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vendor/ruvector/docs/research/sparql/IMPLEMENTATION_GUIDE.md
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# SPARQL PostgreSQL Implementation Guide
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**Project**: RuVector-Postgres SPARQL Extension
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**Date**: December 2025
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**Status**: Research Phase
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---
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## Overview
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This document outlines the implementation strategy for adding SPARQL query capabilities to RuVector-Postgres, enabling semantic graph queries alongside existing vector search operations.
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---
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## Architecture Overview
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### Components
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```
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┌─────────────────────────────────────────────────────────────┐
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│ SPARQL Interface │
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│ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │
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│ │ Query Parser │ │ Query Algebra│ │ SQL Generator│ │
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│ └──────────────┘ └──────────────┘ └──────────────┘ │
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└─────────────────────────────────────────────────────────────┘
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↓
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┌─────────────────────────────────────────────────────────────┐
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│ RDF Triple Store Layer │
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│ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │
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│ │ Triple Store │ │ Indexes │ │ Named Graphs │ │
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│ └──────────────┘ └──────────────┘ └──────────────┘ │
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└─────────────────────────────────────────────────────────────┘
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↓
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┌─────────────────────────────────────────────────────────────┐
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│ PostgreSQL Layer │
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│ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │
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│ │ Tables │ │ Indexes │ │ Functions │ │
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│ └──────────────┘ └──────────────┘ └──────────────┘ │
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└─────────────────────────────────────────────────────────────┘
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```
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---
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## Phase 1: Data Model
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### Triple Store Schema
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```sql
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-- Main triple store table
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CREATE TABLE ruvector_rdf_triples (
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id BIGSERIAL PRIMARY KEY,
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-- Subject
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subject TEXT NOT NULL,
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subject_type VARCHAR(10) NOT NULL CHECK (subject_type IN ('iri', 'bnode')),
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-- Predicate (always IRI)
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predicate TEXT NOT NULL,
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-- Object
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object TEXT NOT NULL,
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object_type VARCHAR(10) NOT NULL CHECK (object_type IN ('iri', 'literal', 'bnode')),
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object_datatype TEXT,
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object_language VARCHAR(20),
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-- Named graph (NULL = default graph)
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graph TEXT,
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-- Metadata
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created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
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modified_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
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);
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-- Indexes for all access patterns
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CREATE INDEX idx_rdf_spo ON ruvector_rdf_triples(subject, predicate, object);
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CREATE INDEX idx_rdf_pos ON ruvector_rdf_triples(predicate, object, subject);
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CREATE INDEX idx_rdf_osp ON ruvector_rdf_triples(object, subject, predicate);
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CREATE INDEX idx_rdf_graph ON ruvector_rdf_triples(graph) WHERE graph IS NOT NULL;
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CREATE INDEX idx_rdf_predicate ON ruvector_rdf_triples(predicate);
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-- Full-text search on literals
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CREATE INDEX idx_rdf_object_text ON ruvector_rdf_triples
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USING GIN(to_tsvector('english', object))
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WHERE object_type = 'literal';
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-- Namespace prefix mapping
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CREATE TABLE ruvector_rdf_namespaces (
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prefix VARCHAR(50) PRIMARY KEY,
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namespace TEXT NOT NULL UNIQUE,
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created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
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);
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-- Named graph metadata
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CREATE TABLE ruvector_rdf_graphs (
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graph_iri TEXT PRIMARY KEY,
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label TEXT,
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description TEXT,
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created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
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modified_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
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);
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```
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### Custom Types
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```sql
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-- RDF term type
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CREATE TYPE ruvector_rdf_term AS (
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value TEXT,
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term_type VARCHAR(10), -- 'iri', 'literal', 'bnode'
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datatype TEXT,
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language VARCHAR(20)
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);
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-- SPARQL result binding
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CREATE TYPE ruvector_sparql_binding AS (
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variable TEXT,
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term ruvector_rdf_term
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);
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```
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---
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## Phase 2: Core Functions
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### Basic RDF Operations
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```sql
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-- Add a triple
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CREATE FUNCTION ruvector_rdf_add_triple(
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subject TEXT,
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subject_type VARCHAR(10),
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predicate TEXT,
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object TEXT,
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object_type VARCHAR(10),
