1、ORACLE歸檔日誌介紹
歸檔日誌暴增是oracle比較常見的問題，遇到歸檔日誌暴增，我們該如何排查：
- 歸檔日誌暴增一般都是應用或者人為引起的
- 理解歸檔日誌儲存的是什麼
- 如何排查歸檔日誌暴增原因
- 如何優化歸檔日誌暴增
1.1 歸檔日誌是什麼
歸檔日誌(Archive Log)是非活動的重做日誌(redo)備份. 通過使用歸檔日誌,可以保留所有重做歷史記錄,當資料庫處於ARCHIVELOG模式並進行日誌切換式,後臺程式ARCH會將重做日誌的內容儲存到歸檔日誌中. 當資料庫出現介質失敗時,使用資料檔案備份,歸檔日誌和重做日誌可以完全恢復資料庫。
1.2 歸檔日誌儲存的是什麼
所有重做的歷史記錄，包括DML語句、資料改變等
1.3 歸檔日誌暴增的原因
一般是DML操作大量的資料，導致歸檔日誌暴增
1.4 排查歸檔日誌暴增的方法
1.SQL語句 2.AWR 3.挖掘歸檔日誌
2、歸檔日誌暴增排查實戰
2.1 製造歸檔日誌暴增
create table scott.object as select * from dba_objects; -- 執行10次 -- insert insert into scott.object select * from scott.object; select count(1) from scott.object; -- 49384448 -- update update SCOTT.object set owner='aa'; -- delete delete from SCOTT.object; truncate table SCOTT.object;
2.2 檢視歸檔日誌切換
SELECT
THREAD# id,SUBSTR(TO_CHAR(first_time, 'MM/DD/RR HH:MI:SS'),1,5) DAY
, SUM(DECODE(SUBSTR(TO_CHAR(first_time, 'MM/DD/RR HH24:MI:SS'),10,2),'00',1,0)) H00
, SUM(DECODE(SUBSTR(TO_CHAR(first_time, 'MM/DD/RR HH24:MI:SS'),10,2),'01',1,0)) H01
, SUM(DECODE(SUBSTR(TO_CHAR(first_time, 'MM/DD/RR HH24:MI:SS'),10,2),'02',1,0)) H02
, SUM(DECODE(SUBSTR(TO_CHAR(first_time, 'MM/DD/RR HH24:MI:SS'),10,2),'03',1,0)) H03
, SUM(DECODE(SUBSTR(TO_CHAR(first_time, 'MM/DD/RR HH24:MI:SS'),10,2),'04',1,0)) H04
, SUM(DECODE(SUBSTR(TO_CHAR(first_time, 'MM/DD/RR HH24:MI:SS'),10,2),'05',1,0)) H05
, SUM(DECODE(SUBSTR(TO_CHAR(first_time, 'MM/DD/RR HH24:MI:SS'),10,2),'06',1,0)) H06
, SUM(DECODE(SUBSTR(TO_CHAR(first_time, 'MM/DD/RR HH24:MI:SS'),10,2),'07',1,0)) H07
, SUM(DECODE(SUBSTR(TO_CHAR(first_time, 'MM/DD/RR HH24:MI:SS'),10,2),'08',1,0)) H08
, SUM(DECODE(SUBSTR(TO_CHAR(first_time, 'MM/DD/RR HH24:MI:SS'),10,2),'09',1,0)) H09
, SUM(DECODE(SUBSTR(TO_CHAR(first_time, 'MM/DD/RR HH24:MI:SS'),10,2),'10',1,0)) H10
, SUM(DECODE(SUBSTR(TO_CHAR(first_time, 'MM/DD/RR HH24:MI:SS'),10,2),'11',1,0)) H11
, SUM(DECODE(SUBSTR(TO_CHAR(first_time, 'MM/DD/RR HH24:MI:SS'),10,2),'12',1,0)) H12
, SUM(DECODE(SUBSTR(TO_CHAR(first_time, 'MM/DD/RR HH24:MI:SS'),10,2),'13',1,0)) H13
, SUM(DECODE(SUBSTR(TO_CHAR(first_time, 'MM/DD/RR HH24:MI:SS'),10,2),'14',1,0)) H14
, SUM(DECODE(SUBSTR(TO_CHAR(first_time, 'MM/DD/RR HH24:MI:SS'),10,2),'15',1,0)) H15
, SUM(DECODE(SUBSTR(TO_CHAR(first_time, 'MM/DD/RR HH24:MI:SS'),10,2),'16',1,0)) H16
, SUM(DECODE(SUBSTR(TO_CHAR(first_time, 'MM/DD/RR HH24:MI:SS'),10,2),'17',1,0)) H17
, SUM(DECODE(SUBSTR(TO_CHAR(first_time, 'MM/DD/RR HH24:MI:SS'),10,2),'18',1,0)) H18
, SUM(DECODE(SUBSTR(TO_CHAR(first_time, 'MM/DD/RR HH24:MI:SS'),10,2),'19',1,0)) H19
