by Mike Ault
The term Oracle ?myth? refers to a principle about Oracle behavior
which either was never true, or, used to be true, but is no longer.
Most Oracle myths originated as the result of changing technology.
||Most people agree that many of today's Oracle Myths were
perfectly valid during their day (e.g. ?disk load
balancing is critical to performance?), but they became
mythological as hardware and Oracle software improved.
Let's not forget that Oracle technology is more than 15
years-old, and the technology of 1989 is far different than
it is today.
Fortunately, most Oracle professionals fully-understand the changing
dynamics of Oracle Mythology and how once-valid advice can become
invalid and take-on mythological status.
Ancient Oracle Myths
There are many old Oracle techniques which were very useful
in the past but have become myths as the technology has
Confounding the problem are the thousands of Oracle shops
that are running on prehistoric hardware and unsupported
releases of Oracle software.
Let's take a look at some of the older myths.
Ancient Myth: Objects perform better in a single
Oracle University courses in the early 1990's stressed that the
compress=y export option would greatly improve the performance
of resulting tables. Today, Locally-Managed Tablespaces (LMT) makes
this advice invalid.
Ancient Myth: A data buffer hit ratio (DBHR) should
be kept greater than 90%
This myth was also propagated by Oracle Corporation in the early
1990's when almost all Oracle databases were I/O-bound and SGA size
was constrained by the 32-bit server technology. Oracle-based
products such as SAP also note in their manuals that the DBHR should
be over 90%. Oracle author Robert Freeman notes:
It has been demonstrated on many occasions that it is easy in a
basic proof to prove just about anything. Given a basic proof I can
prove that the buffer cache hit ratio means nothing, or I can prove
that it is the most important thing in the world.
I know of several scripts which can be run against your database to
give you any DBHR you desire. Does this make a myth? Oracle does
not seem to think so, and ratio-based advisories form the foundation
of the Oracle10g Automatic Memory Management utility and the
But there are some current Oracle myths, let's take a look at them.
Current Oracle Myths
The current Oracle myth debates are largely a result of the changing
Oracle technology and the inability of some Oracle professionals to
adapt to the changes.
Current Myth: Indexes and tables do not need to be
This myth arose because of recommendations by Oracle back in the
early 1990's when disk contention was a major issue and the
"separation" myth is misunderstood.
It wasn't too long ago that separation of indexes and tables
in databases was a good and accepted method for improving
Of course this was because otherwise they would be on the
same disk platter if they weren't separate and would
conflict. Moving indexes to a tablespace on a separate disk
from tables always improved performance, not just the
separation into a separate tablespace.
The main argument, supported by 10046 traces with a single-user
system is that access to tables and indexes in a single query is not
asynchronous in nature, but is rather a linear process. However,
even in single user systems this fails to take into consideration
the required head movement and disk latencies associated with
reading index, then table. In a multi-user environment it fails to
take into consideration all of the above plus the effects of
multi-user access against co-located tables and indexes.
Now with properly laid-out RAID much of the contention issues of
co-location are removed or mitigated, however, maintenance is still
made easier with separation into several tablespaces for tables and
indexes. Separation into discrete tablespaces allows tracking of IO
rates and volumes for specific objects or types of objects and also
allows for use of multiple-block sizes.
Current Myth: High-update tables and indexes rarely
This myth was started by the statements of Oracle experts that
claimed that Oracle indexes always remain balanced and that indexes
rarely benefit from rebuilding. Below we see
the suggestion that, somehow, understanding ?why? table and
indexes become fragmented might help:
unless you want to be caught in the infinite loop of org, reorg,
org, reorg.... You better have a clue as to "why"
While in a perfect world you could rebuild once using the absolute
correct parameters and never have to rebuild again, I am afraid this
doesn't happen in the real world. It's rather like expecting to
clean your house once when it is full of rowdy teenagers, it just
doesn't make sense.
Today, it is well-understood that tables and indexes with high
concurrent insert, update and delete activity system can quickly get
a sub-optimal structure and require reorganization to reduce I/O for
multi-block scan operations (using Oracle's dbms_redefinition
package, alter index move/rebuild, alter index coalesce,
or even alter table move depending on availability
requirements.) The concept of index balance is two-pronged, while a
B-Tree is always height balanced, it can become sparse or
right-handed, so it becomes width or load unbalanced.
