SOCKET_TIMEOUT ClickHouse error

This error occurs when network socket operations exceed their timeout limits. It's common with slow network connections, large data transfers, or insufficient timeout configurations.

The SOCKET_TIMEOUT error in ClickHouse (and Tinybird) happens when network socket operations exceed their configured timeout limits. This typically occurs with slow network connections, large data transfers, network congestion, or when timeout values are set too low for the operation being performed.

What causes this error

You'll typically see it when:

  • Network operations take longer than timeout limits
  • Large data transfers exceed socket timeouts
  • Network congestion or slow connections
  • Insufficient timeout configurations
  • Firewall or proxy issues
  • Network infrastructure problems
  • Client-server network latency
  • Insufficient bandwidth for data volume

Socket timeouts are often configurable. Increase timeout values for operations that require more time.

Example errors

Fails: network operation timeout
SELECT * FROM large_table WHERE timestamp > '2024-01-01'
-- Error: SOCKET_TIMEOUT
Fails: large data transfer timeout
INSERT INTO events FROM INFILE '/path/to/large_file.csv'
-- Error: SOCKET_TIMEOUT
Fails: slow network connection
-- When network is slow or congested
SELECT COUNT(*) FROM events GROUP BY user_id
-- Error: SOCKET_TIMEOUT
Fails: insufficient timeout
-- When timeout is too low for operation
SELECT * FROM very_large_table ORDER BY timestamp
-- Error: SOCKET_TIMEOUT

How to fix it

Increase timeout settings

Adjust timeout values for your operations:

Increase timeouts
-- Set longer timeout values
SET send_receive_timeout = 600;      -- 10 minutes
SET sync_request_timeout = 600;      -- 10 minutes
SET keep_alive_timeout = 60;         -- 1 minute
SET connect_timeout = 30;            -- 30 seconds

Check network connectivity

Verify network connection quality:

Check network
-- Test network connectivity
-- Example for Linux:
-- ping your-clickhouse-host
-- traceroute your-clickhouse-host
--
-- Example for Python:
-- import socket
-- sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
-- sock.settimeout(10)
-- result = sock.connect_ex(('your-host', 9000))
-- sock.close()
-- print(f"Connection result: {result}")

Optimize query performance

Improve query efficiency to reduce transfer time:

Query optimization
-- Use more efficient queries
SELECT user_id, COUNT(*) as event_count
FROM events
WHERE timestamp >= '2024-01-01'
GROUP BY user_id
LIMIT 1000

-- Instead of
SELECT * FROM events WHERE timestamp > '2024-01-01'

Use connection pooling

Implement connection pooling for better reliability:

Connection pooling
-- In your application, implement connection pooling
-- Example for Python clickhouse-driver:
from clickhouse_driver import Client

client = Client(
    host='your-host',
    port=9000,
    settings={
        'send_receive_timeout': 600,
        'sync_request_timeout': 600,
        'connect_timeout': 30
    }
)

Common patterns and solutions

Client timeout configuration

Configure timeouts in your client application:

Client configuration
-- Configure client timeouts
-- Example for Python clickhouse-driver:
client = Client(
    host='your-host',
    port=9000,
    database='your_database',
    settings={
        'send_receive_timeout': 600,      -- 10 minutes
        'sync_request_timeout': 600,      -- 10 minutes
        'keep_alive_timeout': 60,         -- 1 minute
        'connect_timeout': 30,            -- 30 seconds
        'max_execution_time': 300         -- 5 minutes
    }
)

Network optimization

Optimize network operations:

Network optimization
-- Use appropriate network settings
-- Example for Python:
import socket

# Set socket options
sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
sock.setsockopt(socket.SOL_SOCKET, socket.SO_KEEPALIVE, 1)
sock.setsockopt(socket.IPPROTO_TCP, socket.TCP_KEEPIDLE, 60)
sock.setsockopt(socket.IPPROTO_TCP, socket.TCP_KEEPINTVL, 10)
sock.setsockopt(socket.IPPROTO_TCP, socket.TCP_KEEPCNT, 5)

Query batching

Break down large operations into smaller batches:

Query batching
-- Process data in smaller batches
-- Example pseudo-code:
--
-- def process_in_batches(table_name, batch_size=10000):
--     offset = 0
--     while True:
--         query = f"""
--             SELECT * FROM {table_name}
--             ORDER BY id
--             LIMIT {batch_size} OFFSET {offset}
--         """
--
--         try:
--             result = client.execute(query)
--             if not result:
--                 break
--
--             # Process batch
--             process_batch(result)
--             offset += batch_size
--
--         except SocketTimeout:
--             # Handle timeout
--             logger.warning(f"Timeout at offset {offset}")
--             time.sleep(5)  # Wait before retry

Retry logic

Implement retry mechanisms for timeout errors:

Retry logic
-- Implement retry logic for timeouts
-- Example pseudo-code:
--
-- def execute_with_retry(query, max_retries=3, base_delay=1):
--     for attempt in range(max_retries):
--         try:
--             result = client.execute(query)
--             return result
--         except SocketTimeout as e:
--             if attempt < max_retries - 1:
--                 delay = base_delay * (2 ** attempt)
--                 logger.warning(f"Socket timeout, retrying in {delay}s")
--                 time.sleep(delay)
--                 continue
--             else:
--                 raise

Tinybird-specific notes

In Tinybird, SOCKET_TIMEOUT errors often occur when:

  • API endpoints have slow response times
  • Large data transfers exceed timeout limits
  • Network issues between client and Tinybird
  • External data source connectivity problems
  • Rate limiting causes connection delays

To debug in Tinybird:

  1. Check your network connectivity to Tinybird
  2. Verify API endpoint response times
  3. Review data transfer sizes
  4. Check for rate limiting issues

In Tinybird, use the status page to check for known service issues before troubleshooting network problems.

Best practices

Timeout configuration

  • Set appropriate timeout values for different operations
  • Use longer timeouts for large data transfers
  • Implement progressive timeout strategies
  • Monitor timeout patterns and adjust accordingly

Network optimization

  • Use connection pooling for better reliability
  • Implement keep-alive mechanisms
  • Monitor network performance metrics
  • Use appropriate network configurations

Error handling

  • Implement retry logic for timeout errors
  • Use exponential backoff strategies
  • Log timeout occurrences for analysis
  • Provide user feedback for long operations

Configuration options

Socket settings

Socket configuration
-- Check current socket settings
SELECT
    name,
    value,
    description
FROM system.settings
WHERE name LIKE '%timeout%' OR name LIKE '%socket%'

Network settings

Network configuration
-- Configure network parameters
SET send_receive_timeout = 600;
SET sync_request_timeout = 600;
SET keep_alive_timeout = 60;
SET connect_timeout = 30;

Client settings

Client configuration
-- Configure client-side timeouts
-- Example for Python clickhouse-driver:
client = Client(
    host='your-host',
    port=9000,
    settings={
        'send_receive_timeout': 600,
        'sync_request_timeout': 600,
        'connect_timeout': 30,
        'max_execution_time': 300
    }
)

Alternative solutions

Use connection proxies

Implement connection proxying:

Connection proxy
-- Use a connection proxy for better reliability
-- Example pseudo-code:
--
-- class ConnectionProxy:
--     def __init__(self, primary_host, backup_hosts):
--         self.primary_host = primary_host
--         self.backup_hosts = backup_hosts
--         self.current_host = primary_host
--
--     def get_connection(self):
--         try:
--             return Client(host=self.current_host)
--         except SocketTimeout:
--             self._switch_to_backup()
--             return Client(host=self.current_host)
--
--     def _switch_to_backup(self):
--         if self.current_host == self.primary_host:
--             self.current_host = self.backup_hosts[0]
--         else:
--             current_index = self.backup_hosts.index(self.current_host)
--             next_index = (current_index + 1) % len(self.backup_hosts)
--             self.current_host = self.backup_hosts[next_index]

Implement circuit breaker

Add circuit breaker pattern:

Circuit breaker
-- Implement circuit breaker for network operations
-- Example pseudo-code:
--
-- class CircuitBreaker:
--     def __init__(self, failure_threshold=5, recovery_timeout=60):
--         self.failure_threshold = failure_threshold
--         self.recovery_timeout = recovery_timeout
--         self.failure_count = 0
--         self.last_failure_time = 0
--         self.state = 'CLOSED'
--
--     def call(self, func, *args, **kwargs):
--         if self.state == 'OPEN':
--             if time.time() - self.last_failure_time > self.recovery_timeout:
--                 self.state = 'HALF_OPEN'
--             else:
--                 raise Exception("Circuit breaker is OPEN")
--
--         try:
--             result = func(*args, **kwargs)
--             self._on_success()
--             return result
--         except SocketTimeout:
--             self._on_failure()
--             raise
--
--     def _on_success(self):
--         self.failure_count = 0
--         self.state = 'CLOSED'
--
--     def _on_failure(self):
--         self.failure_count += 1
--         self.last_failure_time = time.time()
--
--         if self.failure_count >= self.failure_threshold:
--             self.state = 'OPEN'

Use asynchronous operations

Implement async patterns:

Async operations
-- Use async/await patterns for network operations
-- Example pseudo-code:
--
-- import asyncio
--
-- async def execute_query_async(query):
--     loop = asyncio.get_event_loop()
--     return await loop.run_in_executor(None, execute_query, query)
--
-- async def main():
--     tasks = []
--     for query in queries:
--         task = asyncio.create_task(execute_query_async(query))
--         tasks.append(task)
--
--     results = await asyncio.gather(*tasks, return_exceptions=True)
--     return results

Monitoring and prevention

Timeout monitoring

Timeout tracking
-- Monitor timeout occurrences
-- Example pseudo-code:
--
-- def track_timeout(operation, timeout_value, actual_duration):
--     logger.warning(f"Socket timeout: {operation}")
--     logger.warning(f"Timeout value: {timeout_value}s")
--     logger.warning(f"Actual duration: {actual_duration}s")
--
--     # Track timeout metrics
--     increment_counter('socket_timeouts', {
--         'operation': operation,
--         'timeout_value': timeout_value,
--         'actual_duration': actual_duration
--     })

Network performance tracking

Performance monitoring
-- Track network performance metrics
-- Example pseudo-code:
--
-- class NetworkMonitor:
--     def __init__(self):
--         self.operations = []
--
--     def track_operation(self, operation, duration, success):
--         self.operations.append({
--             'operation': operation,
--             'duration': duration,
--             'success': success,
--             'timestamp': time.time()
--         })
--
--     def get_performance_stats(self):
--         if not self.operations:
--             return {}
--
--         successful = [op for op in self.operations if op['success']]
--         failed = [op for op in self.operations if not op['success']]
--
--         return {
--             'total_operations': len(self.operations),
--             'success_rate': len(successful) / len(self.operations),
--             'avg_duration': sum(op['duration'] for op in successful) / len(successful) if successful else 0,
--             'timeout_count': len(failed)
--         }

Proactive monitoring

Proactive monitoring
-- Implement proactive network monitoring
-- Example pseudo-code:
--
-- def check_network_health():
--     try:
--         # Simple health check
--         start_time = time.time()
--         result = client.execute("SELECT 1")
--         duration = time.time() - start_time
--
--         if duration > 5:  # 5 second threshold
--             send_alert(f"Network latency high: {duration:.2f}s")
--
--         return True
--     except Exception as e:
--         send_alert(f"Network health check failed: {e}")
--         return False

See also

Updated