Issue: Fix wrong SHA in CI tests of HubDatasetModuleFactoryWithParquetExport
State: closed
Author: albertvillanova

Fix wrong SHA in CI tests of HubDatasetModuleFactoryWithParquetExport.

Comments:
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7125). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.

<details>
<summary>Show benchmarks</summary>

PyArrow==8.0.0

<details>
<summary>Show updated benchmarks!</summary>

### Benchmark: benchmark_array_xd.json

| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |
|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 0.005741 / 0.011353 (-0.005612) | 0.004011 / 0.011008 (-0.006998) | 0.063962 / 0.038508 (0.025454) | 0.031512 / 0.023109 (0.008403) | 0.242249 / 0.275898 (-0.033649) | 0.269601 / 0.323480 (-0.053879) | 0.004502 / 0.007986 (-0.003483) | 0.002835 / 0.004328 (-0.001494) | 0.049878 / 0.004250 (0.045628) | 0.048012 / 0.037052 (0.010959) | 0.250454 / 0.258489 (-0.008035) | 0.283266 / 0.293841 (-0.010575) | 0.030752 / 0.128546 (-0.097794) | 0.012655 / 0.075646 (-0.062991) | 0.211043 / 0.419271 (-0.208229) | 0.037165 / 0.043533 (-0.006367) | 0.246815 / 0.255139 (-0.008324) | 0.264306 / 0.283200 (-0.018893) | 0.018343 / 0.141683 (-0.123340) | 1.140452 / 1.452155 (-0.311702) | 1.214849 / 1.492716 (-0.277867) |

### Benchmark: benchmark_getitem\_100B.json

| metric | get_batch_of\_1024\_random_rows | get_batch_of\_1024\_rows | get_first_row | get_last_row |
|--------|---|---|---|---|
| new / old (diff) | 0.098048 / 0.018006 (0.080042) | 0.292201 / 0.000490 (0.291712) | 0.000217 / 0.000200 (0.000017) | 0.000056 / 0.000054 (0.000001) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.018732 / 0.037411 (-0.018679) | 0.062887 / 0.014526 (0.048361) | 0.074353 / 0.176557 (-0.102204) | 0.120794 / 0.737135 (-0.616341) | 0.077066 / 0.296338 (-0.219272) |

### Benchmark: benchmark_iterating.json

| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |
|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 0.276335 / 0.215209 (0.061126) | 2.722905 / 2.077655 (0.645250) | 1.423080 / 1.504120 (-0.081040) | 1.305443 / 1.541195 (-0.235752) | 1.342142 / 1.468490 (-0.126348) | 0.741899 / 4.584777 (-3.842878) | 2.407567 / 3.745712 (-1.338145) | 3.070263 / 5.269862 (-2.199599) | 1.935732 / 4.565676 (-2.629944) | 0.081371 / 0.424275 (-0.342904) | 0.005207 / 0.007607 (-0.002401) | 0.328988 / 0.226044 (0.102943) | 3.240771 / 2.268929 (0.971842) | 1.801028 / 55.444624 (-53.643597) | 1.490593 / 6.876477 (-5.385884) | 1.521317 / 2.142072 (-0.620756) | 0.794051 / 4.805227 (-4.011176) | 0.136398 / 6.500664 (-6.364266) | 0.042902 / 0.075469 (-0.032567) |

### Benchmark: benchmark_map_filter.json

| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |
|--------|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 0.974186 / 1.841788 (-0.867602) | 12.280011 / 8.074308 (4.205703) | 9.453389 / 10.191392 (-0.738003) | 0.132627 / 0.680424 (-0.547797) | 0.014608 / 0.534201 (-0.519593) | 0.309298 / 0.579283 (-0.269985) | 0.275911 / 0.434364 (-0.158452) | 0.348261 / 0.540337 (-0.192077) | 0.439031 / 1.386936 (-0.947905) |

</details>
PyArrow==latest

<details>
<summary>Show updated benchmarks!</summary>

### Benchmark: benchmark_array_xd.json

| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |
|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 0.006248 / 0.011353 (-0.005105) | 0.004369 / 0.011008 (-0.006639) | 0.050588 / 0.038508 (0.012080) | 0.032880 / 0.023109 (0.009771) | 0.268979 / 0.275898 (-0.006919) | 0.294714 / 0.323480 (-0.028766) | 0.004518 / 0.007986 (-0.003467) | 0.002995 / 0.004328 (-0.001333) | 0.048776 / 0.004250 (0.044525) | 0.041696 / 0.037052 (0.004644) | 0.283413 / 0.258489 (0.024924) | 0.322137 / 0.293841 (0.028296) | 0.032809 / 0.128546 (-0.095737) | 0.012559 / 0.075646 (-0.063087) | 0.060456 / 0.419271 (-0.358815) | 0.034564 / 0.043533 (-0.008968) | 0.267263 / 0.255139 (0.012124) | 0.292633 / 0.283200 (0.009434) | 0.019011 / 0.141683 (-0.122672) | 1.199820 / 1.452155 (-0.252335) | 1.251829 / 1.492716 (-0.240887) |

### Benchmark: benchmark_getitem\_100B.json

| metric | get_batch_of\_1024\_random_rows | get_batch_of\_1024\_rows | get_first_row | get_last_row |
|--------|---|---|---|---|
| new / old (diff) | 0.097615 / 0.018006 (0.079609) | 0.313764 / 0.000490 (0.313274) | 0.000220 / 0.000200 (0.000020) | 0.000058 / 0.000054 (0.000003) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.024365 / 0.037411 (-0.013046) | 0.089301 / 0.014526 (0.074775) | 0.092964 / 0.176557 (-0.083592) | 0.131724 / 0.737135 (-0.605412) | 0.094792 / 0.296338 (-0.201546) |

### Benchmark: benchmark_iterating.json

| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |
|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 0.305119 / 0.215209 (0.089910) | 2.932192 / 2.077655 (0.854537) | 1.610573 / 1.504120 (0.106453) | 1.487502 / 1.541195 (-0.053693) | 1.533300 / 1.468490 (0.064810) | 0.717223 / 4.584777 (-3.867554) | 0.964402 / 3.745712 (-2.781310) | 3.111398 / 5.269862 (-2.158464) | 1.957942 / 4.565676 (-2.607734) | 0.079160 / 0.424275 (-0.345116) | 0.005639 / 0.007607 (-0.001968) | 0.358971 / 0.226044 (0.132927) | 3.564401 / 2.268929 (1.295472) | 2.043079 / 55.444624 (-53.401546) | 1.742681 / 6.876477 (-5.133795) | 1.784758 / 2.142072 (-0.357314) | 0.798508 / 4.805227 (-4.006719) | 0.133905 / 6.500664 (-6.366759) | 0.043008 / 0.075469 (-0.032461) |

### Benchmark: benchmark_map_filter.json

| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |
|--------|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 1.031715 / 1.841788 (-0.810073) | 13.374312 / 8.074308 (5.300004) | 10.789098 / 10.191392 (0.597706) | 0.133663 / 0.680424 (-0.546761) | 0.016692 / 0.534201 (-0.517509) | 0.304716 / 0.579283 (-0.274567) | 0.129074 / 0.434364 (-0.305290) | 0.346440 / 0.540337 (-0.193897) | 0.464593 / 1.386936 (-0.922343) |

</details>
</details>

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