Issue: Support fsspec 2024.5.0
State: closed
Author: albertvillanova

Support fsspec 2024.5.0.

Comments:
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6921). 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) | 0.005252 / 0.011353 (-0.006100) | 0.003752 / 0.011008 (-0.007257) | 0.064034 / 0.038508 (0.025526) | 0.031205 / 0.023109 (0.008096) | 0.248903 / 0.275898 (-0.026995) | 0.275808 / 0.323480 (-0.047671) | 0.003135 / 0.007986 (-0.004851) | 0.002635 / 0.004328 (-0.001693) | 0.049869 / 0.004250 (0.045619) | 0.047602 / 0.037052 (0.010549) | 0.259738 / 0.258489 (0.001249) | 0.296131 / 0.293841 (0.002290) | 0.027467 / 0.128546 (-0.101080) | 0.010449 / 0.075646 (-0.065197) | 0.201369 / 0.419271 (-0.217903) | 0.036317 / 0.043533 (-0.007216) | 0.244347 / 0.255139 (-0.010792) | 0.267597 / 0.283200 (-0.015602) | 0.019930 / 0.141683 (-0.121753) | 1.149012 / 1.452155 (-0.303143) | 1.188083 / 1.492716 (-0.304633) |

### 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) | 0.095190 / 0.018006 (0.077184) | 0.300705 / 0.000490 (0.300215) | 0.000222 / 0.000200 (0.000022) | 0.000051 / 0.000054 (-0.000004) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.019297 / 0.037411 (-0.018115) | 0.063183 / 0.014526 (0.048657) | 0.075094 / 0.176557 (-0.101463) | 0.123556 / 0.737135 (-0.613579) | 0.076721 / 0.296338 (-0.219618) |

### 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) | 0.284136 / 0.215209 (0.068927) | 2.814041 / 2.077655 (0.736387) | 1.471038 / 1.504120 (-0.033082) | 1.344002 / 1.541195 (-0.197193) | 1.353875 / 1.468490 (-0.114615) | 0.599495 / 4.584777 (-3.985282) | 2.394491 / 3.745712 (-1.351221) | 2.781734 / 5.269862 (-2.488128) | 1.729829 / 4.565676 (-2.835848) | 0.064194 / 0.424275 (-0.360081) | 0.005022 / 0.007607 (-0.002585) | 0.343384 / 0.226044 (0.117340) | 3.357067 / 2.268929 (1.088139) | 1.816323 / 55.444624 (-53.628301) | 1.549405 / 6.876477 (-5.327072) | 1.594394 / 2.142072 (-0.547679) | 0.660650 / 4.805227 (-4.144578) | 0.120271 / 6.500664 (-6.380393) | 0.042422 / 0.075469 (-0.033047) |

### 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) | 0.975776 / 1.841788 (-0.866011) | 11.828093 / 8.074308 (3.753784) | 9.384164 / 10.191392 (-0.807228) | 0.140761 / 0.680424 (-0.539663) | 0.014038 / 0.534201 (-0.520163) | 0.284904 / 0.579283 (-0.294379) | 0.263430 / 0.434364 (-0.170934) | 0.320856 / 0.540337 (-0.219482) | 0.419199 / 1.386936 (-0.967737) |

</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) | 0.005672 / 0.011353 (-0.005681) | 0.003667 / 0.011008 (-0.007341) | 0.049989 / 0.038508 (0.011481) | 0.033115 / 0.023109 (0.010006) | 0.269808 / 0.275898 (-0.006090) | 0.293286 / 0.323480 (-0.030193) | 0.004238 / 0.007986 (-0.003748) | 0.002722 / 0.004328 (-0.001606) | 0.049516 / 0.004250 (0.045265) | 0.042076 / 0.037052 (0.005024) | 0.282182 / 0.258489 (0.023693) | 0.310817 / 0.293841 (0.016976) | 0.029824 / 0.128546 (-0.098722) | 0.010516 / 0.075646 (-0.065130) | 0.058223 / 0.419271 (-0.361049) | 0.033263 / 0.043533 (-0.010270) | 0.268769 / 0.255139 (0.013630) | 0.288308 / 0.283200 (0.005108) | 0.018531 / 0.141683 (-0.123151) | 1.136806 / 1.452155 (-0.315349) | 1.192636 / 1.492716 (-0.300080) |

### 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) | 0.096583 / 0.018006 (0.078577) | 0.303678 / 0.000490 (0.303188) | 0.000211 / 0.000200 (0.000011) | 0.000044 / 0.000054 (-0.000010) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.022741 / 0.037411 (-0.014670) | 0.075799 / 0.014526 (0.061273) | 0.089930 / 0.176557 (-0.086626) | 0.129093 / 0.737135 (-0.608042) | 0.089672 / 0.296338 (-0.206666) |

### 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) | 0.292789 / 0.215209 (0.077580) | 2.860137 / 2.077655 (0.782483) | 1.566678 / 1.504120 (0.062558) | 1.437756 / 1.541195 (-0.103439) | 1.472347 / 1.468490 (0.003857) | 0.566814 / 4.584777 (-4.017963) | 0.963918 / 3.745712 (-2.781794) | 2.717199 / 5.269862 (-2.552663) | 1.763612 / 4.565676 (-2.802064) | 0.063601 / 0.424275 (-0.360674) | 0.005308 / 0.007607 (-0.002299) | 0.363111 / 0.226044 (0.137066) | 3.458222 / 2.268929 (1.189293) | 1.939185 / 55.444624 (-53.505440) | 1.659552 / 6.876477 (-5.216925) | 1.801006 / 2.142072 (-0.341067) | 0.648884 / 4.805227 (-4.156343) | 0.116259 / 6.500664 (-6.384405) | 0.041384 / 0.075469 (-0.034085) |

### 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) | 1.001594 / 1.841788 (-0.840194) | 12.371125 / 8.074308 (4.296817) | 10.489763 / 10.191392 (0.298371) | 0.132500 / 0.680424 (-0.547924) | 0.014742 / 0.534201 (-0.519459) | 0.282258 / 0.579283 (-0.297026) | 0.122755 / 0.434364 (-0.311608) | 0.346068 / 0.540337 (-0.194269) | 0.424943 / 1.386936 (-0.961994) |

</details>
</details>

![](https://cml.dev/watermark.png#df445c20346a34c08e7e039e4ec1a302eef3a69c "CML watermark")