akar_processor/processor/mapper/
map_scan.rs1use super::ExecutionContext;
2use crate::expression_evaluator::ExpressionEvaluator;
3use crate::physical_operator::*;
4use akar_common::error::ProcessorError;
5use akar_common::types::Value;
6use akar_common::vector::DataChunk;
7use akar_parser::ast::Expression;
8use akar_planner::logical_operator::{LogicalOperator, LogicalScanNode};
9use std::sync::{Arc, Mutex};
10
11fn extract_zone_map_predicate(expr: &Expression, columns: &[String]) -> Option<(usize, String, Value)> {
12 if let Expression::BinaryOp(op, left, right) = expr {
13 let op_str = match op {
14 akar_parser::ast::BinaryOp::Equal => "=",
15 akar_parser::ast::BinaryOp::GreaterThan => ">",
16 akar_parser::ast::BinaryOp::LessThan => "<",
17 akar_parser::ast::BinaryOp::GreaterThanOrEqual => ">=",
18 akar_parser::ast::BinaryOp::LessThanOrEqual => "<=",
19 akar_parser::ast::BinaryOp::NotEqual => "!=",
20 _ => return None,
21 };
22 if let Expression::Variable(var_name) = &**left {
23 if let Expression::Constant(c) = &**right {
24 let col_name = var_name.split('.').next_back().unwrap_or(var_name);
25 if let Some(col_idx) = columns.iter().position(|c| c == col_name) {
26 let val = match c {
27 akar_parser::ast::Constant::Integer(i) => Value::Int64(*i),
28 akar_parser::ast::Constant::Float(f) => Value::Double(*f),
29 akar_parser::ast::Constant::String(s) => Value::String(s.clone()),
30 akar_parser::ast::Constant::Bool(b) => Value::Bool(*b),
31 akar_parser::ast::Constant::Null => Value::Null,
32 };
33 return Some((col_idx, op_str.to_string(), val));
34 }
35 }
36 }
37 }
38 None
39}
40
41pub fn map_and_execute_scan_node(
42 s: &LogicalScanNode,
43 next_op: Option<&LogicalOperator>,
44 current_input: Vec<DataChunk>,
45 ctx: &mut ExecutionContext,
46) -> Result<Vec<DataChunk>, ProcessorError> {
47 let mut pred_owned = None;
48 if let Some(LogicalOperator::Filter(f)) = next_op {
49 pred_owned = extract_zone_map_predicate(&f.expression, &s.columns);
50 }
51
52 let pred_ref = pred_owned
53 .as_ref()
54 .map(|(idx, op_str, val)| (*idx, op_str.as_str(), val));
55
56 let (arrow_data, columns, arrow_num_rows) = ctx.resolve_scan_arrow_data(&s.table_name);
58 let mut scan = if let Some(arrays) = arrow_data {
59 PhysicalScan::new(s.table_name.clone(), s.table_id, arrow_num_rows.max(1)).with_arrow_data(arrays, columns)
60 } else {
61 let (data, fallback_columns, fallback_num_rows) = ctx.resolve_scan_data(&s.table_name, pred_ref);
63 let mut s = PhysicalScan::new(s.table_name.clone(), s.table_id, fallback_num_rows.max(1));
64 if let Some(d) = data {
65 s = s.with_data(d, fallback_columns);
66 }
67 s
68 };
69 if let Some(ref fq) = s.fts_query {
70 scan = scan.with_fts_query(PhysicalFtsScan {
71 index_name: fq.index_name.clone(),
72 query_string: fq.query_string.clone(),
73 table_name: fq.table_name.clone(),
74 column_name: fq.column_name.clone(),
75 table_catalog: ctx
76 .table_catalog
77 .clone()
78 .ok_or_else(|| "Table catalog required for FTS scan".to_string())?,
79 });
80 }
81 if let Some(ref pred) = s.predicate {
82 scan = scan.with_predicate(pred.clone());
83 let registry = ctx
84 .function_registry
85 .clone()
86 .ok_or_else(|| "No function registry available for predicate evaluation".to_string())?;
87 scan = scan.with_evaluator(Arc::new(Mutex::new(ExpressionEvaluator::new(registry))));
88 }
89 let mut result = scan.execute(current_input)?;
90 let prefix = s.alias.as_ref().unwrap_or(&s.table_name);
91
92 for chunk in &mut result {
93 chunk.field_names = chunk.field_names.iter().map(|n| format!("{}.{}", prefix, n)).collect();
94 }
95 Ok(result)
96}
97
98pub fn map_and_execute_scan(
99 op: &LogicalOperator,
100 current_input: Vec<DataChunk>,
101 ctx: &mut ExecutionContext,
102) -> Result<Vec<DataChunk>, ProcessorError> {
103 match op {
