Diagnozowanie nasycenia puli i kolejkowania
Czytaj statystyki PgBouncer, aby wykryć wyczerpane pule i oczekujących klientów, zanim zauważą to użytkownicy.
Diagnozowanie nasycenia puli i kolejkowania to bezpłatna lekcja PostgreSQL Performance & Query Optimization na CoddyKit. To lekcja 4 z 4. Możesz przeczytać całą lekcję poniżej za darmo — a potem ćwiczyć ją interaktywnie w przeglądarce z wbudowanym edytorem kodu i tutorem AI dostępnym 24/7. To część ścieżki edukacyjnej PostgreSQL Performance & Query Optimization, a Twój postęp synchronizuje się między webem a aplikacją CoddyKit. Kurs PostgreSQL Performance & Query Optimization zawiera 4 lekcji w sumie.
Części tej lekcji nie zostały jeszcze przetłumaczone i są wyświetlane po angielsku.
Why Pools Saturate
PgBouncer multiplexes many client connections onto a small set of server connections. In transaction pooling, a server connection is borrowed only for the duration of a transaction, then returned to the pool.
A pool saturates when every server connection is busy and new client requests must wait in a queue. The queue is invisible from the database's side — Postgres just sees a steady, capped number of backends — so you must read PgBouncer's own stats to see the pressure building.
pool_size= max server connections per (database, user) pool- Waiting clients = demand that exceeds that ceiling
Connecting to the Admin Console
PgBouncer exposes a virtual database called pgbouncer. Connect to it with psql using a user listed in admin_users, then run SHOW commands to read its internal state.
This is your primary diagnostic surface — there is no separate dashboard required.
-- Connect to the PgBouncer admin console
psql -h 127.0.0.1 -p 6432 -U pgbouncer pgbouncer
-- Once inside, list the available diagnostic views
SHOW HELP;SHOW POOLS: the cl_waiting Column
SHOW POOLS is the single most important command for spotting saturation. Each row is one pool, identified by database and user.
cl_active— clients currently bound to a server connectioncl_waiting— clients queued, waiting for a free server connectionsv_active— server connections busy serving a transactionsv_idle— server connections free to be assigned
The rule of thumb: any sustained cl_waiting > 0 with sv_idle = 0 means the pool is saturated.
-- Run inside the pgbouncer admin database
SHOW POOLS;Reading a Saturated Pool
Compare two snapshots. A healthy pool keeps spare idle servers and an empty wait queue:
cl_active=18 cl_waiting=0 sv_active=6 sv_idle=14→ plenty of headroomcl_active=20 cl_waiting=47 sv_active=20 sv_idle=0→ saturated and queueing
In the second case sv_active equals pool_size, sv_idle is zero, and 47 clients are stuck in line. Latency users feel = queue wait + actual query time.
maxwait: How Long the Queue Has Been Stuck
SHOW POOLS also reports maxwait and maxwait_us — the time the oldest waiting client has been queued, in seconds and microseconds.
This is your early-warning metric. A non-zero and growing maxwait means clients are not just queued but starving. If maxwait approaches your application's statement or connection timeout, requests will start failing before users even get a response.
maxwait = 0→ nobody is waiting right nowmaxwait = 4and climbing → act now, the pool is too small or the DB is too slow
-- Focus on the queue-pressure columns
-- (column subset shown conceptually; SHOW POOLS returns all)
SHOW POOLS;
-- Watch: database | user | cl_waiting | sv_idle | maxwait | maxwait_usPolling for Saturation Trends
A single snapshot can mislead — pools fill and drain in bursts. Watch the trend by polling the admin console on an interval and logging the key columns.
From a shell you can loop psql and grep the pool you care about. Rising cl_waiting across samples confirms real saturation rather than a momentary spike.
-- Poll PgBouncer every 2 seconds, watch one pool
watch -n 2 "psql -h 127.0.0.1 -p 6432 -U pgbouncer \
-d pgbouncer -c 'SHOW POOLS;' | grep ' app_db '"SHOW STATS: Throughput and Query Time
Saturation has two root causes: too little capacity, or queries that hold server connections too long. SHOW STATS separates them.
avg_query_time— average query duration in microsecondsavg_xact_time— average transaction duration; long transactions hog server connectionsavg_query_count— queries per second
If avg_xact_time is high, raising pool_size only delays the problem — fix the slow transactions instead.
-- Per-database throughput and timing averages
SHOW STATS;Correlating With Postgres Itself
PgBouncer tells you clients are waiting; Postgres tells you why the server connections are busy. Query pg_stat_activity on the real database to see what those backends are doing.
Long-running queries, idle-in-transaction sessions, or lock waits will pin the limited server connections and feed the PgBouncer queue.
-- On the actual Postgres server: find what is holding backends
SELECT pid,
state,
wait_event_type,
wait_event,
now() - xact_start AS xact_age,
left(query, 60) AS query
FROM pg_stat_activity
WHERE datname = 'app_db'
AND state <> 'idle'
ORDER BY xact_age DESC NULLS LAST;The idle in transaction Trap
A frequent cause of PgBouncer queueing is sessions left idle in transaction: the app opened a transaction, then stalled (waiting on an external call, a slow loop, or a bug) without committing. That server connection stays checked out and unavailable to the pool.