Current Myth: Multiple blocksizes don't improve
This myth was perpetuated because multiple blocksizes were
originally designed to support transportable tablespaces and some
people could not see the other important side-benefits of multiple
blocksizes. The chief benefit of different blocksizes is the more
efficient use of limited RAM regions (db_cache_size,
db_32k_cache_size, etc.) and the intelligent segregation of
objects to reduce logical I/O (consistent gets) for multi-block scan
Today, MOSC notes that the multiple blocksize parameters are
among the most important in Oracle tuning, and noted experts such as
Robin Schumacher has demonstrated that Oracle indexes will build
more-optimal b-tree structures within a large blocksize. Also,
Reorganizing a high-DML index, or using small blocksizes for random
single-row fetches (index access unique) of small rows can reduce
the size in db_cache_size and therefore reduce PIO because
more blocks fit into the cache area.
For example, some
attempt to prove the assertion using small, artificial
single-user experiments and suggest that multiple blocksizes are
unlikely to help in a real-world database. However, real-world
shops report a very different experience with multiple blocksizes
and a 32k blocksize for indexes:
"My favorite recent
article was on 32KB indexes - our client (200GB+) saw a 20%
reduction in I/O from this simple change... ?- Steve Taylor,
Technical Services Manager EMEA
So, here we see how changing technology can convert a
perfectly-valid approach from 15 years ago into a ?Myth?, and
reaching a false conclusion from a single-user test-script can
create a modern myth, again because of changing technology.
Emerging Oracle Myths
The mythology continues as Oracle professionals observe different
database behaviors and reach inconsistent conclusions.
We also see some opinion leaders who are heavily promoted by
Oracle Corporation, but who publish
misleading statements about Oracle performance, thereby
creating new Myths:
The consistent gets cannot, will not be affected by any
of the optimizer_* settings. they affect how the optimizer
costs things, they have no effect on how things are actually
Of course, changing the values of optimizer_mode,
optimizer_index_cost_adj and optimizer_index_caching will
change the optimizer's decision about whether to do a full-scan or
an index access execution plan, and this has a direct impact on the
amount of consistent gets for any query.
Types of Oracle Professional
Today there are two distinct groups of Oracle professionals, each
with a very different view of Oracle tuning, and each accusing the
other of perpetuating new Oracle Myths.
The ?Rules of Thumb? Myth - Many
Oracle professionals believe that ?rules-of-thumb? (ROT) are
very dangerous, and note that if a ROT can be shown as invalid,
even in a single artificial test, the ROT is not scientifically
valid and therefore useless.
The 'script Kiddie? Myth - This
myth says that running single-user SQL*Plus scripts to ?prove?
how Oracle will perform are almost always invalid under
This first part of my two part article is meant to lay the
foundation for understanding Oracle mythology and show us how Oracle
myths change over time. In my next installment we will take a
closer look at these widely-different approaches to Oracle
technology and see how they can create confusion.
Part 2 - The New Oracle Myths
In this, our last installment we examine the nature of Oracle myths
and understood how changing technology effects mythological status.
There are two schools of thought about ?proving? Oracle
solutions to performance problems.
Today we see two 'types? of Oracle Professionals, each
saying that other Professionals are perpetuating new Oracle
Myths. In one group, the ?Researcher? seeks ?laws?,
tautologies about Oracle behaviors that are true, while the
Empiricist seeks ?correlations? and deals in probabilities
rather than absolutes.
These mindsets have led to these current Oracle myths:
The ?Rules of Thumb? Myth (sponsored
by Research-oriented Professionals) - Many Research
Professionals believe that ?rules-of-thumb? (ROT) are very
dangerous, and note that if an ROT can be shown as invalid, even
in a single artificial test, the ROT is not scientifically
valid. Detractors note that simple, generalized ?rules? form
the basis for many of the Oracle 10g automation features, such
as Automatic Memory Management (AMM) and the SQLTuning advisor.
The 'script Kiddie? Myth (sponsored by
Empirically-oriented Professionals) - This myth says that
running single-user SQL*Plus scripts to ?prove? how an Oracle
change will behave in production are almost always invalid under
multi-user database activity. Detractors say that it is not
necessary to run large-scale, multi-user benchmarks to ?prove?
how Oracle behaves.
So, are these myths? Borrowing from Don Burleson's hilarious
DBAZine article ?What
type of DBA are you??, we see several Oracle personality types.
