Using the Parquet file format, queries are fast. What optimizations are done using Parquet?

Parquet is a columnar storage format that offers several optimizations for fast queries. First, it stores data by column rather than row, so a query that only needs a few columns reads less data. Second, it writes column statistics (min, max, null count) and page-level metadata, enabling predicate pushdown and partition pruning. Third, it supports efficient compression codecs (Snappy, Gzip, Brotli) that reduce I/O. Fourth, it allows schema evolution, so new columns can be added without rewriting existing data. Finally, many engines (Spark, Hive, Presto) can skip entire blocks or pages if the filter predicates do not match the stored statistics, dramatically reducing scan time. These features together make Parquet ideal for analytical workloads.