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MySQL Guides

Scope
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This section focuses on how MySQL executes queries and how to diagnose performance issues in practice.

Guides here explain:

  • How a SQL statement flows through the MySQL server
  • How the optimizer chooses access paths
  • How to read EXPLAIN output meaningfully
  • How index design affects real workloads
  • How to build a repeatable slow-query diagnostic workflow

If you want step‑by‑step experiments and measured results, see the Labs section.

→ Labs
→ PostgreSQL Labs (for comparison and trade-offs)

Topics covered
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Query execution pipeline
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  • Server layer vs storage engine (InnoDB)
  • Parsing, optimization, and execution phases
  • Where performance problems usually originate

EXPLAIN and diagnostics
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  • Core EXPLAIN fields and what they actually mean
  • Recognizing bad access paths (full scans, filesort, temporary tables)
  • Understanding row estimates vs reality
  • Using EXPLAIN as part of a diagnostic workflow, not in isolation

Index design
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  • Primary vs secondary indexes in InnoDB
  • Composite index rules and common misconceptions
  • Covering indexes and back‑to‑table costs
  • Index selectivity and cardinality pitfalls

Performance workflows
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  • Slow query logging and analysis
  • From symptom → hypothesis → fix → validation
  • Avoiding “fix by accident” tuning
  • Balancing read performance with write cost

Reliability and operations
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  • Replication basics and read scaling
  • Schema changes and operational safety
  • When MySQL is the right choice — and when it is not

How to use these guides
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  1. Use Guides to build a correct mental model of MySQL behavior
  2. Use Labs to validate that model with real execution plans and timings

Typical flow:

  • Guide: How MySQL chooses an index
  • Lab: EXPLAIN-based comparison on realistic datasets

Philosophy
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  • Understand the engine and optimizer, not just SQL syntax
  • Diagnose before tuning
  • Optimize for production behavior, not micro-benchmarks

These guides are written for engineers and architects who need to explain MySQL performance decisions clearly — to teammates, reviewers, and interviewers.