, SUM(DECODE(SUBSTR(TO_CHAR(first_time, 'MM/DD/RR HH24:MI:SS'),10,2),'20',1,0)) H20
, SUM(DECODE(SUBSTR(TO_CHAR(first_time, 'MM/DD/RR HH24:MI:SS'),10,2),'21',1,0)) H21
, SUM(DECODE(SUBSTR(TO_CHAR(first_time, 'MM/DD/RR HH24:MI:SS'),10,2),'22',1,0)) H22
, SUM(DECODE(SUBSTR(TO_CHAR(first_time, 'MM/DD/RR HH24:MI:SS'),10,2),'23',1,0)) H23
FROM
v$log_history a
GROUP BY SUBSTR(TO_CHAR(first_time, 'MM/DD/RR HH:MI:SS'),1,5),THREAD#
ORDER BY id,SUBSTR(TO_CHAR(first_time, 'MM/DD/RR HH:MI:SS'),1,5)
/
代表12月19號，H20(20-21時)，共切換24個歸檔日誌，如果每一個500M，那麼總共約500M*24，對比其餘時間，可以說該時間產生異常的歸檔日誌，目標排查改時間段
2.3 SQL語句判斷
with aa as
(SELECT IID,
USERNAME,
to_char(BEGIN_TIME,'mm/dd hh24:mi') begin_time,
SQL_ID,
decode(COMMAND_TYPE,3,'SELECT',2,'INSERT',6,'UPDATE',7,'DELETE',189,'MERGE INTO','OTH') "SQL_TYPE",
executions "EXEC_NUM",
rows_processed "Change_NUM"
FROM (SELECT s.INSTANCE_NUMBER IID,
PARSING_SCHEMA_NAME USERNAME,COMMAND_TYPE,
cast(BEGIN_INTERVAL_TIME as date) BEGIN_TIME,
s.SQL_ID,
executions_DELTA executions,
rows_processed_DELTA rows_processed,
(IOWAIT_DELTA) /
1000000 io_time,
100*ratio_to_report(rows_processed_DELTA) over(partition by s.INSTANCE_NUMBER, BEGIN_INTERVAL_TIME) RATIO,
sum(rows_processed_DELTA) over(partition by s.INSTANCE_NUMBER, BEGIN_INTERVAL_TIME) totetime,
elapsed_time_DELTA / 1000000 ETIME,
CPU_TIME_DELTA / 1000000 CPU_TIME,
(CLWAIT_DELTA+APWAIT_DELTA+CCWAIT_DELTA+PLSEXEC_TIME_DELTA+JAVEXEC_TIME_DELTA)/1000000 OTIME,
row_number() over(partition by s.INSTANCE_NUMBER,BEGIN_INTERVAL_TIME order by rows_processed_DELTA desc) TOP_D
FROM dba_hist_sqlstat s, dba_hist_snapshot sn,dba_hist_sqltext s2
where s.snap_id = sn.snap_id
and s.INSTANCE_NUMBER = sn.INSTANCE_NUMBER
and rows_processed_DELTA is not null
and s.sql_id = s2.sql_id and COMMAND_TYPE in (2,6,7,189)
and sn.BEGIN_INTERVAL_TIME > sysdate - nvl(180,1)/1440 and PARSING_SCHEMA_NAME<>'SYS')
WHERE TOP_D <= nvl(20,1)
)
select aa.*,s.sql_fulltext "FULL_SQL" from aa left join v$sql s on aa.sql_id=s.sql_id ORDER BY IID, BEGIN_TIME desc,"Change_NUM" desc
檢視2小時的資料該變數，可以看出Change_NUM資料該變數和執行次數EXEC_NUM和SQL語句，update回滾了，所以沒有該變數。 此時可以判斷大量插入資料導致歸檔日誌暴增，此時並不能判斷update。此語句不一定有資料，只能做參考。
2.4 AWR
建立AWR報告
建立AWR報告 @?/rdbms/admin/awrrpt.sql
SQL> @?/rdbms/admin/awrrpt.sql
Current Instance
~~~~~~~~~~~~~~~~
DB Id DB Name Inst Num Instance
----------- ------------ -------- ------------
3830097027 ..... 1 .....
Specify the Report Type
~~~~~~~~~~~~~~~~~~~~~~~
Would you like an HTML report, or a plain text report?
