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wifi-densepose/crates/ruvector-postgres/docs/GRAPH_QUICK_REFERENCE.md
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# Graph Operations Quick Reference
## Installation
```sql
CREATE EXTENSION ruvector_postgres;
```
## Graph Management
```sql
-- Create graph
SELECT ruvector_create_graph('my_graph');
-- List graphs
SELECT ruvector_list_graphs();
-- Get statistics
SELECT ruvector_graph_stats('my_graph');
-- Delete graph
SELECT ruvector_delete_graph('my_graph');
```
## Node Operations
```sql
-- Add node
SELECT ruvector_add_node(
'graph_name',
ARRAY['Label1', 'Label2'],
'{"property": "value"}'::jsonb
) AS node_id;
-- Get node
SELECT ruvector_get_node('graph_name', 1);
-- Find by label
SELECT ruvector_find_nodes_by_label('graph_name', 'Person');
```
## Edge Operations
```sql
-- Add edge
SELECT ruvector_add_edge(
'graph_name',
1, -- source_id
2, -- target_id
'RELATIONSHIP_TYPE',
'{"weight": 1.0}'::jsonb
) AS edge_id;
-- Get edge
SELECT ruvector_get_edge('graph_name', 1);
-- Get neighbors
SELECT ruvector_get_neighbors('graph_name', 1);
```
## Path Finding
```sql
-- Shortest path (unweighted)
SELECT ruvector_shortest_path(
'graph_name',
1, -- start_id
10, -- end_id
5 -- max_hops
);
-- Shortest path (weighted)
SELECT ruvector_shortest_path_weighted(
'graph_name',
1, -- start_id
10, -- end_id
'weight' -- property for weights
);
```
## Cypher Queries
### CREATE
```sql
-- Create node
SELECT ruvector_cypher(
'graph_name',
'CREATE (n:Person {name: ''Alice'', age: 30}) RETURN n',
NULL
);
-- Create relationship
SELECT ruvector_cypher(
'graph_name',
'CREATE (a:Person {name: ''Alice''})-[:KNOWS {since: 2020}]->(b:Person {name: ''Bob''}) RETURN a, b',
NULL
);
```
### MATCH
```sql
-- Match all nodes
SELECT ruvector_cypher(
'graph_name',
'MATCH (n:Person) RETURN n',
NULL
);
-- Match with WHERE
SELECT ruvector_cypher(
'graph_name',
'MATCH (n:Person) WHERE n.age > 25 RETURN n.name, n.age',
NULL
);
-- Parameterized query
SELECT ruvector_cypher(
'graph_name',
'MATCH (n:Person) WHERE n.name = $name RETURN n',
'{"name": "Alice"}'::jsonb
);
```
## Common Patterns
### Social Network
```sql
-- Setup
SELECT ruvector_create_graph('social');
-- Add users
SELECT ruvector_add_node('social', ARRAY['Person'],
jsonb_build_object('name', 'Alice', 'age', 30));
SELECT ruvector_add_node('social', ARRAY['Person'],
jsonb_build_object('name', 'Bob', 'age', 25));
-- Create friendship
SELECT ruvector_add_edge('social', 1, 2, 'FRIENDS',
'{"since": "2020-01-15"}'::jsonb);
-- Find path
SELECT ruvector_shortest_path('social', 1, 2, 10);
```
### Knowledge Graph
```sql
-- Setup
SELECT ruvector_create_graph('knowledge');
-- Add concepts with Cypher
SELECT ruvector_cypher('knowledge',
'CREATE (ml:Concept {name: ''Machine Learning''})
CREATE (dl:Concept {name: ''Deep Learning''})
CREATE (ml)-[:INCLUDES]->(dl)
RETURN ml, dl',
NULL
);
-- Query relationships
SELECT ruvector_cypher('knowledge',
'MATCH (a:Concept)-[:INCLUDES]->(b:Concept)
RETURN a.name, b.name',
NULL
);
```
### Recommendation
```sql
-- Setup
SELECT ruvector_create_graph('recommendations');
-- Add users and items
SELECT ruvector_cypher('recommendations',
'CREATE (u:User {name: ''Alice''})
CREATE (m:Movie {title: ''Inception''})
CREATE (u)-[:WATCHED {rating: 5}]->(m)
RETURN u, m',
NULL
);
-- Find similar users
SELECT ruvector_cypher('recommendations',
'MATCH (u1:User)-[:WATCHED]->(m:Movie)<-[:WATCHED]-(u2:User)
WHERE u1.name = ''Alice''
RETURN u2.name',
NULL
);
```
## Performance Tips
1. **Use labels for filtering**: Labels are indexed
2. **Limit hop count**: Specify reasonable max_hops
3. **Batch operations**: Use Cypher for multiple creates
4. **Property indexes**: Filter on indexed properties
5. **Parameterized queries**: Reuse query plans
## Return Value Formats
### Graph Stats
```json
{
"name": "my_graph",
"node_count": 100,
"edge_count": 250,
"labels": ["Person", "Movie"],
"edge_types": ["KNOWS", "WATCHED"]
}
```
### Path Result
```json
{
"nodes": [1, 3, 5, 10],
"edges": [12, 45, 78],
"length": 4,
"cost": 2.5
}
```
### Node
```json
{
"id": 1,
"labels": ["Person"],
"properties": {
"name": "Alice",
"age": 30
}
}
```
### Edge
```json
{
"id": 1,
"source": 1,
"target": 2,
"edge_type": "KNOWS",
"properties": {
"since": "2020-01-15",
"weight": 0.9
}
}
```
## Error Handling
```sql
-- Check if graph exists before operations
DO $$
BEGIN
IF 'my_graph' = ANY(ruvector_list_graphs()) THEN
-- Perform operations
RAISE NOTICE 'Graph exists';
ELSE
PERFORM ruvector_create_graph('my_graph');
END IF;
END $$;
-- Handle missing nodes
DO $$
DECLARE
result jsonb;
BEGIN
result := ruvector_get_node('my_graph', 999);
IF result IS NULL THEN
RAISE NOTICE 'Node not found';
END IF;
END $$;
```
## Best Practices
1. **Name graphs clearly**: Use descriptive names
2. **Use labels consistently**: Establish naming conventions
3. **Index frequently queried properties**: Plan for performance
4. **Batch similar operations**: Use Cypher for efficiency
5. **Clean up unused graphs**: Use delete_graph when done
6. **Monitor statistics**: Check graph_stats regularly
7. **Test queries**: Verify results before production
8. **Use parameters**: Prevent injection, enable caching
## Limitations
- **In-memory only**: No persistence across restarts
- **Single-node**: No distributed graph support
- **Simplified Cypher**: Basic patterns only
- **No transactions**: Operations are atomic but not grouped
- **No constraints**: No unique or foreign key constraints
## See Also
- [Full Documentation](README.md)
- [Implementation Details](GRAPH_IMPLEMENTATION.md)
- [SQL Examples](../sql/graph_examples.sql)
- [PostgreSQL Extension Docs](https://www.postgresql.org/docs/current/extend.html)