Add comprehensive vector search testing guide

- Complete step-by-step testing procedures for ProxySQL SQLite3 server vector search
- Includes connectivity testing, vector table creation, data insertion, and similarity search
- Provides practical use case examples (product recommendations, user sessions)
- Includes performance testing and error handling scenarios
- Contains Python vector generator and shell test scripts
- Detailed troubleshooting section and expected results
- Suitable for both ProxySQL developers and users
- Enables reproducible testing of sqlite-vec integration

File: doc/Vector-Search-Testing-Guide.md (9,718 lines)
pull/5310/head
Rene Cannao 5 months ago
parent a1dc68833c
commit d4f8385197

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# ProxySQL SQLite3 Server Vector Search Testing Guide
## Table of Contents
1. [Prerequisites](#prerequisites)
2. [Environment Setup](#environment-setup)
3. [Testing Tools](#testing-tools)
4. [Step-by-Step Testing Procedures](#step-by-step-testing-procedures)
5. [Advanced Testing Scenarios](#advanced-testing-scenarios)
6. [Troubleshooting](#troubleshooting)
7. [Expected Results](#expected-results)
8. [Additional Resources](#additional-resources)
## Overview
This guide provides comprehensive step-by-step instructions for testing the vector search capabilities in ProxySQL's SQLite3 server. The testing covers connectivity verification, vector table creation, data insertion, similarity searches, and practical use cases.
**Target Audience**: ProxySQL developers, database administrators, and users who want to verify vector search functionality.
**Prerequisites**:
- ProxySQL built with sqlite-vec support and running with `--sqlite3-server`
- MySQL client tools installed
- Basic knowledge of SQL and vector concepts
---
## Prerequisites
### System Requirements
- ProxySQL version with sqlite-vec integration (v3.1-vec1 or later)
- MySQL client (mysql command line tool)
- Standard Linux/Unix environment
### ProxySQL Configuration
Ensure ProxySQL is running with SQLite3 server enabled:
```bash
# Check if ProxySQL is running
ps aux | grep proxysql
# Check if SQLite3 server is listening on port 6030
netstat -tlnp | grep 6030
# Check logs for any startup errors
tail -f /var/log/proxysql.log
```
---
## Environment Setup
### 1. Test Environment Preparation
```bash
# Create a dedicated testing directory
mkdir -p ~/proxysql-vector-test
cd ~/proxysql-vector-test
# Create a test script file
cat > test_vector_search.sh << 'EOF'
#!/bin/bash
# Test script for ProxySQL vector search functionality
# This script performs comprehensive testing of sqlite-vec integration
set -e
echo "=== ProxySQL Vector Search Testing Script ==="
echo "Starting at: $(date)"
echo ""
# Configuration
PROXYSQL_HOST="127.0.0.1"
PROXYSQL_PORT="6030"
MYSQL_USER="root"
MYSQL_PASS="root"
# Test results tracking
PASSED=0
FAILED=0
# Function to execute MySQL query and handle results
execute_test() {
local test_name="$1"
local sql_query="$2"
local expected="$3"
echo "Testing: $test_name"
echo "Query: $sql_query"
# Execute query and capture results
result=$(mysql -h "$PROXYSQL_HOST" -P "$PROXYSQL_PORT" -u "$MYSQL_USER" -p"$MYSQL_PASS" -s -N -e "$sql_query" 2>&1)
local exit_code=$?
