/platform-quack-quack-ka-ching

The duck escapes with the credits.

Quack Quack Ka-Ching

Playbook for reading snowflake-managed iceberg tables with DuckDB. Blog post at https://medium.com/datamindedbe/quack-quack-ka-ching-cut-costs-by-querying-snowflake-from-duckdb-f19eff2fdf9d

Preparation on AWS

Make an S3 bucket, in our case chapter-platform-iceberg. Make an IAM policy, in our case allow-s3-platform-iceberg that has access to that S3 bucket.

{
	"Version": "2012-10-17",
	"Statement": [
		{
			"Sid": "AllowPlatformIcebergBucket",
			"Effect": "Allow",
			"Action": "s3:*",
			"Resource": [
				"arn:aws:s3:::chapter-platform-iceberg",
				"arn:aws:s3:::chapter-platform-iceberg/*"
			]
		}
	]
}

Make a role, in our case chapter-platform-iceberg, and attach the above policy to it. We'll need to set a trust policy for this role later, so that Snowflake can assume it.

Create external volume

For the STORAGE_AWS_ROLE_ARN field, provide the ARN of the IAM role that we just made. For the STORAGE_ALLOWED_LOCATIONS field, provide your S3 bucket path.

CREATE OR REPLACE EXTERNAL VOLUME chapter_platform_volume
  STORAGE_LOCATIONS =
  	(
    	(
        	NAME = 'chapter_platform_volume'
        	STORAGE_PROVIDER = 'S3'
        	STORAGE_BASE_URL = 's3://chapter-platform-iceberg/icebergs'
        	STORAGE_AWS_ROLE_ARN = 'arn:aws:iam::xxxxxxxxxxxx:role/chapter-platform-iceberg'
    	)
  	);

This ensures that Snowflake is properly configured to interact with your S3 bucket.

Trust relationship

First, grab the arn of the IAM user in your external volume. This IAM user is one that Snowflake created and that lives in Snowflake's AWS account. You will need it to update the trust policy of your AWS role, along with the EXTERNAL_ID. This is because for different external volumes, the same IAM user is used with different EXTERNAL_IDs. ‘’’sql DESCRIBE EXTERNAL VOLUME chapter_platform_volume; ‘’’ One of the property_value` fields - once formatted - will look something like this:

{
    "NAME":"chapter_platform_volume",
    "STORAGE_PROVIDER":"S3",
    "STORAGE_BASE_URL":"s3://chapter-platform-iceberg/icebergs",
    "STORAGE_ALLOWED_LOCATIONS":["s3://chapter-platform-iceberg/icebergs*"],
    "STORAGE_REGION":"eu-west-1",
    "PRIVILEGES_VERIFIED":true,
    "STORAGE_AWS_ROLE_ARN":"arn:aws:iam::xxxxxxxxxxxx:role/chapter-platform-snowflake",
    "STORAGE_AWS_IAM_USER_ARN":"arn:aws:iam::xxxxxxxxxxxx:user/xxxxxxxxxxxx",
    "STORAGE_AWS_EXTERNAL_ID":"XXXXXXXX_SFCRole=xxxxxxxxxxxxxxxxxx",
    "ENCRYPTION_TYPE":"NONE",
    "ENCRYPTION_KMS_KEY_ID":""}

Make sure you copy this STORAGE_AWS_IAM_USER_ARN and STORAGE_AWS_EXTERNAL_ID.

Now, on AWS side, you need to create a trust relationship so that Snowflake's IAM user can assume a role that has permissions to access the S3 bucket. This involves updating the IAM role to have the following trust policy:

{
	"Version": "2012-10-17",
	"Statement": [
    	{
        	"Effect": "Allow",
        	"Principal": {
            	"AWS": "arn:aws:iam::xxxxxxxxxxxx:user/xxxxxxxxxxxx"
        	},
        	"Action": "sts:AssumeRole",
        	"Condition": {
            	"StringEquals": {
                	"sts:ExternalId": [
                    	"XXXXXXXX_SFCRole=xxxxxxxxxxxxxxxxxx"
                	]
            	}
        	}
        }
    ]
}

We can finally create native iceberg tables in Snowflake and you can find your parquet files in the S3 bucket.

CREATE OR REPLACE ICEBERG TABLE line_item
BASE_LOCATION='line_item'
EXTERNAL_VOLUME=chapter_platform_volume
CATALOG=SNOWFLAKE
AS (SELECT * FROM SNOWFLAKE_SAMPLE_DATA.TPCH_SF1.LINEITEM);

DuckDB

To begin, ensure you have the necessary dependencies installed and configured in DuckDB.

install iceberg;
load iceberg;
install aws;
load aws;
install httpfs;
load httpfs;
call load_aws_credentials();

Then, you can start querying your iceberg table.

select * from iceberg_scan(‘s3://chapter-platform-iceberg/icebergs/line_item’);

Finally, you can write your table back to S3, where it's accessible for further use.

COPY line_item TO 's3://chapter-platform-iceberg/parquets/line_item.parquet';

Enjoy!