batching 1: introduce DataCell & retire ComponentBundle

[teh-cmc]

First step of #1619: Introduce DataCell and retire ComponentBundle.

DataCell is the leaf type of our data model, a uniform array of components: [C, C, C, ...]. No more, no less.
Users should prefer using it over raw arrow arrays as it tends to make code a lot simpler (and faster).
Behind the scenes, a DataCell is backed by an erased arrow array living on the heap, which is likely to point into a larger batch of contiguous memory that it shares with its peers.

This PR merely introduces the DataCell type but doesn't quite use it everywhere: the store in particular still shuffles raw arrow arrays around for the most part (for now).

This is mostly grunt work (and a bunch of house cleaning I've wanted done for a while): aside from data_cell.rs there's no notable logic changes.

Nice surprise: we get roughly 5% to 25% performance improvement across all our benchmarks, which I assume is the result of DataCell eliminating a bunch of unneeded list wraps/unwraps all over the place.
Also discovered a major performance pitfall in TryIntoArrow.

Spawned a bunch of issues:

• Dataframe extension for Chunk #1692
• Should be able to build Components/DataCells from non-reference types #1693
• Component should be a single trait #1694
• A Component's DataType should embed its metadata #1696

---

Part of #1619

• Self-review
• No bench regression
• No test regression
• api_demo_rs looking good
• api_demo_py looking good
• TODO all the things that fit into Tracking issue: end-to-end batching #1619
• open issues for everything else

[teh-cmc]

Trouble ahead:

Benchmark suite	Current: 8512de9	Previous: 1802c20	Ratio
datastore/insert/batch/rects/insert	601675 ns/iter (± 2069)	558040 ns/iter (± 2726)	1.08
datastore/latest_at/batch/rects/query	1890 ns/iter (± 17)	1869 ns/iter (± 5)	1.01
datastore/latest_at/missing_components/primary	287 ns/iter (± 0)	287 ns/iter (± 0)	1
datastore/latest_at/missing_components/secondaries	440 ns/iter (± 0)	456 ns/iter (± 0)	0.96
datastore/range/batch/rects/query	154071 ns/iter (± 437)	153037 ns/iter (± 237)	1.01
mono_points_arrow/generate_message_bundles	31957497 ns/iter (± 801251)	52357104 ns/iter (± 640637)	0.61
mono_points_arrow/generate_messages	130995451 ns/iter (± 1129415)	136205204 ns/iter (± 1313776)	0.96
mono_points_arrow/encode_log_msg	152674306 ns/iter (± 1031782)	171213456 ns/iter (± 1741778)	0.89
mono_points_arrow/encode_total	319904451 ns/iter (± 7475615)	362883755 ns/iter (± 2060012)	0.88
mono_points_arrow/decode_log_msg	176332820 ns/iter (± 1853162)	189752854 ns/iter (± 4013520)	0.93
mono_points_arrow/decode_message_bundles	54788523 ns/iter (± 1009136)	75254710 ns/iter (± 1140876)	0.73
mono_points_arrow/decode_total	223955102 ns/iter (± 1700294)	259499357 ns/iter (± 2333802)	0.86
batch_points_arrow/generate_message_bundles	325961 ns/iter (± 4397)	341982 ns/iter (± 553)	0.95
batch_points_arrow/generate_messages	6767 ns/iter (± 106)	6228 ns/iter (± 13)	1.09
batch_points_arrow/encode_log_msg	348719 ns/iter (± 3366)	372885 ns/iter (± 1494)	0.94
batch_points_arrow/encode_total	705107 ns/iter (± 7630)	746449 ns/iter (± 4228)	0.94
batch_points_arrow/decode_log_msg	346301 ns/iter (± 1849)	354317 ns/iter (± 1692)	0.98
batch_points_arrow/decode_message_bundles	1560 ns/iter (± 18)	2018 ns/iter (± 8)	0.77
batch_points_arrow/decode_total	352278 ns/iter (± 2929)	360005 ns/iter (± 2070)	0.98
arrow_mono_points/insert	6291970452 ns/iter (± 18115496)	7101183936 ns/iter (± 48000479)	0.89
arrow_mono_points/query	1750297 ns/iter (± 16858)	1847772 ns/iter (± 25156)	0.95
arrow_batch_points/insert	2945631 ns/iter (± 30202)	2738045 ns/iter (± 81908)	1.08
arrow_batch_points/query	15935 ns/iter (± 220)	16152 ns/iter (± 40)	0.99
arrow_batch_vecs/insert	556514 ns/iter (± 7317)	43144 ns/iter (± 226)	12.90
arrow_batch_vecs/query	382755 ns/iter (± 4626)	389549 ns/iter (± 596)	0.98
tuid/Tuid::random	34 ns/iter (± 0)	34 ns/iter (± 0)	1

