Raise from disconnect error in xopen
_The documentation is not available anymore as the PR was closed or merged._ Could you review this small PR @albertvillanova ? :) <details>
<summary>Show benchmarks</summary>

PyArrow==6.0.0

<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) | 0.011200 / 0.011353 (-0.000153) | 0.006156 / 0.011008 (-0.004852) | 0.119072 / 0.038508 (0.080564) | 0.042616 / 0.023109 (0.019507) | 0.348329 / 0.275898 (0.072431) | 0.418550 / 0.323480 (0.095070) | 0.009302 / 0.007986 (0.001316) | 0.004596 / 0.004328 (0.000267) | 0.090111 / 0.004250 (0.085860) | 0.053341 / 0.037052 (0.016289) | 0.361234 / 0.258489 (0.102745) | 0.400427 / 0.293841 (0.106586) | 0.045601 / 0.128546 (-0.082945) | 0.013806 / 0.075646 (-0.061841) | 0.393178 / 0.419271 (-0.026094) | 0.056809 / 0.043533 (0.013276) | 0.344090 / 0.255139 (0.088951) | 0.370610 / 0.283200 (0.087410) | 0.125728 / 0.141683 (-0.015955) | 1.671931 / 1.452155 (0.219776) | 1.703143 / 1.492716 (0.210427) |

### 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) | 0.226534 / 0.018006 (0.208527) | 0.496487 / 0.000490 (0.495998) | 0.002235 / 0.000200 (0.002035) | 0.000094 / 0.000054 (0.000039) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.031298 / 0.037411 (-0.006113) | 0.137740 / 0.014526 (0.123214) | 0.153497 / 0.176557 (-0.023059) | 0.204201 / 0.737135 (-0.532934) | 0.162324 / 0.296338 (-0.134014) |

### 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) | 0.475922 / 0.215209 (0.260712) | 4.682344 / 2.077655 (2.604689) | 2.107387 / 1.504120 (0.603267) | 1.884792 / 1.541195 (0.343597) | 2.003180 / 1.468490 (0.534690) | 0.810212 / 4.584777 (-3.774564) | 4.631047 / 3.745712 (0.885334) | 4.467606 / 5.269862 (-0.802256) | 2.334196 / 4.565676 (-2.231480) | 0.099713 / 0.424275 (-0.324562) | 0.014732 / 0.007607 (0.007125) | 0.604587 / 0.226044 (0.378543) | 5.951679 / 2.268929 (3.682751) | 2.704761 / 55.444624 (-52.739863) | 2.280695 / 6.876477 (-4.595781) | 2.279489 / 2.142072 (0.137417) | 0.962474 / 4.805227 (-3.842753) | 0.195279 / 6.500664 (-6.305385) | 0.071503 / 0.075469 (-0.003966) |

### 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) | 1.558037 / 1.841788 (-0.283751) | 17.722140 / 8.074308 (9.647832) | 16.229016 / 10.191392 (6.037624) | 0.177148 / 0.680424 (-0.503276) | 0.034162 / 0.534201 (-0.500039) | 0.513945 / 0.579283 (-0.065338) | 0.533542 / 0.434364 (0.099178) | 0.672457 / 0.540337 (0.132119) | 0.762390 / 1.386936 (-0.624546) |

</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) | 0.009739 / 0.011353 (-0.001613) | 0.006095 / 0.011008 (-0.004914) | 0.105968 / 0.038508 (0.067460) | 0.046229 / 0.023109 (0.023120) | 0.449156 / 0.275898 (0.173258) | 0.462182 / 0.323480 (0.138702) | 0.006981 / 0.007986 (-0.001004) | 0.004867 / 0.004328 (0.000539) | 0.082142 / 0.004250 (0.077891) | 0.058652 / 0.037052 (0.021600) | 0.454542 / 0.258489 (0.196052) | 0.494910 / 0.293841 (0.201069) | 0.047159 / 0.128546 (-0.081387) | 0.014677 / 0.075646 (-0.060969) | 0.370819 / 0.419271 (-0.048452) | 0.064603 / 0.043533 (0.021070) | 0.441514 / 0.255139 (0.186375) | 0.442802 / 0.283200 (0.159603) | 0.138603 / 0.141683 (-0.003080) | 1.692810 / 1.452155 (0.240655) | 1.894596 / 1.492716 (0.401880) |

### 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) | 0.281681 / 0.018006 (0.263675) | 0.532693 / 0.000490 (0.532203) | 0.005484 / 0.000200 (0.005284) | 0.000156 / 0.000054 (0.000102) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.032994 / 0.037411 (-0.004417) | 0.134614 / 0.014526 (0.120088) | 0.142286 / 0.176557 (-0.034270) | 0.187220 / 0.737135 (-0.549916) | 0.144897 / 0.296338 (-0.151441) |

### 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) | 0.519536 / 0.215209 (0.304327) | 5.214429 / 2.077655 (3.136775) | 2.612575 / 1.504120 (1.108455) | 2.369085 / 1.541195 (0.827891) | 2.503157 / 1.468490 (1.034667) | 0.834827 / 4.584777 (-3.749950) | 4.586789 / 3.745712 (0.841077) | 4.472605 / 5.269862 (-0.797257) | 2.314471 / 4.565676 (-2.251205) | 0.095817 / 0.424275 (-0.328458) | 0.014086 / 0.007607 (0.006478) | 0.605875 / 0.226044 (0.379831) | 6.153143 / 2.268929 (3.884214) | 3.187456 / 55.444624 (-52.257169) | 2.755377 / 6.876477 (-4.121100) | 2.777118 / 2.142072 (0.635046) | 0.967285 / 4.805227 (-3.837942) | 0.199202 / 6.500664 (-6.301462) | 0.075979 / 0.075469 (0.000510) |

### 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) | 1.481758 / 1.841788 (-0.360030) | 18.053769 / 8.074308 (9.979461) | 15.558780 / 10.191392 (5.367388) | 0.226135 / 0.680424 (-0.454288) | 0.021668 / 0.534201 (-0.512533) | 0.562618 / 0.579283 (-0.016666) | 0.518183 / 0.434364 (0.083819) | 0.628580 / 0.540337 (0.088243) | 0.740368 / 1.386936 (-0.646568) |

</details>
</details>

![](https://cml.dev/watermark.png#4e4d46eec24c36799c0efcc1b7231f597039c497 "CML watermark")

this way we can know the cause of the disconnect

related to https://github.com/huggingface/datasets/issues/5374