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Merged
pull merged 2 commits into from
May 7, 2026
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[pull] master from cube-js:master #456

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10f249e
chore(tesseract): Split member symbol business model and SQL renderin…
waralexrom May 7, 2026
1a64945
perf(cubeorchestrator): Use columnar format between JS->Rust data tra…
ovr May 7, 2026
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35 changes: 1 addition & 34 deletions packages/cubejs-api-gateway/src/gateway.ts
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Original file line number Diff line number Diff line change
Expand Up @@ -19,6 +19,7 @@ import {
ResultArrayWrapper,
ResultMultiWrapper,
ResultWrapper,
rowsToColumnar,
} from '@cubejs-backend/native';
import type {
Application as ExpressApplication,
Expand Down Expand Up @@ -129,40 +130,6 @@ function systemAsyncHandler(handler: (req: Request & { context: ExtendedRequestC
};
}

function rowsToColumnar(rawData: any): { members: string[]; columns: any[][] } {
let rows: any[];

if (Array.isArray(rawData)) {
rows = rawData;
} else if (rawData) {
rows = Array.from(rawData as Iterable<any>);
} else {
rows = [];
}

const rowCount = rows.length;
if (rowCount === 0) {
return { members: [], columns: [] };
}

const members = Object.keys(rows[0]);
const memberCount = members.length;
const columns: any[][] = new Array(memberCount);

for (let j = 0; j < memberCount; j++) {
const member = members[j];
const col = new Array(rowCount);

for (let i = 0; i < rowCount; i++) {
col[i] = rows[i][member];
}

columns[j] = col;
}

return { members, columns };
}

// Prepared CheckAuthFn, default or from config: always async
type PreparedCheckAuthFn = (ctx: any, authorization?: string) => Promise<{
securityContext: any;
Expand Down
52 changes: 48 additions & 4 deletions packages/cubejs-backend-native/js/ResultWrapper.ts
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Original file line number Diff line number Diff line change
Expand Up @@ -15,6 +15,45 @@ export interface DataResult {
getResults(): ResultWrapper[];
}

export interface JsRawColumnarData {
members: string[];
columns: any[][];
}

export function rowsToColumnar(rawData: any): JsRawColumnarData {
let rows: any[];

if (Array.isArray(rawData)) {
rows = rawData;
} else if (rawData) {
rows = Array.from(rawData as Iterable<any>);
} else {
rows = [];
}

const rowCount = rows.length;
if (rowCount === 0) {
return { members: [], columns: [] };
}

const members = Object.keys(rows[0]);
const memberCount = members.length;
const columns: any[][] = new Array(memberCount);

for (let j = 0; j < memberCount; j++) {
const member = members[j];
const col = new Array(rowCount);

for (let i = 0; i < rowCount; i++) {
col[i] = rows[i][member];
}

columns[j] = col;
}

return { members, columns };
}

class BaseWrapper {
public readonly isWrapper: boolean = true;
}
Expand Down Expand Up @@ -140,14 +179,19 @@ export class ResultWrapper extends BaseWrapper implements DataResult {
return [this.nativeReference];
}

// Pivot to columnar before serializing: the row-oriented form repeats
// every column name on every row, which inflates JSON size and forces
// the Rust side to allocate a per-row map before transposing back to
// its native columnar `QueryResult` representation.
//
// Serialize to a Buffer so the Rust side can decode via
// serde_json::from_slice instead of walking a JsArray through the
// serde_json::from_slice instead of walking a JsValue through the
// Neon bridge with JsValueDeserializer. On 5 MB of AoO rows
// (~21k rows × 8 fields) the JsArray walk costs ~80 ms locally;
// (~21k rows × 8 fields) the JsValue walk costs ~80 ms locally;
// Buffer + serde_json is ~7× faster (M3 MAX) and tracks V8's JSON.parse
// (~11 ms on the same payload). On a real server it should be 3-6× slower,
// so avoiding the JsArray walk matters even more there.
return [Buffer.from(JSON.stringify(this.jsResult))];
// so avoiding the JsValue walk matters even more there.
return [Buffer.from(JSON.stringify(rowsToColumnar(this.jsResult)))];
}

public setTransformData(td: any) {
Expand Down
69 changes: 24 additions & 45 deletions packages/cubejs-backend-native/src/orchestrator.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -5,7 +5,7 @@ use cubeorchestrator::query_result_transform::{
DBResponsePrimitive, DBResponseValue, RequestResultData, RequestResultDataMulti,
TransformedData,
};
use cubeorchestrator::transport::{JsRawData, TransformDataRequest};
use cubeorchestrator::transport::{JsRawColumnarData, TransformDataRequest};
use cubesql::compile::engine::df::scan::{ColumnarValueObject, FieldValue, ValueObject};
use cubesql::CubeError;
use neon::context::{Context, FunctionContext, ModuleContext};
Expand Down Expand Up @@ -87,41 +87,27 @@ impl ResultWrapper {

let raw_data_js = raw_data_js_arr.first().unwrap();

let query_result =
if let Ok(js_box) = raw_data_js.downcast::<JsBox<Arc<QueryResult>>, _>(cx) {
Arc::clone(&js_box)
} else if let Ok(js_buffer) = raw_data_js.downcast::<JsBuffer, _>(cx) {
let bytes = js_buffer.as_slice(cx);
let js_raw_data: JsRawData = serde_json::from_slice(bytes).map_err(|e| {
CubeError::internal(format!(
"Can't parse raw data JSON from JS ResultWrapper: {}",
e
))
})?;

