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quinnj avatar quinnj commented on July 18, 2024 1

On current master, I can read the yellow_tripdata file in about 14s. By comparison, TextParse.jl takes about 20s, while pandas takes around 40s.

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quinnj avatar quinnj commented on July 18, 2024

Is there a way you can share the dataset? Even if just privately? Happy to try and take a look profiling on my side and try to post what seems to help.

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udion avatar udion commented on July 18, 2024

https://s3.amazonaws.com/nyc-tlc/trip+data/yellow_tripdata_2015-01.csv

Try this one, I am also currently working on this one, although this is just one months data, there are 11 more such files and that only comprises the data for 2015. But try this one first.

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quinnj avatar quinnj commented on July 18, 2024

I can shave 20% off the read time by doing @time df = CSV.read("issue51.csv"; types=Dict(2=>WeakRefString{UInt8}, 3=>WeakRefString{UInt8})), i.e. specifying the 2nd and 3rd columns should be strings instead of DateTime. This should be fixed in 0.6, however, since DateTime parsing has gotten much faster. I'm trying to get CSV working on 0.6 at the moment, or I would check right now.

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