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https://issues.apache.org/jira/browse/ARROW-6060?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16895387#comment-16895387
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Kun Liu commented on ARROW-6060:
--------------------------------
[~wesmckinn] I used the following code to generate a sample parquet.
{code:java}
import pandas as pd
from pandas.util.testing import rands
def generate_strings(length, nunique, string_length=10):
unique_values = [rands(string_length) for i in range(nunique)]
values = unique_values * (length // nunique)
return values
df = pd.DataFrame()
df['a'] = generate_strings(100000000, 10000)
df['b'] = generate_strings(100000000, 10000)
df.to_parquet('/tmp/test.parquet')
{code}
And run following
import pyarrow.parquet as pq
pq.read_table('/tmp/test.parquet') # crash
pq.read_table('/tmp/test.parquet', use_threads=False) # works
Btw, my machine has 16GB RAM.
> [Python] too large memory cost using pyarrow.parquet.read_table with
> use_threads=True
> -------------------------------------------------------------------------------------
>
> Key: ARROW-6060
> URL: https://issues.apache.org/jira/browse/ARROW-6060
> Project: Apache Arrow
> Issue Type: Bug
> Components: Python
> Affects Versions: 0.14.1
> Reporter: Kun Liu
> Priority: Major
>
> I tried to load a parquet file of about 1.8Gb using the following code. It
> crashed due to out of memory issue.
> {code:java}
> import pyarrow.parquet as pq
> pq.read_table('/tmp/test.parquet'){code}
> However, it worked well with use_threads=True as follows
> {code:java}
> pq.read_table('/tmp/test.parquet', use_threads=False){code}
> If pyarrow is downgraded to 0.12.1, there is no such problem.
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