feat: Add Step 13 - Search System with Apache Solr and Data Persistence

- Implemented search service with Apache Solr instead of Elasticsearch
- Added full-text search, faceted search, and autocomplete capabilities
- Created data indexer for synchronizing data from MongoDB/Kafka to Solr
- Configured external volume mounts for all data services:
  - MongoDB, Redis, Kafka, Zookeeper, MinIO, Solr
  - All data now persists in ./data/ directory
- Added comprehensive search API endpoints
- Created documentation for data persistence and backup strategies

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>
This commit is contained in:
jungwoo choi
2025-09-11 20:27:02 +09:00
parent ee4e50afc9
commit dd165454f0
11 changed files with 1746 additions and 20 deletions

2
.gitignore vendored
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@ -64,4 +64,4 @@ temp/
*.pem
*.key
*.crt
secrets/
secrets/data/

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@ -76,7 +76,7 @@ services:
- CONVERT_TO_WEBP=true
volumes:
- ./services/images/backend:/app
- images_cache:/app/cache
- ./data/images-cache:/app/cache
networks:
- site11_network
restart: unless-stopped
@ -118,8 +118,8 @@ services:
ports:
- "${MONGODB_PORT}:27017"
volumes:
- mongodb_data:/data/db
- mongodb_config:/data/configdb
- ./data/mongodb:/data/db
- ./data/mongodb/configdb:/data/configdb
networks:
- site11_network
restart: unless-stopped
@ -135,7 +135,7 @@ services:
ports:
- "${REDIS_PORT}:6379"
volumes:
- redis_data:/data
- ./data/redis:/data
networks:
- site11_network
restart: unless-stopped
@ -154,8 +154,8 @@ services:
ports:
- "${KAFKA_ZOOKEEPER_PORT}:2181"
volumes:
- zookeeper_data:/var/lib/zookeeper/data
- zookeeper_logs:/var/lib/zookeeper/log
- ./data/zookeeper/data:/var/lib/zookeeper/data
- ./data/zookeeper/logs:/var/lib/zookeeper/log
networks:
- site11_network
restart: unless-stopped
@ -181,7 +181,7 @@ services:
KAFKA_JMX_HOSTNAME: localhost
KAFKA_AUTO_CREATE_TOPICS_ENABLE: 'true'
volumes:
- kafka_data:/var/lib/kafka/data
- ./data/kafka:/var/lib/kafka/data
networks:
- site11_network
restart: unless-stopped
@ -234,7 +234,7 @@ services:
- MINIO_ROOT_USER=${MINIO_ROOT_USER:-minioadmin}
- MINIO_ROOT_PASSWORD=${MINIO_ROOT_PASSWORD:-minioadmin}
volumes:
- minio_data:/data
- ./data/minio:/data
command: server /data --console-address ":9001"
networks:
- site11_network
@ -264,7 +264,7 @@ services:
- MINIO_SECURE=false
volumes:
- ./services/files/backend:/app
- files_temp:/tmp
- ./data/files-temp:/tmp
networks:
- site11_network
restart: unless-stopped
@ -277,6 +277,57 @@ services:
timeout: 10s
retries: 3
# Apache Solr Search Engine
solr:
image: solr:9.4
container_name: ${COMPOSE_PROJECT_NAME}_solr
ports:
- "8983:8983"
volumes:
- ./data/solr:/var/solr
- ./services/search/solr-config:/opt/solr/server/solr/configsets/site11_config
command:
- solr-precreate
- site11
- /opt/solr/server/solr/configsets/site11_config
networks:
- site11_network
restart: unless-stopped
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:8983/solr/site11/admin/ping"]
interval: 30s
timeout: 10s
retries: 3
# Search Service
search-backend:
build:
context: ./services/search/backend
dockerfile: Dockerfile
container_name: ${COMPOSE_PROJECT_NAME}_search_backend
ports:
- "8015:8000"
environment:
- ENV=${ENV}
- PORT=8000
- SOLR_URL=http://solr:8983/solr
- MONGODB_URL=${MONGODB_URL}
- KAFKA_BOOTSTRAP_SERVERS=${KAFKA_BOOTSTRAP_SERVERS}
volumes:
- ./services/search/backend:/app
networks:
- site11_network
restart: unless-stopped
depends_on:
- solr
- mongodb
- kafka
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:8000/health"]
interval: 30s
timeout: 10s
retries: 3
# Statistics Service
statistics-backend:
build:
@ -308,13 +359,15 @@ networks:
driver: bridge
name: site11_network
volumes:
mongodb_data:
mongodb_config:
redis_data:
images_cache:
zookeeper_data:
zookeeper_logs:
kafka_data:
minio_data:
files_temp:
# Named volumes are replaced with bind mounts in ./data/ directory
# volumes:
# mongodb_data:
# mongodb_config:
# redis_data:
# images_cache:
# zookeeper_data:
# zookeeper_logs:
# kafka_data:
# minio_data:
# files_temp:
# solr_data:

140
docs/DATA_PERSISTENCE.md Normal file
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@ -0,0 +1,140 @@
# Data Persistence Configuration
## Overview
All data services are configured to use bind mounts to local directories for data persistence. This ensures data survives container restarts and rebuilds.
