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vortex-row: convert_columns + tests + bench scaffolding
Wire the RowSize/RowEncode scalar functions to the user-facing API: - `convert_columns` accepts a slice of input arrays and per-column SortFields, constructs `RowEncodeOptions` + `VecExecutionArgs`, and returns the encoded `ListViewArray<u8>`. - `compute_row_sizes` returns just the per-row sizes (the `Struct { fixed: u32, var: u32 }` output of `RowSize`). - `initialize()` now registers `RowSize` and `RowEncode` on the given session so they are reachable via the expression layer. Tests cover sort-order round-trips for bool, primitive (i64 asc/desc, u32, f64), utf8, multi-column, nulls_first/last, struct sort-order, the single-buffer invariant of the ListView output, and the structural shape of `RowSize`. Tests that exercise per-encoding fast paths (`constant_path_matches_canonical`, `dict_path_matches_canonical`) land together with their respective kernels in PR 3. The bench file uses divan + mimalloc and reports throughput in GB/s of encoded output bytes for primitive_i64, utf8, and struct_mixed. Each has an `arrow_row` baseline and a `vortex` measurement. Per-encoding fast-path scenarios (constant/dict/patched/bitpacked/for/delta) gain their triplets in PR 3. Baseline measurements at this commit (sample-count=10): primitive_i64_vortex ~1.97 GB/s (vs arrow-row 4.12 GB/s) utf8_vortex ~0.87 GB/s (vs arrow-row 1.56 GB/s) struct_mixed_vortex ~0.95 GB/s (vs arrow-row 1.19 GB/s) PR 2 closes most of the gap by replacing the validating `ListViewArray::try_new` with `new_unchecked`, skipping the buffer zero-init, auto-vectorizing the offsets and varlen-block paths, etc. Signed-off-by: Claude <noreply@anthropic.com>
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Cargo.lock

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Cargo.toml

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@@ -7,12 +7,12 @@ members = [
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"vortex-mask",
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"vortex-utils",
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"vortex-session",
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"vortex-row",
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"vortex-flatbuffers",
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"vortex-metrics",
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"vortex-io",
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"vortex-proto",
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"vortex-array",
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"vortex-row",
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"vortex-tensor",
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"vortex-turboquant",
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"vortex-compressor",
@@ -103,6 +103,7 @@ arrow-cast = "58"
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arrow-data = "58"
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arrow-ipc = "58"
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arrow-ord = "58"
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arrow-row = "58"
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arrow-schema = "58"
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arrow-select = "58"
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arrow-string = "58"

vortex-row/Cargo.toml

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@@ -24,3 +24,17 @@ vortex-buffer = { workspace = true }
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vortex-error = { workspace = true }
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vortex-mask = { workspace = true }
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vortex-session = { workspace = true }
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[dev-dependencies]
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arrow-array = { workspace = true }
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arrow-row = { workspace = true }
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arrow-schema = { workspace = true }
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divan = { workspace = true }
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mimalloc = { workspace = true }
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rand = { workspace = true }
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rstest = { workspace = true }
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vortex-array = { workspace = true, features = ["_test-harness"] }
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[[bench]]
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name = "row_encode"
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harness = false

