Add streaming decompression for ZSTD_CONTENTSIZE_UNKNOWN case #707
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Codecov ReportAll modified and coverable lines are covered by tests ✅
Additional details and impacted files@@ Coverage Diff @@
## main #707 +/- ##
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Coverage 99.96% 99.96%
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Files 63 63
Lines 2712 2726 +14
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+ Hits 2711 2725 +14
Misses 1 1
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BeforeIn [1]: import numcodecs
In [2]: numcodecs.__version__
Out[2]: '0.16.1'
In [3]: codec = numcodecs.Zstd()
In [4]: bytes_val = b'(\xb5/\xfd\x00Xa\x00\x00Hello World!'
In [5]: codec.decode(bytes_val)
---------------------------------------------------------------------------
RuntimeError Traceback (most recent call last)
Cell In[5], line 1
----> 1 codec.decode(bytes_val)
File numcodecs/zstd.pyx:261, in numcodecs.zstd.Zstd.decode()
File numcodecs/zstd.pyx:191, in numcodecs.zstd.decompress()
RuntimeError: Zstd decompression error: invalid input data
In [6]: bytes3 = b'(\xb5/\xfd\x00X$\x02\x00\xa4\x03ABCDEFGHIJKLMNOPQRSTUVWXYZ[\\]^_`abcdefghijklmnopqrstuvwxyz\x01\x00:\xfc\xdfs\x05\x05L\x00\x00\x08s\x01\x00\xfc\xff9\x10\x02L\x00\x00
⋮ \x08k\x01\x00\xfc\xff9\x10\x02L\x00\x00\x08c\x01\x00\xfc\xff9\x10\x02L\x00\x00\x08[\x01\x00\xfc\xff9\x10\x02L\x00\x00\x08S\x01\x00\xfc\xff9\x10\x02L\x00\x00\x08K\x01\x00\xfc\xf
⋮ f9\x10\x02L\x00\x00\x08C\x01\x00\xfc\xff9\x10\x02L\x00\x00\x08u\x01\x00\xfc\xff9\x10\x02L\x00\x00\x08m\x01\x00\xfc\xff9\x10\x02L\x00\x00\x08e\x01\x00\xfc\xff9\x10\x02L\x00\x00\
⋮ x08]\x01\x00\xfc\xff9\x10\x02L\x00\x00\x08U\x01\x00\xfc\xff9\x10\x02L\x00\x00\x08M\x01\x00\xfc\xff9\x10\x02M\x00\x00\x08E\x01\x00\xfc\x7f\x1d\x08\x01'
In [7]: codec.decode(bytes3)
---------------------------------------------------------------------------
RuntimeError Traceback (most recent call last)
Cell In[7], line 1
----> 1 codec.decode(bytes3)
File numcodecs/zstd.pyx:261, in numcodecs.zstd.Zstd.decode()
File numcodecs/zstd.pyx:191, in numcodecs.zstd.decompress()
RuntimeError: Zstd decompression error: invalid input dataAfter |
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@d-v-b @jakirkham could you review? |
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Consider the following script: import zarr, tensorstore as ts, numpy as np
arr = ts.open({
'driver': 'zarr',
'kvstore': {
'driver': 'file',
'path': 'ts_zarr2_zstd',
},
'metadata': {
'compressor': {
'id': 'zstd',
'level': 3,
},
'shape': [1024, 1024],
'chunks': [64, 64],
'dtype': '|u1',
}
}, create=True, delete_existing=True).result()
arr[:,:] = np.random.randint(0, 9, size=(1024,1024), dtype='u1')
arr2 = zarr.open_array("ts_zarr2_zstd")
print(arr2[:,:])BeforeAfter |
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it seems like compatibility with tensorstore is part of the goal here. Would it make sense to add an integration test that uses tensorstore? |
This be better done in another pull request. It would be good to add zarr and tensorstore as optional test dependencies. Also note that the zstd compatability issue only occurs when writing Zarr v2 with tensorstore. The closest analog to numcodecs for tensorstore is riegeli where most of the compression routines are implemented. |
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@normanrz , you may be interested in taking a look as well with regard to Zstandard. |
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Zstandard can use a streaming compression scheme where the total size of the data is not known at the beginning of the process. In this case, the size of the data is unknown
and is not saved in the Zstandard frame header.
Before this pull request, numcodecs would refuse to decompress data if the size were unknown. This pull request adds a routine to decompress data if the size is unknown,
specifically when
ZSTD_getFrameContentSizereturnsZSTD_CONTENTSIZE_UNKNOWN.This pull request is based on prior pull request I made to numcodecs.js:
manzt/numcodecs.js#47
Fixes zarr-developers/zarr-python#2056
xref:
zarr-developers/zarr-python#2056
TODO: