amazon-s3

问题 I am trying to access the file from amazon web service s3. But i am getting error of expired url. Does the expired url deletes the file? Or can it be access by regenerating new url? How can i regenerate the new url? 回答1: You can either Generate a new pre-signed URL. Access the file via an S3 API. If you can't do any of that, you can't access the file. 来源： https://stackoverflow.com/questions/24805094/how-to-access-the-file-from-amazon-s3-expired-url

问题 I have the following policy attached to the IAM user I am using. { "Version": "2012-10-17", "Statement": [ { "Sid": "Stmt1468642330000", "Effect": "Allow", "Action": [ "s3:*" ], "Resource": [ "arn:aws:s3:::elasticbeanstalk-ap-southeast-1-648213736065/documents/*" ] } ] } Problem is when I do something like: return readFile(file.path) .then(function(buffer) { var s3obj = s3.putObject({ Bucket: bucket, Key: `documents/${destFileName}`, Body: buffer }); return s3obj.promise(); }); I get:

问题 when creating Hive table against csv saved in S3, do I absolutely have to order fields in the order of comma separated values for rows in csv? the csv has the first row as header. I understand that csv is row based not columnar, but was wondering if there is a way to match the value of the header with the field name of the hive table and order columns differently. 回答1: Yes, columns in the table definition (DDL) should be in the same order as in the underlying csv files. You can skip header

问题 I am trying to copy data in a bucket in one account, in which I have access to an IAM but not admin, to a bucket in another account, in which I am an admin, and failing. I can't even ls the source bucket. I've followed the directions from AWS and various sources online to give myself list/read/get permissions on the source bucket, with no success. I can provide the details (e.g., the bucket policy json), but it is what is in the AWS docs and other places. What I've done works between two

问题 I have a very simple python function in a lambda which runs fine if I leave VPC disabled. import json import boto3 import botocore def lambda_handler(event, context): s3 = boto3.client('s3', 'us-east-1', config=botocore.config.Config(s3={'addressing_style':'path'})) keys = [] resp = s3.list_objects_v2(Bucket='[BUCKET_NAME]') for obj in resp['Contents']: print(obj['Key']) return { 'statusCode': 200, 'body': json.dumps('Hello from Lambda!') } When VPC is enabled the S3 connection continually

问题 I'm hoping someone can help me with an Amazon S3 Cross Region Replication query. I have two Amazon AWS accounts, each with a bucket in a different region. I want to replicate the data from one bucket to another and from what I understand this should be a simple process to create. However, I'm really struggling and I don't know what I'm doing wrong. I've followed a lot of instructions online including going through various AWS tutorials, seeing lots of examples, but I can't get the data to

问题 I'm hoping someone can help me with an Amazon S3 Cross Region Replication query. I have two Amazon AWS accounts, each with a bucket in a different region. I want to replicate the data from one bucket to another and from what I understand this should be a simple process to create. However, I'm really struggling and I don't know what I'm doing wrong. I've followed a lot of instructions online including going through various AWS tutorials, seeing lots of examples, but I can't get the data to

问题 I configurred S3 bucket for Frankfurt region. Though my Django -based service is able to write files to the bucket, whenever it tried to read them there's InvalidRequest error telling to upgrate authorization mechanizm: <Error> <Code>InvalidRequest</Code> <Message> The authorization mechanism you have provided is not supported. Please use AWS4-HMAC-SHA256. </Message> <RequestId>17E9629D33BF1E24</RequestId> <HostId> ... </HostId> </Error> Is the cause for this error burried in my incorrect

问题 I have uploaded a file 14MB to S3 in chunks (5MB) each and also using spark-md5 calculated the hash of each chunk. The individual hash of each chunk (generated by spark-md5) is matching with ETag of each chunk uploaded to S3. But the ETag hash generated by doing full upload to S3 is not matching with locally calculated hash generated by spark-md5. Below are the steps for local hash: Generate hash (generated by spark-md5) of each chunk Join the hash of each chunk Convert to hex Calculated hash

问题 I'm learning S3 buckets, I read this documents about S3 Server access log format From the given examples, I still not sure what is Bytes Sent, Object Size, Total Time, Turn-round Time, Referer, User-Agent, Version ID. They gave us an example for each but I didn't find relevant information from the five log records examples. Can someone explain a bit with example. Many thanks. 来源： https://stackoverflow.com/questions/59137987/questions-about-s3-server-access-log-format