File "/Users/scott/GitHub/fsspec-reference-maker/fsspec_reference_maker/hdf.py", line 273, in run
    return h5chunks.translate()
  File "/Users/scott/GitHub/fsspec-reference-maker/fsspec_reference_maker/hdf.py", line 54, in translate
    self._h5f.visititems(self.translator)
  File "/Users/scott/miniconda3/envs/fsspec-ref/lib/python3.8/site-packages/h5py/_hl/group.py", line 592, in visititems
    return h5o.visit(self.id, proxy)
  File "h5py/_objects.pyx", line 54, in h5py._objects.with_phil.wrapper
  File "h5py/_objects.pyx", line 55, in h5py._objects.with_phil.wrapper
SystemError: <built-in function visit> returned a result with an error set

[scottyhq]

Just wanted to point people here towards an optimized read-only approach to work with the icesat2 HDF5 data described in this issue http://icesat2sliderule.org/h5coro , would be interesting to compare against the fsspec-reference-maker

[ajelenak]

but I don’t know what fletcher32 is (a checksum?).

Yes, Fletcher32 is a checksum HDF5 filter. It is used to catch any read errors from HDF5 dataset chunks. When using the Fletcher32 filter, a checksum is calculated on every chunk write operation and stored with the chunk.