if [ $exit_code -eq 0 ]; then
echo "✅ SUCCESS: $test_name"
echo "Result: $result"
((PASSED++))
else
echo "❌ FAILED: $test_name"
echo "Error: $result"
((FAILED++))
fi
echo "----------------------------------------"
echo ""
}
# Main testing logic starts here
EOF
# Make script executable
chmod +x test_vector_search.sh
```
### 2. Python Testing Tools
Create a Python script for more complex vector operations:
```python
# Create vector_generator.py
cat > vector_generator.py << 'EOF'
#!/usr/bin/env python3
"""
Vector Generator for ProxySQL Vector Search Testing
Generates test vectors of various dimensions and formats
"""
import json
import random
import math
import sys
class VectorGenerator:
"""Generate test vectors for vector search testing"""
def __init__(self, dimension=128):
self.dimension = dimension
def generate_unit_vector(self, position=None):
"""Generate a unit vector with 1.0 at specified position"""
if position is None:
position = random.randint(0, self.dimension - 1)
vector = [0.0] * self.dimension
vector[position] = 1.0
return vector
def generate_random_vector(self, sparsity=0.1):
"""Generate a random vector with specified sparsity"""
vector = [0.0] * self.dimension
num_non_zero = int(self.dimension * sparsity)
for _ in range(num_non_zero):
idx = random.randint(0, self_dimension - 1)
value = random.uniform(0.1, 1.0)
vector[idx] = value
return vector
def generate_similar_vector(self, original_vector, similarity=0.9):
"""Generate a vector similar to the original"""
new_vector = original_vector.copy()
# Add small random perturbations
for i in range(self.dimension):
if random.random() < 0.3: # 30% of dimensions get modified
perturbation = random.uniform(-0.1, 0.1)
new_vector[i] = max(0.0, new_vector[i] + perturbation)
# Normalize to maintain approximate magnitude
magnitude = math.sqrt(sum(x*x for x in new_vector))
if magnitude > 0:
new_vector = [x/magnitude for x in new_vector]
return new_vector
def vector_to_json(self, vector):
"""Convert vector to JSON string format for SQL"""
return json.dumps(vector)
def generate_test_set(self, count=10):
"""Generate a diverse set of test vectors"""
vectors = []
# Add unit vectors
for i in range(min(3, self.dimension)):
vectors.append({
'id': i + 1,
'type': 'unit',
'vector': self.generate_unit_vector(i),
'description': f'Unit vector with 1.0 at position {i}'
})
# Add random vectors
for i in range(count - 3):
vectors.append({
'id': i + 4,
'type': 'random',
'vector': self.generate_random_vector(),
'description': f'Random vector #{i+1}'
})
return vectors
def main():
if len(sys.argv) < 2:
print("Usage: python3 vector_generator.py <dimension> [count]")
sys.exit(1)
dimension = int(sys.argv[1])
count = int(sys.argv[2]) if len(sys.argv) > 2 else 10
generator = VectorGenerator(dimension)
test_vectors = generator.generate_test_set(count)
print(f"Generated {len(test_vectors)} test vectors of {dimension} dimensions:")
print("-" * 60)
for vec in test_vectors:
print(f"ID: {vec['id']}")
print(f"Type: {vec['type']}")
print(f"Description: {vec['description']}")
print(f"Vector: {generator.vector_to_json(vec['vector'])[:100]}...")
print()
if __name__ == "__main__":
main()
EOF
# Make Python script executable
chmod +x vector_generator.py
```
---
## Testing Tools
### 1. MySQL Command Line Client
The primary tool for testing is the standard MySQL client:
```bash
# Basic connection test
mysql -h 127.0.0.1 -P 6030 -u root -proot -e "SELECT 1 as connectivity_test;"
```
### 2. Comprehensive Test Script
Create an enhanced test script with more comprehensive checks:
```bash
# Enhanced test script
cat > comprehensive_test.sh << 'EOF'
#!/bin/bash
# Comprehensive ProxySQL Vector Search Testing Script
# Tests all aspects of sqlite-vec integration
PROXYSQL_HOST="127.0.0.1"
PROXYSQL_PORT="6030"
MYSQL_USER="root"
MYSQL_PASS="root"
LOG_FILE="vector_test_$(date +%Y%m%d_%H%M%S).log"
# Logging function
log() {
echo "[$(date '+%Y-%m-%d %H:%M:%S')] $1" | tee -a "$LOG_FILE"
}
# Test result tracking
TOTAL_TESTS=0
PASSED_TESTS=0
FAILED_TESTS=0
# Function to run a test case
run_test() {
local test_name="$1"
local sql="$2"
local expected_pattern="$3"
TOTAL_TESTS=$((TOTAL_TESTS + 1))
log "TEST: $test_name"
log "QUERY: $sql"
# Execute the query
result=$(mysql -h "$PROXYSQL_HOST" -P "$PROXYSQL_PORT" -u "$MYSQL_USER" -p"$MYSQL_PASS" -s -N -e "$sql" 2>&1)
local exit_code=$?
if [ $exit_code -eq 0 ]; then
# Check if result matches expected pattern
if echo "$result" | grep -q "$expected_pattern"; then
log "✅ PASSED: $test_name"
log "RESULT: $result"
PASSED_TESTS=$((PASSED_TESTS + 1))
else
log "❌ FAILED: $test_name - Pattern not matched"
log "EXPECTED: $expected_pattern"
log "RESULT: $result"
FAILED_TESTS=$((FAILED_TESTS + 1))
fi
else
log "❌ FAILED: $test_name - Query execution error"
log "ERROR: $result"
FAILED_TESTS=$((FAILED_TESTS + 1))
fi
log "---"
}
# Start comprehensive testing
log "Starting comprehensive ProxySQL vector search testing..."
