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Posted to issues@arrow.apache.org by "Simon (Jira)" <ji...@apache.org> on 2021/06/25 16:54:00 UTC

[jira] [Created] (ARROW-13187) Possibly memory not deallocated when reading in CSV

Simon created ARROW-13187:
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             Summary: Possibly memory not deallocated when reading in CSV
                 Key: ARROW-13187
                 URL: https://issues.apache.org/jira/browse/ARROW-13187
             Project: Apache Arrow
          Issue Type: Bug
          Components: Python
    Affects Versions: 4.0.1
            Reporter: Simon


When one reads in a table from CSV in pyarrow version 4.0.1, it appears that the read-in table variable is not freed (or not fast enough). I'm unsure if this is because of pyarrow or because of the way pyarrow memory allocation interacts with Python memory allocation. I encountered it when processing many large CSVs sequentially.

When I run the following piece of code, the RAM memory usage increases quite rapidly until it runs out of memory.

{code:python}
import pyarrow as pa
import pyarrow.csv

# Generate some CSV file to read in
print("Generating CSV")
with open("example.csv", "w+") as f_out:
    for i in range(0, 10000000):
        f_out.write("123456789,abc def ghi jkl\n")


def read_in_the_csv():
    table = pa.csv.read_csv("example.csv")
    print(table)  # Not strictly necessary to replicate bug, table can also be an unused variable
    # This will free up the memory, as a workaround:
    # table = table.slice(0, 0)


# Read in the
print("Reading in a CSV many times")
for j in range(100000):
    read_in_the_csv()
{code}




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