Session-level statspack

Statspack is a useful tool for easily gathering and reporting some Oracle’s historical workload statistics. However it has its limitations and problems:

One of them that in past it used to record only Oracle statistics, measured from inside Oracle. This made Oracle and people using Oracle ignore other crucial statistics like OS workload below Oracle. For example statspack may show you heavy latch contention as the performance problem, while looking at vmstat output one would see that the server just has been heavily overloaded with numerous other jobs (like multiple backup, export and compress jobs overrunning their run-window) and the latch contention is just a symptom of CPU starvation.

This has been somewhat addressed by adding V$OSSTAT to Oracle 10g and statspack now gathers this info as well. Now we need people to start looking into those stats.

Another problem with statspack is which is described in Dan Fink’s blog, about cursor-level CPU accounting limitations before 10gR2.

However neither of those problems are the main limitations of statspack. The main problem is that statspack samples it’s statistic snapshots from system level views like V$SYSSTAT and V$SYSTEM_EVENT. If every single session in your database is performing exactly the same (kind) of operation, then system level aggregates might be quite OK to get an overview what’s going on in the database. But from the moment you start having different kind of sessions (e.g. OLTP vs batch vs data feed vs report) in your database, then system level aggregates used by statspack do heavily distort what the reality looks like for specific sessions.

There’s another gotcha – by default statspack excludes the “SQL*Net message from client” wait event from main report section, stating that it is not important to look into idle events. However by that we will throw away an important piece of information when diagnosing end-to-end performance, the end user experience. The bad thing is that even if we did include the SQL*Net wait event in our reports (by deleting the corresponding row from STATS$IDLE_EVENT), then we would still have no idea how many of those gazillions of system-wide SQL*Net client wait seconds do belong to our specific session or user.
Statspack doesn’t measure session-experience, it just gives you a system-wide aggregate, which cannot be translated back to individual session statistics (just as you can not convert a hash value back to original value – most of the information is just lost!).

How to get session-level detailed overview of database performance, with historical reporting capability then?

Oracle 10g addresses this partially with ASH and AWR and DBMS_MONITOR’s selective statistic sampling ( V$SERV_MOD_ACT_STATS and V$CLIENT_STATS )

While ASH and AWR are both awesome products, they are not usable in Standard Edition nor before 10g ( you may want to check out Kyle Hailey’s ASH simulator instead ) and for using them you need to pay a separate license fee.

So let me introduce my attempt to solve those problems ( NB! Free stuff!!! ;):

  • The poor-man’s version of Automatic Workload Repository: It’s called… um… Semi-Automatic Workload Repository :)
  • The clever-man’s addition to statspack, which takes session-level snapshots: In other words, Sesspack.

The idea is very simple, just take snapshots of V$SESSION_EVENT and some V$SESSTAT (and V$SESS_TIME_MODEL in 10g) statistics and store those in a repository just like statspack does. Snapshots are taken using sesspack.snap_xyz procedures. As a parameter to these procedures I can pass a specific SID, a group of SIDs, a Oracle db username a OS-username or whatever filtering fields can be found from V$SESSION.

Once you have taken your snapshots when running the workload, you can run a report which calculates statistic and wait event deltas between snapshots and that it.

A demo?

[Read more...]

A gotcha with parallel index builds, parallel degree and query plans

Reading the following article about PARALLEL hint by Jonathan Lewis made me remember a somewhat related gotcha with parallelism.

Often when creating (or rebuilding) an index on a large table, doing it with PARALLEL x option makes it go faster – usually in case when your IO subsystem is not the bottleneck and you have enough spare CPU capacity to throw in.

A small example below:



Tanel@Sol01> create table t1 as select * from all_objects;

Table created.

Tanel@Sol01> create index i1 on t1(object_id);

Index created.

Tanel@Sol01> exec dbms_stats.gather_table_stats(user, 'T1', cascade=>true, no_invalidate=>false);

PL/SQL procedure successfully completed.

Ok, for whatever reason I need to rebuild my index, and for speed I do it in parallel:



Tanel@Sol01> alter index i1 rebuild parallel 4;

Index altered.

