Learned Indexes for a Google-scale Disk-based Database · HackerPapers discussions

Learned Indexes for a Google-scale Disk-based Database — mentioned by kevindamm

Wed, 25 Jun 2025 17:07:51 GMT

In theory, you can treat the objects as i.i.d. giving them a uniform prior. In practice, of course only the inputs are inputs and if you were to take that into account then you could avoid collisions, but as you say, you can't really know that ahead of time. Unless you can, such as when there is structure to the inputs or some other source of non-uniformity that you can account for. The topic of learned indexes is worth investigating if you're interested: https://arxiv.org/abs/1712.01208 https://arxiv.org/abs/2012.12501

Paper and discussion history. A mention is not an endorsement.

Learned Indexes for a Google-scale Disk-based Database — HN submission

Wed, 09 Oct 2024 10:17:44 GMT

Learned Indexes for a Google-Scale Disk-Based Database

1 point; 0 discussion replies on HN. Paper and source history. A submission is not an endorsement.

Learned Indexes for a Google-scale Disk-based Database — mentioned by robertsdionne

Fri, 22 Jul 2022 14:10:45 GMT

Also, Learned Indexes Structures: The Case for Learned Index Structures: https://arxiv.org/abs/1712.01208 Learned Indexes for a Google-scale Disk-based Database: https://arxiv.org/abs/2012.12501 And Noms/Dolt Prolly Trees: How to Chunk Your Database into a Merkle Tree: https://dolthub.com/blog/2022-06-27-prolly-chunker/

Paper and discussion history. A mention is not an endorsement.

Learned Indexes for a Google-scale Disk-based Database — mentioned by bmc7505

Wed, 16 Feb 2022 08:23:16 GMT

> It seems wildly impracticable to productionize at the moment (excepting Google, perhaps). There were a couple related papers [1, 2] from Google on learning to index a few years ago. In fact, I'm a little surprised they weren't cited. [1]: https://dl.acm.org/doi/pdf/10.1145/3183713.3196909 [2]: https://arxiv.org/pdf/2012.12501.pdf

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Learned Indexes for a Google-scale Disk-based Database — mentioned by Traudl

Wed, 27 Jan 2021 12:48:02 GMT

It looks like it found its way into Google Bigtable though: https://arxiv.org/abs/2012.12501

Paper and discussion history. A mention is not an endorsement.