这是我的密码: def transform_pages(company, **context): ds = context.get("execution_date").strftime('%Y-%m-%d') s3 = S3Hook('aws_default') s3_conn = s3.get_conn() keys = s3.list_keys(bucket_name=Variable.get('s3_bucket'), prefix=f'S/{company}/pages/date={ds}/', delimiter=...
sparkContext.textFile()method is used to read a text file from S3 (use this method you can also read from several data sources) and any Hadoop supported file system, this method takes the path as an argument and optionally takes a number of partitions as the second argument. println("##...
obj = s3.Object(s3_bucket_name,file) data=obj.get()['Body'].read()return{'message':"Success!"} 一旦代码尝试执行obj. get()['Body'].read()我就会收到以下错误: Response {"errorMessage":"","errorType":"MemoryError","stackTrace": [" File \"/var/task/lambda_function.py\", line 27...
python pandas amazon-s3 boto3 问题:我在尝试使用pd.read_csv()读取S3位置的CSV文件时遇到编码错误。 下面是我的代码: # parameters s3_bucket = 'my_bucket' s3_key = 'my_key' # create s3 client s3_client = boto3.client('s3') # create s3 object obj = s3_client.get_object(Bucket=s3_buc...
client.upload_fileobj(temp_file,"bucket-name", Key="static/%s"% img_obj.filename)#利用这个接口把文件上传到服务器后一直都是0比特 蛋疼。。。 查询资料发现原因。 我们先来看下 shutil.copyfileobj 的源码: defcopyfileobj(fsrc, fdst, length=16*1024):"""copy data from file-like object fsrc ...
Apache Spark will assume this role to create an Iceberg table, add records to it and read from it. To enable this functionality, grant full table access to spark_role and provide data location permission to the S3 bucket where the table data can be stored. G...
然后,问题来了。 利用下面的 S3 upload_fileobj接口把文件上传到 S3后,对应的文件一直都是 0 比特。 代码如下: 代码语言:python 代码运行次数:0 运行 AI代码解释 fromshutilimportcopyfileobj temp_file=BytesIO()copyfileobj(img_obj.stream,temp_file)client.upload_fileobj(temp_file,"bucket-name",Key="...
fromshutilimportcopyfileobj temp_file = BytesIO() copyfileobj(img_obj.stream, temp_file) temp_file.seek(0)# 让游标回到0处client.upload_fileobj(temp_file,"bucket-name", Key="static/%s"% img_obj.filename) 或者直接把利用 FileStorage 的 stream 属性把文件上传到 S3,代码如下: ...
pq.ParquetFile("bucket_path", filesystem=self.s3_file_system).iter_batches(batch_size), which indeed loads data in batches into memory. Member mapleFU commented Aug 14, 2023 Hmmm as for behavior, parquet will usally load S3 in the granularity of parquet column chunkes, but iter_batches...
get_object(Bucket=bucket, Key=key) content = response['Body'] async with aiohttp.ClientSession() as session: async with session.post('http://downstream', data=content) as resp: # process response Sometimes the client just stops working and hangs until the app is restarted. The problem is...