Troubleshooting Suboptimal ClickHouse Queries

To troubleshoot and optimize slow ClickHouse queries, follow these steps:

1. Use EXPLAIN to Analyze Query Plans

EXPLAIN syntax SELECT * FROM table WHERE condition

Available syntax options:

• EXPLAIN PLAN – shows execution plan
• EXPLAIN PIPELINE – shows detailed processing pipeline
• EXPLAIN ESTIMATE – provides execution cost estimates

2. Profile Queries with EXPLAIN ANALYZE

EXPLAIN ANALYZE SELECT * FROM table WHERE condition

This provides actual execution metrics including time spent in each processing step.

3. Check System Tables

Examine query performance data:

SELECT 
    query_id,
    query,
    read_rows,
    read_bytes,
    memory_usage,
    query_duration_ms
FROM system.query_log
WHERE type = 'QueryFinish'
ORDER BY query_duration_ms DESC
LIMIT 10

4. Common Optimization Techniques

1. Proper Schema Design
   • Use appropriate data types (smaller is better)
   • Order columns by frequency of use in WHERE clauses
   • Choose optimal table engines (MergeTree family for analytics)
2. Optimize JOINs
   • Use the join_algorithm setting to control join methods
   • Consider denormalizing data when possible
3. Improve WHERE Clauses
   • Place high-cardinality columns first
   • Avoid functions on indexed columns
   • Use PREWHERE for filtering before reading full rows
4. Partitioning and Sorting
   • Partition by coarse filters (date, category)
   • Sort by frequently filtered columns
5. Materialized Views
   • Pre-aggregate commonly used queries

5. Adjust Server Settings

SET max_threads = 8;
SET max_memory_usage = 20000000000;

Key settings to consider:

• max_threads
• max_memory_usage
• max_bytes_before_external_sort
• max_bytes_before_external_group_by

6. Use Sampling for Large Datasets

SELECT * FROM table SAMPLE 0.1

This helps test query patterns on a fraction of data.

7. Monitor and Adjust

Continuously monitor query performance and adjust your optimization strategy based on changing workloads and data volumes.

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