arrow-user mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From Wes McKinney <wesmck...@gmail.com>
Subject Re: Reading large csv file with pyarrow
Date Mon, 17 Feb 2020 12:46:49 GMT
I seem to recall discussions about 1 chunk-at-a-time reading of CSV
files. Such an API is not yet available in Python. This is also
required for the C++ Datasets API. If there are not one or more JIRA
issues about this I suggest that we open some to capture the use cases

On Fri, Feb 14, 2020 at 3:16 PM filippo medri <filippo.medri@gmail.com> wrote:
>
> Hi,
> by experimenting with arrow read_csv function to convert csv fie into parquet I found
that it reads the data in memory.
> On a side the ReadOptions class allows to specify a blocksize parameter to limit how
much bytes to process at a time, but by looking at the memory usage my understanding is that
the underlying Table is filled with all data.
> Is there a way to at least specify a parameter to limit the read to a batch of rows?
I see that I can skip rows from the beginning, but I am not finding a way to limit how many
rows to read.
> Which is the intended way to read a csv file that does not fit into memory?
> Thanks in advance,
> Filippo Medri

Mime
View raw message