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// SPDX-License-Identifier: BUSL-1.1
//! Columnar insert dispatcher: builds rows, applies ON CONFLICT semantics,
//! drives the per-row insert, flushes the memtable, updates spatial index.
use nodedb_columnar::MutationEngine;
use nodedb_types::columnar::ColumnType;
use nodedb_types::surrogate::Surrogate;
use nodedb_types::value::Value;
use crate::bridge::envelope::{ErrorCode, Payload, Response, Status};
use crate::bridge::physical_plan::ColumnarInsertIntent;
use crate::bridge::physical_plan::document::UpdateValue;
use crate::data::executor::core_loop::CoreLoop;
use crate::data::executor::handlers::upsert::apply_on_conflict_updates;
use crate::data::executor::response_codec;
use crate::data::executor::task::ExecutionTask;
use super::schema::{
infer_schema_from_value, ndb_field_to_value, prepend_bitemporal_columns, row_values_to_object,
};
impl CoreLoop {
/// Execute a columnar insert: write rows from MessagePack payload to
/// `MutationEngine`, applying intent-specific semantics on duplicate
/// PK (upsert-overwrite for `Insert` and `Put`, silent skip for
/// `InsertIfAbsent`, merge-via-`apply_on_conflict_updates` for `Put`
/// with non-empty `on_conflict_updates`).
#[allow(clippy::too_many_arguments)]
pub(in crate::data::executor) fn execute_columnar_insert(
&mut self,
task: &ExecutionTask,
collection: &str,
payload: &[u8],
_format: &str,
intent: ColumnarInsertIntent,
on_conflict_updates: &[(String, UpdateValue)],
surrogates: &[Surrogate],
) -> Response {
// Parse payload: msgpack-encoded nodedb_types::Value (array or object).
let ndb_rows: Vec<nodedb_types::Value> = match nodedb_types::value_from_msgpack(payload) {
Ok(nodedb_types::Value::Array(arr)) => arr,
Ok(v @ nodedb_types::Value::Object(_)) => vec![v],
Ok(_) => {
return self.response_error(
task,
ErrorCode::Internal {
detail: "columnar insert: payload must be array or object".into(),
},
);
}
Err(e) => {
return self.response_error(
task,
ErrorCode::Internal {
detail: format!("columnar insert: invalid payload: {e}"),
},
);
}
};
if ndb_rows.is_empty() {
return self.response_error(
task,
ErrorCode::Internal {
detail: "empty payload".into(),
},
);
}
let engine_key = (task.request.tenant_id, collection.to_string());
let tid = task.request.tenant_id.as_u64();
let bitemporal = self.is_bitemporal(tid, collection);
// Ensure MutationEngine exists (auto-create on first write).
if !self.columnar_engines.contains_key(&engine_key) {
let base_schema = infer_schema_from_value(&ndb_rows[0]);
let schema = if bitemporal {
prepend_bitemporal_columns(base_schema)
} else {
base_schema
};
let engine = MutationEngine::new(collection.to_string(), schema);
self.columnar_engines.insert(engine_key.clone(), engine);
}
let schema = match self.columnar_engines.get(&engine_key) {
Some(e) => e.schema().clone(),
None => {
return self.response_error(
task,
ErrorCode::Internal {
detail: "columnar engine missing after create".into(),
},
);
}
};
let mut accepted = 0u64;
for (row_idx, row) in ndb_rows.iter().enumerate() {
let obj = match row {
nodedb_types::Value::Object(m) => m,
_ => continue,
};
// Build Value slice in schema order. For bitemporal
// collections, the three reserved columns are auto-populated
// when absent from the user payload: `_ts_system` is always
// clamped to the current wall-clock time (clients cannot
// forge system time), `_ts_valid_from` / `_ts_valid_until`
// default to the open interval `[i64::MIN, i64::MAX)` if
// missing.
let sys_now = if bitemporal {
self.bitemporal_now_ms()
} else {
0
};
let values: Vec<Value> = match schema
.columns
.iter()
.map(|col| match col.name.as_str() {
"_ts_system" if bitemporal => Ok(Value::Integer(sys_now)),
"_ts_valid_from" if bitemporal => Ok(match obj.get("_ts_valid_from") {
Some(Value::Integer(i)) => Value::Integer(*i),
_ => Value::Integer(i64::MIN),
}),
"_ts_valid_until" if bitemporal => Ok(match obj.get("_ts_valid_until") {
Some(Value::Integer(i)) => Value::Integer(*i),
_ => Value::Integer(i64::MAX),
}),
_ => ndb_field_to_value(obj.get(&col.name), &col.column_type),
})
.collect::<Result<Vec<Value>, crate::Error>>()
{
Ok(v) => v,
Err(e) => {
return self.response_error(
task,
ErrorCode::Internal {
detail: format!("columnar insert coercion: {e}"),
},
);
}
};
// Resolve the actual row to write (merged for ON CONFLICT DO
// UPDATE, plain otherwise). This runs before the mutable
// engine borrow needed by the insert call.