## Directory Structure
```
data/
├── mongodb/ # MongoDB database files
├── redis/ # Redis persistence files
├── kafka/ # Kafka log data
├── zookeeper/ # Zookeeper data and logs
│ ├── data/
│ └── logs/
├── minio/ # MinIO object storage
├── solr/ # Solr search index
├── files-temp/ # Temporary file storage
└── images-cache/ # Image processing cache
```
## Volume Mappings
### MongoDB
- `./data/mongodb:/data/db` - Database files
- `./data/mongodb/configdb:/data/configdb` - Configuration database
### Redis
- `./data/redis:/data` - RDB snapshots and AOF logs
### Kafka
- `./data/kafka:/var/lib/kafka/data` - Message logs
### Zookeeper
- `./data/zookeeper/data:/var/lib/zookeeper/data` - Coordination data
- `./data/zookeeper/logs:/var/lib/zookeeper/log` - Transaction logs
### MinIO
- `./data/minio:/data` - Object storage buckets
### Solr
- `./data/solr:/var/solr` - Search index and configuration
### Application Caches
- `./data/files-temp:/tmp` - Temporary file processing
- `./data/images-cache:/app/cache` - Processed image cache
## Backup and Restore
### Backup All Data
```bash
# Stop services
docker-compose down
# Create backup
tar -czf backup-$(date +%Y%m%d).tar.gz data/
# Restart services
docker-compose up -d
```
### Restore Data
```bash
# Stop services
docker-compose down
# Extract backup
tar -xzf backup-YYYYMMDD.tar.gz
# Restart services
docker-compose up -d
```
### Individual Service Backups
#### MongoDB Backup
```bash
docker exec site11_mongodb mongodump --out /data/db/backup
tar -czf mongodb-backup.tar.gz data/mongodb/backup/
```
#### Redis Backup
```bash
docker exec site11_redis redis-cli BGSAVE
# Wait for completion
cp data/redis/dump.rdb redis-backup-$(date +%Y%m%d).rdb
```
## Permissions
Ensure proper permissions for data directories:
```bash
# Set appropriate permissions
chmod -R 755 data/
```
## Disk Space Monitoring
Monitor disk usage regularly:
```bash
# Check data directory size
du -sh data/*
# Check individual services
du -sh data/mongodb
du -sh data/minio
du -sh data/kafka
```
## Clean Up Old Data
### Clear Kafka Logs (older than 7 days)
```bash
docker exec site11_kafka kafka-log-dirs.sh --describe --bootstrap-server localhost:9092
```
### Clear Image Cache
```bash
rm -rf data/images-cache/*
```
### Clear Temporary Files
```bash
rm -rf data/files-temp/*
```
## Migration from Docker Volumes
If migrating from named Docker volumes to bind mounts:
1. Export data from Docker volumes:
```bash
docker run --rm -v site11_mongodb_data:/source -v $(pwd)/data/mongodb:/dest alpine cp -av /source/. /dest/
```
2. Update docker-compose.yml (already done)
3. Restart services with new configuration
## Notes
- The `data/` directory is excluded from git via .gitignore
- Ensure sufficient disk space for data growth
- Consider setting up automated backups for production
- Monitor disk I/O performance for database services

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@ -0,0 +1,21 @@
FROM python:3.11-slim
WORKDIR /app
# Install system dependencies
RUN apt-get update && apt-get install -y \
gcc \
&& rm -rf /var/lib/apt/lists/*
# Copy requirements first for better caching
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt
# Copy application code
COPY . .
# Create necessary directories
RUN mkdir -p /app/logs
# Run the application
CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000", "--reload"]

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@ -0,0 +1,286 @@
"""
Data indexer for synchronizing data from other services to Solr
"""
import asyncio
import logging
from typing import Dict, Any, List
from motor.motor_asyncio import AsyncIOMotorClient
from aiokafka import AIOKafkaConsumer
import json
from solr_client import SolrClient
from datetime import datetime
logger = logging.getLogger(__name__)
class DataIndexer:
def __init__(self, solr_client: SolrClient, mongodb_url: str, kafka_servers: str):
self.solr = solr_client
self.mongodb_url = mongodb_url
self.kafka_servers = kafka_servers
self.mongo_client = None
self.kafka_consumer = None
self.running = False
async def start(self):
"""Start the indexer"""
try:
# Connect to MongoDB
self.mongo_client = AsyncIOMotorClient(self.mongodb_url)
# Initialize Kafka consumer
await self._init_kafka_consumer()
# Start background tasks
self.running = True
asyncio.create_task(self._consume_kafka_events())
asyncio.create_task(self._periodic_sync())
logger.info("Data indexer started")
except Exception as e:
logger.error(f"Failed to start indexer: {e}")
async def stop(self):
"""Stop the indexer"""
self.running = False
if self.kafka_consumer:
await self.kafka_consumer.stop()
if self.mongo_client:
self.mongo_client.close()
logger.info("Data indexer stopped")
async def _init_kafka_consumer(self):
"""Initialize Kafka consumer"""
try:
self.kafka_consumer = AIOKafkaConsumer(
'user_events',
'file_events',
'content_events',
bootstrap_servers=self.kafka_servers,
value_deserializer=lambda m: json.loads(m.decode('utf-8')),
group_id='search_indexer',
auto_offset_reset='latest'
)
await self.kafka_consumer.start()
logger.info("Kafka consumer initialized")
except Exception as e:
logger.warning(f"Kafka consumer initialization failed: {e}")
self.kafka_consumer = None
async def _consume_kafka_events(self):
"""Consume events from Kafka and index them"""
if not self.kafka_consumer:
return
while self.running:
try:
async for msg in self.kafka_consumer:
await self._handle_kafka_event(msg.topic, msg.value)
except Exception as e:
logger.error(f"Kafka consumption error: {e}")
await asyncio.sleep(5)
async def _handle_kafka_event(self, topic: str, event: Dict[str, Any]):
"""Handle a Kafka event"""
try:
event_type = event.get('type')
data = event.get('data', {})
if topic == 'user_events':
await self._index_user_event(event_type, data)
elif topic == 'file_events':
await self._index_file_event(event_type, data)
elif topic == 'content_events':
await self._index_content_event(event_type, data)
except Exception as e:
logger.error(f"Failed to handle event: {e}")
async def _index_user_event(self, event_type: str, data: Dict):
"""Index user-related events"""
if event_type == 'user_created' or event_type == 'user_updated':
user_doc = {
'id': f"user_{data.get('user_id')}",
'doc_type': 'user',
'user_id': data.get('user_id'),
'username': data.get('username'),
'email': data.get('email'),
'name': data.get('name', ''),
'bio': data.get('bio', ''),
'tags': data.get('tags', []),
'created_at': data.get('created_at'),