Tanel@Sol01>
Tanel@Sol01>
Tanel@Sol01> select
  2     sum(object_id)
  3  from
  4     t1
  5  where
  6     object_id > 60000
  7  /

SUM(OBJECT_ID)
--------------
      13233374

Tanel@Sol01>
Tanel@Sol01> @x

PLAN_TABLE_OUTPUT
-----------------------------------------------------------------------------------------------------------------
Plan hash value: 3900446664

--------------------------------------------------------------------------
| Id  | Operation         | Name | Rows  | Bytes | Cost (%CPU)| Time     |
--------------------------------------------------------------------------
|   0 | SELECT STATEMENT  |      |     1 |     5 |     8   (0)| 00:00:01 |
|   1 |  SORT AGGREGATE   |      |     1 |     5 |            |          |
|*  2 |   INDEX RANGE SCAN| I1   |  2923 | 14615 |     8   (0)| 00:00:01 |
--------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   2 - access("OBJECT_ID">60000)

14 rows selected.

The execution plan shows a nice serial range scan for above query. Let’s run the same query with a different value for object_id:



Tanel@Sol01> select
  2     sum(object_id)
  3  from
  4     t1
  5  where
  6     object_id > 10000
  7  /

SUM(OBJECT_ID)
--------------
    1294174783

Tanel@Sol01>
Tanel@Sol01> @x

PLAN_TABLE_OUTPUT
--------------------------------------------------------------------------------------------------------------------
Plan hash value: 2596547647

-------------------------------------------------------------------------------------------------------------------
| Id  | Operation                 | Name     | Rows  | Bytes | Cost (%CPU)| Time     |    TQ  |IN-OUT| PQ Distrib |
-------------------------------------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT          |          |     1 |     5 |    19   (0)| 00:00:02 |        |      |            |
|   1 |  SORT AGGREGATE           |          |     1 |     5 |            |          |        |      |            |
|   2 |   PX COORDINATOR          |          |       |       |            |          |        |      |            |
|   3 |    PX SEND QC (RANDOM)    | :TQ10000 |     1 |     5 |            |          |  Q1,00 | P->S | QC (RAND)  |
|   4 |     SORT AGGREGATE        |          |     1 |     5 |            |          |  Q1,00 | PCWP |            |
|   5 |      PX BLOCK ITERATOR    |          | 42937 |   209K|    19   (0)| 00:00:02 |  Q1,00 | PCWC |            |
|*  6 |       INDEX FAST FULL SCAN| I1       | 42937 |   209K|    19   (0)| 00:00:02 |  Q1,00 | PCWP |            |
-------------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   6 - filter("OBJECT_ID">10000)

18 rows selected.

What? Suddenly my query turned parallel !

I haven’t enabled parallelism for my table! How can Oracle go parallel without my consent?


Tanel@Sol01> select table_name, degree from user_tables  where table_name = 'T1';

TABLE_NAME                     DEGREE
------------------------------ ----------------------------------------
T1                                      1

The answer lies in the result of next query:


Tanel@Sol01> select index_name, degree from user_indexes where table_name = 'T1';

INDEX_NAME                     DEGREE
------------------------------ ----------------------------------------
I1                             4

Parallel index (re)build will persistently set the index parallel degree in data dictionary to the value used during build!

This enables the CBO to be free to consider also parallel query plans and in our second select case a parallel plan seemed to be the best.

Whether this parallel plan actually is the most efficient way to go is a separate question, however this kind of unplanned parallelism may destabilize your system performance, especially as it can kick in only for certain instantiations of your SQL statement. Note that even one parallel-enabled object in your execution plan can parallelize the whole query joining many tables (just as even one table with statistics in a join turns on CBO for the whole cursor).

Combined with bind variable peeking side-effects and way too high parallel_max_servers value (hey it’s just a max value, let’s set it to 500), this can bring your OLTP system to knees at very unexpected times.

So, as my database does not have parallelism planned into it, I will eliminate the troublemaker:

Tanel@Sol01> alter index i1 noparallel;

Index altered.

Tanel@Sol01>
Tanel@Sol01> select
  2     sum(object_id)
  3  from
  4     t1
  5  where
  6     object_id > 10000
  7  /

SUM(OBJECT_ID)
--------------
    1294174783

Tanel@Sol01>
Tanel@Sol01> @x

PLAN_TABLE_OUTPUT
------------------------------------------------------------------------------
Plan hash value: 129980005

------------------------------------------------------------------------------
| Id  | Operation             | Name | Rows  | Bytes | Cost (%CPU)| Time     |
------------------------------------------------------------------------------
|   0 | SELECT STATEMENT      |      |     1 |     5 |    19   (0)| 00:00:02 |
|   1 |  SORT AGGREGATE       |      |     1 |     5 |            |          |
|*  2 |   INDEX FAST FULL SCAN| I1   | 42937 |   209K|    19   (0)| 00:00:02 |
------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   2 - filter("OBJECT_ID">10000)

14 rows selected.

