Utiliser pg_stat_statements et pg_buffercache
Exploitez des extensions puissantes telles que `pg_stat_statements` et `pg_buffercache` pour obtenir des informations détaillées sur les performances.
Utiliser pg_stat_statements et pg_buffercache est une leçon PostgreSQL Performance & Query Optimization gratuite sur CoddyKit. Ceci est la leçon 1 sur 4. Tu peux lire la leçon complète ci-dessous gratuitement — puis la pratiquer en direct dans le navigateur avec un éditeur de code intégré et un tuteur IA 24/7. Elle fait partie du parcours d'apprentissage PostgreSQL Performance & Query Optimization, et ta progression se synchronise sur le web et l'application CoddyKit. Le cours PostgreSQL Performance & Query Optimization comprend 4 leçons au total.
Certaines parties de cette leçon n'ont pas encore été traduites et s'affichent en anglais.
PostgreSQL Extensions: Power-Ups
PostgreSQL is incredibly powerful, and its functionality can be extended even further using extensions.
Extensions are modules that add new functions, data types, operators, and more to your database. They're like plugins that enhance your database's capabilities without modifying its core code.
In this lesson, we'll explore two crucial extensions for performance monitoring: pg_stat_statements and pg_buffercache.
Meet pg_stat_statements: Query Profiler
pg_stat_statements is an invaluable tool for understanding your database's workload. It tracks execution statistics for all SQL statements executed by the server.
This extension helps you identify:
- Which queries are run most frequently.
- Which queries consume the most total time.
- Queries with high average execution times.
- Queries that read/write a lot of disk blocks.
It's your go-to for pinpointing performance bottlenecks at the query level.
Activating pg_stat_statements
To use pg_stat_statements, you first need to enable it in your PostgreSQL configuration.
1. Edit your postgresql.conf file and add pg_stat_statements to the shared_preload_libraries parameter. E.g., shared_preload_libraries = 'pg_stat_statements'.
2. Restart your PostgreSQL server for the change to take effect.
3. Finally, connect to your database and create the extension:
CREATE EXTENSION pg_stat_statements;Deciphering pg_stat_statements Output
Once enabled, pg_stat_statements collects data in a view named pg_stat_statements. Here are some key columns you'll often check:
query: The normalized SQL statement.calls: How many times the query was executed.total_time: Total time spent executing this query (in milliseconds).mean_time: Average execution time per call.rows: Total rows returned or affected.shared_blks_hit/shared_blks_read: Cache hits vs. disk reads.
Sorting by total_time helps find the biggest overall resource consumers.
Practical Example: Top Queries
Let's see how to find the top 5 queries that have consumed the most total execution time. This query helps you prioritize your optimization efforts.
The hit_percent column gives you an idea of how effective PostgreSQL's buffer cache is for that query.
SELECT
query,
calls,
total_time,
mean_time,
rows,
100.0 * shared_blks_hit / (shared_blks_hit + shared_blks_read + 1) AS hit_percent
FROM
pg_stat_statements
ORDER BY
total_time DESC
LIMIT 5;Meet pg_buffercache: Memory Inspector
While pg_stat_statements shows you query performance, pg_buffercache gives you insight into PostgreSQL's shared buffer cache. This is the memory area where PostgreSQL stores frequently accessed data blocks.
Understanding what's in the buffer cache helps you determine:
- Which tables or indexes are most actively used.
- If your
shared_bufferssetting is adequate. - Whether queries are benefiting from cached data or hitting disk.
Activating pg_buffercache
Enabling pg_buffercache is simpler than pg_stat_statements. It typically does not require modification to shared_preload_libraries or a server restart.
You just need to connect to your database and create the extension:
CREATE EXTENSION pg_buffercache;Peeking into the Shared Buffer Cache
After creating the extension, you can query the pg_buffercache view to see which relations (tables or indexes) occupy the most buffers. Each buffer typically represents an 8KB data block.
This query shows the top 5 relations by the number of buffers they occupy in the cache:
SELECT
c.relname AS relation_name,
count(*) AS buffers_in_cache
FROM
pg_buffercache b
JOIN
pg_class c ON b.relfilenode = c.relfilenode
JOIN
pg_database d ON b.reldatabase = d.oid AND d.datname = current_database()
GROUP BY
c.relname
ORDER BY
buffers_in_cache DESC
LIMIT 5;Interpreting Cache Effectiveness
If a table or index consistently appears at the top of the pg_buffercache output with many buffers, it means that data is frequently accessed and kept in memory.
This is generally a good sign, as memory access is much faster than disk I/O. A high hit_percent in pg_stat_statements often correlates with data being present in the buffer cache.
You can use this information to decide if increasing shared_buffers or optimizing queries to access less data would be beneficial.
Quick Check: Monitoring Tools
Which of the following statements are true regarding pg_stat_statements and pg_buffercache?
Recap: Deep Dives with Extensions
Great job! You've learned how to leverage two powerful PostgreSQL extensions for performance monitoring:
pg_stat_statements: Your essential tool for profiling SQL queries, identifying slow-running or frequently executed statements, and understanding their resource consumption.pg_buffercache: Gives you visibility into the shared buffer cache, helping you understand what data is actively residing in memory and how effectively your caching is working.
Combined, these extensions provide deep insights into your database's workload and memory utilization, guiding your optimization efforts.
Questions Fréquemment Posées
La leçon « Utiliser pg_stat_statements et pg_buffercache » est-elle gratuite ?
Oui — le texte complet de « Utiliser pg_stat_statements et pg_buffercache » est gratuit à lire ici sur le web. Pour la pratiquer de manière interactive (un éditeur de code intégré et un tuteur IA 24/7) et déverrouiller le reste du cours PostgreSQL Performance & Query Optimization, passe à CoddyKit PRO. Le cours PostgreSQL Performance & Query Optimization comprend 4 leçons au total.
Qu'est-ce que j'apprendrai dans « Utiliser pg_stat_statements et pg_buffercache » ?
Exploitez des extensions puissantes telles que `pg_stat_statements` et `pg_buffercache` pour obtenir des informations détaillées sur les performances. Tu pratiques PostgreSQL Performance & Query Optimization avec du code pratique que tu exécutes directement dans le navigateur, et un tuteur IA 24/7 répond à tes questions au fur et à mesure que tu avances dans la leçon.
Dois-je avoir de l'expérience pour commencer PostgreSQL Performance & Query Optimization ?
Aucune expérience préalable n'est requise. PostgreSQL Performance & Query Optimization sur CoddyKit est structuré pour les débutants jusqu'aux apprenants avancés, donc tu peux commencer ici ou depuis le début et avancer à ton rythme. Ceci est la leçon 1 sur 4.
Combien de temps prend la leçon « Utiliser pg_stat_statements et pg_buffercache » ?
La plupart des leçons CoddyKit prennent environ 5–10 minutes. Chacune est courte et interactive, tu progresses régulièrement et tu repiques exactement où tu t'es arrêté sur le web et l'app.
Peux-tu écrire et exécuter du code dans cette leçon PostgreSQL Performance & Query Optimization ?
Oui. Chaque leçon PostgreSQL Performance & Query Optimization inclut un éditeur de code intégré, tu écris et exécutes du vrai code directement dans ton navigateur et tu reçois des retours IA instantanés — aucune configuration locale requise.
Toutes les leçons de ce cours
- Utiliser pg_stat_statements et pg_buffercache
- Configuration de la journalisation pour l’analyse
- Intégration d’outils de supervision externes
- Diagnostiquer l’activité en direct avec pg_stat_activity