Issue: Select columns of Dataset or DatasetDict
State: closed
Author: daskol

Close #5474 and #5468.

Comments:
_The documentation is not available anymore as the PR was closed or merged._

<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) | 0.009963 / 0.011353 (-0.001390) | 0.005512 / 0.011008 (-0.005496) | 0.100495 / 0.038508 (0.061987) | 0.039929 / 0.023109 (0.016820) | 0.299749 / 0.275898 (0.023850) | 0.372330 / 0.323480 (0.048850) | 0.008689 / 0.007986 (0.000703) | 0.004334 / 0.004328 (0.000006) | 0.076469 / 0.004250 (0.072218) | 0.048091 / 0.037052 (0.011039) | 0.303884 / 0.258489 (0.045395) | 0.352747 / 0.293841 (0.058906) | 0.038941 / 0.128546 (-0.089605) | 0.012541 / 0.075646 (-0.063105) | 0.334227 / 0.419271 (-0.085044) | 0.048802 / 0.043533 (0.005269) | 0.295800 / 0.255139 (0.040661) | 0.316222 / 0.283200 (0.033022) | 0.108246 / 0.141683 (-0.033437) | 1.452735 / 1.452155 (0.000580) | 1.466293 / 1.492716 (-0.026423) |

### 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) | 0.010497 / 0.018006 (-0.007510) | 0.507427 / 0.000490 (0.506937) | 0.003054 / 0.000200 (0.002854) | 0.000084 / 0.000054 (0.000030) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.029529 / 0.037411 (-0.007883) | 0.114151 / 0.014526 (0.099625) | 0.120599 / 0.176557 (-0.055957) | 0.161881 / 0.737135 (-0.575255) | 0.127669 / 0.296338 (-0.168669) |

### 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) | 0.399631 / 0.215209 (0.184421) | 3.992997 / 2.077655 (1.915343) | 1.803770 / 1.504120 (0.299650) | 1.612301 / 1.541195 (0.071106) | 1.717846 / 1.468490 (0.249356) | 0.706753 / 4.584777 (-3.878024) | 3.798224 / 3.745712 (0.052512) | 2.169733 / 5.269862 (-3.100128) | 1.358264 / 4.565676 (-3.207413) | 0.086828 / 0.424275 (-0.337447) | 0.012606 / 0.007607 (0.004999) | 0.512085 / 0.226044 (0.286041) | 5.101491 / 2.268929 (2.832563) | 2.285688 / 55.444624 (-53.158936) | 1.955160 / 6.876477 (-4.921317) | 2.045887 / 2.142072 (-0.096186) | 0.878836 / 4.805227 (-3.926392) | 0.166483 / 6.500664 (-6.334181) | 0.062656 / 0.075469 (-0.012814) |

### 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) | 1.215152 / 1.841788 (-0.626636) | 15.436187 / 8.074308 (7.361879) | 14.489951 / 10.191392 (4.298559) | 0.199019 / 0.680424 (-0.481404) | 0.029148 / 0.534201 (-0.505053) | 0.440309 / 0.579283 (-0.138974) | 0.452041 / 0.434364 (0.017677) | 0.527102 / 0.540337 (-0.013236) | 0.634302 / 1.386936 (-0.752634) |

</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) | 0.007814 / 0.011353 (-0.003539) | 0.005582 / 0.011008 (-0.005427) | 0.075466 / 0.038508 (0.036958) | 0.034421 / 0.023109 (0.011312) | 0.342345 / 0.275898 (0.066447) | 0.389943 / 0.323480 (0.066463) | 0.006346 / 0.007986 (-0.001639) | 0.004442 / 0.004328 (0.000113) | 0.074440 / 0.004250 (0.070190) | 0.056383 / 0.037052 (0.019331) | 0.340293 / 0.258489 (0.081804) | 0.394416 / 0.293841 (0.100575) | 0.037217 / 0.128546 (-0.091330) | 0.012597 / 0.075646 (-0.063050) | 0.087005 / 0.419271 (-0.332267) | 0.051626 / 0.043533 (0.008094) | 0.336690 / 0.255139 (0.081551) | 0.369143 / 0.283200 (0.085943) | 0.110764 / 0.141683 (-0.030919) | 1.459003 / 1.452155 (0.006849) | 1.557333 / 1.492716 (0.064617) |

### 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) | 0.319596 / 0.018006 (0.301590) | 0.514697 / 0.000490 (0.514207) | 0.005286 / 0.000200 (0.005086) | 0.000086 / 0.000054 (0.000032) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.032579 / 0.037411 (-0.004832) | 0.111094 / 0.014526 (0.096568) | 0.127827 / 0.176557 (-0.048730) | 0.169967 / 0.737135 (-0.567168) | 0.133149 / 0.296338 (-0.163189) |

### 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) | 0.424637 / 0.215209 (0.209428) | 4.217889 / 2.077655 (2.140235) | 2.044844 / 1.504120 (0.540724) | 1.863513 / 1.541195 (0.322319) | 1.975674 / 1.468490 (0.507184) | 0.695493 / 4.584777 (-3.889284) | 3.815562 / 3.745712 (0.069850) | 3.534427 / 5.269862 (-1.735435) | 1.684874 / 4.565676 (-2.880802) | 0.085560 / 0.424275 (-0.338715) | 0.012439 / 0.007607 (0.004832) | 0.541231 / 0.226044 (0.315187) | 5.287166 / 2.268929 (3.018237) | 2.596622 / 55.444624 (-52.848002) | 2.315913 / 6.876477 (-4.560564) | 2.418454 / 2.142072 (0.276381) | 0.838947 / 4.805227 (-3.966281) | 0.168149 / 6.500664 (-6.332515) | 0.066439 / 0.075469 (-0.009030) |

### 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) | 1.264814 / 1.841788 (-0.576974) | 15.861324 / 8.074308 (7.787016) | 14.352515 / 10.191392 (4.161123) | 0.167032 / 0.680424 (-0.513391) | 0.017766 / 0.534201 (-0.516435) | 0.421821 / 0.579283 (-0.157462) | 0.426657 / 0.434364 (-0.007707) | 0.526742 / 0.540337 (-0.013595) | 0.623851 / 1.386936 (-0.763085) |

</details>
</details>

![](https://cml.dev/watermark.png#69b19755e9e37b746ef56780a62d21ef20c574d5 "CML watermark")