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object_datatype TEXT DEFAULT NULL,
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object_language VARCHAR(20) DEFAULT NULL,
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graph TEXT DEFAULT NULL
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) RETURNS BIGINT;
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-- Delete triples matching pattern
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CREATE FUNCTION ruvector_rdf_delete_triple(
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subject TEXT DEFAULT NULL,
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predicate TEXT DEFAULT NULL,
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object TEXT DEFAULT NULL,
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graph TEXT DEFAULT NULL
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) RETURNS INTEGER;
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-- Check if triple exists
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CREATE FUNCTION ruvector_rdf_has_triple(
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subject TEXT,
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predicate TEXT,
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object TEXT,
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graph TEXT DEFAULT NULL
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) RETURNS BOOLEAN;
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-- Get all triples for subject
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CREATE FUNCTION ruvector_rdf_get_triples(
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subject TEXT,
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graph TEXT DEFAULT NULL
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) RETURNS TABLE (
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predicate TEXT,
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object TEXT,
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object_type VARCHAR(10),
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object_datatype TEXT,
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object_language VARCHAR(20)
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);
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```
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### Namespace Management
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```sql
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-- Register namespace prefix
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CREATE FUNCTION ruvector_rdf_register_prefix(
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prefix VARCHAR(50),
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namespace TEXT
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) RETURNS VOID;
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-- Resolve prefixed name to IRI
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CREATE FUNCTION ruvector_rdf_expand_prefix(
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prefixed_name TEXT
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) RETURNS TEXT;
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-- Shorten IRI to prefixed name
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CREATE FUNCTION ruvector_rdf_compact_iri(
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iri TEXT
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) RETURNS TEXT;
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```
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---
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## Phase 3: SPARQL Query Engine
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### Query Execution
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```sql
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-- Execute SPARQL SELECT query
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CREATE FUNCTION ruvector_sparql_query(
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query TEXT,
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parameters JSONB DEFAULT NULL
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) RETURNS TABLE (
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bindings JSONB
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);
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-- Execute SPARQL ASK query
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CREATE FUNCTION ruvector_sparql_ask(
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query TEXT,
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parameters JSONB DEFAULT NULL
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) RETURNS BOOLEAN;
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-- Execute SPARQL CONSTRUCT query
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CREATE FUNCTION ruvector_sparql_construct(
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query TEXT,
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parameters JSONB DEFAULT NULL
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) RETURNS TABLE (
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subject TEXT,
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predicate TEXT,
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object TEXT,
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object_type VARCHAR(10)
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);
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-- Execute SPARQL DESCRIBE query
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CREATE FUNCTION ruvector_sparql_describe(
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resource TEXT,
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graph TEXT DEFAULT NULL
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) RETURNS TABLE (
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predicate TEXT,
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object TEXT,
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object_type VARCHAR(10)
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);
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```
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### Update Operations
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```sql
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-- Execute SPARQL UPDATE
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CREATE FUNCTION ruvector_sparql_update(
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update_query TEXT
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) RETURNS INTEGER;
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-- Bulk insert from N-Triples/Turtle
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CREATE FUNCTION ruvector_rdf_load(
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data TEXT,
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format VARCHAR(20), -- 'ntriples', 'turtle', 'rdfxml'
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graph TEXT DEFAULT NULL
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) RETURNS INTEGER;
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```
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---
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## Phase 4: Query Translation
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### SPARQL to SQL Translation Strategy
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#### 1. Basic Graph Pattern (BGP)
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**SPARQL:**
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```sparql
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?person foaf:name ?name .
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?person foaf:age ?age .
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```
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**SQL:**
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```sql
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SELECT
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t1.subject AS person,
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t1.object AS name,
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t2.object AS age
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FROM ruvector_rdf_triples t1
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JOIN ruvector_rdf_triples t2
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ON t1.subject = t2.subject
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WHERE t1.predicate = 'http://xmlns.com/foaf/0.1/name'
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AND t2.predicate = 'http://xmlns.com/foaf/0.1/age'
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AND t1.object_type = 'literal'
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AND t2.object_type = 'literal';
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||||
```
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||||
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||||
#### 2. OPTIONAL Pattern
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||||
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||||
**SPARQL:**
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```sparql
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?person foaf:name ?name .
