Redis內存詭異增長如何排查問題

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一、現象

實例名：r-bp1cxxxxxxxxxd04(主從)

問題：一分鐘內存上漲了 2G，如下圖所示：

鍵值規模：6000 萬左右

內存一分鐘增長 2G.png

二、Redis 內存分析

1. 內存組成

上圖中的內存統計的是 Redis 的 info memory 命令中的 used_memory 屬性，例如：

redis infomemory#Memoryused_memory:9195978072used_memory_human:8.56Gused_memory_rss:9358786560used_memory_peak:10190212744used_memory_peak_human:9.49Gused_memory_lua:38912mem_fragmentation_ratio:1.02mem_allocator:jemalloc-3.6.0

每個屬性的詳細說明

屬性名屬性說明 used_memoryRedis 分配器分配的內存量，也就是實際存儲數據的內存總量 used_memory_human 以可讀格式返回 Redis 使用的內存總量 used_memory_rss 從操作系統的角度，Redis 進程占用的總物理內存 used_memory_peak 內存分配器分配的最大內存，代表 used_memory 的歷史峰值 used_memory_peak_human 以可讀的格式顯示內存消耗峰值 used_memory_luaLua 引擎所消耗的內存 mem_fragmentation_ratioused_memory_rss /used_memory 比值，表示內存碎片率 mem_allocatorRedis 所使用的內存分配器。默認: jemalloc

計算公式如下：

used_memory = 自身內存 + 對象內存 + 緩沖內存 +lua 內存 used_rss = used_memory + 內存碎片

如下圖所示：

2. 內存分析

(1) 自身內存：一個空的 Redis 占用很小，可以忽略不計

(2) kv 內存：key 對象 + value 對象

(3) 緩沖區：客戶端緩沖區 (普通 + slave 偽裝 + pubsub) 以及 aof 緩沖區(比較固定，一般沒問題)

(4) Lua：Lua 引擎所消耗的內存

3. 內存突增常見問題

(1) kv 內存：bigkey、大量寫入

(2) 客戶端緩沖區：一般常見的有普通客戶端緩沖區 (例如 monitor 命令) 或者 pubsub 客戶端緩沖區

三、問題排查

(1) bigkey ? 經掃描未發現 bigkey

Sampled 67234427 keys in the keyspace!
Total key length in bytes is 1574032382 (avg len 23.41)
Biggest string found  CCARD_DEVICE_CARD_REF_MAP_KEY_016817000004209  has 20862 bytes
Biggest list found  CCARD_VALID_DEVICE_TRAIN_QUEUE_KEY  has 51 items
Biggest hash found  CCARD_VALID_DEVICE_TRAIN_MAP_KEY  has 51 fields
67234359 strings with 71767890 bytes (100.00% of keys, avg size 1.07)
67 lists with 151 items (00.00% of keys, avg size 2.25)
0 sets with 0 members (00.00% of keys, avg size 0.00)
1 hashs with 51 fields (00.00% of keys, avg size 51.00)
0 zsets with 0 members (00.00% of keys, avg size 0.00)

(2) 鍵值個數增加？未發現鍵值有明顯變化

(3) 客戶端緩沖區

由于內存增上去后，長時間沒下落，如果是因為緩沖區問題，會從 info clients 找到明顯問題，執行后發現：

redis  info clients
# Clients
connected_clients:43
client_longest_output_list:0
client_biggest_input_buf:0
blocked_clients:0
admin_clients:6
rejected_vpc_conn_count:0
close_idle_unknown_conn_count:0