[teh-cmc]

Aaaand we're good:

Benchmark suite	Current: 14f23b3	Previous: 1802c20	Ratio
datastore/insert/batch/rects/insert	584558 ns/iter (± 1896)	558040 ns/iter (± 2726)	1.05
datastore/latest_at/batch/rects/query	1830 ns/iter (± 10)	1869 ns/iter (± 5)	0.98
datastore/latest_at/missing_components/primary	288 ns/iter (± 0)	287 ns/iter (± 0)	1.00
datastore/latest_at/missing_components/secondaries	443 ns/iter (± 0)	456 ns/iter (± 0)	0.97
datastore/range/batch/rects/query	152376 ns/iter (± 260)	153037 ns/iter (± 237)	1.00
mono_points_arrow/generate_message_bundles	33976334 ns/iter (± 1653914)	52357104 ns/iter (± 640637)	0.65
mono_points_arrow/generate_messages	130309746 ns/iter (± 1458602)	136205204 ns/iter (± 1313776)	0.96
mono_points_arrow/encode_log_msg	166831936 ns/iter (± 1648600)	171213456 ns/iter (± 1741778)	0.97
mono_points_arrow/encode_total	333659366 ns/iter (± 2495635)	362883755 ns/iter (± 2060012)	0.92
mono_points_arrow/decode_log_msg	187351664 ns/iter (± 1649335)	189752854 ns/iter (± 4013520)	0.99
mono_points_arrow/decode_message_bundles	60453431 ns/iter (± 1676753)	75254710 ns/iter (± 1140876)	0.80
mono_points_arrow/decode_total	244841469 ns/iter (± 2074305)	259499357 ns/iter (± 2333802)	0.94
batch_points_arrow/generate_message_bundles	332330 ns/iter (± 933)	341982 ns/iter (± 553)	0.97
batch_points_arrow/generate_messages	5990 ns/iter (± 9)	6228 ns/iter (± 13)	0.96
batch_points_arrow/encode_log_msg	355456 ns/iter (± 2223)	372885 ns/iter (± 1494)	0.95
batch_points_arrow/encode_total	709792 ns/iter (± 3717)	746449 ns/iter (± 4228)	0.95
batch_points_arrow/decode_log_msg	350449 ns/iter (± 1317)	354317 ns/iter (± 1692)	0.99
batch_points_arrow/decode_message_bundles	1581 ns/iter (± 6)	2018 ns/iter (± 8)	0.78
batch_points_arrow/decode_total	351941 ns/iter (± 764)	360005 ns/iter (± 2070)	0.98
arrow_mono_points/insert	7082926772 ns/iter (± 41336212)	7101183936 ns/iter (± 48000479)	1.00
arrow_mono_points/query	1729903 ns/iter (± 10483)	1847772 ns/iter (± 25156)	0.94
arrow_batch_points/insert	3137240 ns/iter (± 12800)	2738045 ns/iter (± 81908)	1.15
arrow_batch_points/query	16598 ns/iter (± 50)	16152 ns/iter (± 40)	1.03
arrow_batch_vecs/insert	45217 ns/iter (± 122)	43144 ns/iter (± 226)	1.05
arrow_batch_vecs/query	389215 ns/iter (± 34999)	389549 ns/iter (± 596)	1.00
tuid/Tuid::random	34 ns/iter (± 0)	34 ns/iter (± 0)	1

[emilk]

Beautiful!