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parquet vs csv (lemmy.ml)

submitted 2 months ago by [email protected] to c/[email protected]

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What's your take on parquet?

I'm still reading into it. Why is it closely related to apache? Does inly apache push it? Meaning, if apache drops it, there'd be no interest from others to push it further?

It's published under apache hadoop license. It is a permissive license. Is there a drawback to the license?

Do you use it? When?

I assume for sharing small data, csv is sufficient. Also, I assume csv is more accessible than parquet.

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[–] [email protected] 5 points 2 months ago (4 children)

In the deep learning community, I know of someone using parquet for the dataset and annotations. It allows you to select which data you want to retrieve from the dataset and stream only those, and nothing else. It is a rather effective method for that if you have many different annotations for different use cases and want to be able to select only the ones you need for your application.

[–] [email protected] 2 points 2 months ago (3 children)

How does this differ from graphQL?

[–] djnattyp 4 points 2 months ago (1 children)

Parquet is a storage format; graphQL is a query language/transmission strategy.

[–] [email protected] 1 points 2 months ago (1 children)

@djnattyp
exactly. and parquet is optimized for parallel processing, making it ideal for big data frameworks because data gets distributed to the nodes. no need for parquet as long as you can calculate on a local machine. and for the ones who are complaining about csv. most data that make it into a parquet file comes from... csv files 😊
@demesisx

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