let final_values: Vec<Value> = match intent {
ColumnarInsertIntent::Put if !on_conflict_updates.is_empty() => {
let pk_bytes = {
let engine = match self.columnar_engines.get(&engine_key) {
Some(e) => e,
None => {
return self.response_error(
task,
ErrorCode::Internal {
detail: "columnar engine vanished during insert".into(),
},
);
}
};
match engine.encode_pk_from_row(&values) {
Ok(b) => b,
Err(e) => {
return self.response_error(
task,
ErrorCode::Internal {
detail: format!("columnar insert: pk encode failed: {e}"),
},
);
}
}
};
let prior_row = self
.columnar_engines
.get(&engine_key)
.and_then(|e| e.lookup_memtable_row_by_pk(&pk_bytes))
.or_else(|| self.read_flushed_row_by_pk(&engine_key, &pk_bytes));
match prior_row {
None => values,
Some(prior) => {
let existing_val = row_values_to_object(&schema, &prior);
let excluded_val = row_values_to_object(&schema, &values);
let merged = apply_on_conflict_updates(
existing_val,
&excluded_val,
on_conflict_updates,
);
let merged_obj = match merged {
nodedb_types::Value::Object(m) => m,
_ => {
return self.response_error(
task,
ErrorCode::Internal {
detail: "merged ON CONFLICT value was not an object"
.into(),
},
);
}
};
match schema
.columns
.iter()
.map(|col| {
ndb_field_to_value(merged_obj.get(&col.name), &col.column_type)
})
.collect::<Result<Vec<Value>, crate::Error>>()
{
Ok(v) => v,
Err(e) => {
return self.response_error(
task,
ErrorCode::Internal {
detail: format!("columnar ON CONFLICT coercion: {e}"),
},
);
}
}
}
}
}
_ => values,
};
let engine = match self.columnar_engines.get_mut(&engine_key) {
Some(e) => e,
None => {
return self.response_error(
task,
ErrorCode::Internal {
detail: "columnar engine vanished during insert".into(),
},
);
}
};
let row_surrogate = surrogates.get(row_idx).copied();
let result = match intent {
ColumnarInsertIntent::InsertIfAbsent => engine.insert_if_absent(&final_values),
ColumnarInsertIntent::Insert | ColumnarInsertIntent::Put => match row_surrogate {
Some(s) => engine.insert_with_surrogate(&final_values, s),
None => engine.insert(&final_values),
},
};
match result {
Ok(_) => accepted += 1,
Err(e) => {
return self.response_error(
task,
ErrorCode::Internal {
detail: format!("columnar insert failed: {e}"),
},
);
}
}
}
let engine = match self.columnar_engines.get_mut(&engine_key) {
Some(e) => e,
None => {
return self.response_error(
task,
ErrorCode::Internal {
detail: "columnar engine missing after insert loop".into(),
},
);
}
};
// Flush memtable to a segment if the threshold has been reached.
if engine.should_flush() {
let new_segment_id = engine.next_segment_id();
let (schema, columns, row_count) = engine.memtable_mut().drain_optimized();
if row_count > 0 {
let kek = self.columnar_segment_kek.as_ref();
match nodedb_columnar::SegmentWriter::plain()
.write_segment(&schema, &columns, row_count, kek)
{
Ok(bytes) => {
self.columnar_flushed_segments
.entry(engine_key.clone())
.or_default()
.push(bytes);
tracing::debug!(
core = self.core_id,
%collection,
new_segment_id,
row_count,
"columnar memtable flushed and segment bytes retained in memory"
);
}
Err(e) => {
tracing::warn!(
core = self.core_id,
%collection,
error = %e,
"columnar segment encode failed; flushed rows may be lost"
);
}
}
}
if let Err(e) = engine.on_memtable_flushed(new_segment_id) {
return self.response_error(
task,
ErrorCode::Internal {
detail: format!("columnar flush: segment ID counter exhausted: {e}"),
},
);
}
}
// Populate R-tree for geometry columns so spatial predicates work.
{
let tid = task.request.tenant_id;
let schema = engine.schema().clone();
let geom_cols: Vec<usize> = schema
.columns
.iter()
.enumerate()
.filter(|(_, c)| c.column_type == ColumnType::Geometry)
.map(|(i, _)| i)
.collect();
if !geom_cols.is_empty() {
for row in &ndb_rows {
let obj = match row {
nodedb_types::Value::Object(m) => m,
_ => continue,
};
let doc_id = obj
.get("id")
.and_then(|v| v.as_str())
.unwrap_or("")
.to_string();
if doc_id.is_empty() {
continue;
}
for &col_idx in &geom_cols {
let col_def = &schema.columns[col_idx];
let field_val = match obj.get(&col_def.name) {
Some(v) => v,
None => continue,
};
// Geometry may be stored as Value::Geometry or Value::String (GeoJSON).
let geom: nodedb_types::geometry::Geometry = match field_val {
Value::Geometry(g) => g.clone(),
Value::String(s) => match sonic_rs::from_str(s) {
Ok(g) => g,
Err(_) => continue,
},
_ => continue,
};
let bbox = nodedb_types::bbox::geometry_bbox(&geom);
let index_key = (tid, collection.to_string(), col_def.name.clone());
let entry_id = crate::util::fnv1a_hash(doc_id.as_bytes());
let rtree = self.spatial_indexes.entry(index_key.clone()).or_default();
rtree.insert(crate::engine::spatial::RTreeEntry { id: entry_id, bbox });
self.spatial_doc_map.insert(
(tid, collection.to_string(), col_def.name.clone(), entry_id),
doc_id.clone(),
);
}
}
}
}
tracing::debug!(
core = self.core_id,
%collection,
accepted,
total = ndb_rows.len(),
"columnar insert complete"
);
self.checkpoint_coordinator
.mark_dirty("columnar", accepted as usize);
let result = serde_json::json!({
"accepted": accepted,
"collection": collection,
});
let json = match response_codec::encode_json(&result) {
Ok(b) => b,
Err(e) => {
return self.response_error(
task,
ErrorCode::Internal {
detail: e.to_string(),
},
);
}
};
Response {
request_id: task.request.request_id,
status: Status::Ok,
attempt: 1,
partial: false,
payload: Payload::from_vec(json),
watermark_lsn: self.watermark,
error_code: None,
}
}
}