In fairness, he created these deliberate generalizations to
illustrate the mindsets of the Empirical and Scientific
The Empirical DBA
The Empirical DBA observes real-world situations, notes
correlations and then generalizes their ?rules? and applies
their rules and observations to new databases.
The Empirical DBA believes that real-world Oracle databases
with thousands of active users and hundreds of transactions
per minute are often impossible to simulate and they do
their testing with large, multi-user simulations.
Many in-the-trenches Oracle consultants report ?phenomenon?,
transient events that appear only under extreme system load and
often cannot be reproduced. The Empirical professionals utilize the
heuristic approach to observe behavior and apply it to new
Heuristic 1. A rule of thumb, simplification, or
educated guess that reduces or limits the search for solutions in
domains that are difficult and poorly understood. Unlike algorithms,
heuristics do not guarantee optimal, or even feasible, solutions and
are often used with no theoretical guarantee.
The Empiricist DBA does testing with benchmarks, not test scripts.
Robert Freeman, a noted Oracle Press author and expert notes that
the proofs proffered by scientists are often invalid:
Very few things in Oracle are black-and-white or simple and that
is the fallacy of using a simple proof to prove anything. As
complexity is increased, as layers are added, any number of factors
can be introduced that change the conditions of the test, and thus
totally invalidate it.
Does this mean the Empiricist blindly charges in making bold changes
to clients databases without testing, checking statistics, waits, IO
rates and timing and myriad other factors before applying
heuristics? Only if they don't want to get paid or new clients!
Now let's examine the Research-oriented professional.
The Research DBA
The Research DBA has the motto is ?Prove it,? and 'trust,
but Verify?. They love to perform research on their
simple Oracle systems, creating conditions and proving the
behavior of Oracle using reproducible, usually single-user,
The Research DBA believes that a database can be described
with simple SQL*Plus test scripts and every assertion about
database behavior can be proven with such research.
The Research DBA does not believe in relying on ?rules-of-thumb? and
revels in finding exceptions to any general assertion about Oracle
behavior. Firmly-grounded in science, the Research DBA believes
that the scientific method requires experimentation.
notes that the Empirical DBA approach is problematic because it
suggests that novices cannot become expert in Oracle tuning without
many years of experience:
The other problem I have with the empirical approach is that it
relies on many, many years of experience and observation of
different types of Oracle database, and the "sixth sense" you
therefore develop for coming up with performance tuning fixes, and
therefore it's an approach that by definition cannot be taught to
novices in any reasonable amount of time, and cannot be carried out
by anyone other than very experienced DBAs.
Some authors are misleading their trusting followers with the mantra
of ?Prove it?, and they never note that ?your mileage may vary?,
especially for performance-related proofs.
Many times it seems the research DBA spends more time developing
these ?proofs? in seclusion than they do actually applying their
techniques to real-world databases. Often when faced with real-world
situations they will retreat into the mantra ?Rebuild the entire
application and call me in the morning??, a response that while is
probably true, doesn't really help in the real-world where down time
or lost time results in lost money.
In the real-world where I live, most database issues are
code/application related. However, fixing the code is not, in most
cases, a realistic option.
The Empirical DBA (as seen by the Research DBA)
The research DBA believes the Empirical DBA is lax and
sloppy, and does not pay enough attention to details.
They make bold assertions about Oracle behavior that can be
shown wrong under certain circumstances, yet they continue
in their foolhardy ways, using ?rules of thumb? and
real-world observations instead of hard facts.
The Research DBA believes that the Empirical DBA is a ?loose
cannon? and cannot understand their impatience and disregard for
elegant proofs and detail. Secretly, they think that the Empirical
DBA is dangerous, and cringes at their propensity to rush into every
database problem without supporting justification.
The Research DBA (as seen by the Empirical DBA)
The Empirical DBA sees little value in running limited,
single-user SQL*Plus scripts and believes that the Research
DBA is wasting their time ?proving? minutiae that has no
value in the real-world.
