DBAtlas · 数据库运维图谱

测量缓存命中率

Oracle

SELECT metric_name, ROUND(value, 2) AS pct
FROM v$sysmetric
WHERE metric_name = 'Buffer Cache Hit Ratio'
  AND intsize_csec = (SELECT MAX(intsize_csec) FROM v$sysmetric);

命中率低并不总是坏事;应结合工作负载解读,而不是孤立看待。

PostgreSQL

SELECT ROUND(sum(blks_hit) * 100.0 / NULLIF(sum(blks_hit) + sum(blks_read), 0), 2) AS cache_hit_pct
FROM pg_stat_database;

目标通常为 99%+。若偏低,检查 shared_buffers 和操作系统缓存。

MySQL

SELECT ROUND((1 - (
    (SELECT variable_value FROM performance_schema.global_status WHERE variable_name='Innodb_buffer_pool_reads') /
    (SELECT variable_value FROM performance_schema.global_status WHERE variable_name='Innodb_buffer_pool_read_requests')
  )) * 100, 2) AS buffer_pool_hit_pct;

reads 是从磁盘的读取,read_requests 是总读取次数。若命中率低,增大 innodb_buffer_pool_size。

SQL Server

SELECT ROUND(
  100.0 * (SELECT cntr_value FROM sys.dm_os_performance_counters WHERE counter_name='Buffer cache hit ratio')
        / NULLIF((SELECT cntr_value FROM sys.dm_os_performance_counters WHERE counter_name='Buffer cache hit ratio base'), 0), 2) AS pct;

在现代 SQL Server 上,Page Life Expectancy(PLE)是更有意义的内存压力指标。

MongoDB

var c = db.serverStatus().wiredTiger.cache;
({ configuredMB: +(c['maximum bytes configured']/1048576).toFixed(0),
   inCacheMB:    +(c['bytes currently in the cache']/1048576).toFixed(0),
   readIntoCache: c['pages read into cache'],
   evictedPages:  c['unmodified pages evicted'] })

“pages read into cache”和淘汰数量偏高,说明 WiredTiger 缓存过小。

Redis

INFO stats
# keyspace_hits / (keyspace_hits + keyspace_misses) = hit ratio

命中率持续偏低说明需要检查 TTL/淘汰设置或访问模式。

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