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OPTIONAL { ?person foaf:email ?email }
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```
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**SQL:**
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||||
```sql
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SELECT
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t1.subject AS person,
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||||
t1.object AS name,
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t2.object AS email
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FROM ruvector_rdf_triples t1
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LEFT JOIN ruvector_rdf_triples t2
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ON t1.subject = t2.subject
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AND t2.predicate = 'http://xmlns.com/foaf/0.1/email'
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WHERE t1.predicate = 'http://xmlns.com/foaf/0.1/name';
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```
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#### 3. UNION Pattern
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||||
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||||
**SPARQL:**
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||||
```sparql
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{ ?x foaf:name ?name }
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UNION
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{ ?x rdfs:label ?name }
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```
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**SQL:**
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||||
```sql
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SELECT subject AS x, object AS name
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FROM ruvector_rdf_triples
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WHERE predicate = 'http://xmlns.com/foaf/0.1/name'
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UNION ALL
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SELECT subject AS x, object AS name
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FROM ruvector_rdf_triples
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WHERE predicate = 'http://www.w3.org/2000/01/rdf-schema#label';
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```
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#### 4. FILTER with Comparison
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||||
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**SPARQL:**
|
||||
```sparql
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?person foaf:age ?age .
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FILTER(?age >= 18 && ?age < 65)
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```
|
||||
|
||||
**SQL:**
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||||
```sql
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SELECT
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subject AS person,
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object AS age
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FROM ruvector_rdf_triples
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WHERE predicate = 'http://xmlns.com/foaf/0.1/age'
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AND object_type = 'literal'
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AND object_datatype = 'http://www.w3.org/2001/XMLSchema#integer'
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AND CAST(object AS INTEGER) >= 18
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AND CAST(object AS INTEGER) < 65;
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```
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|
||||
#### 5. Property Path (Transitive)
|
||||
|
||||
**SPARQL:**
|
||||
```sparql
|
||||
?person foaf:knows+ ?friend .
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||||
```
|
||||
|
||||
**SQL (with CTE):**
|
||||
```sql
|
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WITH RECURSIVE transitive AS (
|
||||
-- Base case: direct connections
|
||||
SELECT subject, object
|
||||
FROM ruvector_rdf_triples
|
||||
WHERE predicate = 'http://xmlns.com/foaf/0.1/knows'
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||||
|
||||
UNION
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||||
|
||||
-- Recursive case: follow chains
|
||||
SELECT t.subject, r.object
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FROM ruvector_rdf_triples t
|
||||
JOIN transitive r ON t.object = r.subject
|
||||
WHERE t.predicate = 'http://xmlns.com/foaf/0.1/knows'
|
||||
)
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||||
SELECT subject AS person, object AS friend
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||||
FROM transitive;
|
||||
```
|
||||
|
||||
#### 6. Aggregation with GROUP BY
|
||||
|
||||
**SPARQL:**
|
||||
```sparql
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SELECT ?company (COUNT(?employee) AS ?count) (AVG(?salary) AS ?avg)
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WHERE {
|
||||
?employee foaf:workplaceHomepage ?company .
|
||||
?employee ex:salary ?salary .