So the key point is that unless your databases have planned and managed parallelism used in them, it’s worth to run the following query to identify potential troublemakers and disable their parallelism:


SELECT
	'INDEX' OBJECT_TYPE, OWNER, INDEX_NAME, TRIM(DEGREE)
FROM
	DBA_INDEXES
WHERE
	TRIM(DEGREE) > TO_CHAR(1)
UNION ALL
SELECT
	'TABLE', OWNER, TABLE_NAME, TRIM(DEGREE)
FROM
	DBA_TABLES
WHERE
	TRIM(DEGREE) > TO_CHAR(1)
/

On my test environment it returned the following rows:

OBJEC OWNER                          INDEX_NAME                     TRIM(DEGREE)
----- ------------------------------ ------------------------------ -------------
INDEX SYS                            UTL_RECOMP_SORT_IDX1           DEFAULT
TABLE TANEL                          T                              4

From here we see two addtional things:

  • Parallel operations also persist their degree to tables (using alter table move parallel x or CTAS for example)
  • There’s a parallel degree DEFAULT – which is used when you let the appropriate degree to be decided by optimizer

On the other hand, if you have planned for parallelism, then you probably want to keep the parallelism for tables and indexes consistent, e.g. enable it for all tables requiring parallelism and their indexes, not just for couple of indexes by accident.

Update:
Thanks to Adrian Billington for reminding me that also NOLOGGING flag will stick in data dictionary should you perform nologging operations on an object. You should review those too after rebuilds and reorgs.

My version of SQL string to table tokenizer

This one’s a short post on a fairly random topic as unfortunately I don’t have time today to come up with anything deeper :)

I needed to come up with a delimited string to table tokenizer for an Oracle development project. There are quite a few examples out there how to do that, including Adrian Billington’s www.oracle-developer.net and the http://technology.amis.nl/blog/?p=1631.

So far the simplest solution I had seen was using a bunch of INSTR’s, SUBSTR’s and DECODE’s in a CONNECT BY loop.
However as this application is using Oracle 10g, I could use regular expressions to make the SQL even shorter:



Tanel@Sol01> define separator=":"
Tanel@Sol01> define mystring="A:BCD::EFG:H:IJKL"
Tanel@Sol01>
Tanel@Sol01> SELECT
  2             LEVEL,
  3             REGEXP_REPLACE(
  4                     REGEXP_SUBSTR( '&mystring'||'&separator', '(.*?)&separator', 1, LEVEL )
  5                     , '&separator$'
  6                     , ''
  7             ) TOKEN
  8  FROM
  9     DUAL
 10  CONNECT BY
 11     REGEXP_INSTR( '&mystring'||'&separator', '(.*?)&separator', 1, LEVEL ) > 0
 12  ORDER BY
 13     LEVEL ASC
 14  /

LEVEL TOKEN
----- ----------
    1 A
    2 BCD
    3
    4 EFG
    5 H
    6 IJKL

6 rows selected.

For anyone not yet familiar with regular expressions, I definitely recommend to get to know at least the basics – they can save you hours (or even days) of work in some cases. And the cool thing is that regular expressions are fairly standard across the development platforms too (e.g. if you know Oracle regexp, then it’s very easy to handle Java, perl or C# regexp too).

And regexp is not only a developer thing, it can be very useful for everyday production DBAs as well. For example, every decent “grep” utility has regexp support built in – this makes search for complex conditions from log or config files easier for you.

Just a test posting…

This is a test posting, no real content here...
-bash-3.00$ pstack 868
868:    ora_pmon_SOL01
 fffffd7ffc7dddca pollsys  (63726c0, 2, fffffd7fffdfdc90, 0)
 fffffd7ffc7845c2 poll () + 52
 0000000004eb8bd0 ntevpque () + 60
 0000000004eb66e6 ntevque () + b6
 0000000004e93968 nsevwait () + 178
 0000000001905453 ksnwait () + 63
 00000000017b0cc7 ksliwat () + 8a7
 00000000017b1425 kslwaitns () + 15
 00000000018dd89f kskthbwt () + bf
 00000000017b13ed kslwait () + 4d
 00000000017ba502 ksuclnwt () + b2
 00000000017ba8f7 ksucln () + 327
 000000000184ecb5 ksbrdp () + 325
 00000000028d3dd6 opirip () + 2a6
 0000000000e76aea opidrv () + 3ba
 0000000000e73e7b sou2o () + 5b
 0000000000e3a86c opimai_real () + 11c
 0000000000e3a6a4 main () + 64
 0000000000e3a4ec ???????? ()