postgresql 如何查看pg_wal目錄下xlog文件總大小
當然如果你登錄服務器所在主機,直接在$PGDAT/pg_wal下執行:
du -h --max-depth=1 ./
可以得到。
#du -h --max-depth=1 ./ 4.0K ./archive_status 193M ./
如果通過客戶端怎麼做呢?
答案:pg_ls_waldir()函數。pg_ls_waldir()是pg 10.0引入的函數,可以輸出數據庫WAL目錄的所有文件。
postgres=# select sum(size) from pg_ls_waldir(); sum ----------- 201326592 (1 row)
單位是byte,所以當前pg_wal的xlog日志總大小為201326592/1024/1024=192M。
也可以使用:
postgres=# select count(*) from pg_ls_waldir(); count ------- 12 (1 row)
12表示wal日志文件個數,總大小12*16=192M。
16表示單個wal日志文件大小,單位MB,WAL 日志文件大小默認為16MB。
bonus:
1、怎麼調整單個wal日志文件大小?
答:使用 initdb 調整WAL文件大小。
2、pg_ls_logdir() 也是pg10.0版本引入的函數,輸出數據庫日志目錄的所有文件。
postgres=# select * from pg_ls_logdir(); name | size | modification ----------------------------------+---------+------------------------ postgresql-2020-04-28_092020.log | 2277343 | 2020-04-29 11:34:56+08 postgresql-2020-04-28_092020.csv | 140050 | 2020-04-29 11:34:56+08
3、如何列出/data文件夾中的文件?
答:pg_ls_dir
postgres=# select pg_ls_dir('/data'); pg_ls_dir ----------------------
補充:postgresql 查看wal生成頻率和大小
–wal 文件生成數量
–linux ls –full-time stat filename
–pg_stat_file返回一個記錄,其中包含
– 1 size 文件尺寸
– 2 access 最後訪問時間戳(linux:最近訪問) 、
– 3 modification 最後修改時間戳(linux:最近更改–) 、
– 4 change 最後文件狀態改變時間戳(隻支持 Unix 平臺)(linux:最近改動) 、
– 5 creation 文件創建時間戳(隻支持 Windows)
– 6 isdir 一個boolean指示它是否為目錄 isdir
– select * from pg_stat_file('/var/lib/postgresql/9.1/main/pg_xlog/0000000200000BBB000000A9'); – /var/lib/postgresql/9.1/main/pg_xlog – /var/log/postgresql – /mnt/nas_dbbackup/archivelog
with tmp_file as ( select t1.file, t1.file_ls, (pg_stat_file(t1.file)).size as size, (pg_stat_file(t1.file)).access as access, (pg_stat_file(t1.file)).modification as last_update_time, (pg_stat_file(t1.file)).change as change, (pg_stat_file(t1.file)).creation as creation, (pg_stat_file(t1.file)).isdir as isdir from (select dir||'/'||pg_ls_dir(t0.dir) as file, pg_ls_dir(t0.dir) as file_ls from ( select '/var/lib/postgresql/9.1/main/pg_xlog'::text as dir --需要修改這個物理路徑 --select '/mnt/nas_dbbackup/archivelog'::text as dir --select setting as dir from pg_settings where name='log_directory' ) t0 ) t1 where 1=1 order by (pg_stat_file(file)).modification desc ) select to_char(date_trunc('day',tf0.last_update_time),'yyyymmdd') as day_id, sum(case when date_part('hour',tf0.last_update_time) >=0 and date_part('hour',tf0.last_update_time) <24 then 1 else 0 end) as wal_num_all, sum(case when date_part('hour',tf0.last_update_time) >=0 and date_part('hour',tf0.last_update_time) <1 then 1 else 0 end) as wal_num_00_01, sum(case when date_part('hour',tf0.last_update_time) >=1 and date_part('hour',tf0.last_update_time) <2 then 1 else 0 end) as wal_num_01_02, sum(case when date_part('hour',tf0.last_update_time) >=2 and date_part('hour',tf0.last_update_time) <3 then 1 else 0 end) as wal_num_02_03, sum(case when date_part('hour',tf0.last_update_time) >=3 and date_part('hour',tf0.last_update_time) <4 then 1 else 0 end) as wal_num_03_04, sum(case when date_part('hour',tf0.last_update_time) >=4 and date_part('hour',tf0.last_update_time) <5 then 1 else 0 end) as wal_num_04_05, sum(case when