Archiv für die Kategorie TOI
Logical Standby in NOARCHIVELOG mode
This week, I was teaching an 11g Data Guard course in Duesseldorf – my home location. One question that arose in that course was, whether it is possible to run a Logical Standby Database not beeing in archive mode.
Brief explanation: Unlike Physical Standby Databases, the Logical Standby is a quite independent Database that tries to do the same SQL Statements that arose at the Primary to keep up to date with it. In order to be able to do so, it gets the redo protocol transmitted from the primary and analyzes it (with Logminer technique). That redo protocol is stored in Archive Logs on the Logical Standby, which can’t be turned off, of course.
But also, when the SQL Apply on the standby changes blocks, it writes its own redo protocol into its own Online Logfiles and (by default) archives them. Sometimes, this is not needed, because customers use their Logical Standby as kind of „cheap replication“ and do not use it for HA purpose. So can we turn off Archive Logging on the Logical Standby? I saw that in place already at a (not reference, unfortunately) customer site, so the short answer was: Yes, we can 🙂
I tested it then myself and it really works. We can turn off archivelogging on the Logical Standby even with usage of the Data Guard Broker and with no warnings from it. But it seems, as if that is only possible with archiver transmission from the Primary to the Logical Standby. Otherwise (with LogXptMode async or sync), the transmission to the Logical Standby stops.
Retrieve old versions of procedures with Flashback Query

Each stored procedure (or trigger, package etc.) is reflected in DBA_SOURCE, of course. Now imagine, you modified or even dropped a procedure without having the code available to recreate it properly. In this case, you may save the day by using Flashback Query (possible since 9i) against DBA_SOURCE, like in this example:
SQL> select text from dba_source where name='UPD_SALES' order by line;
TEXT
--------------------------------------------------------------------------------
procedure upd_sales as
begin
for i in 1..10000 loop
update sales set amount_sold=amount_sold*1 where rownum<2;
commit;
end loop;
end;
7 rows selected.
SQL> drop procedure upd_sales;
Procedure dropped.
SQL> connect / as sysdba
Connected.
SQL> select text from dba_source
as of timestamp systimestamp - interval '5' minute
where name='UPD_SALES' order by line;
TEXT
--------------------------------------------------------------------------------
procedure upd_sales as
begin
for i in 1..10000 loop
update sales set amount_sold=amount_sold*1 where rownum<2;
commit;
end loop;
end;
7 rows selected.
I could spool the output from above into a text file and use it afterwards to recreate my procedure as it was before 5 minutes! By the way, I know that the commit inside the loop is not a good idea here 🙂
Reducing Buffer Busy Waits with Automatic Segment Space Management & Hash Partitioning
Last week, I was in Frankfurt (Germany) teaching about Performance Tuning & Partitioning in a Private Event for LHS Telecommunication. One demonstration that I developed for that event was about Reducing Buffer Busy Waits. One major reason why the wait event Buffer Busy Waits can occur is if many sessions are inserting at the same time in the same table. Large OLTP installations therefore will see it most likely. This can lead to a performance problem, especially if the site does not make use of Automatic Segment Space Management – a technique introduced in 9i and used by default since 10g. The old fashioned way to determine where to insert a new row in blocks before the high water mark uses Freelists. So if you are going with that „traditional“ technique with freelists (and PCTUSED), then your segment has one freelist by default, which leads to contention easy, because multiple simultaneous sessions that insert look at that one freelist and all pick the same Blocks to insert in. Here is an example:
SQL> create tablespace old datafile '/u01/app/oracle/oradata/orcl/old01.dbf'
size 50m segment space management manual;
Tablespace created.
SQL> create table bbw_freelist (n number, name varchar2(50)) tablespace old;
Table created.
That table now uses (one) freelist and PCTUSED (40 by default) in order to determine what blocks may be used
for insert. The next steps are going to create 10 simultaneous sessions that insert 1 Million rows into the table.
SQL> create or replace procedure bufwait1 as begin for i in 1..100000 loop insert into bbw_freelist values (i, 'BUFFER BUSY WAITS?'); end loop; commit; end; / 2 3 4 5 6 7 8 Procedure created. SQL> create or replace procedure do_bbw1 as v_jobno number:=0;begin FOR i in 1..10 LOOP dbms_job.submit(v_jobno,'bufwait1;', sysdate); END LOOP; commit; end; / 2 3 4 5 6 7 8 Procedure created.SQL> exec do_bbw1 PL/SQL procedure successfully completed.SQL> select count(*) from dba_jobs_running
COUNT(*)
----------
0
One easy way to discover Buffer Busy Waits is v$segment_statistics.Of course, you may see them also in Statspack/AWR reports.
