What is predicate pushdown in Parquet and how does it work end-to-end?

Predicate pushdown is the process of evaluating filter conditions as early as possible — before data reaches the compute layer — using metadata stored inside Parquet files.

End-to-end flow for WHERE amount > 1000:

1. Reader fetches the Parquet footer and reads per-row-group statistics: min_amount, max_amount.
2. For each row group, if max_amount ≤ 1000, the entire row group is skipped — no decompression, no I/O.
3. For surviving row groups, the amount column chunk is decompressed and values are evaluated against > 1000 at the page level (with page-level indexes in Parquet 2.x).
4. Only matching rows are returned to the engine.

Parquet 2.0 introduced column indexes (min/max per page, not just per row group), enabling finer-grained skipping within a row group.

Combined with partition pruning (directory skipping) and Bloom filters (equality skipping), predicate pushdown is the single most important performance feature of the Parquet format.

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