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Creating an AWS S3 Read Connector

Prerequisites:

  • Access credentials
  • Data location on AWS S3
  • Data Schema (column names and column type)

Specify the S3 path

Location

S3 Read Connectors have location settings comprised of:

  • Bucket: The bucket name, such as ascend-io-sample-read-data.
  • Pattern: The pattern used to identify eligible files:
    • Match: Matches the pattern precisely character-for-character.
    • Glob: Glob applies a pattern matching algorithm.
    • Regex: Regex applies a pattern matching algorithm.

IAM access

Enter the Access Key and Secret Key for the IAM User. Here's an example S3 policy configuration for this IAM user to create a read connector for data within the bucket s3://ascend-io-playground-bucket/:

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Effect": "Allow",
            "Action": [
                "s3:ListBucket",
                "s3:GetBucketLocation",
                "s3:GetBucketPolicy",
                "s3:GetBucketAcl",
                "s3:ListBucket",
                "s3:GetObject",
                "s3:GetObjectAcl"
            ],
            "Resource": [
                "arn:aws:s3:::ascend-io-playground-bucket",
                "arn:aws:s3:::ascend-io-playground-bucket/*"
            ]
        }
    ]
}

Testing Connection

Use Test Connection to check whether all S3 permissions are correctly configured.

Here is an example:

Parsers & Schema

Data formats currently available are: Avro, Grok, JSON, Parquet and XSV. However, you can create your own parser functions or define a UDP (User Defined Parser) to process a file format.

Schema information will automatically be fetched for JSON, Parquet and XSV files with a header row.

Here's an example:

Updated 10 months ago

AWS S3


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