[jira] [Updated] (ARROW-11024) Writing List to parquet sometimes writes wrong data

["George Deamont (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/ARROW-11024?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

George Deamont updated ARROW-11024:
-----------------------------------
    Description: 
 Sometimes when writing tables that contain List<Struct> columns, the data is written incorrectly. Here is a code sample that produces the error. There are no exceptions raised here, but a simple equality check via equals() yields False for the second test case... 
{code:java}
import pyarrow as pa
import pyarrow.parquet as pq

# Input records look like this...
# [
#     [{'x':'abc','y':'abc'}],
#     [{'x':'abc','y':'abc'}],
#     [{'x':'abc','y':'abc'}],
#     ...
#     [{'x':'abc','y':'gcb'}],
#     [{'x':'abc','y':'gcb'}],
#     [{'x':'abc','y':'gcb'}],
# ]

# Write small amount of data to parquet file, and read it back. In this case, both tables are equal.
data1 = [[{'x':'abc','y':'abc'}]]*100 + [[{'x':'abc','y':'gcb'}]]*100
array1 = pa.array(data1)
table1 = pa.table([array1],names=['column'])
pq.write_table(table1,'temp1.parquet')
table1_1 = pq.read_table('temp1.parquet')
print(table1_1.equals(table1))

# Write larger amount of data to parquet file, and read it back. In this case, the tables are not equal.
data2 = data1*100
array2 = pa.array(data2)
table2 = pa.table([array2],names=['column'])
pq.write_table(table2,'temp2.parquet')
table2_1 = pq.read_table('temp2.parquet')
print(table2_1.equals(table2))

{code}
 

 

  was:
 

Sometimes when writing tables that contain List<Struct> columns, the data is written incorrectly. Here is a code sample that produces the error. There are no exceptions raised here, but a simple equality check via equals() yields False for the second test case...

 
{code:java}
import pyarrow as pa
import pyarrow.parquet as pq

# Input records look like this...
# [
#     [{'x':'abc','y':'abc'}],
#     [{'x':'abc','y':'abc'}],
#     [{'x':'abc','y':'abc'}],
#     ...
#     [{'x':'abc','y':'gcb'}],
#     [{'x':'abc','y':'gcb'}],
#     [{'x':'abc','y':'gcb'}],
# ]

# Write small amount of data to parquet file, and read it back. In this case, both tables are equal.
data1 = [[{'x':'abc','y':'abc'}]]*100 + [[{'x':'abc','y':'gcb'}]]*100
array1 = pa.array(data1)
table1 = pa.table([array1],names=['column'])
pq.write_table(table1,'temp1.parquet')
table1_1 = pq.read_table('temp1.parquet')
print(table1_1.equals(table1))

# Write larger amount of data to parquet file, and read it back. In this case, the tables are not equal.
data2 = data1*100
array2 = pa.array(data2)
table2 = pa.table([array2],names=['column'])
pq.write_table(table2,'temp2.parquet')
table2_1 = pq.read_table('temp2.parquet')
print(table2_1.equals(table2))

{code}
 

 


> Writing List<Struct> to parquet sometimes writes wrong data
> -----------------------------------------------------------
>
>                 Key: ARROW-11024
>                 URL: https://issues.apache.org/jira/browse/ARROW-11024
>             Project: Apache Arrow
>          Issue Type: Bug
>          Components: Python
>    Affects Versions: 2.0.0
>         Environment: macOS Catalina, Python 3.7.3, Pyarrow 2.0.0
>            Reporter: George Deamont
>            Priority: Major
>
>  Sometimes when writing tables that contain List<Struct> columns, the data is written incorrectly. Here is a code sample that produces the error. There are no exceptions raised here, but a simple equality check via equals() yields False for the second test case... 
> {code:java}
> import pyarrow as pa
> import pyarrow.parquet as pq
> # Input records look like this...
> # [
> #     [{'x':'abc','y':'abc'}],
> #     [{'x':'abc','y':'abc'}],
> #     [{'x':'abc','y':'abc'}],
> #     ...
> #     [{'x':'abc','y':'gcb'}],
> #     [{'x':'abc','y':'gcb'}],
> #     [{'x':'abc','y':'gcb'}],
> # ]
> # Write small amount of data to parquet file, and read it back. In this case, both tables are equal.
> data1 = [[{'x':'abc','y':'abc'}]]*100 + [[{'x':'abc','y':'gcb'}]]*100
> array1 = pa.array(data1)
> table1 = pa.table([array1],names=['column'])
> pq.write_table(table1,'temp1.parquet')
> table1_1 = pq.read_table('temp1.parquet')
> print(table1_1.equals(table1))
> # Write larger amount of data to parquet file, and read it back. In this case, the tables are not equal.
> data2 = data1*100
> array2 = pa.array(data2)
> table2 = pa.table([array2],names=['column'])
> pq.write_table(table2,'temp2.parquet')
> table2_1 = pq.read_table('temp2.parquet')
> print(table2_1.equals(table2))
> {code}
>  
>  



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