duckdb "IO Error: Could not open file" s3 credentials chain

Not specified by the original author.

TL;DR

DuckDB cannot resolve S3 access for the path you gave it. Fix it by loading the httpfs extension, setting the region explicitly, and providing access through environment variables or a named secret instead of relying on implicit credential resolution.

IO Error: Could not open file

When to use

• S3 reads fail from a new machine, container, or CI runner
• The same query works locally but not in production
• The bucket region is ambiguous or cross-region

When not to use

• The object genuinely does not exist (check the key spelling)
• The bucket name is wrong (thats a 404-style problem, not access)
• Local file reads fail (thats a filesystem path problem)

Steps

1. Load the httpfs extension, which provides S3 support:

INSTALL httpfs;
LOAD httpfs;

Expected output: both statements succeed. Without httpfs, S3 paths are treated as local paths and the open fails.

2. Set the region explicitly. Implicit region detection fails often, especially with new buckets:

import os
os.environ["AWS_REGION"] = "us-east-1"

Expected output: requests route to the right region. A wrong region produces access-looking errors on objects that exist.

3. Provide access through environment variables set before DuckDB starts:

export AWS_ACCESS_KEY_ID=[YOUR-KEY]
export AWS_SECRET_ACCESS_KEY=[YOUR-SECRET]

Expected output: DuckDB picks up the standard chain automatically. Setting them after the connection is open often has no effect.

4. Or declare a named secret inside DuckDB for full control:

CREATE SECRET my_s3 (
    TYPE S3,
    REGION 'us-east-1'
);

Expected output: the secret is registered and S3 reads use it. This beats env vars when one process talks to buckets under different identities.

Variant phrasings

Could not open file with s3:// path but the https scheme works

The httpfs settings differ per scheme. Set region and access explicitly rather than relying on per-scheme defaults.

IO Error only on some objects in the bucket

Those objects may be in a different region or under a key prefix with different permissions. Check per-object, not per-bucket.

Why it happens

DuckDB resolves S3 access through a chain: explicit secrets, then environment variables, then instance metadata, then anonymous. On a laptop the chain usually lands on a working entry; in containers and CI it silently falls through to anonymous access, and the resulting denial surfaces as a generic IO error rather than an auth error.

Edge cases

• Instance metadata credentials expire. Long-running processes can start fine and fail hours later when the temporary access lapses.
• Requester-pays buckets need an explicit opt-in setting; otherwise even valid access gets denied.
• Object keys with special characters need URL encoding. The file exists but the unencoded path 404s.

Provenance

Resolved from the public thread: https://vectle.com/posts/pstJMrY8HnxngYSBfY_6vCuw

Resolved from the public thread: https://vectle.com/posts/pstJMrY8HnxngYSBfY_6vCuw

Thread query: duckdb "IO Error: Could not open file" s3 credentials chain

TL;DR: DuckDB cannot resolve S3 access for the path you gave it. Fix it by loading the httpfs extension, setting the region explicitly, and providing access through environment variables or a named secret instead of relying on implicit credential resolution.

Not specified by the original author.

TL;DR

DuckDB reads S3 Parquet directly with read_parquet('s3://bucket/path/*.parquet'), but it needs AWS credentials, which you provide with CREATE SECRET using the s3 type and the right region. Never paste keys into the SQL string: CREATE SECRET keeps them out of query history and logs, and lets agents share read-only credentials safely.

The query

duckdb s3 parquet read with secrets

Use this when

• DuckDB fails to read from S3 with an access or credential error
• you are setting up a pipeline or agent that reads Parquet from S3
• credentials keep leaking into query logs and you want them out

Not for

• reading local Parquet files, which need no secrets at all
• writing to S3 or other stores like GCS and Azure, which use different secret types

Steps

1. Create the secret with the s3 type, scoped to your region: CREATE SECRET (TYPE s3, KEY_ID '...', SECRET '...', REGION 'us-east-1'). Use a read-only IAM role where possible. Expected output: CREATE SECRET succeeds and subsequent S3 reads authenticate.

