perf(parquet): reuse boolean Bloom filter hashes

[fallintoplace]

What

• Precompute the xxHash values for false ([]byte{0}) and true ([]byte{1}).
• Reuse them in dense and spaced boolean bitmap Bloom-filter paths.
• Keep custom Hasher implementations on the existing path.

This removes a Sum64 call for every boolean while keeping the same hash values.

Benchmark

Apple M1 Pro, Go 1.26.3, 7 samples, one CPU:

go test -vet=off ./parquet/metadata -run '^$' -bench '^BenchmarkBloomFilter(HashingFromBitmap|BooleanBitmap)' -benchmem -benchtime=150ms -count=7 -cpu=1

The benchmark matrix covers 100K and 1M booleans, all false, all true, alternating, random, and spaced values with 10% and 50% nulls.

Median results for alternating values:

Case	Before	After
Hash, 100K	636.0 us, 802,819 B/op, 2 allocs	181.6 us, 802,816 B/op, 1 alloc
Insert, 100K	1.840 ms, 8,193 B/op, 2 allocs	943.3 us, 8,193 B/op, 2 allocs
Hash, 1M	7.206 ms, 8,003,596 B/op, 2 allocs	1.510 ms, 8,003,584 B/op, 1 alloc
Insert, 1M	18.832 ms, 8,193 B/op, 2 allocs	9.767 ms, 8,193 B/op, 2 allocs

For alternating data, hashing is 3.5x to 4.8x faster and insertion is about 1.9x faster.

Tests

• go test ./parquet/metadata
• PARQUET_TEST_DATA="$PWD/parquet-testing/data" go test ./...
• go vet ./parquet/metadata