关于CACHE BUFFERS CHAINS描述

CACHE BUFFERS CHAINS latch is acquired when searching for data blocks cached in the buffer cache.
Since the Buffer cache is implemented as a sum of chains of blocks, each of those chains is protected
by a child of this latch when needs to be scanned. Contention in this latch can be caused by very heavy
access to a single block. This can require the application to be reviewed.

产生CACHE BUFFERS CHAINS原因

The main cause of the cache buffers chains latch contention is usually a hot block issue.
This happens when multiple sessions repeatedly access one or more blocks that are protected
by the same child cache buffers chains latch.

CACHE BUFFERS CHAINS 处理方法
1) Examine the application to see if the execution of certain DML and SELECT statements can be reorganized to eliminate contention on the object.

处理方法如下:
--通过报告确定latch: cache buffers chains 等待
Top 5 Timed Events                                      Avg    %Total
~~~~~~~~~~~~~~~~~~                                      wait   Call
Event                          Waits        Time (s)    (ms)   Time   Wait Class
------------------------------ ------------ ----------- ------ ------ ----------
latch: cache buffers chains          74,642      35,421    475    6.1 Concurrenc
CPU time                                         11,422           2.0
log file sync                        34,890       1,748     50    0.3 Commit
latch free                            2,279         774    340    0.1 Other
db file parallel write               18,818         768     41    0.1 System I/O
-------------------------------------------------------------
--找出逻辑读高sql
SQL ordered by Gets         DB/Inst:  Snaps: 1-2
-> Resources reported for PL/SQL code includes the resources used by all SQL
statements called by the code.
-> Total Buffer Gets:   265,126,882
-> Captured SQL account for   99.8% of Total
                            Gets                CPU      Elapsed
Buffer Gets    Executions   per Exec     %Total Time (s) Time (s)  SQL Id
-------------- ------------ ------------ ------ -------- --------- -------------
   256,763,367       19,052     13,477.0   96.8 ######## ######### a9nchgksux6x2
Module: JDBC Thin Client
SELECT * FROM SALES ....
     1,974,516      987,056          2.0    0.7    80.31    110.94 ct6xwvwg3w0bv
SELECT COUNT(*) FROM ORDERS ....
--逻辑读大对象
Segments by Logical Reads
-> Total Logical Reads:     265,126,882
-> Captured Segments account for   98.5% of Total
           Tablespace                      Subobject  Obj.       Logical
Owner         Name    Object Name            Name     Type         Reads  %Total
---------- ---------- -------------------- ---------- ----- ------------ -------
DMSUSER    USERS      SALES                           TABLE  212,206,208   80.04
DMSUSER    USERS      SALES_PK                        INDEX   44,369,264   16.74
DMSUSER    USERS      SYS_C0012345                    INDEX    1,982,592     .75
DMSUSER    USERS      ORDERS_PK                       INDEX      842,304     .32
DMSUSER    USERS      INVOICES                        TABLE      147,488     .06
          -------------------------------------------------------------
处理思路：
1.Look for SQL that accesses the blocks in question and determine if the repeated reads are necessary.
  This may be within a single session or across multiple sessions.
2.Check for suboptimal SQL (this is the most common cause of the events)
 look at the execution plan for the SQL being run and try to reduce the
 gets per executions which will minimize the number of blocks being accessed
 and therefore reduce the chances of multiple sessions contending for the same block.

Note:1342917.1 Troubleshooting ‘latch: cache buffers chains’ Wait Contention

2) Decrease the buffer cache -although this may only help in a small amount of cases.

3) DBWR throughput may have a factor in this as well.If using multiple DBWR’s then increase the number of DBWR’s.

4) Increase the PCTFREE for the table storage parameters via ALTER TABLE or rebuild. This will result in less rows per block.

找出热点对象
First determine which latch id(ADDR) are interesting by examining the number of
sleeps for this latch. The higher the sleep count, the more interesting the
latch id(ADDR) is:
SQL> select CHILD#  "cCHILD"
     ,      ADDR    "sADDR"
     ,      GETS    "sGETS"
     ,      MISSES  "sMISSES"
     ,      SLEEPS  "sSLEEPS"
     from v$latch_children
     where name = 'cache buffers chains'
     order by 5, 1, 2, 3;
Run the above query a few times to to establish the id(ADDR) that has the most
consistent amount of sleeps. Once the id(ADDR) with the highest sleep count is found
then this latch address can be used to get more details about the blocks
currently in the buffer cache protected by this latch.
The query below should be run just after determining the ADDR with
the highest sleep count.
SQL> column segment_name format a35
     select /*+ RULE */
       e.owner ||'.'|| e.segment_name  segment_name,
       e.extent_id  extent#,
       x.dbablk - e.block_id + 1  block#,
       x.tch,
       l.child#
     from
       sys.v$latch_children  l,
       sys.x$bh  x,
       sys.dba_extents  e
     where
       x.hladdr  = '&ADDR' and
       e.file_id = x.file# and
       x.hladdr = l.addr and
       x.dbablk between e.block_id and e.block_id + e.blocks -1
     order by x.tch desc ;
Example of the output :
SEGMENT_NAME                     EXTENT#      BLOCK#       TCH    CHILD#
-------------------------------- ------------ ------------ ------ ----------
SCOTT.EMP_PK                       5            474          17     7,668
SCOTT.EMP                          1            449           2     7,668
Depending on the TCH column (The number of times the block is hit by a SQL
statement), you can identify a hot block. The higher the value of the TCH column,
the more frequent the block is accessed by SQL statements.

5) Consider implementing reverse key indexes (if range scans aren’t commonly used against the segment)