ProxySQL Query Rules: Capture Groups and Backreferences

Introduction

ProxySQL's query rules engine supports regular expression capture groups and backreferences, allowing sophisticated query rewriting. This document explains how to use these features to transform SQL queries dynamically.

Core Concepts

Table Columns for Pattern Matching

Regex Engine Support

ProxySQL supports two regex engines (configurable via mysql-query_processor_regex):

• PCRE (default, query_processor_regex=1): Full regex support including capture groups
• RE2 (query_processor_regex=2): Google's RE2 library, supports capture groups in replacement patterns

Both engines support backreferences (\1, \2, etc.) in replace_pattern.

Basic Syntax

Capture Groups in match_pattern

Use parentheses () to define capture groups:

-- Two capture groups: column list and WHERE clause
INSERT INTO mysql_query_rules (
    match_pattern, replace_pattern, apply
) VALUES (
    'SELECT (.*) FROM users WHERE (.*)',
    'SELECT \1 FROM customers WHERE \2',
    1
);

Backreferences in replace_pattern

Reference captured groups with \1, \2, etc.:

-- \1 = column list, \2 = WHERE conditions
'\1 FROM modified_table WHERE \2'

Important: Use single backslash (\1), not double (\\1), in the SQL INSERT statement.

Practical Examples

Example 1: Changing Table Names While Preserving Query Structure

Goal: Rewrite queries from old_table to new_table while keeping all other parts unchanged.

INSERT INTO mysql_query_rules (
    rule_id, active, match_pattern, replace_pattern, re_modifiers, apply
) VALUES (
    1, 1,
    '(SELECT .* FROM )old_table( WHERE .*)',
    '\1new_table\2',
    'CASELESS',
    1
);

Matches: SELECT id, name FROM old_table WHERE status = 'active' Becomes: SELECT id, name FROM new_table WHERE status = 'active'

Example 2: Adding Hints to Specific Queries

Goal: Add FORCE INDEX (primary) to SELECT queries on orders table with specific conditions.

INSERT INTO mysql_query_rules (
    rule_id, active, digest, match_pattern, replace_pattern, apply
) VALUES (
    2, 1, '0x1234567890abcdef',
    '(SELECT .* FROM orders)( WHERE customer_id = \d+.*)',
    '\1 FORCE INDEX (primary)\2',
    1
);

Matches: SELECT * FROM orders WHERE customer_id = 100 AND date > '2024-01-01' Becomes: SELECT * FROM orders FORCE INDEX (primary) WHERE customer_id = 100 AND date > '2024-01-01'

Example 3: Column Renaming in SELECT Queries

Goal: Rename column legacy_id to new_id in all SELECT queries.

INSERT INTO mysql_query_rules (
    rule_id, active, match_pattern, replace_pattern, re_modifiers, apply
) VALUES (
    3, 1,
    '(SELECT.*?)legacy_id(.*FROM.*)',
    '\1new_id\2',
    'CASELESS',
    1
);

Matches: SELECT legacy_id, name FROM products WHERE category = 'electronics' Becomes: SELECT new_id, name FROM products WHERE category = 'electronics'

Example 4: Conditional Rewriting Based on Values

Goal: Add USE INDEX hint only for queries with status = 'pending'.

INSERT INTO mysql_query_rules (
    rule_id, active, match_pattern, replace_pattern, re_modifiers, apply
) VALUES (
    4, 1,
    '(SELECT .* FROM tasks)( WHERE.*status\s*=\s*''pending''.*)',
    '\1 USE INDEX (idx_status)\2',
    'CASELESS',
    1
);

Matches: SELECT * FROM tasks WHERE status = 'pending' AND due_date < NOW() Becomes: SELECT * FROM tasks USE INDEX (idx_status) WHERE status = 'pending' AND due_date < NOW()

Example 5: Complex Multi-Group Rewriting

Goal: Reorder WHERE clause conditions and add optimizer hint.