'updated_at': datetime.utcnow().isoformat()
}
self.solr.index_document(user_doc)
elif event_type == 'user_deleted':
self.solr.delete_document(f"user_{data.get('user_id')}")
async def _index_file_event(self, event_type: str, data: Dict):
"""Index file-related events"""
if event_type == 'file_uploaded':
file_doc = {
'id': f"file_{data.get('file_id')}",
'doc_type': 'file',
'file_id': data.get('file_id'),
'filename': data.get('filename'),
'content_type': data.get('content_type'),
'size': data.get('size'),
'user_id': data.get('user_id'),
'tags': data.get('tags', []),
'description': data.get('description', ''),
'created_at': data.get('created_at'),
'updated_at': datetime.utcnow().isoformat()
}
self.solr.index_document(file_doc)
elif event_type == 'file_deleted':
self.solr.delete_document(f"file_{data.get('file_id')}")
async def _index_content_event(self, event_type: str, data: Dict):
"""Index content-related events"""
if event_type in ['content_created', 'content_updated']:
content_doc = {
'id': f"content_{data.get('content_id')}",
'doc_type': 'content',
'content_id': data.get('content_id'),
'title': data.get('title'),
'content': data.get('content', ''),
'summary': data.get('summary', ''),
'author_id': data.get('author_id'),
'tags': data.get('tags', []),
'category': data.get('category'),
'status': data.get('status', 'draft'),
'created_at': data.get('created_at'),
'updated_at': datetime.utcnow().isoformat()
}
self.solr.index_document(content_doc)
elif event_type == 'content_deleted':
self.solr.delete_document(f"content_{data.get('content_id')}")
async def _periodic_sync(self):
"""Periodically sync data from MongoDB"""
while self.running:
try:
# Sync every 5 minutes
await asyncio.sleep(300)
await self.sync_all_data()
except Exception as e:
logger.error(f"Periodic sync error: {e}")
async def sync_all_data(self):
"""Sync all data from MongoDB to Solr"""
try:
logger.info("Starting full data sync")
# Sync users
await self._sync_users()
# Sync files
await self._sync_files()
# Optimize index after bulk sync
self.solr.optimize_index()
logger.info("Full data sync completed")
except Exception as e:
logger.error(f"Full sync failed: {e}")
async def _sync_users(self):
"""Sync users from MongoDB"""
try:
db = self.mongo_client['users_db']
collection = db['users']
users = []
async for user in collection.find({'deleted_at': None}):
user_doc = {
'id': f"user_{str(user['_id'])}",
'doc_type': 'user',
'user_id': str(user['_id']),
'username': user.get('username'),
'email': user.get('email'),
'name': user.get('name', ''),
'bio': user.get('bio', ''),
'tags': user.get('tags', []),
'created_at': user.get('created_at').isoformat() if user.get('created_at') else None,
'updated_at': datetime.utcnow().isoformat()
}
users.append(user_doc)
# Bulk index every 100 documents
if len(users) >= 100:
self.solr.bulk_index(users, 'user')
users = []
# Index remaining users
if users:
self.solr.bulk_index(users, 'user')
logger.info(f"Synced users to Solr")
except Exception as e:
logger.error(f"Failed to sync users: {e}")
async def _sync_files(self):
"""Sync files from MongoDB"""
try:
db = self.mongo_client['files_db']
collection = db['file_metadata']
files = []
async for file in collection.find({'deleted_at': None}):
file_doc = {
'id': f"file_{str(file['_id'])}",
'doc_type': 'file',
'file_id': str(file['_id']),
'filename': file.get('filename'),
'original_name': file.get('original_name'),
'content_type': file.get('content_type'),
'size': file.get('size'),
'user_id': file.get('user_id'),
'tags': list(file.get('tags', {}).keys()),
'description': file.get('metadata', {}).get('description', ''),
'created_at': file.get('created_at').isoformat() if file.get('created_at') else None,
'updated_at': datetime.utcnow().isoformat()
}
files.append(file_doc)
# Bulk index every 100 documents
if len(files) >= 100:
self.solr.bulk_index(files, 'file')
files = []
# Index remaining files
if files:
self.solr.bulk_index(files, 'file')
logger.info(f"Synced files to Solr")
except Exception as e:
logger.error(f"Failed to sync files: {e}")
async def reindex_collection(self, collection_name: str, doc_type: str):
"""Reindex a specific collection"""
try:
# Delete existing documents of this type
self.solr.delete_by_query(f'doc_type:{doc_type}')
# Sync the collection
if collection_name == 'users':
await self._sync_users()
elif collection_name == 'files':
await self._sync_files()
logger.info(f"Reindexed {collection_name}")
except Exception as e:
logger.error(f"Failed to reindex {collection_name}: {e}")

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@ -0,0 +1,362 @@
"""
Search Service with Apache Solr
"""
from fastapi import FastAPI, Query, HTTPException
from fastapi.responses import JSONResponse
from contextlib import asynccontextmanager
import logging
import os
from typing import Optional, List, Dict, Any
from datetime import datetime
from solr_client import SolrClient
from indexer import DataIndexer
import asyncio
import time
# Configure logging
logging.basicConfig(
level=logging.INFO,
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
)
logger = logging.getLogger(__name__)
# Global instances
solr_client = None
data_indexer = None
@asynccontextmanager
async def lifespan(app: FastAPI):
"""Manage application lifecycle"""
global solr_client, data_indexer
# Startup
logger.info("Starting Search Service...")
# Wait for Solr to be ready
solr_url = os.getenv("SOLR_URL", "http://solr:8983/solr")
max_retries = 30
for i in range(max_retries):
try:
solr_client = SolrClient(solr_url=solr_url, core_name="site11")
logger.info("Connected to Solr")
break
except Exception as e:
logger.warning(f"Waiting for Solr... ({i+1}/{max_retries})")
await asyncio.sleep(2)
if solr_client:
# Initialize data indexer
mongodb_url = os.getenv("MONGODB_URL", "mongodb://mongodb:27017")
kafka_servers = os.getenv("KAFKA_BOOTSTRAP_SERVERS", "kafka:9092")
data_indexer = DataIndexer(solr_client, mongodb_url, kafka_servers)
await data_indexer.start()
# Initial data sync
asyncio.create_task(data_indexer.sync_all_data())
yield
# Shutdown
if data_indexer:
await data_indexer.stop()
logger.info("Search Service stopped")
app = FastAPI(
title="Search Service",
description="Full-text search with Apache Solr",
version="1.0.0",
lifespan=lifespan
)
@app.get("/health")
async def health_check():
"""Health check endpoint"""
return {
"status": "healthy",
"service": "search",
"timestamp": datetime.utcnow().isoformat(),
"solr_connected": solr_client is not None
}
@app.get("/api/search")
async def search(
q: str = Query(..., description="Search query"),
doc_type: Optional[str] = Query(None, description="Filter by document type"),
start: int = Query(0, ge=0, description="Starting offset"),
rows: int = Query(10, ge=1, le=100, description="Number of results"),
sort: Optional[str] = Query(None, description="Sort order (e.g., 'created_at desc')"),
facet: bool = Query(False, description="Enable faceting"),
facet_field: Optional[List[str]] = Query(None, description="Fields to facet on")
):
"""
Search documents across all indexed content
"""
if not solr_client:
raise HTTPException(status_code=503, detail="Search service unavailable")
try:
# Build filter query
fq = []
if doc_type:
fq.append(f"doc_type:{doc_type}")
# Prepare search parameters
search_params = {
'start': start,
'rows': rows,
'facet': facet
}
if fq:
search_params['fq'] = fq
if sort:
search_params['sort'] = sort
if facet_field:
search_params['facet_field'] = facet_field
# Execute search
results = solr_client.search(q, **search_params)
return {
"query": q,
"total": results['total'],
"start": start,
"rows": rows,
"documents": results['documents'],
"facets": results.get('facets', {}),
"highlighting": results.get('highlighting', {})
}
except Exception as e:
logger.error(f"Search failed: {e}")
raise HTTPException(status_code=500, detail=str(e))
@app.get("/api/search/suggest")
async def suggest(
q: str = Query(..., min_length=1, description="Query prefix"),
field: str = Query("title", description="Field to search in"),
limit: int = Query(10, ge=1, le=50, description="Maximum suggestions")
):
"""
Get autocomplete suggestions
"""
if not solr_client:
raise HTTPException(status_code=503, detail="Search service unavailable")
try:
suggestions = solr_client.suggest(q, field, limit)
return {
"query": q,
"suggestions": suggestions,
"count": len(suggestions)
}
except Exception as e:
logger.error(f"Suggest failed: {e}")
raise HTTPException(status_code=500, detail=str(e))
@app.get("/api/search/similar/{doc_id}")
async def find_similar(
doc_id: str,
rows: int = Query(5, ge=1, le=20, description="Number of similar documents")
):
"""
Find documents similar to the given document
"""
if not solr_client:
raise HTTPException(status_code=503, detail="Search service unavailable")
try:
similar_docs = solr_client.more_like_this(doc_id, rows=rows)
return {
"source_document": doc_id,
"similar_documents": similar_docs,
"count": len(similar_docs)
}
except Exception as e:
logger.error(f"Similar search failed: {e}")
raise HTTPException(status_code=500, detail=str(e))
@app.post("/api/search/index")
async def index_document(document: Dict[str, Any]):
"""
Index a single document
"""
if not solr_client:
raise HTTPException(status_code=503, detail="Search service unavailable")
try:
doc_type = document.get('doc_type', 'general')
success = solr_client.index_document(document, doc_type)
if success:
return {
"status": "success",
"message": "Document indexed",
"document_id": document.get('id')
}
else:
raise HTTPException(status_code=500, detail="Failed to index document")
except Exception as e:
logger.error(f"Indexing failed: {e}")
raise HTTPException(status_code=500, detail=str(e))
@app.post("/api/search/bulk-index")
async def bulk_index(documents: List[Dict[str, Any]]):
"""
Bulk index multiple documents
"""
if not solr_client:
raise HTTPException(status_code=503, detail="Search service unavailable")
try:
indexed = solr_client.bulk_index(documents)
return {
"status": "success",
"message": f"Indexed {indexed} documents",
"count": indexed
}
except Exception as e:
logger.error(f"Bulk indexing failed: {e}")
raise HTTPException(status_code=500, detail=str(e))
@app.delete("/api/search/document/{doc_id}")
async def delete_document(doc_id: str):
"""
Delete a document from the index
"""
if not solr_client:
raise HTTPException(status_code=503, detail="Search service unavailable")
try:
success = solr_client.delete_document(doc_id)
if success:
return {
"status": "success",
"message": "Document deleted",
"document_id": doc_id
}
else:
raise HTTPException(status_code=500, detail="Failed to delete document")
except Exception as e:
logger.error(f"Deletion failed: {e}")
raise HTTPException(status_code=500, detail=str(e))
@app.get("/api/search/stats")
async def get_stats():
"""
Get search index statistics
"""
if not solr_client:
raise HTTPException(status_code=503, detail="Search service unavailable")
try:
stats = solr_client.get_stats()
return {
"status": "success",
"statistics": stats,
"timestamp": datetime.utcnow().isoformat()
}
except Exception as e:
logger.error(f"Failed to get stats: {e}")
raise HTTPException(status_code=500, detail=str(e))
@app.post("/api/search/reindex/{collection}")
async def reindex_collection(
collection: str,
doc_type: Optional[str] = Query(None, description="Document type for the collection")
):
"""
Reindex a specific collection
"""
if not data_indexer:
raise HTTPException(status_code=503, detail="Indexer service unavailable")
try:
if not doc_type:
# Map collection to doc_type
doc_type_map = {
'users': 'user',
'files': 'file',
'content': 'content'
}
doc_type = doc_type_map.get(collection, collection)
asyncio.create_task(data_indexer.reindex_collection(collection, doc_type))
return {
"status": "success",
"message": f"Reindexing {collection} started",
"collection": collection,
"doc_type": doc_type
}
except Exception as e:
logger.error(f"Reindex failed: {e}")
raise HTTPException(status_code=500, detail=str(e))
@app.post("/api/search/optimize")
async def optimize_index():
"""
Optimize the search index
"""
if not solr_client:
raise HTTPException(status_code=503, detail="Search service unavailable")
try:
success = solr_client.optimize_index()
if success:
return {
"status": "success",
"message": "Index optimization started"
}
else:
raise HTTPException(status_code=500, detail="Failed to optimize index")
except Exception as e:
logger.error(f"Optimization failed: {e}")
raise HTTPException(status_code=500, detail=str(e))
@app.post("/api/search/clear")
async def clear_index():
"""
Clear all documents from the index (DANGER!)
"""
if not solr_client:
raise HTTPException(status_code=503, detail="Search service unavailable")
try:
success = solr_client.clear_index()
if success:
return {
"status": "success",
"message": "Index cleared",
"warning": "All documents have been deleted!"
