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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