執行 client 中也沒有明顯的 omem 大于 0 的情況

id=80207addr=10.xx.0.4:63920fd=46name=age=624idle=1flags=N db=0sub=0psub=0multi=-1qbuf=0qbuf-free=0obl=0oll=0omem=0events=r cmd=ping read=0write=0type=user
id=80215addr=10.xx.0.23:43489fd=36name=age=591idle=1flags=N db=0sub=0psub=0multi=-1qbuf=0qbuf-free=0obl=0oll=0omem=0events=r cmd=ping read=0write=0type=user
id=80366addr=10.xx.0.8:59785fd=18name=age=84idle=1flags=N db=0sub=0psub=0multi=-1qbuf=0qbuf-free=0obl=0oll=0omem=0events=r cmd=delread=0write=0type=user
id=80356addr=10.xx.0.33:32117fd=13name=age=114idle=0flags=N db=0sub=0psub=0multi=-1qbuf=0qbuf-free=32768obl=0oll=0omem=0events=r cmd=ping read=0write=0type=user
id=80064addr=10.xx.59.4:53446fd=38name=age=1070idle=1070flags=N db=0sub=0psub=0multi=-1qbuf=0qbuf-free=0obl=0oll=0omem=0events=r cmd=NULL read=0write=0type=admin
id=80276addr=10.xx.0.23:48511fd=8name=age=387idle=1flags=N db=0sub=0psub=0multi=-1qbuf=0qbuf-free=0obl=0oll=0omem=0events=r cmd=ping read=0write=0type=user
id=80188addr=10.xx.0.33:16265fd=42name=age=681idle=3flags=N db=0sub=0psub=0multi=-1qbuf=0qbuf-free=0obl=0oll=0omem=0events=r cmd=ping read=0write=0type=user
id=80326addr=10.xx.0.32:59779fd=16name=age=209idle=0flags=N db=0sub=0psub=0multi=-1qbuf=0qbuf-free=32768obl=0oll=0omem=0events=r cmd=ping read=0write=0type=user
id=80065addr=10.xx.59.4:53447fd=45name=age=1070idle=1070flags=N db=0sub=0psub=0multi=-1qbuf=0qbuf-free=0obl=0oll=0omem=0events=r cmd=NULL read=0write=0type=admin
id=79936addr=10.xx.0.22:10607fd=30name=age=1480idle=1flags=N db=0sub=0psub=0multi=-1qbuf=0qbuf-free=32768obl=0oll=0omem=0events=r cmd=ping read=0write=0type=user
id=80174addr=10.xx.0.5:60914fd=6name=age=722idle=2flags=N db=0sub=0psub=0multi=-1qbuf=0qbuf-free=0obl=0oll=0omem=0events=r cmd=ping read=0write=0type=user
id=80300addr=10.xx.0.22:22757fd=48name=age=298idle=1flags=N db=0sub=0psub=0multi=-1qbuf=0qbuf-free=32768obl=0oll=0omem=0events=r cmd=ping read=0write=0type=user
id=80037addr=10.xx.0.5:55189fd=15name=age=1143idle=2flags=N db=0sub=0psub=0multi=-1qbuf=0qbuf-free=0obl=0oll=0omem=0events=r cmd=ping read=0write=0type=user
id=80330addr=10.xx.0.8:48533fd=17name=age=199idle=10flags=N db=0sub=0psub=0multi=-1qbuf=0qbuf-free=0obl=0oll=0omem=0events=r cmd=ping read=0write=0type=user
id=79896addr=10.xx.0.30:26814fd=11name=age=1616idle=1flags=N db=0sub=0psub=0multi=-1qbuf=0qbuf-free=0obl=0oll=0omem=0events=r cmd=ping read=0write=0type=user
id=80299addr=10.xx.0.24:11227fd=44name=age=303idle=3flags=N db=0sub=0psub=0multi=-1qbuf=0qbuf-free=0obl=0oll=0omem=0events=r cmd=ping read=0write=0type=user
id=80086addr=10.xx.0.32:52526fd=40name=age=1002idle=1flags=N db=0sub=0psub=0multi=-1qbuf=0qbuf-free=0obl=0oll=0omem=0events=r cmd=ping read=0write=0type=user
id=80202addr=10.xx.0.33:16658fd=26name=age=636idle=3flags=N db=0sub=0psub=0multi=-1qbuf=0qbuf-free=0obl=0oll=0omem=0events=r cmd=ping read=0write=0type=user
id=80256addr=10.xx.0.24:60496fd=19name=age=448idle=2flags=N db=0sub=0psub=0multi=-1qbuf=0qbuf-free=0obl=0oll=0omem=0events=r cmd=ping read=0write=0type=user
id=79908addr=10.xx.0.29:18975fd=12name=age=1583idle=1flags=N db=0sub=0psub=0multi=-1qbuf=0qbuf-free=0obl=0oll=0omem=0events=r cmd=ping read=0write=0type=user
id=80365addr=10.xx.0.29:46429fd=14name=age=85idle=1flags=N db=0sub=0psub=0multi=-1qbuf=0qbuf-free=32768obl=0oll=0omem=0events=r cmd=ping read=0write=0type=user
id=79869addr=10.xx.27.4:48455fd=35name=age=1700idle=1700flags=N db=0sub=0psub=0multi=-1qbuf=0qbuf-free=0obl=0oll=0omem=0events=r cmd=NULL read=0write=0type=admin