Hunt these down explicitly — they often explain a saturated pool whose avg_query_time looks low.
-- Sessions holding a connection open but doing no work
SELECT pid,
usename,
now() - state_change AS idle_for,
left(query, 80) AS last_query
FROM pg_stat_activity
WHERE state = 'idle in transaction'
ORDER BY idle_for DESC;SHOW CLIENTS and SHOW SERVERS
For finer detail, two more admin views drill into individual connections:
SHOW CLIENTS— every client link; astateofwaitingplus a largewaitvalue pinpoints the starving clientsSHOW SERVERS— every server link and which client (if any) currently owns it
Use these when SHOW POOLS shows queueing and you need to identify exactly which clients or application hosts are affected.
-- Per-connection detail; look for state='waiting' and high 'wait'
SHOW CLIENTS;
-- Which server links are linked to which clients
SHOW SERVERS;Turning Diagnosis Into Action
Once the stats point to a cause, the fix follows directly:
- High
cl_waiting, lowavg_xact_time→ genuine capacity shortage; raisepool_size(and check Postgresmax_connectionshas room) - High
avg_xact_timeor manyidle in transaction→ fix the app/queries; more pool size won't help maxwaitnear app timeout → tunequery_wait_timeoutso clients fail fast instead of hanging- One pool starved, others idle → consider a dedicated pool or
reserve_pool_size
-- Example pgbouncer.ini tuning after diagnosis
[databases]
app_db = host=10.0.0.5 port=5432 dbname=app_db pool_size=40
[pgbouncer]
pool_mode = transaction
default_pool_size = 20
reserve_pool_size = 5
reserve_pool_timeout = 3
query_wait_timeout = 10Quick Check
You read SHOW POOLS and see this row for one pool.
Recap
You can now diagnose PgBouncer pool saturation before users feel it:
- SHOW POOLS — watch
cl_waiting,sv_idle, andmaxwait; sustained waiting with zero idle servers means saturation - SHOW STATS — use
avg_xact_timeto tell a capacity shortage from slow transactions - pg_stat_activity — find the long-running and
idle in transactionbackends pinning your pool - SHOW CLIENTS / SHOW SERVERS — drill down to the exact affected connections
Act on the cause: add capacity only when queries are fast; otherwise fix the transactions, and tune query_wait_timeout so clients fail fast instead of hanging.
Często zadawane pytania
Czy lekcja „Diagnozowanie nasycenia puli i kolejkowania” jest bezpłatna?
Tak — pełny tekst „Diagnozowanie nasycenia puli i kolejkowania” jest dostępny za darmo tutaj w sieci. Aby ćwiczyć ją interaktywnie (wbudowany edytor kodu i tutor AI dostępny 24/7) i odblokować resztę kursu PostgreSQL Performance & Query Optimization, przejdź na CoddyKit PRO. Kurs PostgreSQL Performance & Query Optimization zawiera 4 lekcji w sumie.
Co nauczysz się w „Diagnozowanie nasycenia puli i kolejkowania”?
Czytaj statystyki PgBouncer, aby wykryć wyczerpane pule i oczekujących klientów, zanim zauważą to użytkownicy. Ćwiczysz PostgreSQL Performance & Query Optimization z praktycznym kodem, który uruchamiasz bezpośrednio w przeglądarce, a tutor AI dostępny 24/7 odpowiada na Twoje pytania podczas pracy nad lekcją.
Czy potrzebuję doświadczenia, aby zacząć PostgreSQL Performance & Query Optimization?
Nie wymagamy żadnego doświadczenia. PostgreSQL Performance & Query Optimization w CoddyKit jest strukturyzowany dla początkujących i zaawansowanych użytkowników, więc możesz zacząć tutaj lub od początku i uczyć się w swoim tempie. To lekcja 4 z 4.
Ile czasu zajmuje lekcja „Diagnozowanie nasycenia puli i kolejkowania”?
Większość lekcji CoddyKit trwa około 5–10 minut. Każda lekcja to mały, interaktywny krok, dzięki czemu robisz systematyczne postępy i zawsze wracasz dokładnie do tego samego miejsca — na webie i w aplikacji.
Czy mogę pisać i uruchamiać kod w tej lekcji PostgreSQL Performance & Query Optimization?
Tak. Każda lekcja PostgreSQL Performance & Query Optimization zawiera wbudowany edytor kodu, więc piszesz i uruchamiasz prawdziwy kod bezpośrednio w przeglądarce i od razu otrzymujesz sprzężenie zwrotne od AI — bez konfiguracji na komputerze.
Wszystkie lekcje w tym kursie
- Dlaczego połączenia są kosztowne w PostgreSQL
- Tryby puli transakcyjnej i sesyjnej
- Dopasowanie puli do liczby rdzeni
- Diagnozowanie nasycenia puli i kolejkowania