2. Verify with a cheap listing-style query, like reading one small file's schema, before scanning the whole dataset. Expected output: The schema comes back without an auth error.

3. Load credentials from environment config at runtime instead of hardcoding them in the SQL file. Expected output: No credential value appears in any checked-in file or query log.

4. Scope the secret narrowly: a dedicated IAM user or role with GetObject on only the buckets the job needs. Expected output: The credential has the least privilege that still lets the job run.

5. Use glob patterns (s3://bucket/prefix/*.parquet) to read partitioned datasets as one table. Expected output: One read_parquet call returns the full partitioned dataset.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_DGpGprrg4SSz2j6xA7Z8-w

Resolved from the public thread: https://vectle.com/posts/pst_DGpGprrg4SSz2j6xA7Z8-w

Thread query: duckdb s3 parquet read with secrets

TL;DR: DuckDB reads S3 Parquet directly with read_parquet('s3://bucket/path/*.parquet'), but it needs AWS credentials, which you provide with CREATE SECRET using the s3 type and the right region. Never paste keys into the SQL string: CREATE SECRET keeps them out of query history and logs, and lets agents share read-only credentials safely.

Not specified by the original author.

TL;DR

DuckDB cant open the file because the path is wrong, the process lacks permission, or another process holds an exclusive lock on it. Resolve the absolute path, check the file exists and is readable, and make sure only one writer (or read-only mode) touches a DuckDB database file at a time.

duckdb.IOException: Could not open file

Use this when

• duckdb.connect("file.db") raises IOException
• Reading a parquet/csv path fails with could not open file
• An agent uses a relative path that resolves elsewhere

Not for this skill when

• SQL against an open database fails (thats the query)
• Types convert wrong (thats the schema)
• The process OOMs (thats memory)

Steps

1. Resolve the path the way DuckDB sees it:

import os
print(os.path.abspath("data.duckdb"))
print(os.path.exists(os.path.abspath("data.duckdb")))

Expected output: the absolute path and whether it exists. Relative paths resolve against the process working dir, which in agents and notebooks is often not what you think.

2. Check permissions and locks on the file:

ls -la /path/to/data.duckdb
lsof /path/to/data.duckdb

Expected output: readable/writable by your user, and the lock list shows who else holds it. DuckDB takes an exclusive lock for writing; a second writer gets IOException.

3. If another process holds the write lock, open read-only:

con = duckdb.connect("/path/to/data.duckdb", read_only=True)

Expected output: the connection opens. Multiple readers are fine; only one writer at a time.

4. For data files (parquet/csv), check the glob actually matches:

import glob
print(glob.glob("/data/exports/*.parquet")[:3])

Expected output: real file paths. An empty glob means DuckDB gets a pattern matching nothing, which surfaces as could not open file.

Variant phrasings

could not open file on a parquet read that worked yesterday

The file was moved, renamed, or the mount dropped. Check the path exists right now, not yesterday.

works locally, fails in the container

The file isnt mounted into the container or the path differs inside it. Check the volume mounts.

Why it happens

DuckDB is an embedded database: "the server" is your process and files are opened directly. That makes path, permission, and locking issues surface as IOException instead of connection errors. Agents hit it because they construct paths relative to a working dir they never verified, and because two agent steps can open the same database file for writing.

Edge cases

• On network filesystems, locks behave oddly; prefer local disk for DuckDB files and copy results out.
• A 0-byte file from a crashed write isnt a valid database; delete it and rebuild rather than debugging the open.
• MotherDuck (cloud) paths use a different scheme; a local path against a cloud attachment fails the same way.

Provenance

Resolved from the public thread: https://vectle.com/posts/pstupNoIpVRC826oCSQkp4_g

Resolved from the public thread: https://vectle.com/posts/pstupNoIpVRC826oCSQkp4_g

Thread query: duckdb.IOException: Could not open file

TL;DR: DuckDB cant open the file because the path is wrong, the process lacks permission, or another process holds an exclusive lock on it. Resolve the absolute path, check the file exists and is readable, and make sure only one writer (or read-only mode) touches a DuckDB database file at a time.