}
else:
raise HTTPException(status_code=500, detail="Failed to clear index")
except Exception as e:
logger.error(f"Clear index failed: {e}")
raise HTTPException(status_code=500, detail=str(e))
if __name__ == "__main__":
import uvicorn
uvicorn.run(app, host="0.0.0.0", port=8000)

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fastapi==0.109.0
uvicorn[standard]==0.27.0
pydantic==2.5.3
python-dotenv==1.0.0
pysolr==3.9.0
httpx==0.25.2
motor==3.5.1
pymongo==4.6.1
aiokafka==0.10.0
redis==5.0.1

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"""
Apache Solr client for search operations
"""
import pysolr
import logging
from typing import Dict, List, Any, Optional
from datetime import datetime
import json
logger = logging.getLogger(__name__)
class SolrClient:
def __init__(self, solr_url: str = "http://solr:8983/solr", core_name: str = "site11"):
self.solr_url = f"{solr_url}/{core_name}"
self.core_name = core_name
self.solr = None
self.connect()
def connect(self):
"""Connect to Solr instance"""
try:
self.solr = pysolr.Solr(
self.solr_url,
always_commit=True,
timeout=10
)
# Test connection
self.solr.ping()
logger.info(f"Connected to Solr at {self.solr_url}")
except Exception as e:
logger.error(f"Failed to connect to Solr: {e}")
raise
def index_document(self, document: Dict[str, Any], doc_type: str = None) -> bool:
"""Index a single document"""
try:
# Add metadata
if doc_type:
document["doc_type"] = doc_type
if "id" not in document:
document["id"] = f"{doc_type}_{document.get('_id', '')}"
# Add indexing timestamp
document["indexed_at"] = datetime.utcnow().isoformat()
# Index the document
self.solr.add([document])
logger.info(f"Indexed document: {document.get('id')}")
return True
except Exception as e:
logger.error(f"Failed to index document: {e}")
return False
def bulk_index(self, documents: List[Dict[str, Any]], doc_type: str = None) -> int:
"""Bulk index multiple documents"""
try:
indexed = 0
for doc in documents:
if doc_type:
doc["doc_type"] = doc_type
if "id" not in doc:
doc["id"] = f"{doc_type}_{doc.get('_id', '')}"
doc["indexed_at"] = datetime.utcnow().isoformat()
self.solr.add(documents)
indexed = len(documents)
logger.info(f"Bulk indexed {indexed} documents")
return indexed
except Exception as e:
logger.error(f"Failed to bulk index: {e}")
return 0
def search(self, query: str, **kwargs) -> Dict[str, Any]:
"""
Search documents
Args:
query: Search query string
**kwargs: Additional search parameters
- fq: Filter queries
- fl: Fields to return
- start: Starting offset
- rows: Number of rows
- sort: Sort order
- facet: Enable faceting
- facet.field: Fields to facet on
"""
try:
# Default parameters
params = {
'q': query,
'start': kwargs.get('start', 0),
'rows': kwargs.get('rows', 10),
'fl': kwargs.get('fl', '*,score'),
'defType': 'edismax',
'qf': 'title^3 content^2 tags description name', # Boost fields
'mm': '2<-25%', # Minimum match
'hl': 'true', # Highlighting
'hl.fl': 'title,content,description',
'hl.simple.pre': '<mark>',
'hl.simple.post': '</mark>'
}
# Add filter queries
if 'fq' in kwargs:
params['fq'] = kwargs['fq']
# Add sorting
if 'sort' in kwargs:
params['sort'] = kwargs['sort']
# Add faceting
if kwargs.get('facet'):
params.update({
'facet': 'true',
'facet.field': kwargs.get('facet_field', ['doc_type', 'tags', 'status']),
'facet.mincount': 1
})
# Execute search
results = self.solr.search(**params)
# Format response
response = {
'total': results.hits,
'documents': [],
'facets': {},
'highlighting': {}
}
# Add documents
for doc in results.docs:
response['documents'].append(doc)
# Add facets if available
if hasattr(results, 'facets') and results.facets:
if 'facet_fields' in results.facets:
for field, values in results.facets['facet_fields'].items():
response['facets'][field] = [
{'value': values[i], 'count': values[i+1]}
for i in range(0, len(values), 2)
]
# Add highlighting if available
if hasattr(results, 'highlighting'):
response['highlighting'] = results.highlighting
return response
except Exception as e:
logger.error(f"Search failed: {e}")
return {'total': 0, 'documents': [], 'error': str(e)}
def suggest(self, prefix: str, field: str = "suggest", limit: int = 10) -> List[str]:
"""Get autocomplete suggestions"""
try:
params = {
'q': f'{field}:{prefix}*',
'fl': field,
'rows': limit,
'start': 0
}
results = self.solr.search(**params)
suggestions = []
for doc in results.docs:
if field in doc:
value = doc[field]
if isinstance(value, list):
suggestions.extend(value)
else:
suggestions.append(value)
# Remove duplicates and limit
seen = set()
unique_suggestions = []
for s in suggestions:
if s not in seen:
seen.add(s)
unique_suggestions.append(s)
if len(unique_suggestions) >= limit:
break
return unique_suggestions
except Exception as e:
logger.error(f"Suggest failed: {e}")
return []
def more_like_this(self, doc_id: str, mlt_fields: List[str] = None, rows: int = 5) -> List[Dict]:
"""Find similar documents"""
try:
if not mlt_fields:
mlt_fields = ['title', 'content', 'tags', 'description']
params = {
'q': f'id:{doc_id}',
'mlt': 'true',
'mlt.fl': ','.join(mlt_fields),
'mlt.mindf': 1,
'mlt.mintf': 1,
'mlt.count': rows,
'fl': '*,score'
}
results = self.solr.search(**params)
if results.docs:
# The MLT results are in the moreLikeThis section
if hasattr(results, 'moreLikeThis'):
mlt_results = results.moreLikeThis.get(doc_id, {})
if 'docs' in mlt_results:
return mlt_results['docs']
return []
except Exception as e:
logger.error(f"More like this failed: {e}")
return []
def delete_document(self, doc_id: str) -> bool:
"""Delete a document by ID"""
try:
self.solr.delete(id=doc_id)
logger.info(f"Deleted document: {doc_id}")
return True
except Exception as e:
logger.error(f"Failed to delete document: {e}")
return False
def delete_by_query(self, query: str) -> bool:
"""Delete documents matching a query"""
try:
self.solr.delete(q=query)
logger.info(f"Deleted documents matching: {query}")
return True
except Exception as e:
logger.error(f"Failed to delete by query: {e}")
return False
def clear_index(self) -> bool:
"""Clear all documents from index"""
try:
self.solr.delete(q='*:*')
logger.info("Cleared all documents from index")
return True
except Exception as e:
logger.error(f"Failed to clear index: {e}")
return False
def get_stats(self) -> Dict[str, Any]:
"""Get index statistics"""
try:
# Get document count
results = self.solr.search(q='*:*', rows=0)
# Get facet counts for doc_type
facet_results = self.solr.search(
q='*:*',
rows=0,
facet='true',
**{'facet.field': ['doc_type', 'status']}
)
stats = {
'total_documents': results.hits,
'doc_types': {},
'status_counts': {}
}
if hasattr(facet_results, 'facets') and facet_results.facets:
if 'facet_fields' in facet_results.facets:
# Parse doc_type facets
doc_type_facets = facet_results.facets['facet_fields'].get('doc_type', [])
for i in range(0, len(doc_type_facets), 2):
stats['doc_types'][doc_type_facets[i]] = doc_type_facets[i+1]
# Parse status facets
status_facets = facet_results.facets['facet_fields'].get('status', [])
for i in range(0, len(status_facets), 2):
stats['status_counts'][status_facets[i]] = status_facets[i+1]
return stats
except Exception as e:
logger.error(f"Failed to get stats: {e}")
return {'error': str(e)}
def optimize_index(self) -> bool:
"""Optimize the Solr index"""
try:
self.solr.optimize()
logger.info("Index optimized")
return True
except Exception as e:
logger.error(f"Failed to optimize index: {e}")
return False

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#!/usr/bin/env python3
"""
Test script for Search Service with Apache Solr
"""
import asyncio
import httpx
import json
from datetime import datetime
BASE_URL = "http://localhost:8015"
async def test_search_api():
"""Test search API endpoints"""
async with httpx.AsyncClient() as client:
print("\n🔍 Testing Search Service API...")