INSERT INTO mysql_query_rules (
    rule_id, active, match_pattern, replace_pattern, re_modifiers, apply
) VALUES (
    5, 1,
    'SELECT (.*) FROM (\w+) WHERE (column1 = .*) AND (column2 = .*)',
    'SELECT /*+ MAX_EXECUTION_TIME(1000) */ \1 FROM \2 WHERE \4 AND \3',
    'CASELESS',
    1
);

Matches: SELECT id, name FROM accounts WHERE column1 = 'value1' AND column2 = 'value2' Becomes: SELECT /*+ MAX_EXECUTION_TIME(1000) */ id, name FROM accounts WHERE column2 = 'value2' AND column1 = 'value1'

Advanced Techniques

Combining digest and match_pattern

For precise targeting, combine digest (hash of normalized query) with match_pattern (specific values):

INSERT INTO mysql_query_rules (
    rule_id, active, digest, match_pattern, replace_pattern, apply
) VALUES (
    6, 1, '0xa1b2c3d4e5f67890',
    '(SELECT .* FROM users)( WHERE id = 12345.*)',
    '\1 FORCE INDEX (primary)\2',
    1
);

Using re_modifiers

• CASELESS: Case-insensitive matching
• GLOBAL: Replace all occurrences (not just first)

INSERT INTO mysql_query_rules (
    rule_id, active, match_pattern, re_modifiers, replace_pattern, apply
) VALUES (
    7, 1,
    '(SELECT)(.*)(FROM)(.*)',
    'CASELESS,GLOBAL',
    '\1 SQL_NO_CACHE \2\3\4',
    1
);

Rule Chaining with flagIN/flagOUT

For complex transformations, chain rules using flags:

-- Rule 1: Match pattern and set flagOUT
INSERT INTO mysql_query_rules (
    rule_id, active, match_pattern, flagOUT, apply
) VALUES (
    8, 1, 'SELECT .* FROM sensitive_table', 100, 0
);

-- Rule 2: Apply transformation only when flagIN matches
INSERT INTO mysql_query_rules (
    rule_id, active, flagIN, match_pattern, replace_pattern, apply
) VALUES (
    9, 1, 100,
    '(SELECT .* FROM )sensitive_table( WHERE .*)',
    '\1audited_sensitive_table\2',
    1
);

Testing and Validation

1. Verify Rule Matching

-- Check stats for specific rule
SELECT * FROM stats_mysql_query_rules WHERE rule_id = 1;

-- Test pattern matching
SELECT * FROM mysql_query_rules
WHERE match_pattern = '(SELECT .* FROM )old_table( WHERE .*)';

2. Monitor Rule Performance

-- View hits and performance
SELECT rule_id, hits, mysql_query_rules.match_pattern,
       sum_time, min_time, max_time
FROM stats_mysql_query_rules
JOIN mysql_query_rules USING (rule_id)
ORDER BY hits DESC;

Common Pitfalls and Solutions

Problem 1: Groups Not Capturing Entire Needed Text

Symptom: Replacement loses part of the original query.

Solution: Expand capture groups to include more context:

-- Before (loses WHERE clause):
'(SELECT .* FROM table)( WHERE)'

-- After (captures entire WHERE clause):
'(SELECT .* FROM table)( WHERE.*)'

Problem 2: Backreferences Not Working

Symptom: \1 appears literally in output instead of replaced text.

Solution: Ensure:

1. Parentheses in match_pattern define capture groups
2. replace_pattern uses \1, not \\1 or $1
3. Rule is active (active = 1)

Problem 3: Overly Broad Matching

Symptom: Rule applies to unintended queries.

Solution: Add more specific constraints:

• Use digest column to restrict to specific query patterns
• Add username or schemaname restrictions
• Make match_pattern more specific

INSERT INTO mysql_query_rules (
    active, username, digest, match_pattern, replace_pattern, apply
) VALUES (
    1, 'app_user', '0x1234567890abcdef',
    '(SELECT .* FROM orders)( WHERE .*)',
    '\1 FORCE INDEX (primary)\2',
    1
);

Best Practices

1. Test Incrementally: Start with simple patterns, then add complexity.
2. Use digest for Precision: Combine digest with match_pattern for exact targeting.
3. Case-Insensitive by Default: Use re_modifiers = 'CASELESS' unless case sensitivity is required.
4. Monitor Performance: Regularly check stats_mysql_query_rules for rule hits and timing.
5. Document Rules: Add comments to rules explaining their purpose:

INSERT INTO mysql_query_rules (
    rule_id, active, match_pattern, replace_pattern, apply, comment
) VALUES (
    10, 1,
    '(SELECT .* FROM )products( WHERE .*)',
    '\1products_v2\2',
    1,
    'Rewrite: Route queries from products to products_v2 table'
);

6. Version Control: Keep query rule definitions in version-controlled SQL files.

Conclusion

ProxySQL's capture group and backreference capabilities provide powerful query rewriting options. By understanding how to properly structure match_pattern with parentheses and reference captured groups with \1, \2 in replace_pattern, you can implement sophisticated query transformations while maintaining query correctness.

Always test rules in a staging environment before deploying to production, and monitor their impact on query performance and correctness.