104 LogicalOperator::ScanRel(s) => {
105 let (data, columns, _num_rows) = ctx.resolve_scan_data(&s.table_name, None);
106 let scan = PhysicalScanRel {
107 table_name: s.table_name.clone(),
108 table_id: s.table_id,
109 direction: s.direction.clone(),
110 table_data: data,
111 table_columns: columns,
112 };
113 let mut result = scan.execute(current_input)?;
114 let prefix = &s.table_name;
115 for chunk in &mut result {
116 chunk.field_names = chunk.field_names.iter().map(|n| format!("{}.{}", prefix, n)).collect();
117 }
118 Ok(result)
119 }
120 LogicalOperator::VectorSimilarityScan(vs) => {
121 let tc = ctx
122 .table_catalog
123 .clone()
124 .ok_or_else(|| "No table catalog available for VECTOR SIMILARITY SCAN".to_string())?;
125 let index_name = {
129 let mut by_column = None;
130 let mut first_on_table = None;
131 for entry in tc.all_vector_indexes() {
132 if entry.table_name == vs.table_name {
133 if by_column.is_none() && entry.column_name == vs.column_name {
134 by_column = Some(entry.name.clone());
135 }
136 if first_on_table.is_none() {
137 first_on_table = Some(entry.name.clone());
138 }
139 }
140 }
141 by_column.or(first_on_table).ok_or_else(|| {
142 format!(
143 "No vector index found on table '{}' for column '{}'",
144 vs.table_name, vs.column_name
145 )
146 })?
147 };
148 let scan = PhysicalVectorSimilarityScan {
149 index_name,
150 index_id: 0,
151 query_vector: vs.query_vector.clone(),
152 top_k: vs.top_k,
153 table_name: vs.table_name.clone(),
154 table_catalog: Some(tc),
155 };
156 let mut result = scan.execute(current_input)?;
157 if let Some(alias) = &vs.alias {
162 for chunk in &mut result {
163 chunk.field_names = chunk.field_names.iter().map(|n| format!("{alias}.{n}")).collect();
164 }
165 }
166 Ok(result)
167 }
168 LogicalOperator::ArtIndexRangeScan(ars) => {
169 let scan = PhysicalArtIndexRangeScan {
170 table_name: ars.table_name.clone(),
171 table_id: ars.table_id,
172 lower_bound: ars.lower_bound.clone(),
173 upper_bound: ars.upper_bound.clone(),
174 lower_inclusive: ars.lower_inclusive,
175 upper_inclusive: ars.upper_inclusive,
176 table_catalog: ctx.table_catalog.clone(),
177 };
178 let mut result = scan.execute(current_input)?;
179 let prefix = ars.alias.as_ref().unwrap_or(&ars.table_name);
180 for chunk in &mut result {
181 chunk.field_names = chunk.field_names.iter().map(|n| format!("{}.{}", prefix, n)).collect();
182 }
183 Ok(result)
184 }
185 LogicalOperator::IndexLookup(il) => {
186 let table_catalog = ctx
187 .table_catalog
188 .clone()
189 .ok_or_else(|| "No table catalog available for INDEX LOOKUP".to_string())?;
190 let lookup_op = PhysicalIndexLookup {
191 table_name: il.table_name.clone(),
192 table_id: il.table_id,
193 key_value: il.key_value.clone(),
194 table_catalog,
195 };
196 let result = lookup_op.execute(current_input)?;
197 Ok(result)
198 }
199 LogicalOperator::ExpressionsScan(_es) => Ok(vec![DataChunk::new(vec![], vec![])]),
200 LogicalOperator::PathPropertyProbe(p) => {
201 let properties = p
202 .properties
203 .iter()
204 .map(|(t, is_node, props)| crate::physical::scan_filter::PathPropertySpec {
205 table_name: t.clone(),
206 is_node: *is_node,
207 property_names: props.clone(),
208 })
209 .collect();
210
211 let probe = crate::physical::scan_filter::PhysicalPathPropertyProbe {
212 node_ids_col_idx: p.node_ids_col_idx,
213 edge_ids_col_idx: p.edge_ids_col_idx,
214 properties,
215 table_catalog: ctx
216 .table_catalog
217 .clone()
218 .ok_or_else(|| "table catalog required for PathPropertyProbe".to_string())?,
219 };
220
221 let input = if !p.children.is_empty() {
222 ctx.execute_children(&p.children)?
223 } else {
224 current_input
225 };
226
227 let result = probe.execute(input)?;
228 Ok(result)
229 }
230 _ => Err(format!("Not a scan operator: {:?}", op).into()),
231 }
232}