أوضاع تجميع المعاملات مقابل الجلسات
اختر وضع PgBouncer المناسب واعرف الميزات التي تتعطل عند استخدام تجميع المعاملات.
أوضاع تجميع المعاملات مقابل الجلسات درس مجاني في PostgreSQL Performance & Query Optimization على CoddyKit. هذا هو الدرس 2 من أصل 4. يمكنك قراءة الدرس كاملاً أدناه مجاناً — ثم تمرن عليه مباشرة في المتصفح باستخدام محرر أكواد مدمج ومدرس ذكاء اصطناعي متاح 24/7. هذا الدرس جزء من مسار التعلم في PostgreSQL Performance & Query Optimization، وتقدمك يتزامن عبر الويب وتطبيق CoddyKit. تتضمن دورة PostgreSQL Performance & Query Optimization 4 دروس في المجموع.
بعض أجزاء هذا الدرس لم تُترجم بعد وتظهر باللغة الإنجليزية.
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.
الأسئلة الشائعة
هل درس «أوضاع تجميع المعاملات مقابل الجلسات» مجاني؟
نعم — نص درس «أوضاع تجميع المعاملات مقابل الجلسات» كامل متاح مجاناً هنا على الويب. لتمرينه بشكل تفاعلي (محرر أكواد مدمج ومدرس ذكاء اصطناعي متاح 24/7) وفتح باقي دورة PostgreSQL Performance & Query Optimization، انتقل إلى CoddyKit PRO. تتضمن دورة PostgreSQL Performance & Query Optimization 4 دروس في المجموع.
ماذا ستتعلم في «أوضاع تجميع المعاملات مقابل الجلسات»؟
اختر وضع PgBouncer المناسب واعرف الميزات التي تتعطل عند استخدام تجميع المعاملات. تتمرن على PostgreSQL Performance & Query Optimization مع أكواد عملية تشغلها مباشرة في المتصفح، ومدرس ذكاء اصطناعي متاح 24/7 يجيب على أسئلتك أثناء عملك.
هل أحتاج إلى خبرة سابقة لأبدأ PostgreSQL Performance & Query Optimization؟
لا تُشترط خبرة سابقة. PostgreSQL Performance & Query Optimization على CoddyKit منظم للمبتدئين حتى المتقدمين، لذا يمكنك البدء من هنا أو من البداية والتقدم بسرعتك الخاصة. هذا هو الدرس 2 من أصل 4.
كم من الوقت يستغرق درس «أوضاع تجميع المعاملات مقابل الجلسات»؟
معظم دروس CoddyKit تستغرق حوالي 5–10 دقائق. كل منها موجز وتفاعلي، لذا تحرز تقدماً مستمراً وتستأنف من حيث توقفت عبر الويب والتطبيق.
هل يمكنني كتابة وتشغيل أكواد في درس PostgreSQL Performance & Query Optimization هذا؟
نعم. كل درس في PostgreSQL Performance & Query Optimization يتضمن محرر أكواد مدمج، لذا تكتب وتشغل أكواداً حقيقية مباشرة في متصفحك وتحصل على تعليقات فورية من الذكاء الاصطناعي — بدون إعداد محلي.
جميع الدروس في هذه الدورة
- لماذا تكون الاتصالات مكلفة في PostgreSQL
- أوضاع تجميع المعاملات مقابل الجلسات
- تحديد حجم مجموعات الاتصالات وفق عدد الأنوية
- تشخيص تشبّع التجميع والانتظار في الطوابير