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jtbakerlast Wednesday at 6:56 AM1 replyview on HN

Look into using duckdb with remote http/s3 parquet files. The parquet files are organized as columnar vectors, grouped into chunks of rows. Each row group stores metadata about the set it contains that can be used to prune out data that doesn’t need to be scanned by the query engine. https://duckdb.org/docs/stable/guides/performance/indexing

LanceDB has a similar mechanism for operating on remote vector embeddings/text search.

It’s a fun time to be a dev in this space!


Replies

nextaccounticyesterday at 1:44 AM

> Look into using duckdb with remote http/s3 parquet files. The parquet files are organized as columnar vectors, grouped into chunks of rows. Each row group stores metadata about the set it contains that can be used to prune out data that doesn’t need to be scanned by the query engine. https://duckdb.org/docs/stable/guides/performance/indexing

But, when using this on frontend, are portions of files fetched specifically with http range requests? I tried to search for it but couldn't find details