En yavaş / en maliyetli sorguları bul

Oracle

SELECT sql_id,
       ROUND(elapsed_time/1e6, 1) AS elapsed_sec,
       executions,
       ROUND(elapsed_time/1e6/NULLIF(executions,0), 3) AS sec_per_exec,
       sql_text
FROM v$sql
ORDER BY elapsed_time DESC
FETCH FIRST 10 ROWS ONLY;

Geçmiş analiz için AWR: dba_hist_sqlstat. sql_id ile DBMS_XPLAN.DISPLAY_CURSOR planı verir.

PostgreSQL

SELECT calls,
       ROUND(total_exec_time::numeric, 1) AS total_ms,
       ROUND(mean_exec_time::numeric, 2) AS mean_ms,
       query
FROM pg_stat_statements
ORDER BY total_exec_time DESC
LIMIT 10;

pg_stat_statements eklentisi gerekir (shared_preload_libraries). Sıfırlamak için pg_stat_statements_reset().

MySQL

SELECT digest_text,
       count_star AS calls,
       ROUND(sum_timer_wait/1e12, 2) AS total_sec,
       ROUND(avg_timer_wait/1e9, 2) AS avg_ms
FROM performance_schema.events_statements_summary_by_digest
ORDER BY sum_timer_wait DESC
LIMIT 10;

Alternatif: slow_query_log = ON ve long_query_time ayarıyla yavaş sorgu logu.

SQL Server

SELECT TOP 10
       qs.execution_count,
       qs.total_elapsed_time/1000 AS total_ms,
       qs.total_elapsed_time/qs.execution_count/1000 AS avg_ms,
       SUBSTRING(t.text, 1, 200) AS sql_text
FROM sys.dm_exec_query_stats qs
CROSS APPLY sys.dm_exec_sql_text(qs.sql_handle) t
ORDER BY qs.total_elapsed_time DESC;

Query Store açıksa daha zengin tarihsel analiz için sys.query_store_runtime_stats kullanın.

MongoDB

// Profiler'ı 100ms üstü için aç:
db.setProfilingLevel(1, { slowms: 100 })
// Sonra en yavaşları oku:
db.system.profile.find().sort({ millis: -1 }).limit(10)

Profiler yazma yükü getirir; teşhis sonrası db.setProfilingLevel(0) ile kapatın.

Redis

SLOWLOG GET 10
# Eşiği ayarla (mikrosaniye): CONFIG SET slowlog-log-slower-than 10000

slowlog-log-slower-than mikrosaniye cinsindendir (10000 = 10 ms). SLOWLOG RESET ile temizlenir.