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Uwe L. Korn commented on PARQUET-1361: -------------------------------------- What is the problem with the generated Parquet file? I don't understand where there is an issue. > [C++] 1.4.1 library allows creation of parquet file w/NULL values for INT > types > ------------------------------------------------------------------------------- > > Key: PARQUET-1361 > URL: https://issues.apache.org/jira/browse/PARQUET-1361 > Project: Parquet > Issue Type: Bug > Components: parquet-cpp > Affects Versions: cpp-1.4.0 > Reporter: Ken Terada > Priority: Major > Attachments: parquet-1361-repro-1.py, parquet-1361-repro-2.py, > sample_w_null.csv > > > The parquet-cpp v1.4.1 library allows generation of parquet files with NULL > values for INT type columns which causes unexpected parsing errors in > downstream systems ingesting those files. > e.g., > {{Error parsing the parquet file: UNKNOWN can not be applied to a primitive > type}} > *+Reproduction Steps+* > OS: CentOS 7.5.1804 > Python: 3.4.8 > +Prerequisites:+ > * Install the following packages: {{Numpy: 1.14.5}}, {{Pandas: 0.22.0}}, > {{PyArrow: 0.9.0}} > +Step 1+ > Generate the parquet file. > {{sample_w_null.csv}} > {code} > col1,col2,col3,col4,col5 > 1,2,,4,5 > {code} > {{parquet-1361-repro-1.py}} > {code} > #!/usr/bin/python > import numpy as np > import pyarrow as pa > import pyarrow.parquet as pq > import pandas as pd > input_file = 'sample_w_null.csv' > output_file = 'int_unknown.parquet' > p_schema = {'col1': np.int32, > 'col2': np.int32, > 'col3': np.unicode_, > 'col4': np.int32, > 'col5': np.int32} > df = pd.read_csv(input_file, dtype=p_schema) > table = pa.Table.from_pandas(df) > pq.write_table(table, output_file) > {code} > +Step 2+ > Inspect the metadata of the generated file. > {{parquet-1361-repro-2.py}} > {code} > #!/usr/bin/python > import pyarrow.parquet as pq > for filename in ['int_unknown.parquet']: > pq_file = pq.ParquetFile(filename) > print(pq_file.metadata) > print(pq_file.schema) > print(pq_file.num_row_groups) > print(pq.read_table(filename, > columns=['col1','col2','col3','col4','col5']).to_pandas()) > {code} > Results > {code} > <pyarrow._parquet.FileMetaData object at 0x7f53e8621100> > created_by: parquet-cpp version 1.4.1-SNAPSHOT > num_columns: 6 > num_rows: 1 > num_row_groups: 1 > format_version: 1.0 > serialized_size: 1434 > <pyarrow._parquet.ParquetSchema object at 0x7f53e85bd170> > col1: INT32 > col2: INT32 > col3: INT32 UNKNOWN > col4: INT32 > col5: INT32 > __index_level_0__: INT64 > 1 > col1 col2 col3 col4 col5 > 0 1 2 None 4 5 > {code} -- This message was sent by Atlassian JIRA (v7.6.3#76005)