ClickHouse trace_log: Understanding System Tracing

What is trace_log?

The trace_log is a system table in ClickHouse that provides detailed information about query execution and system events. It captures low-level traces of various operations, including query parsing, optimization, and execution stages. This table is an invaluable tool for performance analysis, debugging, and understanding the internal workings of ClickHouse.

Best practices

1. Enable trace logging selectively: Due to its detailed nature, enable trace_log only when needed for specific investigations to minimize performance overhead.

2. Use appropriate filters: When querying trace_log, use filters on query_id, event_date, and event_time to narrow down the results to relevant data.

3. Combine with other system tables: Correlate trace_log data with other system tables like query_log and part_log for comprehensive analysis.

4. Regular cleanup: Implement a retention policy to prevent trace_log from growing too large over time.

5. Use trace visualization tools: Leverage tools like Jaeger or custom visualizations to interpret trace data more effectively.

Common issues or misuses

1. Overuse in production: Keeping trace_log enabled constantly in production can lead to performance degradation and excessive disk usage.

2. Misinterpreting trace data: Without proper context, trace data can be misinterpreted, leading to incorrect conclusions about query performance.

3. Neglecting to correlate with other metrics: Analyzing trace_log in isolation may not provide a complete picture of system performance.

4. Insufficient filtering: Querying trace_log without proper filters can result in slow queries and excessive resource consumption.

Additional information

The trace_log table structure includes columns such as:

• event_date: Date of the event
• event_time: Timestamp of the event
• revision: ClickHouse server revision
• trace_type: Type of trace event
• thread_id: ID of the thread that generated the event
• query_id: Unique identifier of the query
• trace: Detailed trace information in JSON format

Trace logging can be configured using server settings like trace_log.component and trace_log.probability.

Frequently Asked Questions

Q: How do I enable trace_log in ClickHouse?
A: You can enable trace_log by setting trace_log.component to the components you want to trace (e.g., 'query_execution,query_plan') in the ClickHouse configuration file or using SET commands for specific sessions.

Q: What's the performance impact of using trace_log?
A: The performance impact can be significant, especially with high query volumes. It's recommended to use it selectively and monitor system resources when enabled.

Q: How long are records kept in trace_log?
A: By default, trace_log retains data based on the TTL settings of the table. You can customize this using the ENGINE definition of the trace_log table in your ClickHouse configuration.

Q: Can trace_log help in identifying query bottlenecks?
A: Yes, trace_log can be very helpful in identifying bottlenecks by providing detailed timing information for different stages of query execution and system operations.

Q: Is it possible to export trace_log data for external analysis?
A: Yes, you can export trace_log data like any other table in ClickHouse. You can use SELECT queries with appropriate filters and export the results to various formats supported by ClickHouse, such as CSV or JSON.