Using lakeFS with DuckDB

DuckDB is an in-process SQL OLAP database management system.

Configuration

Querying data in lakeFS from DuckDB is similar to querying data in S3 from DuckDB. It is done using the httpfs extension.

Configure the lakeFS S3 Gateway endpoint

If not loaded already, install and load the HTTPFS extension:

INSTALL httpfs;
LOAD httpfs;

Then run the following to configure the connection.

SET s3_region='us-east-1';
SET s3_endpoint='lakefs.example.com';
SET s3_access_key_id='AKIAIOSFODNN7EXAMPLE';
SET s3_secret_access_key='wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY';
SET s3_url_style='path';

-- Uncomment in case the endpoint listen on non-secure, for example running lakeFS locally.
-- SET s3_use_ssl=false;

• s3_endpoint is the host (and port, if necessary) of your lakeFS server
• s3_access_key_id and s3_secret_access_key are the access credentials for your lakeFS user
• s3_url_style needs to be set to path
• s3_region is the S3 region on which your bucket resides. If local storage, or not S3, then just set it to us-east-1.

Querying Data

Once configured, you can query data using the lakeFS S3 Gateway using the following URI pattern:

s3://<REPOSITORY NAME>/<REFERENCE ID>/<PATH TO DATA>

Since the S3 Gateway implemenets all S3 functionality required by DuckDB, you can query using globs and patterns, including support for Hive-partitioned data.

Example:

SELECT * 
FROM parquet_scan('s3://example-repo/main/data/population/by-region/*.parquet', HIVE_PARTITIONING=1) 
ORDER BY name;

Writing Data

No special configuration required for writing to a branch. Assuming the configuration above and write permissions to a dev branch, a write operation would look like any DuckDB write:

CREATE TABLE sampled_population AS SELECT * 
FROM parquet_scan('s3://example-repo/main/data/population/by-region/*.parquet', HIVE_PARTITIONING=1) 
USING SAMPLE reservoir(50000 ROWS) REPEATABLE (100);

COPY sampled_population TO 's3://example-repo/main/data/population/sample.parquet'; -- actual write happens here