# Test health check
print("\n1. Testing health check...")
response = await client.get(f"{BASE_URL}/health")
print(f"Health check: {response.json()}")
# Test index sample documents
print("\n2. Indexing sample documents...")
# Index user document
user_doc = {
"id": "user_test_001",
"doc_type": "user",
"user_id": "test_001",
"username": "john_doe",
"email": "john@example.com",
"name": "John Doe",
"bio": "Software developer passionate about Python and microservices",
"tags": ["python", "developer", "backend"],
"created_at": datetime.utcnow().isoformat()
}
response = await client.post(f"{BASE_URL}/api/search/index", json=user_doc)
print(f"Indexed user: {response.json()}")
# Index file documents
file_docs = [
{
"id": "file_test_001",
"doc_type": "file",
"file_id": "test_file_001",
"filename": "architecture_diagram.png",
"content_type": "image/png",
"size": 1024000,
"user_id": "test_001",
"tags": ["architecture", "design", "documentation"],
"description": "System architecture diagram showing microservices",
"created_at": datetime.utcnow().isoformat()
},
{
"id": "file_test_002",
"doc_type": "file",
"file_id": "test_file_002",
"filename": "user_manual.pdf",
"content_type": "application/pdf",
"size": 2048000,
"user_id": "test_001",
"tags": ["documentation", "manual", "guide"],
"description": "Complete user manual for the application",
"created_at": datetime.utcnow().isoformat()
}
]
response = await client.post(f"{BASE_URL}/api/search/bulk-index", json=file_docs)
print(f"Bulk indexed files: {response.json()}")
# Index content documents
content_docs = [
{
"id": "content_test_001",
"doc_type": "content",
"content_id": "test_content_001",
"title": "Getting Started with Microservices",
"content": "Microservices architecture is a method of developing software applications as a suite of independently deployable services.",
"summary": "Introduction to microservices architecture patterns",
"author_id": "test_001",
"tags": ["microservices", "architecture", "tutorial"],
"category": "technology",
"status": "published",
"created_at": datetime.utcnow().isoformat()
},
{
"id": "content_test_002",
"doc_type": "content",
"content_id": "test_content_002",
"title": "Python Best Practices",
"content": "Learn the best practices for writing clean, maintainable Python code including PEP 8 style guide.",
"summary": "Essential Python coding standards and practices",
"author_id": "test_001",
"tags": ["python", "programming", "best-practices"],
"category": "programming",
"status": "published",
"created_at": datetime.utcnow().isoformat()
}
]
response = await client.post(f"{BASE_URL}/api/search/bulk-index", json=content_docs)
print(f"Bulk indexed content: {response.json()}")
# Wait for indexing
await asyncio.sleep(2)
# Test basic search
print("\n3. Testing basic search...")
response = await client.get(
f"{BASE_URL}/api/search",
params={"q": "microservices"}
)
results = response.json()
print(f"Search for 'microservices': Found {results['total']} results")
if results['documents']:
print(f"First result: {results['documents'][0].get('title', results['documents'][0].get('filename', 'N/A'))}")
# Test search with filters
print("\n4. Testing filtered search...")
response = await client.get(
f"{BASE_URL}/api/search",
params={
"q": "*:*",
"doc_type": "file",
"rows": 5
}
)
results = response.json()
print(f"Files search: Found {results['total']} files")
# Test faceted search
print("\n5. Testing faceted search...")
response = await client.get(
f"{BASE_URL}/api/search",
params={
"q": "*:*",
"facet": "true",
"facet_field": ["doc_type", "tags", "category", "status"]
}
)
results = response.json()
print(f"Facets: {json.dumps(results['facets'], indent=2)}")
# Test autocomplete/suggest
print("\n6. Testing autocomplete...")
response = await client.get(
f"{BASE_URL}/api/search/suggest",
params={
"q": "micro",
"field": "title",
"limit": 5
}
)
suggestions = response.json()
print(f"Suggestions for 'micro': {suggestions['suggestions']}")
# Test similar documents
print("\n7. Testing similar documents...")
response = await client.get(f"{BASE_URL}/api/search/similar/content_test_001")
if response.status_code == 200:
similar = response.json()
print(f"Found {similar['count']} similar documents")
else:
print(f"Similar search: {response.status_code}")
# Test search with highlighting
print("\n8. Testing search with highlighting...")
response = await client.get(
f"{BASE_URL}/api/search",
params={"q": "Python"}
)
results = response.json()
if results['highlighting']:
print(f"Highlighting results: {len(results['highlighting'])} documents highlighted")
# Test search statistics
print("\n9. Testing search statistics...")
response = await client.get(f"{BASE_URL}/api/search/stats")
if response.status_code == 200:
stats = response.json()
print(f"Index stats: {stats['statistics']}")
# Test complex query
print("\n10. Testing complex query...")
response = await client.get(
f"{BASE_URL}/api/search",
params={
"q": "architecture OR python",
"doc_type": "content",
"sort": "created_at desc",
"rows": 10
}
)
results = response.json()
print(f"Complex query: Found {results['total']} results")
# Test delete document
print("\n11. Testing document deletion...")
response = await client.delete(f"{BASE_URL}/api/search/document/content_test_002")
if response.status_code == 200:
print(f"Deleted document: {response.json()}")
# Verify deletion
await asyncio.sleep(1)
response = await client.get(
f"{BASE_URL}/api/search",
params={"q": "id:content_test_002"}
)
results = response.json()
print(f"Verify deletion: Found {results['total']} results (should be 0)")
async def test_performance():
"""Test search performance"""
print("\n\n⚡ Testing Search Performance...")
async with httpx.AsyncClient(timeout=30.0) as client:
# Index many documents
print("Indexing 100 test documents...")
docs = []
for i in range(100):
docs.append({
"id": f"perf_test_{i}",
"doc_type": "content",
"title": f"Test Document {i}",
"content": f"This is test content for document {i} with various keywords like search, Solr, Python, microservices",
"tags": [f"tag{i%10}", f"category{i%5}"],
"created_at": datetime.utcnow().isoformat()
})
response = await client.post(f"{BASE_URL}/api/search/bulk-index", json=docs)
print(f"Indexed {response.json().get('count', 0)} documents")
# Wait for indexing
await asyncio.sleep(2)
# Test search speed
print("\nTesting search response times...")
import time
queries = ["search", "Python", "document", "test", "microservices"]
for query in queries:
start = time.time()
response = await client.get(
f"{BASE_URL}/api/search",
params={"q": query, "rows": 20}
)
elapsed = time.time() - start
results = response.json()
print(f"Query '{query}': {results['total']} results in {elapsed:.3f}s")
async def test_reindex():
"""Test reindexing from MongoDB"""
print("\n\n🔄 Testing Reindex Functionality...")
async with httpx.AsyncClient() as client:
# Trigger reindex for users collection
print("Triggering reindex for users collection...")
response = await client.post(
f"{BASE_URL}/api/search/reindex/users",
params={"doc_type": "user"}
)
if response.status_code == 200:
print(f"Reindex started: {response.json()}")
else:
print(f"Reindex failed: {response.status_code}")
# Test index optimization
print("\nTesting index optimization...")
response = await client.post(f"{BASE_URL}/api/search/optimize")
if response.status_code == 200:
print(f"Optimization: {response.json()}")
async def main():
"""Run all tests"""
print("=" * 60)
print("SEARCH SERVICE TEST SUITE (Apache Solr)")
print("=" * 60)
print(f"Started at: {datetime.now().isoformat()}")
# Run tests
await test_search_api()
await test_performance()
await test_reindex()
print("\n" + "=" * 60)
print("✅ All search tests completed!")
print(f"Finished at: {datetime.now().isoformat()}")
print("=" * 60)
if __name__ == "__main__":
asyncio.run(main())

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<?xml version="1.0" encoding="UTF-8"?>
<schema name="site11" version="1.6">
<!-- Field Types -->
<fieldType name="string" class="solr.StrField" sortMissingLast="true" omitNorms="true"/>
<fieldType name="boolean" class="solr.BoolField" sortMissingLast="true" omitNorms="true"/>
<fieldType name="int" class="solr.IntPointField" omitNorms="true"/>
<fieldType name="long" class="solr.LongPointField" omitNorms="true"/>
<fieldType name="float" class="solr.FloatPointField" omitNorms="true"/>
<fieldType name="double" class="solr.DoublePointField" omitNorms="true"/>
<fieldType name="date" class="solr.DatePointField" omitNorms="true"/>
<!-- Text field with analysis -->
<fieldType name="text_general" class="solr.TextField" positionIncrementGap="100">
<analyzer type="index">
<tokenizer class="solr.StandardTokenizerFactory"/>
<filter class="solr.StopFilterFactory" ignoreCase="true" words="stopwords.txt"/>
<filter class="solr.LowerCaseFilterFactory"/>
<filter class="solr.EdgeNGramFilterFactory" minGramSize="2" maxGramSize="15"/>
</analyzer>
<analyzer type="query">
<tokenizer class="solr.StandardTokenizerFactory"/>
<filter class="solr.StopFilterFactory" ignoreCase="true" words="stopwords.txt"/>
<filter class="solr.SynonymGraphFilterFactory" synonyms="synonyms.txt" ignoreCase="true" expand="true"/>
<filter class="solr.LowerCaseFilterFactory"/>
</analyzer>
</fieldType>
<!-- Text field for exact matching -->
<fieldType name="text_exact" class="solr.TextField">
<analyzer>
<tokenizer class="solr.KeywordTokenizerFactory"/>
<filter class="solr.LowerCaseFilterFactory"/>
</analyzer>
</fieldType>
<!-- Autocomplete/Suggest field -->
<fieldType name="text_suggest" class="solr.TextField" positionIncrementGap="100">
<analyzer>
<tokenizer class="solr.StandardTokenizerFactory"/>
<filter class="solr.LowerCaseFilterFactory"/>
<filter class="solr.EdgeNGramFilterFactory" minGramSize="1" maxGramSize="20"/>
</analyzer>
</fieldType>
<!-- Fields -->
<field name="id" type="string" indexed="true" stored="true" required="true"/>
<field name="_version_" type="long" indexed="true" stored="true"/>
<!-- Document type and metadata -->
<field name="doc_type" type="string" indexed="true" stored="true" docValues="true"/>
<field name="indexed_at" type="date" indexed="true" stored="true"/>
<!-- Common fields across document types -->
<field name="title" type="text_general" indexed="true" stored="true" termVectors="true"/>
<field name="content" type="text_general" indexed="true" stored="true" termVectors="true"/>
<field name="description" type="text_general" indexed="true" stored="true"/>
<field name="summary" type="text_general" indexed="true" stored="true"/>
<field name="tags" type="string" indexed="true" stored="true" multiValued="true" docValues="true"/>
<field name="category" type="string" indexed="true" stored="true" docValues="true"/>
<field name="status" type="string" indexed="true" stored="true" docValues="true"/>
<!-- User-specific fields -->
<field name="user_id" type="string" indexed="true" stored="true"/>
<field name="username" type="text_exact" indexed="true" stored="true"/>
<field name="email" type="text_exact" indexed="true" stored="true"/>
<field name="name" type="text_general" indexed="true" stored="true"/>
<field name="bio" type="text_general" indexed="true" stored="true"/>
<!-- File-specific fields -->
<field name="file_id" type="string" indexed="true" stored="true"/>
<field name="filename" type="text_general" indexed="true" stored="true"/>
<field name="original_name" type="text_general" indexed="true" stored="true"/>
<field name="content_type" type="string" indexed="true" stored="true" docValues="true"/>
<field name="size" type="long" indexed="true" stored="true"/>
<!-- Content-specific fields -->
<field name="content_id" type="string" indexed="true" stored="true"/>
<field name="author_id" type="string" indexed="true" stored="true"/>
