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Chris Ellison edited comment on ARROW-2242 at 3/1/18 8:10 PM: -------------------------------------------------------------- Related ticket is not code-related, but workflow-related in terms of reading/writing binary data was (Author: leftscreencorner): Not code-related, but workflow related in terms of reading/writing binary data. > [Python] ParquetFile.read does not accommodate large binary data > ----------------------------------------------------------------- > > Key: ARROW-2242 > URL: https://issues.apache.org/jira/browse/ARROW-2242 > Project: Apache Arrow > Issue Type: Bug > Components: Python > Affects Versions: 0.8.0 > Reporter: Chris Ellison > Priority: Major > Fix For: 0.9.0 > > > When reading a parquet file with binary data > 2 GiB, we get an ArrowIOError > due to it not creating chunked arrays. Reading each row group individually > and then concatenating the tables works, however. > > {code:java} > import pandas as pd > import pyarrow as pa > import pyarrow.parquet as pq > x = pa.array(list('1' * 2**30)) > demo = 'demo.parquet' > def scenario(): > t = pa.Table.from_arrays([x], ['x']) > writer = pq.ParquetWriter(demo, t.schema) > for i in range(2): > writer.write_table(t) > writer.close() > pf = pq.ParquetFile(demo) > # pyarrow.lib.ArrowIOError: Arrow error: Invalid: BinaryArray cannot > contain more than 2147483646 bytes, have 2147483647 > t2 = pf.read() > # Works, but note, there are 32 row groups, not 2 as suggested by: > # > https://arrow.apache.org/docs/python/parquet.html#finer-grained-reading-and-writing > tables = [pf.read_row_group(i) for i in range(pf.num_row_groups)] > t3 = pa.concat_tables(tables) > scenario() > {code} -- This message was sent by Atlassian JIRA (v7.6.3#76005)