id=80334addr=10.xx.0.23:50012fd=39name=age=189idle=1flags=N db=0sub=0psub=0multi=-1qbuf=0qbuf-free=32768obl=0oll=0omem=0events=r cmd=ping read=0write=0type=user
id=80041addr=10.xx.0.32:51107fd=33name=age=1132idle=3flags=N db=0sub=0psub=0multi=-1qbuf=0qbuf-free=0obl=0oll=0omem=0events=r cmd=ping read=0write=0type=user
id=79992addr=10.xx.0.22:12068fd=28name=age=1289idle=1flags=N db=0sub=0psub=0multi=-1qbuf=0qbuf-free=32768obl=0oll=0omem=0events=r cmd=ping read=0write=0type=user
id=80251addr=10.xx.0.30:44213fd=23name=age=468idle=1flags=N db=0sub=0psub=0multi=-1qbuf=0qbuf-free=32768obl=0oll=0omem=0events=r cmd=ping read=0write=0type=user
id=80006addr=10.xx.0.2:45895fd=31name=age=1242idle=1flags=N db=0sub=0psub=0multi=-1qbuf=0qbuf-free=0obl=0oll=0omem=0events=r cmd=ping read=0write=0type=user
id=80321addr=10.xx.0.30:48048fd=5name=age=224idle=3flags=N db=0sub=0psub=0multi=-1qbuf=0qbuf-free=0obl=0oll=0omem=0events=r cmd=ping read=0write=0type=user
id=80381addr=10.xx.0.8:13360fd=22name=age=24idle=1flags=N db=0sub=0psub=0multi=-1qbuf=0qbuf-free=32768obl=0oll=0omem=0events=r cmd=delread=0write=0type=user
id=80200addr=10.xx.0.24:59183fd=24name=age=640idle=0flags=N db=0sub=0psub=0multi=-1qbuf=0qbuf-free=32768obl=0oll=0omem=0events=r cmd=ping read=0write=0type=user
id=80113addr=10.xx.0.2:52492fd=21name=age=915idle=1flags=N db=0sub=0psub=0multi=-1qbuf=0qbuf-free=32768obl=0oll=0omem=0events=r cmd=ping read=0write=0type=user
id=174addr=11.216.117.242:53027fd=9name=age=281390idle=0flags=S db=0sub=0psub=0multi=-1qbuf=0qbuf-free=32768obl=0oll=0omem=0events=r cmd=replconf read=0write=0type=admin
id=79991addr=10.xx.0.4:48412fd=25name=age=1296idle=0flags=N db=0sub=0psub=0multi=-1qbuf=0qbuf-free=32768obl=0oll=0omem=0events=r cmd=ping read=0write=0type=user
id=80301addr=127.0.0.1:47869fd=49name=age=291idle=261flags=N db=0sub=0psub=0multi=-1qbuf=0qbuf-free=0obl=0oll=0omem=0events=r cmd=strlen read=0write=0type=admin
id=80047addr=10.xx.59.4:53184fd=41name=age=1114idle=1114flags=N db=0sub=0psub=0multi=-1qbuf=0qbuf-free=0obl=0oll=0omem=0events=r cmd=NULL read=0write=0type=admin
id=80236addr=10.xx.0.5:62546fd=47name=age=516idle=1flags=N db=0sub=0psub=0multi=-1qbuf=0qbuf-free=32768obl=0oll=0omem=0events=r cmd=ping read=0write=0type=user
id=80364addr=10.xx.0.4:18794fd=7name=age=85idle=1flags=N db=0sub=0psub=0multi=-1qbuf=0qbuf-free=32768obl=0oll=0omem=0events=r cmd=ping read=0write=0type=user
id=80175addr=10.xx.0.4:62245fd=29name=age=718idle=1flags=N db=0sub=0psub=0multi=-1qbuf=0qbuf-free=32768obl=0oll=0omem=0events=r cmd=ping read=0write=0type=user
id=80336addr=10.xx.0.29:45701fd=50name=age=180idle=1flags=N db=0sub=0psub=0multi=-1qbuf=0qbuf-free=32768obl=0oll=0omem=0events=r cmd=ping read=0write=0type=user
id=80050addr=10.xx.59.4:53188fd=43name=age=1114idle=1114flags=N db=0sub=0psub=0multi=-1qbuf=0qbuf-free=0obl=0oll=0omem=0events=r cmd=NULL read=0write=0type=admin
id=79765addr=10.xx.0.2:33832fd=37name=age=2027idle=177flags=N db=0sub=0psub=0multi=-1qbuf=0qbuf-free=0obl=0oll=0omem=0events=r cmd=info read=0write=0type=user
id=80170addr=10.xx.0.2:57853fd=20name=age=728idle=24flags=N db=0sub=0psub=0multi=-1qbuf=0qbuf-free=0obl=0oll=0omem=0events=r cmd=ping read=0write=0type=user
id=80390addr=127.0.0.1:49449fd=27name=age=0idle=0flags=N db=0sub=0psub=0multi=-1qbuf=0qbuf-free=32768obl=0oll=0omem=0events=r cmd=client read=0write=0type=admin