QueryResult::from_js_raw_data(js_raw_data)
.map(Arc::new)
.map_cube_err("Can't build results data from JS rawData")?
} else if let Ok(js_array) = raw_data_js.downcast::<JsArray, _>(cx) {
let deserializer = JsValueDeserializer::new(cx, js_array.upcast());
let js_raw_data: JsRawData = match Deserialize::deserialize(deserializer) {
Ok(data) => data,
Err(_) => {
return Err(CubeError::internal(
"Can't deserialize results raw data from JS ResultWrapper object"
.to_string(),
));
}
};
let query_result = if let Ok(js_box) =
raw_data_js.downcast::<JsBox<Arc<QueryResult>>, _>(cx)
{
Arc::clone(&js_box)
} else if let Ok(js_buffer) = raw_data_js.downcast::<JsBuffer, _>(cx) {
let bytes = js_buffer.as_slice(cx);
let js_raw_data: JsRawColumnarData = serde_json::from_slice(bytes).map_err(|e| {
CubeError::internal(format!(
"Can't parse raw data JSON from JS ResultWrapper: {}",
e
))
})?;

QueryResult::from_js_raw_data(js_raw_data)
.map(Arc::new)
.map_cube_err("Can't build results data from JS rawData")?
} else {
return Err(CubeError::internal(
"Can't deserialize results raw data from JS ResultWrapper object".to_string(),
));
};
QueryResult::from_js_raw_data(js_raw_data)
.map(Arc::new)
.map_cube_err("Can't build results data from JS rawData")?
} else {
return Err(CubeError::internal(
"Can't deserialize results raw data from JS ResultWrapper object".to_string(),
));
};

Ok(Self {
transform_data: transform_request,
Expand Down Expand Up @@ -315,21 +301,14 @@ fn extract_query_result(
Ok(Arc::clone(&js_box))
} else if let Ok(js_buffer) = data_arg.downcast::<JsBuffer, _>(cx) {
let bytes = js_buffer.as_slice(cx);
let js_raw_data: JsRawData = serde_json::from_slice(bytes)?;

QueryResult::from_js_raw_data(js_raw_data)
.map(Arc::new)
.map_err(anyhow::Error::from)
} else if let Ok(js_array) = data_arg.downcast::<JsArray, _>(cx) {
let deserializer = JsValueDeserializer::new(cx, js_array.upcast());
let js_raw_data: JsRawData = Deserialize::deserialize(deserializer)?;
let js_raw_data: JsRawColumnarData = serde_json::from_slice(bytes)?;

QueryResult::from_js_raw_data(js_raw_data)
.map(Arc::new)
.map_err(anyhow::Error::from)
} else {
Err(anyhow::anyhow!(
"Second argument must be an Array of JsBox<Arc<QueryResult>> or JsArray"
"Second argument must be a JsBox<Arc<QueryResult>> or a JsBuffer with columnar JsRawColumnarData JSON"
))
}
}
Expand Down Expand Up @@ -357,7 +336,7 @@ pub fn get_cubestore_result(mut cx: FunctionContext) -> JsResult<JsValue> {
for (i, row) in result.rows.iter().enumerate() {
let js_row = cx.execute_scoped(|mut cx| {
let js_row = JsObject::new(&mut cx);
for (key, value) in result.columns.iter().zip(row.iter()) {
for (key, value) in result.members.iter().zip(row.iter()) {
let js_key = cx.string(key);
let js_value: Handle<'_, JsValue> = match value {
DBResponseValue::Primitive(DBResponsePrimitive::Null) => cx.null().upcast(),
Expand Down
124 changes: 95 additions & 29 deletions rust/cube/cubeorchestrator/benches/transform.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -5,10 +5,9 @@ use criterion::{criterion_group, criterion_main, BenchmarkId, Criterion, Through
use cubeorchestrator::query_message_parser::QueryResult;
use cubeorchestrator::query_result_transform::{DBResponsePrimitive, TransformedData};
use cubeorchestrator::transport::{
ConfigItem, JsRawData, MemberOrMemberExpression, NormalizedQuery, QueryType, ResultType,
TransformDataRequest,
ConfigItem, JsRawColumnarData, MemberOrMemberExpression, NormalizedQuery, QueryType,
ResultType, TransformDataRequest,
};
use indexmap::IndexMap;

