İşlem ve Oturum Havuzlama Kipleri
Doğru PgBouncer kipini seçin ve işlem havuzlamasında hangi özelliklerin çalışmadığını öğrenin.
İşlem ve Oturum Havuzlama Kipleri, CoddyKit'te ücretsiz bir PostgreSQL Performance & Query Optimization dersidir. Bu, 4 dersinin 2. dersidir. Aşağıdan dersin tamamını ücretsiz okuyabilir, sonra tarayıcıda yerleşik kod editörü ve 7/24 yapay zeka koçu ile uygulamalı olarak pratik yapabilirsin. Bu, PostgreSQL Performance & Query Optimization öğrenme yolunun bir parçasıdır ve ilerlemeniz web ve CoddyKit uygulaması arasında senkronize olur. PostgreSQL Performance & Query Optimization kursu toplamda 4 dersten oluşur.
Bu dersin bazı bölümleri henüz çevrilmemiş olup İngilizce olarak gösterilmektedir.
Why Pooling Modes Matter
Each PostgreSQL backend process costs memory (work_mem, catalog caches, plan caches) and CPU. A few thousand idle client connections can exhaust a server even when nothing is running.
PgBouncer sits between your app and PostgreSQL, multiplexing many client connections onto a small set of real server connections. The pool_mode setting decides when a server connection is handed back to the pool.
- session — server held for the client's whole session
- transaction — server held only for one transaction
- statement — server released after every statement
Session Pooling Mode
In session pooling, a server connection is assigned to a client when it connects and is only returned to the pool when the client disconnects.
This is the safest mode: the client gets a dedicated backend for its entire lifetime, so every PostgreSQL feature behaves exactly as if it connected directly. The cost is poor reuse — an idle but connected client still pins a server connection.
; PgBouncer config: pgbouncer.ini
[pgbouncer]
pool_mode = session
max_client_conn = 10000
default_pool_size = 20
[databases]
appdb = host=127.0.0.1 port=5432 dbname=appdbTransaction Pooling Mode
In transaction pooling, the server connection is assigned only for the duration of a single transaction. The instant the transaction commits or rolls back, the backend goes back to the pool and may serve a different client next.
This gives dramatically better reuse: thousands of mostly-idle clients can share a tiny pool, because a server connection is only borrowed during active work. It is the recommended mode for web apps with many short-lived requests.
[pgbouncer]
pool_mode = transaction
max_client_conn = 10000
default_pool_size = 20
; 10000 clients multiplexed onto only 20 backendsThe Core Tradeoff
The decision is reuse versus feature compatibility:
- Session: full compatibility, low connection reuse.
- Transaction: high reuse, but anything that relies on state outside a transaction can break.
The key insight: in transaction mode, consecutive transactions from the same client may land on different backends. Anything that lives on the connection between transactions is unsafe.
What Breaks: Session-Level State
Because a backend is shared across clients between transactions, any session-scoped state set in one transaction can leak to another client or be lost.
These commonly break under transaction pooling:
SET/SET SESSIONsession GUCs (e.g.SET statement_timeout,SET search_pathoutside a transaction)- Session-level advisory locks (
pg_advisory_lock) LISTEN/NOTIFYsubscriptions- Unparameterized session variables and
WITH HOLDcursors
-- Unsafe in transaction pooling: runs in its own tx,
-- the GUC is reset before your next query reuses a backend
SET statement_timeout = '5s';
-- Session advisory lock may be acquired on one backend
-- and never matched by the unlock on another
SELECT pg_advisory_lock(42);What Breaks: Prepared Statements
Named prepared statements are stored on a specific backend. In transaction mode, your next execution may hit a different backend that has never seen that prepared statement, causing errors like prepared statement "sN" does not exist.
Mitigations:
- Disable client-side prepared statements, or use simple/unnamed protocol.
- PgBouncer 1.21+ supports
max_prepared_statementsto track and re-prepare named statements per backend automatically.
; PgBouncer 1.21+ : safely allow named prepared statements
; in transaction mode by tracking them per server connection
[pgbouncer]
pool_mode = transaction
max_prepared_statements = 200Keep Settings Inside the Transaction
If you need a GUC like statement_timeout or search_path under transaction pooling, scope it to the transaction with SET LOCAL. It applies only until the transaction ends, so it can never leak to the next client on that backend.
Use this pattern instead of a bare SET.
BEGIN;
SET LOCAL statement_timeout = '5s';
SET LOCAL search_path = analytics, public;
SELECT count(*) FROM orders WHERE created_at >= now() - interval '1 day';
COMMIT;Long Transactions Pin the Pool
Transaction pooling only reuses backends between transactions. A long-running or idle-in-transaction query holds its backend the entire time, just like session mode would.
If many clients hold open transactions, the small pool drains and new requests queue. Guard against this:
- Set a low
idle_in_transaction_session_timeouton the server. - Keep transactions short; never
BEGINthen wait on app-side I/O.