Enter 'html' for an HTML report, or 'text' for plain text
Defaults to 'html'
Enter value for report_type: html
Type Specified: html
Instances in this Workload Repository schema
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
DB Id Inst Num DB Name Instance Host
------------ -------- ------------ ------------ ------------
* 3830097027 1 ..... ..... dbserver01
Using 3830097027 for database Id
Using 1 for instance number
Specify the number of days of snapshots to choose from
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Entering the number of days (n) will result in the most recent
(n) days of snapshots being listed. Pressing <return> without
specifying a number lists all completed snapshots.
Enter value for num_days: 1
Listing the last day's Completed Snapshots
Snap
Instance DB Name Snap Id Snap Started Level
------------ ------------ --------- ------------------ -----
..... ..... 36 19 Dec 2021 14:03 1
37 19 Dec 2021 15:00 1
38 19 Dec 2021 16:00 1
39 19 Dec 2021 17:00 1
40 19 Dec 2021 18:00 1
41 19 Dec 2021 20:12 1
42 19 Dec 2021 21:03 1
Specify the Begin and End Snapshot Ids
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Enter value for begin_snap: 41
Begin Snapshot Id specified: 41
Enter value for end_snap: 42
End Snapshot Id specified: 42
Specify the Report Name
~~~~~~~~~~~~~~~~~~~~~~~
The default report file name is awrrpt_1_41_42.html. To use this name,
press <return> to continue, otherwise enter an alternative.
Enter value for report_name: /tmp/awrrpt_1_41_42.html
解析AWR報告
可以看出大量redo，該時間段總該變數3762494/1024/1024=3674,每秒約產生3.5M
產生塊最多的是scott使用者，object物件，改變數是44684992,佔比99%，說明是該物件產生的
根據物件可以在AWR報告中檢視是否有懷疑的SQL，發現update語句。
其實根據SQL語句和AWR報告可以排查出大部分歸檔日誌暴增的問題，如果無法排查可以繼續進行挖掘歸檔日誌。
2.5 挖掘歸檔日誌
-rw-r-----. 1 oracle oinstall 794697216 Dec 19 20:37 1_66_1077902149.dbf -rw-r-----. 1 oracle oinstall 794697216 Dec 19 20:37 1_67_1077902149.dbf -rw-r-----. 1 oracle oinstall 794697216 Dec 19 21:03 1_68_1077902149.dbf -rw-r-----. 1 oracle oinstall 733794304 Dec 19 21:03 1_69_1077902149.dbf -rw-r-----. 1 oracle oinstall 756531200 Dec 19 21:03 1_70_1077902149.dbf -rw-r-----. 1 oracle oinstall 761492480 Dec 19 21:14 1_71_1077902149.dbf -rw-r-----. 1 oracle oinstall 794697216 Dec 19 21:14 1_72_1077902149.dbf -rw-r-----. 1 oracle oinstall 265107968 Dec 19 21:14 1_73_1077902149.dbf
-- 最好sys或相關許可權的使用者，也可以使用toad工具 -- 第一次 @?/rdbms/admin/dbmslm.sql @?/rdbms/admin/dbmslmd.sql -- 開始執行 execute dbms_logmnr.add_logfile(logfilename=>'../../1_66_1077902149.dbf',options=>dbms_logmnr.new); execute dbms_logmnr.add_logfile(logfilename=>'../../1_67_1077902149.dbf',options=>dbms_logmnr.new); execute dbms_logmnr.add_logfile(logfilename=>'../../1_68_1077902149.dbf',options=>dbms_logmnr.new); execute dbms_logmnr.add_logfile(logfilename=>'../../1_69_1077902149.dbf',options=>dbms_logmnr.new); execute dbms_logmnr.add_logfile(logfilename=>'../../1_70_1077902149.dbf',options=>dbms_logmnr.new); execute dbms_logmnr.start_logmnr(options=>dbms_logmnr.dict_from_online_catalog); -- 依次類推小批量解析歸檔日誌 -- 儲存記錄 create table scott.logmnr_contents as select * from v$logmnr_contents; -- 分批執行...迴圈執行上面記錄 alter session set nls_date_format='yyyy-mm-dd hh24:mi:ss'; -- 最後釋放pga execute dbms_logmnr.end_logmnr;
select sql_redo from scott.logmnr_contents where table_name='OBJECT'; select count(*) from scott.logmnr_contents where table_name='OBJECT';
可以從歸檔日誌中檢視大量的update語句，此時基本可以排查出歸檔日誌暴增原因
2.6 歸檔日誌暴增優化
1.delete是否可以改造成truncate分割槽表（ps: truncate需謹慎，無法恢復相關資料） 2.dml可以適量使用臨時表 3.避免大事務 4.避免大量for迴圈dml