Question

我正在尝试使用AWS Machine学习SDK创建数据源。起初我将csv数据文件也上传到S3存储器。然后我更新此文件的存储桶策略。只有在我尝试创建数据源但我收到错误之后：

失败（1）：您无权访问's3：//training-data/input/test-likes.csv'。联系's3：//training-data/input/test-likes.csv'的所有者以获取读取权限。

还需要哪些权限？

这是我的保管政策：

{
"Version": "2012-10-17",
"Statement": [
    {
        "Sid": "AmazonML_s3:ListBucket",
        "Effect": "Allow",
        "Principal": {
            "AWS": "arn:aws:iam::831986290820:user/pavel.emsow",
            "Service": "machinelearning.amazonaws.com"
        },
        "Action": "s3:ListBucket",
        "Resource": "arn:aws:s3:::trainig-data",
        "Condition": {
            "StringLike": {
                "s3:prefix": [
                    "input/common-likes.csv*",
                    "input/test-likes.csv*"
                ]
            }
        }
    },
    {
        "Sid": "AmazonML_s3:GetObject",
        "Effect": "Allow",
        "Principal": {
            "AWS": "arn:aws:iam::831986290820:user/pavel.emsow",
            "Service": "machinelearning.amazonaws.com"
        },
        "Action": "s3:GetObject",
        "Resource": [
            "arn:aws:s3:::trainig-data/input/common-likes.csv*",
            "arn:aws:s3:::trainig-data/input/test-likes.csv*"
        ]
    }
]
}

Answer 1

尝试从S3数据源创建ML模型时遇到此错误。除了我的（类似）存储桶策略之外，我还必须修改调用机器学习API时使用的IAM角色。我将完全访问S3策略附加到IAM角色，并且调用成功。完全访问策略可能过于宽泛，可能会将其减少为S3只读并仍然可以使呼叫成功。

Cretae Datasourse机器通过SDK学习AWS

1 个答案: