QUERY_WITH_SAME_ID_IS_ALREADY_RUNNING ClickHouse error¶

The QUERY_WITH_SAME_ID_IS_ALREADY_RUNNING error in ClickHouse (and Tinybird) happens when you try to execute a query with an ID that's already being processed by the system. This is a concurrency control mechanism to prevent duplicate query execution.

What causes this error¶

You'll typically see it when:

• Running the same query multiple times simultaneously
• Retrying a failed query too quickly
• Using the same query ID across multiple concurrent requests
• Having long-running queries that block subsequent identical queries
• Using client libraries that reuse query IDs

Example scenarios¶

-- Query 1 (running)
SELECT COUNT(*) FROM events WHERE timestamp >= now() - INTERVAL 1 HOUR

-- Query 2 (fails - same ID)
SELECT COUNT(*) FROM events WHERE timestamp >= now() - INTERVAL 1 HOUR

-- Query fails due to timeout
SELECT * FROM large_table LIMIT 1000000

-- Immediate retry (fails - same ID)
SELECT * FROM large_table LIMIT 1000000

How to fix it¶

Wait for the query to complete¶

The simplest solution is to wait for the original query to finish:

SELECT query_id, query, status 
FROM system.processes 
WHERE query LIKE '%your_query_pattern%'

Use different query IDs¶

If your client supports it, generate unique query IDs:

-- Client should generate unique query_id for each request
SELECT query_id, query FROM system.processes

Generate unique query IDs¶

Use unique query IDs instead of random elements:

-- Set a unique query ID
SET query_id = 'unique_id_123'
SELECT COUNT(*) FROM events WHERE user_id > 0

Use query hints¶

Some clients allow you to specify query hints:

SELECT /*+ QUERY_ID('unique_id_123') */ 
       COUNT(*) FROM events

Common patterns and solutions¶

Long-running queries¶

For queries that take a long time to complete:

SELECT query_id, query, elapsed, status
FROM system.processes 
ORDER BY elapsed DESC
LIMIT 10

Kill conflicting queries¶

If you need to stop the conflicting query:

KILL QUERY WHERE query_id = 'your_query_id'

Use query timeouts¶

Set appropriate timeouts to prevent long-running queries:

SET max_execution_time = 300  -- 5 minutes
SELECT * FROM large_table

Implement retry logic¶

Add delays between retries:

-- Wait 5 seconds before retry
SELECT sleep(5);
SELECT COUNT(*) FROM events

Advanced solutions¶

Using connection pooling¶

Configure your client to use connection pooling:

-- Configure connection pool in your client
-- This helps manage concurrent connections

Query deduplication¶

Implement query deduplication in your application:

-- Check if query is already running before executing
-- Use unique identifiers for each query instance

Monitoring query execution¶

Set up monitoring for query execution:

SELECT 
    query_id,
    query,
    status,
    elapsed,
    read_rows,
    read_bytes
FROM system.processes 
WHERE status = 'Running'

Tinybird-specific notes¶

In Tinybird, this error often occurs when:

• Running the same query multiple times in quick succession
• Using the same query ID across different API calls
• Having long-running queries in the Query Builder
• Using Materialized Views that take a long time to build

To debug in Tinybird:

1. Check the Query Builder for running queries
2. Wait for long-running queries to complete
3. Use different query parameters to make queries unique
4. Implement proper retry logic in your applications

Tinybird-specific notes¶

REST API: When using the REST API, pass the X-ClickHouse-Query-Id header if you need idempotency; otherwise let the client generate unique IDs.

UI Console: In the Tinybird UI, you can see running queries in the console; there's no need to kill queries via raw SQL.

Best practices¶

Query management¶

• Use unique query IDs when possible
• Implement proper retry logic with exponential backoff
• Monitor query execution times
• Set appropriate timeouts for different query types

Concurrency handling¶

• Limit concurrent queries when necessary
• Use connection pooling effectively
• Implement query queuing for high-load scenarios
• Monitor system resources during query execution

Error handling¶

• Implement proper error handling for this specific error
• Add delays between retries
• Log query conflicts for debugging
• Use circuit breakers for repeated failures

See also¶

• ClickHouse Query Management
• Working with Large Datasets
• Common function errors