vortex-row/benches/row_encode.rs

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// SPDX-License-Identifier: Apache-2.0
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// SPDX-FileCopyrightText: Copyright the Vortex contributors
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#![expect(
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clippy::unwrap_used,
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clippy::clone_on_ref_ptr,
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clippy::cloned_ref_to_slice_refs,
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clippy::cast_possible_truncation,
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clippy::cast_possible_wrap,
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clippy::redundant_clone
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)]
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//! Row-encode throughput benchmarks comparing `arrow-row` against vortex's `convert_columns`
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//! for the canonical scenarios shipped in PR 1: a primitive i64 column, a Utf8 column,
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//! and a mixed-field struct. Per-encoding fast paths (Constant, Dict, Patched, BitPacked,
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//! FoR, Delta) gain their own triplets in PR 3.
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use std::sync::Arc;
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use arrow_array::Int64Array;
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use arrow_array::StringArray;
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use arrow_array::StructArray as ArrowStructArray;
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use arrow_row::RowConverter;
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use arrow_row::SortField as ArrowSortField;
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use arrow_schema::DataType;
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use arrow_schema::Field;
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use divan::counter::BytesCount;
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use mimalloc::MiMalloc;
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use rand::RngExt;
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use rand::SeedableRng;
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use rand::distr::Alphanumeric;
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use rand::rngs::StdRng;
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use vortex_array::IntoArray;
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use vortex_array::LEGACY_SESSION;
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use vortex_array::VortexSessionExecute;
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use vortex_array::arrays::PrimitiveArray;
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use vortex_array::arrays::StructArray;
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use vortex_array::arrays::VarBinViewArray;
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use vortex_row::SortField;
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use vortex_row::convert_columns;
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#[global_allocator]
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static GLOBAL: MiMalloc = MiMalloc;
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const N: usize = 100_000;
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fn main() {
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divan::main();
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}
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fn gen_i64(n: usize, seed: u64) -> Vec<i64> {
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let mut rng = StdRng::seed_from_u64(seed);
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(0..n)
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.map(|_| rng.random_range(i64::MIN..i64::MAX))
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.collect()
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}
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fn gen_words(n: usize, mean_len: usize, seed: u64) -> Vec<String> {
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let rng = &mut StdRng::seed_from_u64(seed);
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(0..n)
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.map(|_| {
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let len = rng.random_range(mean_len.saturating_sub(4)..=mean_len + 4);
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rng.sample_iter(&Alphanumeric)
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.take(len)
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.map(char::from)
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.collect::<String>()
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})
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.collect()
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}
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// ---------- primitive_i64 ----------
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#[divan::bench]
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fn primitive_i64_arrow_row(bencher: divan::Bencher) {
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let v = gen_i64(N, 0);
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let arr = Arc::new(Int64Array::from(v.clone())) as arrow_array::ArrayRef;
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let conv = RowConverter::new(vec![ArrowSortField::new(DataType::Int64)]).unwrap();
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let bytes = (N * (1 + 8)) as u64;
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bencher
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.counter(BytesCount::new(bytes))
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.bench_local(|| conv.convert_columns(&[arr.clone()]).unwrap())
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}
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#[divan::bench]
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fn primitive_i64_vortex(bencher: divan::Bencher) {
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let v = gen_i64(N, 0);
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let col = PrimitiveArray::from_iter(v.clone()).into_array();
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let bytes = (N * (1 + 8)) as u64;
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bencher.counter(BytesCount::new(bytes)).bench_local(|| {
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let mut ctx = LEGACY_SESSION.create_execution_ctx();
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convert_columns(&[col.clone()], &[SortField::default()], &mut ctx).unwrap()
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})
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}
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// ---------- utf8 ----------
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#[divan::bench]
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fn utf8_arrow_row(bencher: divan::Bencher) {
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let words = gen_words(N, 16, 7);
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let total: u64 = words
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.iter()
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.map(|w| 1 + (w.len().div_ceil(32) * 33) as u64)
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.sum();
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let arr = Arc::new(StringArray::from(words.clone())) as arrow_array::ArrayRef;
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let conv = RowConverter::new(vec![ArrowSortField::new(DataType::Utf8)]).unwrap();
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bencher
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.counter(BytesCount::new(total))
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.bench_local(|| conv.convert_columns(&[arr.clone()]).unwrap())
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}
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#[divan::bench]
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fn utf8_vortex(bencher: divan::Bencher) {
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let words = gen_words(N, 16, 7);
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let total: u64 = words
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.iter()
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.map(|w| 1 + (w.len().div_ceil(32) * 33) as u64)
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.sum();
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let col = VarBinViewArray::from_iter_str(words.iter().map(String::as_str)).into_array();
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bencher.counter(BytesCount::new(total)).bench_local(|| {
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let mut ctx = LEGACY_SESSION.create_execution_ctx();
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convert_columns(&[col.clone()], &[SortField::default()], &mut ctx).unwrap()
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})
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}
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// ---------- struct_mixed ----------
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fn struct_mixed_inputs() -> (Vec<i64>, Vec<String>, u64) {
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let ids = gen_i64(N, 1);
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let names = gen_words(N, 16, 2);
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// sentinel (1) + i64 (1+8=9) + utf8-name (1 + ceil(len/32)*33)
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let total: u64 = (0..N)
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.map(|i| {
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let name_bytes = 1 + (names[i].len().div_ceil(32) * 33) as u64;
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1u64 + 9u64 + name_bytes
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})
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.sum();
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(ids, names, total)
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}
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#[divan::bench]
141+
fn struct_mixed_arrow_row(bencher: divan::Bencher) {
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let (ids, names, total) = struct_mixed_inputs();
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let id_arr = Arc::new(Int64Array::from(ids)) as arrow_array::ArrayRef;
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let name_arr = Arc::new(StringArray::from(names)) as arrow_array::ArrayRef;
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let arrow_struct = Arc::new(ArrowStructArray::from(vec![
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(Arc::new(Field::new("id", DataType::Int64, false)), id_arr),
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(
148+
Arc::new(Field::new("name", DataType::Utf8, false)),
149+
name_arr,
150+
),
151+
])) as arrow_array::ArrayRef;
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let struct_fields = vec![
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Arc::new(Field::new("id", DataType::Int64, false)),
154+
Arc::new(Field::new("name", DataType::Utf8, false)),
155+
];
156+
let conv = RowConverter::new(vec![ArrowSortField::new(DataType::Struct(
157+
struct_fields.into(),
158+
))])
159+
.unwrap();
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bencher
161+
.counter(BytesCount::new(total))
162+
.bench_local(|| conv.convert_columns(&[arrow_struct.clone()]).unwrap())
163+
}
164+
165+
#[divan::bench]
166+
fn struct_mixed_vortex(bencher: divan::Bencher) {
167+
let (ids, names, total) = struct_mixed_inputs();
168+
let id_arr = PrimitiveArray::from_iter(ids).into_array();
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let name_arr = VarBinViewArray::from_iter_str(names.iter().map(String::as_str)).into_array();
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let struct_arr = StructArray::from_fields(&[("id", id_arr), ("name", name_arr)])
171+
.unwrap()
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.into_array();
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bencher.counter(BytesCount::new(total)).bench_local(|| {
174+
let mut ctx = LEGACY_SESSION.create_execution_ctx();
175+
convert_columns(&[struct_arr.clone()], &[SortField::default()], &mut ctx).unwrap()
176+
})
177+
}