|
||||
}
|
||||
GROUP BY ?company
|
||||
HAVING (COUNT(?employee) >= 10)
|
||||
```
|
||||
|
||||
**SQL:**
|
||||
```sql
|
||||
SELECT
|
||||
t1.object AS company,
|
||||
COUNT(*) AS count,
|
||||
AVG(CAST(t2.object AS NUMERIC)) AS avg
|
||||
FROM ruvector_rdf_triples t1
|
||||
JOIN ruvector_rdf_triples t2
|
||||
ON t1.subject = t2.subject
|
||||
WHERE t1.predicate = 'http://xmlns.com/foaf/0.1/workplaceHomepage'
|
||||
AND t2.predicate = 'http://example.org/salary'
|
||||
AND t2.object_type = 'literal'
|
||||
GROUP BY t1.object
|
||||
HAVING COUNT(*) >= 10;
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Phase 5: Optimization
|
||||
|
||||
### Query Optimization Strategies
|
||||
|
||||
#### 1. Statistics Collection
|
||||
|
||||
```sql
|
||||
-- Predicate statistics
|
||||
CREATE TABLE ruvector_rdf_stats (
|
||||
predicate TEXT PRIMARY KEY,
|
||||
triple_count BIGINT,
|
||||
distinct_subjects BIGINT,
|
||||
distinct_objects BIGINT,
|
||||
avg_object_length NUMERIC,
|
||||
last_updated TIMESTAMP
|
||||
);
|
||||
|
||||
-- Update statistics
|
||||
CREATE FUNCTION ruvector_rdf_update_stats() RETURNS VOID AS $$
|
||||
BEGIN
|
||||
DELETE FROM ruvector_rdf_stats;
|
||||
|
||||
INSERT INTO ruvector_rdf_stats
|
||||
SELECT
|
||||
predicate,
|
||||
COUNT(*) as triple_count,
|
||||
COUNT(DISTINCT subject) as distinct_subjects,
|
||||
COUNT(DISTINCT object) as distinct_objects,
|
||||
AVG(LENGTH(object)) as avg_object_length,
|
||||
CURRENT_TIMESTAMP
|
||||
FROM ruvector_rdf_triples
|
||||
GROUP BY predicate;
|
||||
END;
|
||||
$$ LANGUAGE plpgsql;
|
||||
```
|
||||
|
||||
#### 2. Join Ordering
|
||||
|
||||
Use statistics to order joins by selectivity:
|
||||
1. Most selective (fewest results) first
|
||||
2. Predicates with fewer distinct values
|
||||
3. Literal objects before IRI objects
|
||||
|
||||
#### 3. Materialized Property Paths
|
||||
|
||||
```sql
|
||||
-- Materialize common transitive closures
|
||||
CREATE MATERIALIZED VIEW ruvector_rdf_knows_closure AS
|
||||
WITH RECURSIVE transitive AS (
|
||||
SELECT subject, object, 1 as depth
|
||||
FROM ruvector_rdf_triples
|
||||
WHERE predicate = 'http://xmlns.com/foaf/0.1/knows'
|
||||
|
||||
UNION
|
||||
|
||||
SELECT t.subject, r.object, r.depth + 1
|
||||
FROM ruvector_rdf_triples t
|
||||
JOIN transitive r ON t.object = r.subject
|
||||
WHERE t.predicate = 'http://xmlns.com/foaf/0.1/knows'
|
||||
AND r.depth < 10 -- Limit depth
|
||||
)
|
||||
SELECT * FROM transitive;
|
||||
|
||||
CREATE INDEX idx_knows_closure_so ON ruvector_rdf_knows_closure(subject, object);
|
||||
```
|
||||
|
||||
#### 4. Cached Queries
|
||||
|
||||
```sql
|
||||
-- Query cache
|
||||
CREATE TABLE ruvector_sparql_cache (
|
||||
query_hash TEXT PRIMARY KEY,
|
||||
query TEXT,
|
||||
plan JSONB,
|
||||
result JSONB,
|
||||
created_at TIMESTAMP,
|
||||
hit_count INTEGER DEFAULT 0,
|
||||
avg_exec_time INTERVAL
|
||||
);
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Phase 6: Integration with RuVector
|
||||
|
||||
### Hybrid Queries (SPARQL + Vector Search)
|
||||
|
||||
```sql
|
||||
-- Function to combine SPARQL with vector similarity
|
||||
CREATE FUNCTION ruvector_sparql_vector_search(
|
||||
sparql_query TEXT,
|
||||
embedding_predicate TEXT,
|
||||
query_vector ruvector,
|
||||
similarity_threshold FLOAT,
|
||||
top_k INTEGER
|
||||
) RETURNS TABLE (
|
||||
subject TEXT,
|
||||
bindings JSONB,
|
||||
similarity FLOAT
|
||||
);
|
||||
```
|
||||
|
||||
**Example Usage:**
|
||||
|
||||
```sql
|
||||
-- Find similar people based on semantic description
|
||||
SELECT * FROM ruvector_sparql_vector_search(
|
||||
'SELECT ?person ?name ?interests
|
||||
WHERE {
|
||||
?person foaf:name ?name .
