Kerchunking to Parquet¶
Proof-of-Concept with an issue pending software updates
The example works with not-yet-released versions of :
- filesystem_spec post [commit 2e3f022][ffspec-commit-2e3f022]
- Kerchunk post commit b9659c3
Example data¶
This goes on with the same example data as in Kerchunking to JSON.
ls -1
SISin202001010000004231000101MA.nc
SISin202001020000004231000101MA.nc
SISin202001030000004231000101MA.nc
SISin202001040000004231000101MA.nc
Reference to Parquet store¶
We create Parquet stores using the Kerchunk engine
rekx reference-multi-parquet . -v
Creating the following Parquet stores in . :
SISin202001020000004231000101MA.parquet
SISin202001030000004231000101MA.parquet
SISin202001040000004231000101MA.parquet
SISin202001010000004231000101MA.parquet
Done!
Let's check for the new files :
ls -1
SISin202001010000004231000101MA.nc
SISin202001010000004231000101MA.parquet
SISin202001020000004231000101MA.nc
SISin202001020000004231000101MA.parquet
SISin202001030000004231000101MA.nc
SISin202001030000004231000101MA.parquet
SISin202001040000004231000101MA.nc
SISin202001040000004231000101MA.parquet
There is one .parquet store for each input file.
Combine references¶
We then combine the multiple Parquet stores into a single one
We verify the new file is there :
ls -1tr
SISin202001030000004231000101MA.nc
SISin202001010000004231000101MA.nc
SISin202001020000004231000101MA.nc
SISin202001040000004231000101MA.nc
SISin202001010000004231000101MA.parquet
SISin202001030000004231000101MA.parquet
SISin202001020000004231000101MA.parquet
SISin202001040000004231000101MA.parquet
combined_kerchunk.parquet
Verify¶
Does it work ? We verify the aggregated Parquet store is readable
read-performance won't show more than just the time it took to load the data
in memory. Let's go a step further and print out the values :
rekx select-parquet combined_kerchunk.parquet SIS 8 45
🗴 Something went wrong in selecting the data : "not all values found in index 'lon'. Try setting the
`method` keyword argument (example: method='nearest')."
Error
No panic! The above error is a good sign actually since there is no exact pair of coordinates at longitude, latitude : (8, 45) over which location to retrieve data.
Let's get the closest pair of coordinates that really exists in the data by
instructing the --neighbor-lookup nearest option :
rekx select-parquet combined_kerchunk.parquet SIS 8 45 --neighbor-lookup nearest
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 46.0, 114.0, 179.0, 238.0,
290.0, 333.0, 359.0, 379.0, 377.0, 372.0, 344.0, 306.0, 262.0, 206.0, 137.0, 69.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 46.0, 110.0, 175.0, 231.0, 291.0, 332.0, 356.0, 378.0, 376.0, 370.0,
344.0, 308.0, 260.0, 203.0, 137.0, 69.0, 7.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 13.0, 61.0,
74.0, 112.0, 142.0, 162.0, 185.0, 251.0, 251.0, 176.0, 152.0, 136.0, 111.0, 84.0, 65.0, 44.0, 3.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 46.0, 105.0, 173.0, 236.0, 259.0, 322.0, 371.0, 373.0, 382.0,
358.0, 347.0, 311.0, 267.0, 205.0, 147.0, 74.0, 9.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0
or add -v for a Xarray-styled output
rekx select-parquet combined_kerchunk.parquet SIS 8 45 --neighbor-lookup nearest -v
✓ Coordinates : 8.0, 45.0.
<xarray.DataArray 'SIS' (time: 192)>
array([ 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 46., 114., 179., 238., 290., 333., 359., 379., 377.,
372., 344., 306., 262., 206., 137., 69., 0., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 46., 110., 175., 231., 291., 332., 356., 378., 376.,
370., 344., 308., 260., 203., 137., 69., 7., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 13., 61., 74., 112., 142., 162., 185., 251., 251.,
176., 152., 136., 111., 84., 65., 44., 3., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 46., 105., 173., 236., 259., 322., 371., 373., 382.,
358., 347., 311., 267., 205., 147., 74., 9., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
dtype=float32)
Coordinates:
lat float32 45.03
lon float32 8.025
* time (time) datetime64[ns] 2020-01-01 ... 2020-01-04T23:30:00
Attributes:
cell_methods: time: point
long_name: Surface Downwelling Shortwave Radiation
standard_name: surface_downwelling_shortwave_flux_in_air
units: W m-2
Now it worked! One more option : let's get a statistical overview instead :
rekx select-parquet combined_kerchunk.parquet SIS 8 45 --neighbor-lookup nearest --statistics
Selected series
Statistic Value
────────────────────────────────────────────────────
Start 2020-01-01T00:00:00.000000000
End 2020-01-04T23:30:00.000000000
Count 192
Min 0.0
25th Percentile 0.0
Mean 72.97396
Median 0.0
Mode 0.0
Max 382.0
Sum 14011.0
Variance 14933.45
Standard deviation 122.2025
Time of Min 2020-01-01T00:00:00.000000000
Index of Min 0
Time of Max 2020-01-04T11:30:00.000000000
Index of Max 167
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