vortex-row/public-api.lock

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@@ -102,6 +102,12 @@ pub fn vortex_row::codec::field_size(&vortex_array::canonical::Canonical, vortex
102102

103103
pub fn vortex_row::codec::row_width_for_dtype(&vortex_array::dtype::DType) -> vortex_error::VortexResult<vortex_row::codec::RowWidth>
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105+
pub mod vortex_row::convert
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pub fn vortex_row::convert::compute_row_sizes(&[vortex_array::array::erased::ArrayRef], &[vortex_row::options::SortField], &mut vortex_array::executor::ExecutionCtx) -> vortex_error::VortexResult<vortex_array::array::erased::ArrayRef>
108+
109+
pub fn vortex_row::convert::convert_columns(&[vortex_array::array::erased::ArrayRef], &[vortex_row::options::SortField], &mut vortex_array::executor::ExecutionCtx) -> vortex_error::VortexResult<vortex_array::arrays::listview::vtable::ListViewArray>
110+
105111
pub mod vortex_row::encode
106112

107113
pub struct vortex_row::encode::RowEncode
@@ -410,4 +416,8 @@ pub trait vortex_row::RowSizeKernel: vortex_array::array::vtable::VTable
410416

411417
pub fn vortex_row::RowSizeKernel::row_size_contribution(vortex_array::array::view::ArrayView<'_, Self>, vortex_row::options::SortField, &mut [u32], &mut vortex_array::executor::ExecutionCtx) -> vortex_error::VortexResult<core::option::Option<()>>
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419+
pub fn vortex_row::compute_row_sizes(&[vortex_array::array::erased::ArrayRef], &[vortex_row::options::SortField], &mut vortex_array::executor::ExecutionCtx) -> vortex_error::VortexResult<vortex_array::array::erased::ArrayRef>
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pub fn vortex_row::convert_columns(&[vortex_array::array::erased::ArrayRef], &[vortex_row::options::SortField], &mut vortex_array::executor::ExecutionCtx) -> vortex_error::VortexResult<vortex_array::arrays::listview::vtable::ListViewArray>
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413423
pub fn vortex_row::initialize(&vortex_session::VortexSession)