|
||||
?person ex:interests ?interests .
|
||||
?person ex:embedding ?embedding .
|
||||
}',
|
||||
'http://example.org/embedding',
|
||||
'[0.15, 0.25, ...]'::ruvector,
|
||||
0.8,
|
||||
10
|
||||
);
|
||||
```
|
||||
|
||||
### Knowledge Graph + Vector Embeddings
|
||||
|
||||
```sql
|
||||
-- Store both RDF triples and embeddings
|
||||
INSERT INTO ruvector_rdf_triples (subject, predicate, object, object_type)
|
||||
VALUES
|
||||
('http://example.org/alice', 'http://xmlns.com/foaf/0.1/name', 'Alice', 'literal'),
|
||||
('http://example.org/alice', 'http://xmlns.com/foaf/0.1/age', '30', 'literal');
|
||||
|
||||
-- Add vector embedding using RuVector
|
||||
CREATE TABLE person_embeddings (
|
||||
person_iri TEXT PRIMARY KEY,
|
||||
embedding ruvector(384)
|
||||
);
|
||||
|
||||
INSERT INTO person_embeddings VALUES
|
||||
('http://example.org/alice', '[0.1, 0.2, ...]'::ruvector);
|
||||
|
||||
-- Query combining both
|
||||
SELECT
|
||||
r.subject AS person,
|
||||
r.object AS name,
|
||||
v.embedding <=> $1::ruvector AS similarity
|
||||
FROM ruvector_rdf_triples r
|
||||
JOIN person_embeddings v ON r.subject = v.person_iri
|
||||
WHERE r.predicate = 'http://xmlns.com/foaf/0.1/name'
|
||||
AND v.embedding <=> $1::ruvector < 0.5
|
||||
ORDER BY similarity
|
||||
LIMIT 10;
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Phase 7: Advanced Features
|
||||
|
||||
### 1. SPARQL Federation
|
||||
|
||||
Support for SERVICE keyword to query remote endpoints:
|
||||
|
||||
```sql
|
||||
CREATE FUNCTION ruvector_sparql_federated_query(
|
||||
query TEXT,
|
||||
remote_endpoints JSONB
|
||||
) RETURNS TABLE (bindings JSONB);
|
||||
```
|
||||
|
||||
### 2. Full-Text Search Integration
|
||||
|
||||
```sql
|
||||
-- SPARQL query with full-text search
|
||||
CREATE FUNCTION ruvector_sparql_text_search(
|
||||
search_term TEXT,
|
||||
language TEXT DEFAULT 'english'
|
||||
) RETURNS TABLE (
|
||||
subject TEXT,
|
||||
predicate TEXT,
|
||||
object TEXT,
|
||||
rank FLOAT
|
||||
);
|
||||
```
|
||||
|
||||
### 3. GeoSPARQL Support
|
||||
|
||||
```sql
|
||||
-- Spatial predicates
|
||||
CREATE FUNCTION ruvector_geo_within(
|
||||
point1 GEOMETRY,
|
||||
point2 GEOMETRY,
|
||||
distance_meters FLOAT
|
||||
) RETURNS BOOLEAN;
|
||||
```
|
||||
|
||||
### 4. Reasoning and Inference
|
||||
|
||||
```sql
|
||||
-- Simple RDFS entailment
|
||||
CREATE FUNCTION ruvector_rdf_infer_rdfs() RETURNS INTEGER;
|
||||
|
||||
-- Materialize inferred triples
|
||||
CREATE TABLE ruvector_rdf_inferred (
|
||||
LIKE ruvector_rdf_triples INCLUDING ALL,
|
||||
inference_rule TEXT
|
||||
);
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Implementation Roadmap
|
||||
|
||||
### Phase 1: Foundation (Weeks 1-2)
|
||||
- [ ] Design and implement triple store schema
|
||||
- [ ] Create basic RDF manipulation functions
|
||||
- [ ] Implement namespace management
|
||||
- [ ] Build indexes for all access patterns
|
||||
|
||||
### Phase 2: Parser (Weeks 3-4)
|
||||
