> read_parquet() making tons of tiny range requests to load a parquet's footer from S3
This is somewhat unavoidable if you have a number of files and a tight filter which rejects most of them. The footer choice was a bad one in hindsight (not for HDFS), but for anything which uses XOR or other kind of erasure coding. The other other file format I worked with used headers only instead of footers, to save a few ms in latency for the initial GET
I don't think Ducklake can maintain a zone-map or ART index over parquet files, but there is no equivalent of iceberg metadata/something which has min/max/HLL compacted across multiple files yet.
The secondary indexes with file identifiers stored in a sequential file is most likely the next useful thing duckdb can make.
This is somewhat unavoidable if you have a number of files and a tight filter which rejects most of them. The footer choice was a bad one in hindsight (not for HDFS), but for anything which uses XOR or other kind of erasure coding. The other other file format I worked with used headers only instead of footers, to save a few ms in latency for the initial GET
I don't think Ducklake can maintain a zone-map or ART index over parquet files, but there is no equivalent of iceberg metadata/something which has min/max/HLL compacted across multiple files yet.
The secondary indexes with file identifiers stored in a sequential file is most likely the next useful thing duckdb can make.