SQL> select sum(value) from v$segment_statistics where OBJECT_NAME='BBW_FREELIST' and statistic_name='buffer busy waits'; SUM(VALUE) ---------- 1623Next we are doing exactly the same inserts with a table that uses Automatic Segment Space Management.
Simply speaking, ASSM achieves a better distribution of the new rows across multiple blocks if multiple
inserts occur at the same time. It is determined at the tablespace level:
SQL> select SEGMENT_SPACE_MANAGEMENT from dba_tablespaces where tablespace_name='USERS'; SEGMEN ------ AUTO SQL> create table bbw_assm (n number, name varchar2(50)) tablespace users; Table created. create or replace procedure bufwait2 as begin for i in 1..100000 loop insert into bbw_assm values (i, 'BUFFER BUSY WAITS?'); end loop; commit; end; / create or replace procedure do_bbw2 as v_jobno number:=0;begin FOR i in 1..10 LOOP dbms_job.submit(v_jobno,'bufwait2;', sysdate); END LOOP; commit; end; / SQL> exec do_bbw2 PL/SQL procedure successfully completed. SQL> select count(*) from dba_jobs_running; COUNT(*) ---------- 10 SQL> select count(*) from dba_jobs_running; COUNT(*) ---------- 0 SQL> select sum(value) from v$segment_statistics where OBJECT_NAME='BBW_ASSM' and statistic_name='buffer busy waits'; SUM(VALUE) ---------- 295As you can see, ASSM reduced strongly the number of Buffer Busy Waits! But still there are some,
and still this may be a performance problem for very large OLTP sites. Right now, the table is
not partitioned, so we have only one „hot extent“ if the table is continually growing, all inserts
occur in the newest allocated extent – where they are distributed nicely via ASSM. If that same table
would be Hash Partitioned, then we could have multiple „hot extents“ further more reducing the contention:
SQL> create table bbw_hash (n number, name varchar2(50))tablespace users partition by hash (n) partitions 256; Table created. SQL> create or replace procedure bufwait3 as begin for i in 1..100000 loop insert into bbw_hash values (i, 'BUFFER BUSY WAITS?'); end loop; commit; end; / 2 3 4 5 6 7 8 Procedure created. SQL> create or replace procedure do_bbw3 as v_jobno number:=0;begin FOR i in 1..10 LOOP dbms_job.submit(v_jobno,'bufwait3;', sysdate); END LOOP; commit; end; / 2 3 4 5 6 7 8 Procedure created. SQL> exec do_bbw3 PL/SQL procedure successfully completed. SQL> select sum(value) from v$segment_statistics where OBJECT_NAME='BBW_HASH' and statistic_name='buffer busy waits'; SUM(VALUE) ---------- 226We observe a (in this case) moderate further decrease of the Buffer Busy Waits. That
is one major reason for hash partitioning: Fighting against contention. Another reason
is – as in other kinds of partitioning – the possibilty for Partiton Pruning, if the
partition key is part of the where-clause of our statement. Then the optimizer
implicitly knows what partitions to scan. Even in my (relatively tiny) two tables, that
effect is visible:
SQL> set timing on SQL> select * from bbw_assm where n=4711; N NAME ---------- -------------------------------------------------- 4711 BUFFER BUSY WAITS? 4711 BUFFER BUSY WAITS? 4711 BUFFER BUSY WAITS? 4711 BUFFER BUSY WAITS? 4711 BUFFER BUSY WAITS? 4711 BUFFER BUSY WAITS? 4711 BUFFER BUSY WAITS? 4711 BUFFER BUSY WAITS? 4711 BUFFER BUSY WAITS? 4711 BUFFER BUSY WAITS? 10 rows selected. Elapsed: 00:00:00.11 SQL> select * from bbw_hash where n=4711; N NAME ---------- -------------------------------------------------- 4711 BUFFER BUSY WAITS? 4711 BUFFER BUSY WAITS? 4711 BUFFER BUSY WAITS? 4711 BUFFER BUSY WAITS? 4711 BUFFER BUSY WAITS? 4711 BUFFER BUSY WAITS? 4711 BUFFER BUSY WAITS? 4711 BUFFER BUSY WAITS? 4711 BUFFER BUSY WAITS? 4711 BUFFER BUSY WAITS? 10 rows selected. Elapsed: 00:00:00.01