vortex-row/src/convert.rs

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// SPDX-License-Identifier: Apache-2.0
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// SPDX-FileCopyrightText: Copyright the Vortex contributors
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//! User-facing entry point: turn N columnar arrays into one row-encoded `ListView<u8>`.
5+
6+
use vortex_array::ArrayRef;
7+
use vortex_array::ExecutionCtx;
8+
use vortex_array::arrays::ListViewArray;
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use vortex_array::scalar_fn::ScalarFnVTable;
10+
use vortex_array::scalar_fn::VecExecutionArgs;
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use vortex_error::VortexResult;
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use vortex_error::vortex_bail;
13+
14+
use crate::encode::RowEncode;
15+
use crate::options::RowEncodeOptions;
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use crate::options::SortField;
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use crate::size::RowSize;
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/// Convert N columnar arrays into a single row-oriented [`ListViewArray`] of `u8` whose
20+
/// bytes are lexicographically comparable in the same order as a tuple comparison of the
21+
/// input values according to `fields`.
22+
pub fn convert_columns(
23+
cols: &[ArrayRef],
24+
fields: &[SortField],
25+
ctx: &mut ExecutionCtx,
26+
) -> VortexResult<ListViewArray> {
27+
if cols.len() != fields.len() {
28+
vortex_bail!(
29+
"convert_columns: cols.len() ({}) does not match fields.len() ({})",
30+
cols.len(),
31+
fields.len()
32+
);
33+
}
34+
if cols.is_empty() {
35+
vortex_bail!("convert_columns: at least one column is required");
36+
}
37+
let nrows = cols[0].len();
38+
for (i, col) in cols.iter().enumerate() {
39+
if col.len() != nrows {
40+
vortex_bail!(
41+
"convert_columns: column {} has length {} but expected {}",
42+
i,
43+
col.len(),
44+
nrows
45+
);
46+
}
47+
}
48+
49+
let options = RowEncodeOptions::new(fields.iter().copied());
50+
let args = VecExecutionArgs::new(cols.to_vec(), nrows);
51+
let result = RowEncode.execute(&options, &args, ctx)?;
52+
result.execute::<ListViewArray>(ctx)
53+
}
54+
55+
/// Compute only the per-row sizes (in bytes) of the row-encoded form for N columns.
56+
pub fn compute_row_sizes(
57+
cols: &[ArrayRef],
58+
fields: &[SortField],
59+
ctx: &mut ExecutionCtx,
60+
) -> VortexResult<ArrayRef> {
61+
if cols.len() != fields.len() {
62+
vortex_bail!(
63+
"compute_row_sizes: cols.len() ({}) does not match fields.len() ({})",
64+
cols.len(),
65+
fields.len()
66+
);
67+
}
68+
if cols.is_empty() {
69+
vortex_bail!("compute_row_sizes: at least one column is required");
70+
}
71+
let nrows = cols[0].len();
72+
let options = RowEncodeOptions::new(fields.iter().copied());
73+
let args = VecExecutionArgs::new(cols.to_vec(), nrows);
74+
RowSize.execute(&options, &args, ctx)
75+
}

vortex-row/src/lib.rs

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@@ -3,23 +3,54 @@
33

44
//! Row-oriented byte encoder, analogous to Apache Arrow's `arrow-row` crate.
55
//!
6-
//! Subsequent commits add the encoder, decoder helpers, and per-encoding fast paths.
7-
//! This commit only establishes the crate skeleton and an `initialize` stub.
6+
//! The encoder converts N columnar arrays into a single `List<u8>` array where each row's
7+
//! bytes are lexicographically comparable in the same order as a tuple comparison of the
8+
//! original values. This is useful for sorting, hashing into row containers, and other
9+
//! operations that benefit from a sort-friendly opaque byte representation of a multi-column
10+
//! key.
11+
//!
12+
//! Two variadic scalar functions drive the implementation:
13+
//! - [`RowSize`] computes per-row byte sizes across all N input columns.
14+
//! - [`RowEncode`] writes the row-encoded bytes into a single `ListView<u8>` accumulator
15+
//! in one left-to-right pass.
16+
//!
17+
//! Each scalar function exposes a per-encoding fast-path trait
18+
//! ([`RowSizeKernel`] / [`RowEncodeKernel`]) for downstream encodings to plug into; PR 3
19+
//! adds in-crate impls for `Constant`, `Dict`, and `Patched` and an inventory-based
20+
//! registry for external encodings.
21+
//!
22+
//! The user-facing entry point is [`convert_columns`].
23+
//!
24+
//! Row-encoding scalar functions are not registered in the default
25+
//! [`VortexSession`]. Call [`initialize`] on a session to make `RowSize` and `RowEncode`
26+
//! available via the expression layer.
827
928
pub mod codec;
29+
pub mod convert;
1030
pub mod encode;
1131
pub mod options;
1232
pub mod size;
1333

34+
#[cfg(test)]
35+
mod tests;
36+
37+
pub use convert::compute_row_sizes;
38+
pub use convert::convert_columns;
1439
pub use encode::RowEncode;
1540
pub use encode::RowEncodeKernel;
1641
pub use options::RowEncodeOptions;
1742
pub use options::SortField;
1843
pub use size::RowSize;
1944
pub use size::RowSizeKernel;
45+
use vortex_array::scalar_fn::session::ScalarFnSessionExt;
2046
use vortex_session::VortexSession;
2147

22-
/// Register the row-encoding scalar functions on the given session.
48+
/// Register the row-encoding scalar functions ([`RowSize`] and [`RowEncode`]) on the given
49+
/// session.
2350
///
24-
/// Currently a stub: subsequent commits register `RowSize` and `RowEncode` here.
25-
pub fn initialize(_session: &VortexSession) {}
51+
/// Call once on session construction if you want row encoding available via the expression
52+
/// layer or via [`convert_columns`].
53+
pub fn initialize(session: &VortexSession) {
54+
session.scalar_fns().register(RowSize);
55+
session.scalar_fns().register(RowEncode);
56+
}

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