Struct ApiaryQueryContext 

pub struct ApiaryQueryContext { /* private fields */ }

The Apiary query context — wraps DataFusion with Apiary namespace resolution.

Implementations

impl ApiaryQueryContext

pub fn new( storage: Arc<dyn StorageBackend>, registry: Arc<RegistryManager>, ) -> ApiaryQueryContext

Create a new query context.

pub fn with_node_id( storage: Arc<dyn StorageBackend>, registry: Arc<RegistryManager>, node_id: NodeId, ) -> ApiaryQueryContext

Create a new query context with a specific node ID.

pub async fn sql( &mut self, query: &str, ) -> Result<Vec<RecordBatch>, ApiaryError>

Execute a SQL query and return results as RecordBatches.

pub async fn execute_distributed( &self, sql: &str, assignments: HashMap<NodeId, Vec<CellInfo>>, ) -> Result<Vec<RecordBatch>, ApiaryError>

Execute a query using distributed execution (stub for Step 7).

For v1, this is a simplified implementation that:

• Creates tasks from cell assignments
• Generates SQL fragments (simple pass-through)
• Writes the query manifest
• Executes local tasks
• Polls for partial results from other nodes
• Merges results (simple concatenation)
• Cleans up query files

pub async fn execute_task( &self, sql: &str, cell_keys: &[String], ) -> Result<Vec<RecordBatch>, ApiaryError>

Execute a task on a specific set of cells.

Arguments

• sql - The SQL query to execute
• cell_keys - Storage keys of cells to scan. Only these cells are registered as the table for the query, enabling true work partitioning across nodes.