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Vortex: An extensible, state of the art columnar file format
- nahnahno 11mo agohow does this compare to Arrow IPC / Feather v2?
- rubenvanwyk 11mo agoI've never understood why people say Feather file format isn't meant for "long-term" storage and prefer Parquet for that. Access is much faster from Feather, compression better with Parquet but Feather is really good.
- sheepscreek 11mo agoHonestly I think Arrow makes Feather redundant. To answer your question, Parquet is optimized for storage on disk - can store with compression to take leas space, and might include clever tricks or some form of indices to query data from the file. Feather on the other hand is optimized for loading onto memory. It uses the same representation on disk as it does in memory. Very little in the way of compression (if any). No optimized for disk at all. BUT you can memory map a Feather file and randomly access any part of it in O(1) time (I believe, but do your own due diligence :)
- ozgrakkurt 11mo agoIt is wildly more complex
- deleted 11mo ago[deleted]
- sys13 11mo agoHow does this compare with delta lake and iceberg?
- oa335 11mo agoVortex is a file format, where as delta lake and iceberg are table formats. it should be compared to Parquet rather than delta lake and iceberg. This guest lecture by a maintainer of Vortex provides a good overview of the file format, motivations for its creation and its key features. https://www.youtube.com/watch?v=zyn_T5uragA https://www.youtube.com/watch?v=zyn_T5uragA
- sys13 11mo agoI think it would still make sense to compare with those table formats, or is the idea that you would only use this if you could not use a table format?
- bz_bz_bz 11mo agoThat’s like comparing words with characters. Vortex is, roughly, how you save data to files and Iceberg is the database-like manager of those files. You’ll soon be able to run Iceberg using Vortex because they are complementary, not competing, technologies.
- ks2048 11mo agoThe website could use a comparison / motivation in comparison to Parquet (beyond just stating it's 100x better).
- 3eb7988a1663 11mo agoAgreed, really need a tl;dr here, because Parquet is boring technology. Going to require quite the sales pitch to move. At minimum, I assume it will be years before I could expect native integration in pandas/polars/etc which would make it low effort enough to consider. Parquet is ..fine, I guess. It is good enough. Why invoke churn? Sell me on the vision.
- frisbm 11mo agoDuckDB just added support for vortex in their last release using the Vortex Python package so hopefully other tools wont be too far behind
- kipukun 11mo agoThe cuDF interop in the roadmap [1] will be huge for my workloads. XGBoost has the fastest inference time on GPUs, so a fast path straight from these Vortex files to GPU memory seems promising. [1] https://github.com/vortex-data/vortex/issues/2116 https://github.com/vortex-data/vortex/issues/2116
- reactordev 11mo agoCan you explain how it’s faster? GPU memory is just a blob with an address. Is it because the loading algorithms for vortex align better with XGBoost or just plain uploading to the GPU?
- robert3005 11mo agoWhat you can do if you have gpu friendly format is you send compressed data over PCI-E and then decompress on the gpu. Thus your overall throughput will increase since PCI-E bandwidth is the limiting factor of the overall system.
- reactordev 11mo agoThat doesn’t explain how vortex is faster. Yes, you should send compressed data to the GPU and let it uncompress. You should maximize your PCI-E throughput to minimize latency in execution, but what does Vortex bring? Other than Parque bad, Vortex good.
- kipukun 11mo agoXGBoost is just faster on the GPU, regardless of the file format. A sibling post also pointed out compression helping out on bandwidth.
- xigoi 11mo agoCan we stop with the cringe emojis at the start of every heading?
- mrbluecoat 11mo agoI guess not surprising from a project that combines Polars & Vortex
- kh_hk 11mo agoI tend to agree, but I don't see this one as any of the worst offenders, unless I am missing something. This readme has what, max two or three emojis? Compare that to most LLM generated readmes with a zillion of emojis for every single feature.
- rubenvanwyk 11mo agoVortex and Lance both seem really cool but will have to infiltrate either the Delta or Iceberg specs to become mainstream.
- robert3005 11mo agoCan’t wait for https://github.com/apache/iceberg/issues/12225 https://github.com/apache/iceberg/issues/12225 to merge so there’s an api to integrate against
- meehai 11mo agoCan you append new columns to a file stored on disk without reading it all in mempey? Somehoe this is beyond parquet capabilities.
- robert3005 11mo agoThe default writer will decompress the values, however, right now you can implement your own write strategy that will avoid doing it. We plan on adding that as an option since it’s quite common.
- deleted 11mo ago[deleted]
- andyferris 11mo agoOne thing I found interesting is the logical type system doesn't seem to include sum types or unions, unlike Arrow etc. I'd generally encourage new type systems to include sum types as a first-class concept.
- infogulch 11mo agoI wonder if a columnar storage format should implement sum types with a struct of arrays where only one array has a nun-null value for each index.
- ozgrakkurt 11mo agoArrow has two variants of it and this is one of them. Other variant has a seperate offsets array that you use to index into the active “field” array, so it is slower to process in most cases but is more compact