How to inline a variable in PL/SQL? - oracle

The Situation
I have some trouble with my query execution plan for a medium-sized query over a large amount of data in Oracle 11.2.0.2.0. In order to speed things up, I introduced a range filter that does roughly something like this:
PROCEDURE DO_STUFF(
org_from VARCHAR2 := NULL,
org_to VARCHAR2 := NULL)
-- [...]
JOIN organisations org
ON (cust.org_id = org.id
AND ((org_from IS NULL) OR (org_from <= org.no))
AND ((org_to IS NULL) OR (org_to >= org.no)))
-- [...]
As you can see, I want to restrict the JOIN of organisations using an optional range of organisation numbers. Client code can call DO_STUFF with (supposed to be fast) or without (very slow) the restriction.
The Trouble
The trouble is, PL/SQL will create bind variables for the above org_from and org_to parameters, which is what I would expect in most cases:
-- [...]
JOIN organisations org
ON (cust.org_id = org.id
AND ((:B1 IS NULL) OR (:B1 <= org.no))
AND ((:B2 IS NULL) OR (:B2 >= org.no)))
-- [...]
The Workaround
Only in this case, I measured the query execution plan to be a lot better when I just inline the values, i.e. when the query executed by Oracle is actually something like
-- [...]
JOIN organisations org
ON (cust.org_id = org.id
AND ((10 IS NULL) OR (10 <= org.no))
AND ((20 IS NULL) OR (20 >= org.no)))
-- [...]
By "a lot", I mean 5-10x faster. Note that the query is executed very rarely, i.e. once a month. So I don't need to cache the execution plan.
My questions
How can I inline values in PL/SQL? I know about EXECUTE IMMEDIATE, but I would prefer to have PL/SQL compile my query, and not do string concatenation.
Did I just measure something that happened by coincidence or can I assume that inlining variables is indeed better (in this case)? The reason why I ask is because I think that bind variables force Oracle to devise a general execution plan, whereas inlined values would allow for analysing very specific column and index statistics. So I can imagine that this is not just a coincidence.
Am I missing something? Maybe there is an entirely other way to achieve query execution plan improvement, other than variable inlining (note I have tried quite a few hints as well but I'm not an expert on that field)?

In one of your comments you said:
"Also I checked various bind values.
With bind variables I get some FULL
TABLE SCANS, whereas with hard-coded
values, the plan looks a lot better."
There are two paths. If you pass in NULL for the parameters then you are selecting all records. Under those circumstances a Full Table Scan is the most efficient way of retrieving data. If you pass in values then indexed reads may be more efficient, because you're only selecting a small subset of the information.
When you formulate the query using bind variables the optimizer has to take a decision: should it presume that most of the time you'll pass in values or that you'll pass in nulls? Difficult. So look at it another way: is it more inefficient to do a full table scan when you only need to select a sub-set of records, or to do indexed reads when you need to select all records?
It seems as though the optimizer has plumped for full table scans as being the least inefficient operation to cover all eventualities.
Whereas when you hard code the values the Optimizer knows immediately that 10 IS NULL evaluates to FALSE, and so it can weigh the merits of using indexed reads for find the desired sub-set records.
So, what to do? As you say this query is only run once a month I think it would only require a small change to business processes to have separate queries: one for all organisations and one for a sub-set of organisations.
"Btw, removing the :R1 IS NULL clause
doesn't change the execution plan
much, which leaves me with the other
side of the OR condition, :R1 <=
org.no where NULL wouldn't make sense
anyway, as org.no is NOT NULL"
Okay, so the thing is you have a pair of bind variables which specify a range. Depending on the distribution of values, different ranges might suit different execution plans. That is, this range would (probably) suit an indexed range scan...
WHERE org.id BETWEEN 10 AND 11
...whereas this is likely to be more fitted to a full table scan...
WHERE org.id BETWEEN 10 AND 1199999
That is where Bind Variable Peeking comes into play.
(depending on distribution of values, of course).

