Document that to_json defaults to JSON Lines
Opened by albertvillanova (closed)

Document that `Dataset.to_json` defaults to JSON Lines, by adding explanation in the corresponding docstring.

Fix #6894.

Comments:
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6895). 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) | 0.004914 / 0.011353 (-0.006439) | 0.003621 / 0.011008 (-0.007387) | 0.062841 / 0.038508 (0.024333) | 0.031630 / 0.023109 (0.008520) | 0.247666 / 0.275898 (-0.028232) | 0.288192 / 0.323480 (-0.035288) | 0.003145 / 0.007986 (-0.004841) | 0.002655 / 0.004328 (-0.001674) | 0.049484 / 0.004250 (0.045233) | 0.046593 / 0.037052 (0.009540) | 0.271550 / 0.258489 (0.013061) | 0.293228 / 0.293841 (-0.000613) | 0.026941 / 0.128546 (-0.101606) | 0.009936 / 0.075646 (-0.065710) | 0.201741 / 0.419271 (-0.217530) | 0.035435 / 0.043533 (-0.008098) | 0.251868 / 0.255139 (-0.003271) | 0.272082 / 0.283200 (-0.011118) | 0.019731 / 0.141683 (-0.121952) | 1.125752 / 1.452155 (-0.326403) | 1.152058 / 1.492716 (-0.340659) |

### 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) | 0.099695 / 0.018006 (0.081689) | 0.308306 / 0.000490 (0.307816) | 0.000223 / 0.000200 (0.000023) | 0.000044 / 0.000054 (-0.000010) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.018616 / 0.037411 (-0.018795) | 0.061886 / 0.014526 (0.047360) | 0.074059 / 0.176557 (-0.102498) | 0.124902 / 0.737135 (-0.612234) | 0.075108 / 0.296338 (-0.221230) |

### 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) | 0.336707 / 0.215209 (0.121498) | 2.805197 / 2.077655 (0.727542) | 1.565826 / 1.504120 (0.061706) | 1.443708 / 1.541195 (-0.097486) | 1.341167 / 1.468490 (-0.127323) | 0.566814 / 4.584777 (-4.017963) | 2.374536 / 3.745712 (-1.371176) | 2.804921 / 5.269862 (-2.464941) | 1.739848 / 4.565676 (-2.825829) | 0.062779 / 0.424275 (-0.361496) | 0.005341 / 0.007607 (-0.002266) | 0.326482 / 0.226044 (0.100438) | 3.273460 / 2.268929 (1.004531) | 1.803656 / 55.444624 (-53.640968) | 1.502518 / 6.876477 (-5.373958) | 1.523665 / 2.142072 (-0.618407) | 0.642443 / 4.805227 (-4.162784) | 0.117820 / 6.500664 (-6.382844) | 0.042540 / 0.075469 (-0.032929) |

### 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) | 0.963399 / 1.841788 (-0.878388) | 11.503648 / 8.074308 (3.429340) | 9.483957 / 10.191392 (-0.707435) | 0.129118 / 0.680424 (-0.551306) | 0.014136 / 0.534201 (-0.520065) | 0.286766 / 0.579283 (-0.292517) | 0.273328 / 0.434364 (-0.161036) | 0.324075 / 0.540337 (-0.216262) | 0.420408 / 1.386936 (-0.966528) |

</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) | 0.005099 / 0.011353 (-0.006254) | 0.003721 / 0.011008 (-0.007288) | 0.050614 / 0.038508 (0.012106) | 0.031882 / 0.023109 (0.008773) | 0.267619 / 0.275898 (-0.008279) | 0.291874 / 0.323480 (-0.031606) | 0.004254 / 0.007986 (-0.003731) | 0.002766 / 0.004328 (-0.001563) | 0.049291 / 0.004250 (0.045041) | 0.043302 / 0.037052 (0.006249) | 0.274891 / 0.258489 (0.016402) | 0.304977 / 0.293841 (0.011136) | 0.029088 / 0.128546 (-0.099459) | 0.010425 / 0.075646 (-0.065221) | 0.057781 / 0.419271 (-0.361491) | 0.033589 / 0.043533 (-0.009943) | 0.264293 / 0.255139 (0.009154) | 0.284861 / 0.283200 (0.001661) | 0.018025 / 0.141683 (-0.123658) | 1.124954 / 1.452155 (-0.327200) | 1.161957 / 1.492716 (-0.330759) |

### 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) | 0.103622 / 0.018006 (0.085615) | 0.310915 / 0.000490 (0.310425) | 0.000241 / 0.000200 (0.000041) | 0.000051 / 0.000054 (-0.000003) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.022550 / 0.037411 (-0.014862) | 0.076466 / 0.014526 (0.061940) | 0.088297 / 0.176557 (-0.088260) | 0.128659 / 0.737135 (-0.608477) | 0.091823 / 0.296338 (-0.204516) |

### 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) | 0.293431 / 0.215209 (0.078222) | 2.888105 / 2.077655 (0.810450) | 1.559581 / 1.504120 (0.055461) | 1.421424 / 1.541195 (-0.119771) | 1.437941 / 1.468490 (-0.030549) | 0.577544 / 4.584777 (-4.007233) | 0.968840 / 3.745712 (-2.776872) | 2.799796 / 5.269862 (-2.470066) | 1.744791 / 4.565676 (-2.820885) | 0.064159 / 0.424275 (-0.360116) | 0.005043 / 0.007607 (-0.002564) | 0.341039 / 0.226044 (0.114995) | 3.354402 / 2.268929 (1.085474) | 1.904093 / 55.444624 (-53.540532) | 1.604046 / 6.876477 (-5.272431) | 1.610384 / 2.142072 (-0.531688) | 0.658129 / 4.805227 (-4.147098) | 0.119297 / 6.500664 (-6.381367) | 0.041396 / 0.075469 (-0.034073) |

### 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) | 1.001109 / 1.841788 (-0.840678) | 12.081856 / 8.074308 (4.007548) | 10.090943 / 10.191392 (-0.100449) | 0.150433 / 0.680424 (-0.529991) | 0.015850 / 0.534201 (-0.518351) | 0.286590 / 0.579283 (-0.292693) | 0.131137 / 0.434364 (-0.303227) | 0.389033 / 0.540337 (-0.151304) | 0.421382 / 1.386936 (-0.965554) |

</details>
</details>

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