How do I debug OverflowError: value too large to convert to int32_t?

Question

我正在尝试做什么

我正在使用 PyArrow 读取一些 CSV 并将它们转换为 Parquet。我阅读的一些文件有很多列并且占用大量内存（足以使机器崩溃运行作业）所以我正在分块阅读文件。

这是我用来生成箭头表的函数的样子（为简洁起见，片段）：

import pyarrow as pa
import pyarrow.parquet as pq
from pyarrow import csv as arrow_csv

def generate_arrow_tables(
        input_buffer: pa.lib.Buffer,
        arrow_schema: pa.Schema,
        batch_size: int
) -> Generator[pa.Table, None, None]:
    """
    Generates an Arrow Table from given data.
    :param batch_size: Size of batch streamed from CSV at a time
    :param input_buffer: Takes in an Arrow BufferOutputStream
    :param arrow_schema: Takes in an Arrow Schema
    :return: Returns an Arrow Table
    """

    # Preparing convert options
    co = arrow_csv.ConvertOptions(column_types=arrow_schema, strings_can_be_null=True)

    # Preparing read options
    ro = arrow_csv.ReadOptions(block_size=batch_size)
    # Streaming contents of CSV into batches
    with arrow_csv.open_csv(input_buffer, convert_options=co, read_options=ro) as stream_reader:
        for chunk in stream_reader:
            if chunk is None:
                break

            # Emit batches from generator. Arrow schema is inferred unless explicitly specified
            yield pa.Table.from_batches(batches=[chunk], schema=arrow_schema)

这就是我如何使用该函数将批次写入 S3（为简洁起见的片段）：

GB = 1024 ** 3
# data.size here is the size of the buffer
arrow_tables: Generator[Table, None, None] = generate_arrow_tables(pg_data, arrow_schema, min(data.size, GB ** 10))
# Iterate through generated tables and write to S3
count = 0
for table in arrow_tables:
    count += 1  # Count based on batch size

    # Write keys to S3
    file_name = f'{ARGS.run_id}-{count}.parquet'
    write_to_s3(table, output_path=f"s3://{bucket}/{bucket_prefix}/{file_name}")

怎么回事

我收到以下错误OverflowError: value too large to convert to int32_t这是堆栈跟踪（为简洁起见的片段）：

[2021-08-04 11:26:45,479] {pod_launcher.py:156} INFO - b'    ro = arrow_csv.ReadOptions(block_size=batch_size)\n'
[2021-08-04 11:26:45,479] {pod_launcher.py:156} INFO - b'  File "pyarrow/_csv.pyx", line 87, in pyarrow._csv.ReadOptions.__init__\n'
[2021-08-04 11:26:45,479] {pod_launcher.py:156} INFO - b'  File "pyarrow/_csv.pyx", line 119, in pyarrow._csv.ReadOptions.block_size.__set__\n'
[2021-08-04 11:26:45,479] {pod_launcher.py:156} INFO - b'OverflowError: value too large to convert to int32_t\n'

我该如何调试这个问题 and/or 解决它？

如果需要，我很乐意提供更多信息

Answer 1

如果我理解正确，generate_arrow_tables 的第三个参数是 batch_size，您将其作为 block_size 传递给 CSV reader。我不确定 data.size 的值是多少，但你用 min(data.size, GB ** 10).

保护它

10GB 的 block_size 将不起作用。您收到的错误是块大小不适合带符号的 32 位整数（最大 ~2GB）。

除此限制外，我不确定使用比默认值 (1MB) 大得多的块大小是否是个好主意。我不期望您会看到很多性能优势，并且您最终会使用比您需要的更多的 RAM。

How do I debug OverflowError: value too large to convert to int32_t?

How do I debug OverflowError: value too large to convert to int32_t?

python

apache-arrow

pyarrow