date_part('hour',tf0.last_update_time) >=5 and date_part('hour',tf0.last_update_time) <6 then 1 else 0 end) as wal_num_05_06, sum(case when date_part('hour',tf0.last_update_time) >=6 and date_part('hour',tf0.last_update_time) <7 then 1 else 0 end) as wal_num_06_07, sum(case when date_part('hour',tf0.last_update_time) >=7 and date_part('hour',tf0.last_update_time) <8 then 1 else 0 end) as wal_num_07_08, sum(case when date_part('hour',tf0.last_update_time) >=8 and date_part('hour',tf0.last_update_time) <9 then 1 else 0 end) as wal_num_08_09, sum(case when date_part('hour',tf0.last_update_time) >=9 and date_part('hour',tf0.last_update_time) <10 then 1 else 0 end) as wal_num_09_10, sum(case when date_part('hour',tf0.last_update_time) >=10 and date_part('hour',tf0.last_update_time) <11 then 1 else 0 end) as wal_num_10_11, sum(case when date_part('hour',tf0.last_update_time) >=11 and date_part('hour',tf0.last_update_time) <12 then 1 else 0 end) as wal_num_11_12, sum(case when date_part('hour',tf0.last_update_time) >=12 and date_part('hour',tf0.last_update_time) <13 then 1 else 0 end) as wal_num_12_13, sum(case when date_part('hour',tf0.last_update_time) >=13 and date_part('hour',tf0.last_update_time) <14 then 1 else 0 end) as wal_num_13_14, sum(case when date_part('hour',tf0.last_update_time) >=14 and date_part('hour',tf0.last_update_time) <15 then 1 else 0 end) as wal_num_14_15, sum(case when date_part('hour',tf0.last_update_time) >=15 and date_part('hour',tf0.last_update_time) <16 then 1 else 0 end) as wal_num_15_16, sum(case when date_part('hour',tf0.last_update_time) >=16 and date_part('hour',tf0.last_update_time) <17 then 1 else 0 end) as wal_num_16_17, sum(case when date_part('hour',tf0.last_update_time) >=17 and date_part('hour',tf0.last_update_time) <18 then 1 else 0 end) as wal_num_17_18, sum(case when date_part('hour',tf0.last_update_time) >=18 and date_part('hour',tf0.last_update_time) <19 then 1 else 0 end) as wal_num_18_19, sum(case when date_part('hour',tf0.last_update_time) >=19 and date_part('hour',tf0.last_update_time) <20 then 1 else 0 end) as wal_num_19_20, sum(case when date_part('hour',tf0.last_update_time) >=20 and date_part('hour',tf0.last_update_time) <21 then 1 else 0 end) as wal_num_20_21, sum(case when date_part('hour',tf0.last_update_time) >=21 and date_part('hour',tf0.last_update_time) <22 then 1 else 0 end) as wal_num_21_22, sum(case when date_part('hour',tf0.last_update_time) >=22 and date_part('hour',tf0.last_update_time) <23 then 1 else 0 end) as wal_num_22_23, sum(case when date_part('hour',tf0.last_update_time) >=23 and date_part('hour',tf0.last_update_time) <24 then 1 else 0 end) as wal_num_23_24 from tmp_file tf0 where 1=1 and tf0.file_ls not in ('archive_status') group by to_char(date_trunc('day',tf0.last_update_time),'yyyymmdd') order by to_char(date_trunc('day',tf0.last_update_time),'yyyymmdd') desc ;
以上為個人經驗,希望能給大傢一個參考,也希望大傢多多支持WalkonNet。如有錯誤或未考慮完全的地方,望不吝賜教。
推薦閱讀:
- postgresql 利用xlog進行熱備操作
- postgreSQL數據庫的監控及數據維護操作
- PostgreSQL中的日期/時間函數詳解
- PostgreSQL timestamp踩坑記錄與填坑指南
- PostgreSQL數據類型格式化函數操作