# How to get remote data in newline terminating chunks?

**URL:** <https://discourse.julialang.org/t/how-to-get-remote-data-in-newline-terminating-chunks/115717>\
**Category:** Web Stack\
**Created:** [June 16, 2024, 3:36pm UTC](https://discourse.julialang.org/t/how-to-get-remote-data-in-newline-terminating-chunks/115717 "2024-06-16T15:36:29Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![sylvaticus](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/sylvaticus/32/203883_2.png) [@sylvaticus](https://discourse.julialang.org/u/sylvaticus)\
**Post date:** [June 16, 2024, 3:36pm UTC](https://discourse.julialang.org/t/how-to-get-remote-data-in-newline-terminating-chunks/115717/1 "2024-06-16T15:36:29Z")

</div>

I thought that this would end up in several some buffer-size chunks, but actually the 9GB file seems to be downloaded at once:

```julia
data_url = "https://zenodo.org/records/11549846/files/U2018_CLC2018_V2020_20u1.gpkg?download=1"
chunk_counter = 1
HTTP.open("GET", data_url) do io # Note the SSL support
    while !eof(io)
        global chunk_counter
        println(chunk_counter)
        data = String(read(io))
        chunk_counter += 1
    end
end

```

In this case it’s a binary data, but is there a way to stream a remote resource in chunks that are guaranteed to ends with a newline, so that I can process them with some online algorithm (i.e. train a ML model that supports multiple fitting ) ?