四、揪出元兇

常用的幾招都用了，還是不行，同事 @徑遠幫忙一起分析，懷疑是不是因為 Redis 的 kv 哈希表做了 rehash。

1. Redis 的 kv 存儲結構

如下圖所示，Redis 的所有 kv 保存在 dict 中，其中 ht 對應兩個哈希表 ht[0]和 ht[1]，平時一個空閑，一個用于存儲數據，只有當需要 rehash 時，ht[1]才會用到。

2. Redis 的字典 rehash

為了保證哈希表的負載，當哈希表的元素個數等于哈希表槽數時候，會進行 rehash 擴容。擴容后 h[1]的容量等于第一個大于等于 ht[0].size* 2 的 2n，例如 hash 表的初始化容量是 4，那么下一次擴容就是 8，以此類推。

3. 測試

(1) 測試方法

先批量寫入到 rehash 閾值附近，然后在逐條去寫，觀察內存變化

//  為每個鍵設置 1 天過期時間
int expireTime = 60 * 60 * 24;
// rehash 閾值  - 50 為了方便觀察 rehash 內存變化
int rehashThreshold = (int) Math.pow(2, 25) - 50;
// 1. 批量寫入：pipeline 批量寫入，由于是本機測試，這里用 10000，實際生產不要這么用
Pipeline pipeline = jedis.pipelined();
pipeline = jedis.pipelined();
for (int i = 0; i   rehashThreshold; i++) { pipeline.setex(String.valueOf(i), expireTime, String.valueOf(i));
 if (i % 10000 == 0) { pipeline.sync();
 }
pipeline.sync();
// 2. 等待寫增量
TimeUnit.SECONDS.sleep(5);
for (int i = rehashThreshold; i   rehashThreshold + 200; i++) { jedis.setex(String.valueOf(i), expireTime, String.valueOf(i));
 TimeUnit.SECONDS.sleep(1);
}

(2) 開始測試

(a) 當閾值 =215=32768，從下面可以看出到 key 的個數為 32769 時，內存漲了一些，但是還不明顯。

keys mem clients blocked requests connections32766 4.69M 3 0 32797 (+2) 4
32767 4.69M 3 0 32799 (+2) 4
32768 4.69M 3 0 32801 (+2) 4
32769 5.44M 3 0 32803 (+2) 4

(b) 當閾值 =220=1048576，從下面可以看出到 key 的個數為 1048577 時，內存漲了 32M。因為 rehash 會擴容，所以新的哈希表中的槽位變為了 221 * 2（因為每個 key 都設置了過期時間，expires 表），指針為 8 個字節，221 ? 2 ? 8 = 225 = 32MB。

keys mem clients blocked requests connections1048574 128.69M 3 0 3364129 (+2) 16
1048575 128.69M 3 0 3364131 (+2) 16
1048576 128.69M 3 0 3364133 (+2) 16
1048577 160.69M 3 0 3364135 (+2) 16
1048578 160.69M 3 0 3364137 (+2) 16

(c) 當閾值 =226=67108864，從下面可以看出到 key 的個數為 67108865 時，內存漲了 2GB。因為 rehash 會擴容，所以新的哈希表中的槽位變為了 227 * 2（因為每個 key 都設置了過期時間，expires 表），指針為 8 個字節，227 ? 2 ? 8 = 231 = 2GB。

keys mem clients blocked requests connections67108862 9.70G 3 0 70473683 (+2) 18
67108863 9.70G 3 0 70473685 (+2) 18
67108864 9.70G 3 0 70473687 (+2) 18
67108865 11.70G 3 0 70473689 (+2) 18
67108866 11.70G 3 0 70473691 (+2) 18
67108867 11.70G 3 0 70473693 (+2) 18

回過來看 r -bp1c15fd9b142d04 的 key 和內存變化圖，可以發現上面的規則是正確的：

4. 后續觀察

17 點時，rehash 結束，內存降了增加的 2G 的一半。

感謝各位的閱讀！關于“Redis 內存詭異增長如何排查問題”這篇文章就分享到這里了，希望以上內容可以對大家有一定的幫助，讓大家可以學到更多知識，如果覺得文章不錯，可以把它分享出去讓更多的人看到吧！

正文完