处理大文件时,AWS Lambda函数有内存和执行时间的限制,因此需要对大文件进行分片处理。以下是一个示例代码,用于将S3桶中的大文件分片上传到Google Drive:
import os
import io
import boto3
from google.oauth2 import service_account
from googleapiclient.discovery import build
def lambda_handler(event, context):
# 获取S3桶和文件名
s3_bucket = event['Records'][0]['s3']['bucket']['name']
s3_key = event['Records'][0]['s3']['object']['key']
# 获取Google Drive的凭证和服务
credentials = service_account.Credentials.from_service_account_file('credentials.json')
drive_service = build('drive', 'v3', credentials=credentials)
# 设置分片大小(5MB)
chunk_size = 5 * 1024 * 1024
# 获取S3对象
s3_client = boto3.client('s3')
s3_object = s3_client.get_object(Bucket=s3_bucket, Key=s3_key)
# 获取S3对象的内容长度
file_size = s3_object['ContentLength']
# 计算分片数
total_chunks = int(file_size / chunk_size) + 1
# 创建Google Drive文件
drive_file = drive_service.files().create(body={'name': s3_key}).execute()
drive_file_id = drive_file['id']
# 分片上传到Google Drive
for i in range(total_chunks):
# 读取分片数据
start_byte = i * chunk_size
end_byte = min((i + 1) * chunk_size, file_size)
file_part = s3_client.get_object(Bucket=s3_bucket, Key=s3_key, Range=f"bytes={start_byte}-{end_byte}")['Body'].read()
# 上传分片到Google Drive
media_body = io.BytesIO(file_part)
drive_service.files().update(fileId=drive_file_id, media_body=media_body).execute()
return 'File uploaded to Google Drive successfully!'
上述代码通过分片处理大文件,将每个分片上传到Google Drive。为了使用Google Drive服务,我们需要将凭证存储在credentials.json
文件中,并确保已经安装了必需的依赖包(例如google-auth
和google-api-python-client
)。
请注意,上述示例仅为参考,你可能需要根据实际情况进行修改和调整。