const ROW_COUNTS: &[usize] = &[1_000, 10_000, 50_000, 100_000];
const COLUMN_COUNTS: &[usize] = &[8, 16, 32, 64];
Expand Down Expand Up @@ -171,40 +170,48 @@ fn build_dataset(
dimensions: &[(String, String)],
measures: &[(String, String)],
time_dims: &[TimeColumn],
) -> JsRawData {
) -> JsRawColumnarData {
let total_cols = dimensions.len() + measures.len() + time_dims.len();
let mut rows = Vec::with_capacity(row_count);

for i in 0..row_count {
let mut row = IndexMap::with_capacity(total_cols);
for (j, (_, alias)) in dimensions.iter().enumerate() {
row.insert(
alias.clone(),
DBResponsePrimitive::String(format!("dim_{}_{}", j, i % 1000)),
);
let mut members = Vec::with_capacity(total_cols);
let mut columns: Vec<Vec<DBResponsePrimitive>> = Vec::with_capacity(total_cols);

for (j, (_, alias)) in dimensions.iter().enumerate() {
members.push(alias.clone());
let mut col = Vec::with_capacity(row_count);
for i in 0..row_count {
col.push(DBResponsePrimitive::String(format!(
"dim_{}_{}",
j,
i % 1000
)));
}
for (j, (_, alias)) in measures.iter().enumerate() {
row.insert(
alias.clone(),
DBResponsePrimitive::Number(((i * (j + 1)) as f64) * 0.5),
);
columns.push(col);
}
for (j, (_, alias)) in measures.iter().enumerate() {
members.push(alias.clone());
let mut col = Vec::with_capacity(row_count);
for i in 0..row_count {
col.push(DBResponsePrimitive::Number(((i * (j + 1)) as f64) * 0.5));
}
for (j, td) in time_dims.iter().enumerate() {
columns.push(col);
}
for (j, td) in time_dims.iter().enumerate() {
members.push(td.alias.clone());
let mut col = Vec::with_capacity(row_count);
for i in 0..row_count {
// Format mirrors typical CubeStore output: ISO-8601 with millisecond
// fractional and no timezone. None of `transform_value`'s six chrono
// parsers fully match this shape, so the function falls through to
// `s.clone()` — measuring the production worst case.
// fractional and no timezone.
let month = ((i + j) % 12) + 1;
let day = ((i / 12) % 28) + 1;
row.insert(
td.alias.clone(),
DBResponsePrimitive::String(format!("2024-{:02}-{:02}T00:00:00.000", month, day)),
);
col.push(DBResponsePrimitive::String(format!(
"2024-{:02}-{:02}T00:00:00.000",
month, day
)));
}
rows.push(row);
columns.push(col);
}

rows
JsRawColumnarData { members, columns }
}

fn bench_transform(c: &mut Criterion) {
Expand Down Expand Up @@ -305,5 +312,64 @@ fn bench_transform_time_scenarios(c: &mut Criterion) {
group.finish();
}

criterion_group!(benches, bench_transform, bench_transform_time_scenarios);
/// Bench the JS→Rust raw-data ingest path: `serde_json::from_slice` then
/// `QueryResult::from_js_raw_data`. This is the part of the pipeline that the
/// columnar wire format change actually touches; `bench_transform` above
/// consumes an already-built `QueryResult` and is unaffected.
fn bench_from_js_raw_data(c: &mut Criterion) {
let mut group = c.benchmark_group("QueryResult::from_js_raw_data");

let combos: &[(usize, usize)] = &[(8, 10_000), (16, 10_000), (16, 100_000), (32, 100_000)];

for &(col_count, row_count) in combos {
let (dim_count, measure_count) = split_dim_measure(col_count);
let dimensions = make_member_aliases("dim", dim_count);
let measures = make_member_aliases("measure", measure_count);

let dataset = build_dataset(row_count, &dimensions, &measures, &[]);
let payload = serde_json::to_vec(&dataset).expect("to_vec");
let payload_len = payload.len();

eprintln!(
"from_js_raw_data: c{:02}_r{} payload_bytes={}",
col_count, row_count, payload_len
);

group.throughput(Throughput::Elements((row_count * col_count) as u64));

let id_param = format!("c{:02}_r{}", col_count, row_count);

// Parse only: serde_json::from_slice into the wire type.
group.bench_with_input(BenchmarkId::new("parse_only", &id_param), &(), |b, _| {
b.iter(|| {
let parsed: JsRawColumnarData =
serde_json::from_slice(black_box(&payload)).expect("from_slice");
black_box(parsed);
});
});

// End-to-end: parse + transpose into QueryResult — what the Neon bridge does.
group.bench_with_input(
BenchmarkId::new("parse_plus_build", &id_param),
&(),
|b, _| {
b.iter(|| {
let parsed: JsRawColumnarData =
serde_json::from_slice(black_box(&payload)).expect("from_slice");
let built = QueryResult::from_js_raw_data(parsed).expect("from_js_raw_data");
black_box(built);
});
},
);
}

group.finish();
}

criterion_group!(
benches,
bench_transform,
bench_transform_time_scenarios,
bench_from_js_raw_data
);
criterion_main!(benches);
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