Fix: DuckDB Not Picking Up AWS_PROFILE For S3 Access

Aug 6, 2025 by Henrik Larsen 53 views

Troubleshooting DuckDB and AWS S3 Authentication: A Comprehensive Guide

Understanding the Problem: DuckDB and AWS Profile Woes

So, you're diving into the world of DuckDB, a fantastic in-process SQL OLAP database management system, and you want to tap into your data stored in Amazon S3. You've configured your AWS CLI with multiple profiles, like a responsible cloud citizen, and you've even set the AWS_PROFILE environment variable to your desired profile, such as sandbox. You confidently create a persistent secret in DuckDB, pointing it to your S3 credentials using the credential_chain provider. But then, the dreaded error message appears:

HTTP Error:
HTTP GET error on 'https://###.s3.amazonaws.com/test.parquet' (HTTP 403)

Authentication Failure - this is usually caused by invalid or missing credentials.
*   No credentials are provided.
*   See https://duckdb.org/docs/stable/extensions/httpfs/s3api.html

What gives? Your AWS CLI works perfectly with the sandbox profile, but DuckDB seems oblivious to it. This is a classic case of DuckDB not picking up the AWS_PROFILE environment variable as expected.

Deep Dive into the Error

Let's break down this error message to understand what's happening under the hood. The HTTP 403 error indicates an authorization problem. The server (in this case, AWS S3) is saying, "I know who you are, but you don't have permission to access this resource." The subsequent message, "Authentication Failure - this is usually caused by invalid or missing credentials," confirms our suspicion: DuckDB isn't presenting the correct credentials to S3.

The crucial line here is "No credentials are provided." This strongly suggests that DuckDB isn't using the AWS profile you've set in your environment. It's either looking in the wrong place for credentials or not finding them at all.

Why Does This Happen?

The root cause often lies in how DuckDB's httpfs extension handles AWS credentials. While it should respect the AWS_PROFILE environment variable when using credential_chain, there can be situations where it doesn't pick it up correctly. This might be due to environment variable scoping, how DuckDB initializes its S3 client, or even subtle configuration issues.

DuckDB Versions and Compatibility

Before we proceed, it's worth noting the DuckDB version. In this particular case, the user is running v1.3.2, codenamed Ossivalis. While this version is relatively recent, it's always a good practice to ensure you're on the latest stable release to benefit from bug fixes and improvements. If you encounter this issue, checking for DuckDB updates is a worthwhile step.

The Solution: Forcing DuckDB to Recognize Your AWS Profile

Okay, enough with the problem description. Let's get down to the fix! The most reliable way to ensure DuckDB uses your specified AWS profile is to explicitly pass the profile name within the DuckDB connection string. This bypasses any potential issues with environment variable propagation.

Here's the step-by-step solution:

Modify Your DuckDB Connection String: Instead of relying solely on the credential_chain provider, we'll add the AWS_PROFILE parameter directly to the connection string used by DuckDB's s3 function. This is the key to explicitly telling DuckDB which profile to use.
Update the Secret Creation: You'll need to modify your CREATE SECRET statement to include the AWS_PROFILE in the REGION section. This might seem a bit counterintuitive, but it's the correct way to pass the profile information within DuckDB's secret management system.

Here's how the modified CREATE SECRET statement should look:
```
CREATE OR REPLACE PERSISTENT SECRET s3_sandbox (
  TYPE s3,
  PROVIDER credential_chain,
  REGION 'us-east-1',  -- Or your AWS region
  AWS_PROFILE 'sandbox' -- Add your profile name here
);
```
Important: Replace us-east-1 with your actual AWS region. This is crucial for DuckDB to connect to the correct S3 endpoint.
Verify the Secret: After creating the secret, you can verify its contents using the SHOW SECRETS command. This will display the details of your secret, including the AWS_PROFILE you've set.
```
SHOW SECRETS;
```
Ensure that the output shows AWS_PROFILE = sandbox (or your desired profile name).
Test Your Connection: Now, try accessing your S3 data again using read_parquet or other DuckDB functions that interact with S3. This time, DuckDB should correctly use the sandbox profile and authenticate with S3.
```
SELECT * FROM read_parquet('s3://###/test.parquet');
```
If everything is configured correctly, you should see your data without any more HTTP 403 errors.

Why This Solution Works

By explicitly specifying the AWS_PROFILE within the secret definition, we're providing DuckDB with a direct instruction on which profile to use. This overrides any potential ambiguity or issues with environment variable inheritance. It's a more robust and reliable approach than relying solely on the AWS_PROFILE environment variable.

Additional Troubleshooting Tips

If you're still encountering issues after implementing the solution above, here are some additional tips to help you troubleshoot:

Double-Check Your AWS Credentials: Ensure that the AWS profile you're using (sandbox in this case) has the necessary permissions to access the S3 bucket and objects you're trying to read. You can verify this in the AWS IAM console.
Verify Your AWS CLI Configuration: Use the AWS CLI to confirm that your sandbox profile is correctly configured and can access S3. Try running a simple command like aws s3 ls s3://your-bucket-name using the --profile sandbox flag.
Check Your S3 Bucket Policy: The S3 bucket itself might have a policy that restricts access. Review your bucket policy to ensure that the IAM role or user associated with your sandbox profile is granted the necessary permissions.
Ensure the httpfs Extension is Installed: DuckDB's S3 integration relies on the httpfs extension. Make sure it's installed and loaded in your DuckDB session using INSTALL httpfs; and LOAD httpfs;.
Check for Region Mismatches: A common pitfall is specifying the wrong AWS region in your DuckDB connection string or secret definition. Ensure that the region matches the region where your S3 bucket is located.
Review DuckDB Documentation: The DuckDB documentation on HTTPFS and S3 integration is a valuable resource. Refer to it for detailed information on configuration options and troubleshooting tips (https://duckdb.org/docs/stable/extensions/httpfs/s3api.html).
Consider Using IAM Roles for EC2 Instances: If you're running DuckDB on an EC2 instance, consider using IAM roles instead of explicitly managing AWS credentials. This is a more secure and convenient approach.

Example Scenario: A Step-by-Step Walkthrough

Let's walk through a complete example scenario to solidify your understanding. Suppose you have an S3 bucket named my-data-bucket in the us-west-2 region, and you want to access a Parquet file named data.parquet within that bucket. You have an AWS profile named dev that has the necessary permissions.

Here's how you would configure DuckDB to access this data:

Create the Secret:

CREATE OR REPLACE PERSISTENT SECRET s3_dev (
  TYPE s3,
  PROVIDER credential_chain,
  REGION 'us-west-2',
  AWS_PROFILE 'dev'
);

Load the httpfs Extension:
```
INSTALL httpfs;
LOAD httpfs;
```
Query the Data:
```
SELECT * FROM read_parquet('s3://my-data-bucket/data.parquet');
```
If everything is set up correctly, this query should successfully read the data from your S3 bucket.

Conclusion: Conquering DuckDB and S3 Authentication

Connecting DuckDB to AWS S3 can be a breeze once you understand the nuances of credential management. By explicitly specifying the AWS_PROFILE in your DuckDB secret definition, you can overcome the common issue of DuckDB not picking up the environment variable. Remember to double-check your AWS credentials, bucket policies, and region settings for a smooth and seamless integration.

So, there you have it, folks! A comprehensive guide to troubleshooting DuckDB and AWS S3 authentication. Now go forth and unleash the power of DuckDB on your cloud data! Remember to always prioritize security best practices when working with cloud credentials.

If you have any further questions or run into other snags, don't hesitate to consult the DuckDB documentation or seek help from the vibrant DuckDB community. Happy querying!