Re: In what circumstances might optimizer not choose the lowest cost?

From: stephen van linge <>
Date: Tue, 20 Jan 2015 14:42:12 +0000
Message-ID: <>

Just a thought, could it be that your old execution plan is still cached?  If you can reproduce on a dev machine you might try flushing the shared pool (dev machine only!) and then rerunning the query. Stephen Van Linge

      From: Kim Berg Hansen <>  To:; Cc: "" <>  Sent: Tuesday, January 20, 2015 6:33 AM  Subject: Re: In what circumstances might optimizer not choose the lowest cost?    

Hi again

Yes, I have histograms, including the hidden columns.

It does appear that the unpeeked bind variable is involved here. I did a trial with bind variables in SQL*Plus that I've set before the parsing/call of the queries - that worked nicely no matter if my check constraint is in place or not. As unfortunately I cannot help that my production environment isn't really using bind variable peeking, I'll research this further and see if I hit something similar to Doc ID 4112254.8. In normal operation this hasn't been a problem before, but then I'm using very very few FBI's. If I can make something reproducible testcase, I'll try it out on version 12 and see - if it's fixed there, I can wait until Easter where we (probably) will upgrade. Until then I'll just have to beware how I use FBI's in an environment without bind variable peeking...

Thanks all, for the inputs. Very helpful to get some pointers where to look :-)


Kim Berg Hansen

On Tue, Jan 20, 2015 at 3:20 PM, Kim Berg Hansen <> wrote:

Hi, Mauro and Lothar
Thanks for fast feedback ;-)

Adding "<expression> is not null" makes no difference at all, neither to cardinality estimates, nor to cost. As I am doing "<expression> between something and something", the optimizer knows that this can only be true for non-null values and the FBI will contain all non-null values of <expression>. It seems the optimizer is smart enough here ;-) If I use "between :1 and :2" instead of "between upperalphanum(:1) and upperalphanum(:2)", the cardinality estimates and IO cost is identical, the total cost is a bit lower reflecting a lower CPU cost.

Unpeeked bind might be something to look into. Unfortunately this old old ERP application environment parses SQL before populating bind variables, so I haven't much help from bind variable peeking. Although that doc is an old bug that should be fixed in version 10.2 (and we're running, I can't rule out that this may be involved.

I can make a 10053 trace, but asking you all to read through such a document might be relying on your generosity a bit too much ;-)Anyway, I can fix this query with various workarounds, no problem.I am mostly a bit worried that the optimizer didn't use the lowest cost, so I am looking for any "underlying reasons" that could influence other of my queries that at present I might be unaware that they perform badly. I think I'll try the 10053 and at least try myself to see if I can spot something ;-)


Kim Berg Hansen

On Tue, Jan 20, 2015 at 2:49 PM, Lothar Flatz <> wrote:

  Hi Kim,  

 first of all to finally answer your question I think we would need a 10053 trace.  However, maybe we can get away with a bit simpler approach.  I would try to add to your query "case dataset when 'DAT' then upperalphanum(eksterntvarenr) end" is not NULL.  You can well expect the optimizer does not understand your function. Therefore it does not know that you deliberately are skipping nulls.  It could be that the optimizer thinks the index access is not save (in terms of missing some rows) and you are helping him with your Index FBI hint.  Actually the optimizer should never do an unsafe transformation.  Not even hinted. But maybe Jonathan Lewis would know about exceptions.  

 One more additional suggestion: If you can, avoid upperalphanum(:bind1) , but rather send a pre calculated bind variable. The estimate of the optimizer should be better.  Did you try cardinality feedback?  



 (BTW: a salted banana is a throw away of a table row. A banana is a throw away from the index entry)  ;-)  

 Am 20.01.2015 um 14:20 schrieb Kim Berg Hansen:   

 Hi, fellows.
  I had a weird little case today, which I'll try to describe simply:   

  Two tables - Tab1 with 4 million rows, Tab2 with 3/4 million rows. Tab1 has a function based index on an expression: "case dataset when 'DAT' then upperalphanum(eksterntvarenr) end" - upperalphanum is a function returning uppercase of input stripped of any whitespace and non-alphanumeric characters. The FBI contains about two hundred thousand of the 4 million rows of Tab1, for the rest the expression is NULL.   

  Query is a simple join between the two tables joining on a two-column key. There is a predicate on Tab1 on the FBI expression:    "case dataset when 'DAT' then upperalphanum(eksterntvarenr) end BETWEEN upperalphanum(:bind1) and upperalphanum(:bind2)" And a filter predicate on two columns of Tab2. The access I want (and normally get) is index range scan of the FBI index on Tab1 and nested loop/index access of Tab2. (The whole purpose of the FBI is to have a small fast index for this and other similar queries.)   

  I have three versions of the query for testing: Q1: Hinted to use FBI index access on Tab1. Q2: Hinted to use an alternative normal index on Tab1 containing the columns of the FBI expression, where the expression then will be evaluated for all rows. Q3: Unhinted (my normal query.) Apart from hints, the three queries are identical.   Normally they get plans costed like this: Q1 hinted to FBI gets total Cost=26276.   Q2 hinted to normal index gets total Cost=40473. So normal index has a higher cost than FBI. Q3 unhinted picks the lower cost access plan and uses FBI with total Cost=26676.    Then I added a check constraint "check( dataset='DAT' )" on Tab2 on one of the two key columns used for the join. This changed the access plans for the queries - suddenly appeared (optimizer generated) a filter predicate dataset='DAT' on Tab1, as the optimizer know nows via the check constraint on Tab2 and the join between Tab1 and Tab2, that accessing any Tab1 rows with dataset NOT equal to 'DAT' would be folly, because they would be certain to be "thrown away" when we join to Tab1 on dataset column. ("Salted banana", as NoCoug Journal recently called it ;-)   When that filter predicate was added, my three test queries got new costs, of course: Q1 hinted to FBI gets total Cost=24374.   Q2 hinted to normal index gets total Cost=35493. So even with the new filter predicate reducing estimated cardinality (and cost) slightly, normal index is still higher cost than FBI.   BUT... Q3 unhinted picks the HIGHER cost access plan and uses normal index with total Cost=35493 ??   

  I can understand that my check constraint has a sideeffect of adding a filter predicate. I have also tested dropping the constraint again and instead added the same filter predicate manually to the queries - it gives the same result (so it is not specifically because there's a check constraint.)   What I canNOT understand is, that with the extra filter predicate in place, the optimizer picks the HIGHER costed of the two access plans?      

  So my question really is:
  Are there known circumstances where the optimizer does NOT choose the lowest cost, even though same query with a hint CAN produce a plan with a lower cost?   Or is this "buggy" behaviour? (My version is EE.)   

  Thanks in advance for any hints I can research ;-)  


  Kim Berg Hansen _at_kibeha         


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Received on Tue Jan 20 2015 - 15:42:12 CET

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