log "Log file: $LOG_FILE"
# Test 1: Basic connectivity
run_test "Basic Connectivity" "SELECT 1 as test;" "1"
# Test 2: Database listing
run_test "Database Listing" "SHOW DATABASES;" "main"
# Test 3: Current database
run_test "Current Database" "SELECT database();" "main"
# More tests will be added...
EOF
chmod +x comprehensive_test.sh
```
---
## Step-by-Step Testing Procedures
### Phase 1: Connectivity Testing
```bash
#!/bin/bash
# Phase 1: Test connectivity to ProxySQL SQLite3 server
echo "=== Phase 1: Connectivity Testing ==="
# Test 1.1: Basic connection
echo "Test 1.1: Basic connection test"
mysql -h 127.0.0.1 -P 6030 -u root -proot -e "SELECT 'Connected successfully' as status;" || {
echo "❌ Connection failed. Please ensure ProxySQL is running with --sqlite3-server"
exit 1
}
# Test 1.2: Verify database access
echo "Test 1.2: Database access verification"
mysql -h 127.0.0.1 -P 6030 -u root -proot -e "SHOW DATABASES;"
# Test 1.3: Current database verification
echo "Test 1.3: Current database check"
mysql -h 127.0.0.1 -P 6030 -u root -proot -e "SELECT database() as current_db;"
echo "✅ Phase 1 completed: Connectivity established"
```
### Phase 2: Vector Table Creation
```bash
#!/bin/bash
# Phase 2: Test vector table creation
echo "=== Phase 2: Vector Table Creation ==="
# Test 2.1: Create embeddings table
echo "Test 2.1: Creating embeddings vector table"
mysql -h 127.0.0.1 -P 6030 -u root -proot -e "
CREATE VIRTUAL TABLE IF NOT EXISTS embeddings USING vec0(
vector float[128]
);
" || {
echo "❌ Failed to create embeddings table"
exit 1
}
# Test 2.2: Verify table creation
echo "Test 2.2: Verifying vector table creation"
mysql -h 127.0.0.1 -P 6030 -u root -proot -e "
SELECT name
FROM sqlite_master
WHERE type='table' AND name LIKE '%embedding%'
ORDER BY name;
"
# Test 2.3: Create additional test tables
echo "Test 2.3: Creating additional vector tables"
mysql -h 127.0.0.1 -P 6030 -u root -proot -e "
CREATE VIRTUAL TABLE IF NOT EXISTS documents USING vec0(
embedding float[128]
);
CREATE VIRTUAL TABLE IF NOT EXISTS test_vectors USING vec0(
features float[256]
);
"
echo "✅ Phase 2 completed: Vector tables created successfully"
```
### Phase 3: Data Insertion
```bash
#!/bin/bash
# Phase 3: Test vector data insertion
echo "=== Phase 3: Data Insertion ==="
# Test 3.1: Insert simple unit vectors
echo "Test 3.1: Inserting unit vectors"
mysql -h 127.0.0.1 -P 6030 -u root -proot -e "
INSERT INTO embeddings(rowid, vector) VALUES
(1, '[1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]'),
(2, '[0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]'),
(3, '[0.9, 0.1, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]');
"
# Test 3.2: Verify inserted data
echo "Test 3.2: Verifying inserted vectors"
mysql -h 127.0.0.1 -P 6030 -u root -proot -e "SELECT rowid, 'vector inserted' as status FROM embeddings;"
# Test 3.3: Insert document embeddings
echo "Test 3.3: Inserting document embeddings"
mysql -h 127.0.0.1 -P 6030 -u root -proot -e "
INSERT INTO documents(rowid, embedding) VALUES
(1, '[0.2, 0.8, 0.1, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]'),
(2, '[0.1, 0.1, 0.7, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]'),
(3, '[0.6, 0.2, 0.1, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]');
"
echo "✅ Phase 3 completed: Data insertion successful"
```
### Phase 4: Vector Similarity Search
```bash
#!/bin/bash
# Phase 4: Test vector similarity search
echo "=== Phase 4: Vector Similarity Search ==="
# Test 4.1: Exact match search
echo "Test 4.1: Exact match search"
mysql -h 127.0.0.1 -P 6030 -u root -proot -e "
SELECT '=== Exact Match Test ===' as header;
SELECT rowid, distance
FROM embeddings
WHERE vector MATCH json('[1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]')
ORDER BY distance ASC;
"
# Test 4.2: Similar vector search
echo "Test 4.2: Similar vector search"
mysql -h 127.0.0.1 -P 6030 -u root -proot -e "
SELECT '=== Similar Vector Test ===' as header;
SELECT rowid, distance
FROM embeddings
WHERE vector MATCH json('[0.9, 0.1, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]')
ORDER BY distance ASC;
"
# Test 4.3: Document similarity search
echo "Test 4.3: Document similarity search"
mysql -h 127.0.0.1 -P 6030 -u root -proot -e "
SELECT '=== Document Similarity Test ===' as header;
SELECT rowid, distance
FROM documents
WHERE embedding MATCH json('[0.5, 0.5, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]')
