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    <title>topic Re: Databricks can write to s3 bucket through panda but not from spark in Data Engineering</title>
    <link>https://community.databricks.com/t5/data-engineering/databricks-can-write-to-s3-bucket-through-panda-but-not-from/m-p/10453#M5628</link>
    <description>&lt;P&gt;Could you try to map s3 bucket location with Databricks&amp;nbsp;File System then write output to this new location instead of directly write to S3 location.&lt;/P&gt;</description>
    <pubDate>Tue, 31 Jan 2023 13:17:32 GMT</pubDate>
    <dc:creator>Nhan_Nguyen</dc:creator>
    <dc:date>2023-01-31T13:17:32Z</dc:date>
    <item>
      <title>Databricks can write to s3 bucket through panda but not from spark</title>
      <link>https://community.databricks.com/t5/data-engineering/databricks-can-write-to-s3-bucket-through-panda-but-not-from/m-p/10452#M5627</link>
      <description>&lt;P&gt;&lt;B&gt;Hey,&lt;/B&gt;&lt;/P&gt;&lt;P&gt;I have problem with access to s3 bucket using cross account bucket permission, i got the following error:&lt;/P&gt;&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper" image-alt="Access_Denied_S3_Bucket"&gt;&lt;img src="https://community.databricks.com/t5/image/serverpage/image-id/762i65AA915F649F592C/image-size/large?v=v2&amp;amp;px=999" role="button" title="Access_Denied_S3_Bucket" alt="Access_Denied_S3_Bucket" /&gt;&lt;/span&gt;&lt;B&gt;Steps to repreduce:&lt;/B&gt;&lt;/P&gt;&lt;UL&gt;&lt;LI&gt;Checking the role that assoicated to ec2 instance:&lt;/LI&gt;&lt;/UL&gt;&lt;PRE&gt;&lt;CODE&gt;{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Effect": "Allow",
            "Action": [
                "s3:*",
                "s3-object-lambda:*"
            ],
            "Resource": "*"
        }
    ]
}&lt;/CODE&gt;&lt;/PRE&gt;&lt;P&gt;Also the bucket policy for specific s3 bucket is:&lt;/P&gt;&lt;PRE&gt;&lt;CODE&gt;{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Sid": "Databricks Access",
            "Effect": "Allow",
            "Principal": {
                "AWS": [
                    "arn:aws:iam::692503192357:user/product-similarity-s3-access",
                    "arn:aws:iam::692503192357:role/dev-databricks-role",
                    "arn:aws:iam::692503192357:role/dev-databricks-hy1-crossaccount"
                ]
            },
            "Action": [
                "s3:DeleteObject",
                "s3:GetBucketLocation",
                "s3:GetObject",
                "s3:ListBucket",
                "s3:PutObject"
            ],
            "Resource": [
                "arn:aws:s3:::product-similarity-dev",
                "arn:aws:s3:::product-similarity-dev/*"
            ]
        }
    ]
}&lt;/CODE&gt;&lt;/PRE&gt;&lt;P&gt;Please note that read access working as expected with spark but not write,&lt;/P&gt;&lt;P&gt;Also i can write to this s3 bucket using panda.&lt;/P&gt;&lt;P&gt;&lt;B&gt;I would really appreciate your help&lt;/B&gt;&lt;/P&gt;</description>
      <pubDate>Tue, 31 Jan 2023 09:09:02 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/databricks-can-write-to-s3-bucket-through-panda-but-not-from/m-p/10452#M5627</guid>
      <dc:creator>LidorAbo</dc:creator>
      <dc:date>2023-01-31T09:09:02Z</dc:date>
    </item>
    <item>
      <title>Re: Databricks can write to s3 bucket through panda but not from spark</title>
      <link>https://community.databricks.com/t5/data-engineering/databricks-can-write-to-s3-bucket-through-panda-but-not-from/m-p/10453#M5628</link>
      <description>&lt;P&gt;Could you try to map s3 bucket location with Databricks&amp;nbsp;File System then write output to this new location instead of directly write to S3 location.&lt;/P&gt;</description>
      <pubDate>Tue, 31 Jan 2023 13:17:32 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/databricks-can-write-to-s3-bucket-through-panda-but-not-from/m-p/10453#M5628</guid>
      <dc:creator>Nhan_Nguyen</dc:creator>
      <dc:date>2023-01-31T13:17:32Z</dc:date>
    </item>
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