Performance
A dashboard that took ninety seconds to load was not waiting on a slow database — it was reading far more data than the question needed. Pushing the filters down to the storage layer, so whole blocks are skipped before they ever leave the disk, brought it under eight seconds without a single extra server. The idea is simpler than the name suggests.
The cheapest data to process is the data you never read. Predicate pushdown is the discipline of deciding what to skip as early as physically possible.
In a columnar warehouse, most query time is spent moving bytes off disk and across the network. If a filter can eliminate a row group before it is ever read, that is pure saved cost.
Parquet stores min/max statistics per row group and page. A query for orders > $1,000 can skip any block whose maximum is below that threshold — often most of the file.
The trick is teaching every layer — planner, scanner, storage — to honor the predicate instead of re-checking it at the top. Each layer that drops rows early shrinks the work for everything above it.
On a 4 PB warehouse, pushdown took a representative dashboard query from 90 seconds to under 8 — with the exact same hardware.
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