<!-- Dates -->
<field name="created_at" type="date" indexed="true" stored="true"/>
<field name="updated_at" type="date" indexed="true" stored="true"/>
<!-- Suggest field for autocomplete -->
<field name="suggest" type="text_suggest" indexed="true" stored="false" multiValued="true"/>
<!-- Copy fields for better search -->
<copyField source="title" dest="suggest"/>
<copyField source="name" dest="suggest"/>
<copyField source="filename" dest="suggest"/>
<copyField source="tags" dest="suggest"/>
<!-- Dynamic fields -->
<dynamicField name="*_i" type="int" indexed="true" stored="true"/>
<dynamicField name="*_l" type="long" indexed="true" stored="true"/>
<dynamicField name="*_f" type="float" indexed="true" stored="true"/>
<dynamicField name="*_d" type="double" indexed="true" stored="true"/>
<dynamicField name="*_s" type="string" indexed="true" stored="true"/>
<dynamicField name="*_t" type="text_general" indexed="true" stored="true"/>
<dynamicField name="*_dt" type="date" indexed="true" stored="true"/>
<dynamicField name="*_b" type="boolean" indexed="true" stored="true"/>
<!-- Unique Key -->
<uniqueKey>id</uniqueKey>
</schema>

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<?xml version="1.0" encoding="UTF-8" ?>
<config>
<luceneMatchVersion>9.4.0</luceneMatchVersion>
<!-- Data Directory -->
<dataDir>${solr.data.dir:}</dataDir>
<!-- Index Config -->
<indexConfig>
<ramBufferSizeMB>100</ramBufferSizeMB>
<maxBufferedDocs>1000</maxBufferedDocs>
<mergePolicyFactory class="org.apache.solr.index.TieredMergePolicyFactory">
<int name="maxMergeAtOnce">10</int>
<int name="segmentsPerTier">10</int>
</mergePolicyFactory>
</indexConfig>
<!-- Update Handler -->
<updateHandler class="solr.DirectUpdateHandler2">
<updateLog>
<str name="dir">${solr.ulog.dir:}</str>
<int name="numVersionBuckets">${solr.ulog.numVersionBuckets:65536}</int>
</updateLog>
<autoCommit>
<maxTime>${solr.autoCommit.maxTime:15000}</maxTime>
<openSearcher>false</openSearcher>
</autoCommit>
<autoSoftCommit>
<maxTime>${solr.autoSoftCommit.maxTime:1000}</maxTime>
</autoSoftCommit>
</updateHandler>
<!-- Query Settings -->
<query>
<maxBooleanClauses>1024</maxBooleanClauses>
<filterCache class="solr.CaffeineCache" size="512" initialSize="512" autowarmCount="0"/>
<queryResultCache class="solr.CaffeineCache" size="512" initialSize="512" autowarmCount="0"/>
<documentCache class="solr.CaffeineCache" size="512" initialSize="512" autowarmCount="0"/>
<enableLazyFieldLoading>true</enableLazyFieldLoading>
<queryResultWindowSize>20</queryResultWindowSize>
<queryResultMaxDocsCached>200</queryResultMaxDocsCached>
</query>
<!-- Request Dispatcher -->
<requestDispatcher>
<requestParsers enableRemoteStreaming="true" multipartUploadLimitInKB="2048000"
formdataUploadLimitInKB="2048" addHttpRequestToContext="false"/>
<httpCaching never304="true"/>
</requestDispatcher>
<!-- Request Handlers -->
<!-- Standard search handler -->
<requestHandler name="/select" class="solr.SearchHandler">
<lst name="defaults">
<str name="echoParams">explicit</str>
<int name="rows">10</int>
<str name="df">content</str>
<str name="q.op">OR</str>
<str name="defType">edismax</str>
<str name="qf">
title^3.0 name^2.5 content^2.0 description^1.5 summary^1.5
filename^1.5 tags^1.2 category username email bio
</str>
<str name="pf">
title^4.0 name^3.0 content^2.5 description^2.0
</str>
<str name="mm">2&lt;-25%</str>
<str name="hl">true</str>
<str name="hl.fl">title,content,description,summary</str>
<str name="hl.simple.pre">&lt;mark&gt;</str>
<str name="hl.simple.post">&lt;/mark&gt;</str>
<str name="facet">true</str>
<str name="facet.mincount">1</str>
</lst>
</requestHandler>
<!-- Update handler -->
<requestHandler name="/update" class="solr.UpdateRequestHandler"/>
<!-- Get handler -->
<requestHandler name="/get" class="solr.RealTimeGetHandler">
<lst name="defaults">
<str name="omitHeader">true</str>
</lst>
</requestHandler>
<!-- Admin handlers -->
<requestHandler name="/admin/ping" class="solr.PingRequestHandler">
<lst name="invariants">
<str name="q">solrpingquery</str>
</lst>
<lst name="defaults">
<str name="echoParams">all</str>
</lst>
</requestHandler>
<!-- Suggest/Autocomplete handler -->
<requestHandler name="/suggest" class="solr.SearchHandler">
<lst name="defaults">
<str name="suggest">true</str>
<str name="suggest.count">10</str>
<str name="suggest.dictionary">suggest</str>
</lst>
<arr name="components">
<str>suggest</str>
</arr>
</requestHandler>
<!-- Spell check component -->
<searchComponent name="spellcheck" class="solr.SpellCheckComponent">
<str name="queryAnalyzerFieldType">text_general</str>
<lst name="spellchecker">
<str name="name">default</str>
<str name="field">content</str>
<str name="classname">solr.DirectSolrSpellChecker</str>
<str name="distanceMeasure">internal</str>
<float name="accuracy">0.5</float>
<int name="maxEdits">2</int>
<int name="minPrefix">1</int>
<int name="maxInspections">5</int>
<int name="minQueryLength">4</int>
<float name="maxQueryFrequency">0.01</float>
</lst>
</searchComponent>
<!-- Suggest component -->
<searchComponent name="suggest" class="solr.SuggestComponent">
<lst name="suggester">
<str name="name">suggest</str>
<str name="lookupImpl">FuzzyLookupFactory</str>
<str name="dictionaryImpl">DocumentDictionaryFactory</str>
<str name="field">suggest</str>
<str name="suggestAnalyzerFieldType">text_suggest</str>
<str name="buildOnStartup">false</str>
</lst>
</searchComponent>
<!-- More Like This handler -->
<requestHandler name="/mlt" class="solr.MoreLikeThisHandler">
<lst name="defaults">
<str name="mlt.fl">title,content,description,tags</str>
<int name="mlt.mindf">1</int>
<int name="mlt.mintf">1</int>
<int name="mlt.count">10</int>
</lst>
</requestHandler>
<!-- Schema handler -->
<requestHandler name="/schema" class="solr.SchemaHandler"/>
<!-- Config handler -->
<requestHandler name="/config" class="solr.ConfigHandler"/>
</config>