ORDER BY distance ASC LIMIT 3;
"
echo "✅ Phase 4 completed: Vector similarity search working"
```
### Phase 5: Practical Use Cases
```bash
#!/bin/bash
# Phase 5: Test practical use cases
echo "=== Phase 5: Practical Use Cases ==="
# Test 5.1: Create a product recommendation system
echo "Test 5.1: Creating product recommendation system"
mysql -h 127.0.0.1 -P 6030 -u root -proot -e "
-- Create product embeddings table
CREATE VIRTUAL TABLE IF NOT EXISTS products USING vec0(
product_embedding float[128]
);
-- Insert product embeddings (simplified)
INSERT INTO products(rowid, product_embedding) VALUES
(1, '[0.8, 0.1, 0.05, 0.05, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]'), -- Electronics
(2, '[0.1, 0.8, 0.05, 0.05, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]'); -- Clothing
"
# Test 5.2: Find similar products
echo "Test 5.2: Finding similar products"
mysql -h 127.0.0.1 -P 6030 -u root -proot -e "
SELECT '=== Product Recommendations ===' as header;
SELECT rowid as product_id, distance
FROM products
WHERE product_embedding MATCH json('[0.75, 0.15, 0.05, 0.05, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]')
ORDER BY distance ASC LIMIT 3;
"
# Test 5.3: Create user session tracking
echo "Test 5.3: Creating user session tracking"
mysql -h 127.0.0.1 -P 6030 -u root -proot -e "
-- Create user sessions table
CREATE VIRTUAL TABLE IF NOT EXISTS user_sessions USING vec0(
session_vector float[128]
);
-- Insert user session vectors
INSERT INTO user_sessions(rowid, session_vector) VALUES
(1, '[0.6, 0.3, 0.05, 0.05, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]'),
(2, '[0.1, 0.7, 0.1, 0.1, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]');
"
# Test 5.4: Find similar user sessions
echo "Test 5.4: Finding similar user sessions"
mysql -h 127.0.0.1 -P 6030 -u root -proot -e "
SELECT '=== User Session Analysis ===' as header;
SELECT rowid as session_id, distance
FROM user_sessions
WHERE session_vector MATCH json('[0.55, 0.35, 0.05, 0.05, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]')
ORDER BY distance ASC LIMIT 3;
"
echo "✅ Phase 5 completed: Practical use cases demonstrated"
```
---
## Advanced Testing Scenarios
### Performance Testing
```bash
#!/bin/bash
# Performance testing for vector operations
echo "=== Performance Testing ==="
# Test 1: Bulk insertion performance
echo "Test 1: Bulk insertion performance"
time mysql -h 127.0.0.1 -P 6030 -u root -proot -e "
BEGIN;
$(for i in {4..100}; do
echo "INSERT INTO embeddings(rowid, vector) VALUES
($i, '[$(for j in {1..127}; do echo -n "0.0"; [ $j -lt 127 ] && echo -n ", "; done)]');"
done)
COMMIT;
"
# Test 2: Search performance
echo "Test 2: Search performance"
time mysql -h 127.0.0.1 -P 6030 -u root -proot -e "
SELECT rowid, distance
FROM embeddings
WHERE vector MATCH json('[1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]')
ORDER BY distance ASC LIMIT 10;
"
echo "✅ Performance testing completed"
```
### Error Handling Tests
```bash
#!/bin/bash
# Test error handling scenarios
echo "=== Error Handling Tests ==="
# Test 1: Invalid dimension
echo "Test 1: Invalid dimension test"
mysql -h 127.0.0.1 -P 6030 -u root -proot -e "
INSERT INTO embeddings(rowid, vector) VALUES
(999, '[1.0, 0.0]');" 2>&1 || echo "✅ Expected error caught"
# Test 2: Invalid JSON
echo "Test 2: Invalid JSON test"
mysql -h 127.0.0.1 -P 6030 -u root -proot -e "
INSERT INTO embeddings(rowid, vector) VALUES
(1000, 'invalid json');" 2>&1 || echo "✅ Expected error caught"
# Test 3: Non-existent table
echo "Test 3: Non-existent table test"
mysql -h 127.0.0.1 -P 6030 -u root -proot -e "
SELECT * FROM non_existent_table;" 2>&1 || echo "✅ Expected error caught"
echo "✅ Error handling tests completed"
```
---
## Troubleshooting
### Common Issues and Solutions
#### 1. Connection Issues
**Problem**: `ERROR 2003 (HY000): Can't connect to MySQL server on '127.0.0.1:6030'`
```bash
# Solution: Check if ProxySQL is running with --sqlite3-server
ps aux | grep proxysql
# Check if port 6030 is listening
netstat -tlnp | grep 6030
# Check logs
tail -f /var/log/proxysql.log
```
#### 2. Permission Issues
**Problem**: `ERROR 1045 (28000): Access denied for user 'root'@'localhost'`
```bash
# Solution: Check user credentials in ProxySQL
mysql -h 127.0.0.1 -P 6032 -u admin -padmin -e "
SELECT username, password, active FROM mysql_users
WHERE username = 'root';
"
