AWS RDS 导出 parquet 格式表格时，会根据所选的文件大小进行自动分段，以确保数据的高效性和可伸缩性。

AWS SDK 提供了一个 python 示例代码，可以用来导出 parquet 格式的数据，并将其分段：

import sys
import boto3
from boto3.session import Session

session = Session(aws_access_key_id='YOUR_ACCESS_KEY', aws_secret_access_key='YOUR_SECRET_KEY')
s3 = session.resource('s3')
aws_bucket = 'YOUR_AWS_BUCKET_NAME'
aws_object_key = 'YOUR_AWS_OBJECT_KEY'
local_file = '/tmp/MY_LOCAL_FILE.parquet'

# Create an S3 resource
s3 = boto3.resource('s3')

# Get the bucket
bucket = s3.Bucket(aws_bucket)

# Download the object to local file
bucket.download_file(aws_object_key, local_file)

# Partition the data using pandas
import pandas as pd

# Read the parquet file
df = pd.read_parquet(local_file)

# Write the parquet partitions to S3
import awswrangler as wr

# Write the data partitioned to Parquet
wr.s3.to_parquet(
    df=df,
    dataset=True,
    database='mydatabase',
    table='mytable',
    path='s3://aws-bucket/mytable/',
    partition_cols=['year', 'month', 'day'],
    mode='overwrite',
    concurrent_partitioning=True
)

其中 concurrent_partitioning=True 选项表示并发分区。如果您的表格非常大，则会自动分段。