- [ ] SPARQL 1.1 query parser (using Rust crate like `sparql-grammar`)
|
||||
- [ ] Parse PREFIX declarations
|
||||
- [ ] Parse SELECT, ASK, CONSTRUCT, DESCRIBE queries
|
||||
- [ ] Parse WHERE clauses with BGP, OPTIONAL, UNION, FILTER
|
||||
|
||||
### Phase 3: Algebra (Week 5)
|
||||
- [ ] Translate parsed queries to SPARQL algebra
|
||||
- [ ] Implement BGP, Join, LeftJoin, Union, Filter operators
|
||||
- [ ] Handle property paths
|
||||
- [ ] Support subqueries
|
||||
|
||||
### Phase 4: SQL Generation (Weeks 6-7)
|
||||
- [ ] Translate algebra to PostgreSQL SQL
|
||||
- [ ] Optimize join ordering using statistics
|
||||
- [ ] Generate CTEs for property paths
|
||||
- [ ] Handle aggregates and solution modifiers
|
||||
|
||||
### Phase 5: Query Execution (Week 8)
|
||||
- [ ] Execute generated SQL
|
||||
- [ ] Format results as JSON/XML/CSV/TSV
|
||||
- [ ] Implement result streaming for large datasets
|
||||
- [ ] Add query timeout and resource limits
|
||||
|
||||
### Phase 6: Update Operations (Week 9)
|
||||
- [ ] Implement INSERT DATA, DELETE DATA
|
||||
- [ ] Implement DELETE/INSERT with WHERE
|
||||
- [ ] Implement LOAD, CLEAR, CREATE, DROP
|
||||
- [ ] Transaction support for updates
|
||||
|
||||
### Phase 7: Optimization (Week 10)
|
||||
- [ ] Query result caching
|
||||
- [ ] Statistics-based query planning
|
||||
- [ ] Materialized property path views
|
||||
- [ ] Prepared statement support
|
||||
|
||||
### Phase 8: RuVector Integration (Week 11)
|
||||
- [ ] Hybrid SPARQL + vector similarity queries
|
||||
- [ ] Semantic search with knowledge graphs
|
||||
- [ ] Vector embeddings in RDF
|
||||
- [ ] Combined ranking (semantic + vector)
|
||||
|
||||
### Phase 9: Testing & Documentation (Week 12)
|
||||
- [ ] Unit tests for all components
|
||||
- [ ] Integration tests with W3C SPARQL test suite
|
||||
- [ ] Performance benchmarks
|
||||
- [ ] User documentation and examples
|
||||
|
||||
---
|
||||
|
||||
## Testing Strategy
|
||||
|
||||
### Unit Tests
|
||||
|
||||
```sql
|
||||
-- Test basic triple insertion
|
||||
DO $$
|
||||
DECLARE
|
||||
triple_id BIGINT;
|
||||
BEGIN
|
||||
triple_id := ruvector_rdf_add_triple(
|
||||
'http://example.org/alice',
|
||||
'iri',
|
||||
'http://xmlns.com/foaf/0.1/name',
|
||||
'Alice',
|
||||
'literal'
|
||||
);
|
||||
|
||||
ASSERT triple_id IS NOT NULL, 'Triple insertion failed';
|
||||
END $$;
|
||||
```
|
||||
|
||||
### W3C Test Suite
|
||||
|
||||
Implement tests from:
|
||||
- SPARQL 1.1 Query Test Cases
|
||||
- SPARQL 1.1 Update Test Cases
|
||||
- Property Path Test Cases
|
||||
|
||||
### Performance Benchmarks
|
||||
|
||||
```sql
|
||||
-- Benchmark query execution time
|
||||
CREATE FUNCTION benchmark_sparql_query(
|
||||
query TEXT,
|
||||
iterations INTEGER DEFAULT 100
|
||||
) RETURNS TABLE (
|
||||
avg_time INTERVAL,
|
||||
min_time INTERVAL,
|
||||
max_time INTERVAL,
|
||||
stddev_time INTERVAL
|
||||
);
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Documentation Structure
