Method execute_sparse_insert

nodedb/src/data/executor/handlers/vector_sparse.rs:45–80

Insert a sparse vector for a document.

(
        &mut self,
        task: &ExecutionTask,
        tid: u64,
        collection: &str,
        field_name: &str,
        doc_id: &str,
        entries: &[(u32, f32)],
    )

    /// Insert a sparse vector for a document.
    pub(in crate::data::executor) fn execute_sparse_insert(
        &mut self,
        task: &ExecutionTask,
        tid: u64,
        collection: &str,
        field_name: &str,
        doc_id: &str,
        entries: &[(u32, f32)],
    ) -> Response {
        debug!(
            core = self.core_id,
            %collection,
            %field_name,
            %doc_id,
            nnz = entries.len(),
            "sparse insert"
        );

        let sv = match nodedb_types::SparseVector::from_entries(entries.to_vec()) {
            Ok(sv) => sv,
            Err(e) => {
                return self.response_error(
                    task,
                    ErrorCode::RejectedConstraint {
                        detail: String::new(),
                        constraint: e.to_string(),
                    },
                );
            }
        };

        let index = self.get_or_create_sparse_index(tid, collection, field_name);
        index.insert(doc_id, &sv);
        self.checkpoint_coordinator.mark_dirty("vector", 1);
        self.response_ok(task)
    }

    /// Search the sparse inverted index via dot-product scoring.
    pub(in crate::data::executor) fn execute_sparse_search(