These 'script Kiddies? don't test their hypothesis on large
multi-user databases and they don't understand how a high
concurrency and load Oracle environment will change the
The Empirical DBA says that beginner Professionals are lulled into a
false sense of security by running invalid ?performance proofs?,
using single-user instances of Oracle under small loads. According
to Don Burleson, relying on these artificial pseudo-proofs can spell
?Many Oracle performance issues only manifest themselves under
high systems load. Time and time again I see cases where the DBA
bad advice from some limited SQL*Plus testing and assumed that
their small-scale test was sufficient to prove the system's speed
Now that we understand a bit about the mind-set of each group let's
look at how they accuse the other of perpetuating dangerous Oracle
The ?Rules-of-Thumb? Myth
Proponents of the ?No Rules-of-thumb (heuristics) allowed? myth say
that if any decision rule can be shown to be false, in even a single
case, it is invalid. They believe that the scientific method is the
only way to effectively approach an Oracle performance problem, and
all broad-brush tuning (changes to system-wide parameters, using
faster hardware) are unscientific, non-elegant and offensive.
Empirical DBA? Might as well call them a "medium", because what
you suggest here is merely "Database Meets Psychic Friends Network".
Unless you analyze, test, analyze again (you know the drill) you
aren't solving (or preventing) a problem.
The Empirical DBA Response
As Oracle technology becomes more available on personal computers, a
movement has arose where ?Oracle
Research Scientists? adopted the mantra ?Prove it? and started
publishing SQL*Plus scripts as evidence of how Oracle actually
behaves. The heuristic approach has been codified inside the Oracle
10g advisory tools (Automatic Memory Manager, SQLTuning advisor,
Oracle Data Mining), and heuristic techniques are well-proven and
accepted within the scientific community.
The Empirical professionals note that it is very difficult to
document a transient performance issue, and impossible to set-up any
repeatable ?proof? of the behavior without disclosing the client's
schema and table data. In sum, the Empirical DBA says that you
often have to rely on end-user testimonials and 'trust your
The 'script Kiddie? Myth
The Empirical DBA will tell you the foundation of science is not in
finding ?proofs? of Oracle behavior, but in observing the
real-world. With math you can prove that for a given gravity well, a
feather and a lead ball will accelerate at the same rate toward the
center of that gravity well.
In the real world we know the affects
of the surface area to weight and resistance will result in widely
different rates of acceleration. The successive refinement of their
heuristic rules form the experiential basis for ?expert? Oracle
tuning as noted in the book "Oracle
Silver Bullets?. Proponents of the 'script Kiddie? myth say
that performing Oracle database testing in a single-user environment
can lead to disaster.
The Research DBA Response
The research DBA says that Oracle software behaves the same in all
environments, and that their proofs offer valuable insights into the
behavior of the Oracle software.
The author of that book was smoking something funny. You have
my book -- you see when I say something,
I show all factors involved, I show the proof, I show the hard
numbers and I make it so you can reproduce it
The single-user "proofs" are quite factual for what they are, but
what they are (single-user, single CPU, single disk, no concurrent
access) often does not describe real-world behavior. This from
Robin Schumacher, author of
Oracle Performance Troubleshooting:
It's fine for DBAs to perform trials and postulate theories as
long as they realize those theories may crash and burn in the real
Or, as someone well said a while back, "watch out when a
beautiful theory meets a brutal gang of facts."
So, what do we make of this? It's clear that both groups believe in
the value of testing and benchmarks, but they do it in very
There is a big difference between a benchmark and a SQL*Plus ?proof?
and the real-world of high concurrent transactions makes most
performance proofs useless. For example, I published the results of
my benchmark study on how Solid-state disks (SSD) are faster then
traditional disks in a
135-page justification in the code depot of my book ?Oracle
Solid State Disk Tuning?. An Oracle benchmark uses realistic
data volumes and realistic user scenarios, proofs are a valuable
Remember, unless luckily placed, a single shotgun pellet is rarely
fatal, but the combined effect of the entire content of a shotgun
shell is nearly always fatal. Volume does make a difference, be it
users, data or both!
Back in the days before load testing software, we used to
simulate system load by paying the staff to stay late in the
I used a ?cheerleader? bullhorn and I would get everyone to
set-up the transaction, turn-on tracing, and then I would do
a 3-2-1-?Go? countdown to get valid performance statistics.
Today we see the widespread use of load testing tools instead of
SQL*Plus scripts, which allow you to simulate the effect of hundreds
of people conducting a transaction at the same time. In fact, many
tools let you take that single-user script and then multiple its
affects many times, thus making it far more valuable in predicting
real Oracle performance.
While single-user proofs validate how Oracle reacts in a single-user
environment rely on real-world benchmarks whenever possible for
decisions involving multi-user systems.
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