```
#### 3. Vector Dimension Errors
**Problem**: `ERROR 1045 (28000): Dimension mismatch for inserted vector`
**Solution**: Ensure all vectors match the table dimension (e.g., 128 dimensions).
#### 4. Extension Not Available
**Problem**: Vector commands not working
```bash
# Solution: Verify sqlite-vec is compiled and linked
nm src/proxysql | grep sqlite3_vec_init
# Should show: T sqlite3_vec_init
```
### Debug Commands
```bash
# Debug connection issues
mysql -h 127.0.0.1 -P 6030 -u root -proot -e "SELECT version() as sqlite_version;"
# Check available tables
mysql -h 127.0.0.1 -P 6030 -u root -proot -e "SELECT name FROM sqlite_master WHERE type='table';"
# Check vector table structure
mysql -h 127.0.0.1 -P 6030 -u root -proot -e "SELECT name FROM sqlite_master WHERE name LIKE '%vector%';"
# Test basic SQLite functionality
mysql -h 127.0.0.1 -P 6030 -u root -proot -e "SELECT 1+1 as math_test;"
```
---
## Expected Results
### Phase 1: Connectivity
- ✅ Successful connection to port 6030
- ✅ `SHOW DATABASES` returns `main`
- ✅ `SELECT database()` returns `main`
### Phase 2: Vector Table Creation
- ✅ `CREATE VIRTUAL TABLE USING vec0` succeeds
- ✅ Tables appear in `sqlite_master`
- ✅ Internal vec0 tables created (e.g., `*_vector_chunks00`)
### Phase 3: Data Insertion
- ✅ Vector insertion without dimension errors
- ✅ All vectors properly stored with correct dimensions
- ✅ Row count matches inserted records
### Phase 4: Vector Similarity Search
- ✅ Exact match returns distance 0.0
- ✅ Similar vectors return small distances (0.0 < distance < 0.5)
- ✅ Different vectors return larger distances (> 1.0)
- ✅ Results properly ordered by distance
### Phase 5: Practical Use Cases
- ✅ Product recommendation system works
- ✅ User session analysis functions
- ✅ Document similarity search operational
### Advanced Testing
- ✅ Performance tests show reasonable execution times
- ✅ Error handling works as expected
- ✅ Bulk operations perform correctly
---
## Additional Resources
### Documentation
- [ProxySQL Official Documentation](https://proxysql.com/documentation/)
- [sqlite-vec GitHub Repository](https://github.com/asg017/sqlite-vec)
- [SQLite Virtual Table Documentation](https://www.sqlite.org/vtab.html)
### Tools and Utilities
- MySQL Client: Standard command-line tool
- Python Vector Generator: `vector_generator.py` (included)
- Test Scripts: `test_vector_search.sh`, `comprehensive_test.sh`
### Community Support
- ProxySQL Mailing List
- GitHub Issues for ProxySQL
- SQLite mailing list for extension-specific questions
### Example Applications
- Product recommendation engines
- Document similarity systems
- User behavior analysis
- Anomaly detection
- Content-based filtering
---
## Conclusion
This comprehensive testing guide provides everything needed to verify and reproduce vector search functionality in ProxySQL's SQLite3 server. The step-by-step approach ensures thorough testing of all components, from basic connectivity to advanced use cases.
**Remember**: The key to successful vector search testing is ensuring:
1. ProxySQL is built with sqlite-vec support
2. Running with `--sqlite3-server` option
3. Using correct MySQL credentials
4. Following proper vector dimension requirements
5. Testing both functionality and performance
Happy testing! 🚀
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