|
||||
|
||||
```
|
||||
docs/research/sparql/
|
||||
├── SPARQL_SPECIFICATION.md # Complete SPARQL 1.1 spec
|
||||
├── IMPLEMENTATION_GUIDE.md # This document
|
||||
├── API_REFERENCE.md # SQL function reference
|
||||
├── EXAMPLES.md # Usage examples
|
||||
├── PERFORMANCE_TUNING.md # Optimization guide
|
||||
└── MIGRATION_GUIDE.md # Migration from other triple stores
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Performance Targets
|
||||
|
||||
| Operation | Target | Notes |
|
||||
|-----------|--------|-------|
|
||||
| Simple BGP (3 patterns) | < 10ms | With proper indexes |
|
||||
| Complex query (joins + filters) | < 100ms | 1M triples |
|
||||
| Property path (depth 5) | < 500ms | 1M triples |
|
||||
| Aggregate query | < 200ms | GROUP BY over 100K groups |
|
||||
| INSERT DATA (1000 triples) | < 100ms | Bulk insert |
|
||||
| DELETE/INSERT (pattern) | < 500ms | Affects 10K triples |
|
||||
|
||||
---
|
||||
|
||||
## Security Considerations
|
||||
|
||||
1. **SQL Injection Prevention**: Parameterized queries only
|
||||
2. **Resource Limits**: Query timeout, memory limits
|
||||
3. **Access Control**: Row-level security on triple store
|
||||
4. **Audit Logging**: Log all UPDATE operations
|
||||
5. **Rate Limiting**: Prevent DoS via complex queries
|
||||
|
||||
---
|
||||
|
||||
## Dependencies
|
||||
|
||||
### Rust Crates
|
||||
|
||||
- `sparql-parser` or `oxigraph` - SPARQL parsing
|
||||
- `pgrx` - PostgreSQL extension framework
|
||||
- `serde_json` - JSON serialization
|
||||
- `regex` - FILTER regex support
|
||||
|
||||
### PostgreSQL Extensions
|
||||
|
||||
- `plpgsql` - Procedural language
|
||||
- `pg_trgm` - Trigram text search
|
||||
- `btree_gin` / `btree_gist` - Advanced indexing
|
||||
|
||||
---
|
||||
|
||||
## Future Enhancements
|
||||
|
||||
1. **SPARQL 1.2 Support**: When specification is finalized
|
||||
2. **SHACL Validation**: Shape constraint language
|
||||
3. **GraphQL Interface**: Map GraphQL to SPARQL
|
||||
4. **Streaming Updates**: Real-time triple stream processing
|
||||
5. **Distributed Queries**: Federate across multiple databases
|
||||
6. **Machine Learning**: Train embeddings from knowledge graph
|
||||
|
||||
---
|
||||
|
||||
## References
|
||||
|
||||
- [SPARQL Specification Document](./SPARQL_SPECIFICATION.md)
|
||||
- [RuVector PostgreSQL Extension](../../crates/ruvector-postgres/README.md)
|
||||
- [W3C SPARQL 1.1 Test Suite](https://www.w3.org/2009/sparql/docs/tests/)
|
||||
- [Apache Jena Documentation](https://jena.apache.org/documentation/query/)
|
||||
- [Oxigraph Implementation](https://github.com/oxigraph/oxigraph)
|
||||
|
||||
---
|
||||
|
||||
**Status**: Research Complete - Ready for Implementation
|
||||
|
||||
**Next Steps**:
|
||||
1. Review implementation guide with team
|
||||
2. Create GitHub issues for each phase
|
||||
3. Set up development environment
|
||||
4. Begin Phase 1 implementation
|
||||
Reference in New Issue
Block a user