-- Server-side safety net (postgresql.conf or ALTER ROLE)
ALTER ROLE app_user SET idle_in_transaction_session_timeout = '10s';
-- Now an app that BEGINs and stalls gets its backend
-- reclaimed instead of starving the PgBouncer poolSizing default_pool_size
Under transaction pooling, default_pool_size is the number of real backends per (database, user) pair. Because work is interleaved, you need far fewer backends than clients.
A common starting point is roughly the number of CPU cores available for queries, not the number of clients. Oversizing the pool just recreates the connection-storm problem you used PgBouncer to avoid.
[pgbouncer]
pool_mode = transaction
default_pool_size = 20 ; ~ matches Postgres CPU capacity
min_pool_size = 5 ; keep warm backends ready
reserve_pool_size = 5 ; burst headroom
max_client_conn = 10000 ; how many apps can attachInspecting Pool Behavior
PgBouncer exposes a virtual admin database. Connect to it and run SHOW POOLS; to see, per pool, how many clients are active/waiting and how many server connections are active/idle.
If cl_waiting is consistently above zero, clients are queuing for a backend — either raise default_pool_size or shorten transactions.
-- psql -p 6432 pgbouncer
SHOW POOLS;
-- columns: database | user | cl_active | cl_waiting
-- sv_active | sv_idle | sv_used | pool_mode
SHOW STATS; -- query/transaction throughput per databasePer-Database Mode Overrides
You do not have to pick one mode globally. Set a default pool_mode and override it per database. A typical split:
- Main OLTP app database in transaction mode for maximum reuse.
- A legacy or admin database that uses
LISTEN/NOTIFY, advisory locks, or temp tables in session mode for correctness.
[databases]
; high-concurrency web traffic -> transaction reuse
appdb = host=127.0.0.1 dbname=appdb pool_mode=transaction
; uses LISTEN/NOTIFY + session advisory locks -> keep session
jobsdb = host=127.0.0.1 dbname=jobsdb pool_mode=sessionQuick Check
Choose the correct behavior under PgBouncer transaction pooling.
Recap
Session vs transaction pooling, distilled:
- Session mode: backend held until client disconnects. Full feature compatibility, low reuse. Use it for databases needing LISTEN/NOTIFY, session advisory locks, or persistent prepared statements.
- Transaction mode: backend released per transaction. High reuse for many short requests, but session-level state can leak or vanish.
- What breaks in transaction mode: bare
SETGUCs, named prepared statements, session advisory locks, LISTEN/NOTIFY, WITH HOLD cursors. - Fixes:
SET LOCALinside a transaction,max_prepared_statements(1.21+), short transactions,idle_in_transaction_session_timeout, and per-databasepool_modeoverrides.
Sıkça Sorulan Sorular
“İşlem ve Oturum Havuzlama Kipleri” dersi ücretsiz mi?
Evet — “İşlem ve Oturum Havuzlama Kipleri” dersin tüm metni burada web'de ücretsiz olarak okunabilir. Etkileşimli olarak pratik yapmak (yerleşik kod editörü ve 7/24 yapay zeka koçu) ve PostgreSQL Performance & Query Optimization kursunun geri kalanını açmak için CoddyKit PRO'ya yükselt. PostgreSQL Performance & Query Optimization kursu toplamda 4 dersten oluşur.
“İşlem ve Oturum Havuzlama Kipleri” dersinde ne öğreneceğim?
Doğru PgBouncer kipini seçin ve işlem havuzlamasında hangi özelliklerin çalışmadığını öğrenin. PostgreSQL Performance & Query Optimization ile uygulamalı kodu tarayıcıda doğrudan çalıştırarak pratik yaparsın ve 7/24 yapay zeka koçu dersi çalışırken sorularını yanıtlar.
PostgreSQL Performance & Query Optimization öğrenmeye başlamak için deneyim gerekli mi?
Önceden deneyim gerekmez. CoddyKit'te PostgreSQL Performance & Query Optimization, başlangıçtan ileri seviyeye kadar yapılandırıldığı için buradan başlayabilir veya başından başlayıp kendi hızında ilerleme yapabilirsin. Bu, 4 dersinin 2. dersidir.
“İşlem ve Oturum Havuzlama Kipleri” dersi ne kadar sürer?
Çoğu CoddyKit dersi yaklaşık 5–10 dakika sürer. Her biri kısa ve etkileşimli olduğu için sabit ilerleme yaparsın ve web ile uygulama arasında tam olarak bıraktığın yerden devam edebilirsin.
Bu PostgreSQL Performance & Query Optimization dersinde kod yazıp çalıştırabilir miyim?
Evet. Her PostgreSQL Performance & Query Optimization dersi yerleşik bir kod editörü içerir, bu sayede tarayıcıda gerçek kod yazıp çalıştırabilir ve anlık yapay zeka geri bildirimi alırsın — yerel kurulum gerekli değildir.
Bu kursun tüm dersleri
- PostgreSQL'de Bağlantılar Neden Maliyetlidir
- İşlem ve Oturum Havuzlama Kipleri
- Havuzları Çekirdek Sayısına Göre Boyutlandırma
- Havuz Doygunluğunu ve Kuyrukları Tanılama