Since the query plans are actually consistently different, that implies that the optimizer's cardinality estimates are off for some reason. Can you confirm from the query plans that the optimizer expects the conditions to be insufficiently selective when bind variables are used? Since you're using 11.2, Oracle should be using adaptive cursor sharing so it shouldn't be a bind variable peeking issue (assuming you are calling the version with bind variables many times with different NO values in your testing.
Are the cardinality estimates on the good plan actually correct? I know you said that the statistics on the NO column are accurate but I would be suspicious of a stray histogram that may not be updated by your regular statistics gathering process, for example.
You could always use a hint in the query to force a particular index to be used (though using a stored outline or optimizer plan stability would be preferable from a long-term maintenance perspective). Any of those options would be preferable to resorting to dynamic SQL.
One additional test to try, however, would be to replace the SQL 99 join syntax with Oracle's old syntax, i.e.
SELECT <<something>>
FROM <<some other table>> cust,
organization org
WHERE cust.org_id = org.id
AND ( ((org_from IS NULL) OR (org_from <= org.no))
AND ((org_to IS NULL) OR (org_to >= org.no)))
That obviously shouldn't change anything, but there have been parser issues with the SQL 99 syntax so that's something to check.

It smells like Bind Peeking, but I am only on Oracle 10, so I can't claim the same issue exists in 11.

This looks a lot like a need for Adaptive Cursor Sharing, combined with SQLPlan stability.
I think what is happening is that the capture_sql_plan_baselines parameter is true. And the same for use_sql_plan_baselines. If this is true, the following is happening:
The first time that a query started it is parsed, it gets a new plan.
The second time, this plan is stored in the sql_plan_baselines as an accepted plan.
All following runs of this query use this plan, regardless of what the bind variables are.
If Adaptive Cursor Sharing is already active,the optimizer will generate a new/better plan, store it in the sql_plan_baselines but is not able to use it, until someone accepts this newer plan as an acceptable alternative plan. Check dba_sql_plan_baselines and see if your query has entries with accepted = 'NO' and verified = null
You can use dbms_spm.evolve to evolve the new plan and have it automatically accepted if the performance of the plan is at least 1,5 times better than without the new plan.
I hope this helps.

I added this as a comment, but will offer up here as well. Hope this isn't overly simplistic, and looking at the detailed responses I may be misunderstanding the exact problem, but anyway...
Seems your organisations table has column no (org.no) that is defined as a number. In your hardcoded example, you use numbers to do the compares.
JOIN organisations org
ON (cust.org_id = org.id
AND ((10 IS NULL) OR (10 <= org.no))
AND ((20 IS NULL) OR (20 >= org.no)))
In your procedure, you are passing in varchar2:
PROCEDURE DO_STUFF(
org_from VARCHAR2 := NULL,
org_to VARCHAR2 := NULL)
So to compare varchar2 to number, Oracle will have to do the conversions, so this may cause the full scans.
Solution: change proc to pass in numbers

Related

CHARINDEX vs LIKE search gives very different performance, why?

We use Entity Frameworks for DB access and when we "think" LIKE statement - it actually generates CHARINDEX stuff. So, here is 2 simple queries, after I simplified them to prove a point on our certain server:
-- Runs about 2 seconds
SELECT * FROM LOCAddress WHERE Address1 LIKE '%1124%'
-- Runs about 16 seconds
SELECT * FROM LOCAddress WHERE ( CAST(CHARINDEX(LOWER(N'1124'), LOWER([Address1])) AS int)) = 1
Table contains about 100k records right now. Address1 is VarChar(100) field, nothing special.
Here is snip of 2 plans side by side. Doesn't make any sense, shows 50% and 50% but execution times like 1:8
I searched online and general advice is to use CHARINDEX instead of LIKE. In our experience it's opposite. My question is what causing this and how we can fix it without code change?
I will answer my own question since it was hard to find correct answer and I was pointed to the problem by SQL Server 2012 Execution Plan output. As you see in original question - everything looks OK on surface. This is SQL Server 2008.
When I run same query on 2012 I got warning on CHARINDEX query. Problem is - SQL Server had to do type conversion. Address1 is VarChar and query has N'1124' which is Unicode or NVarChar. If I change this query as so:
SELECT *
FROM LOCAddress
WHERE (CAST(CHARINDEX(LOWER('1124'), LOWER([Address1])) AS int))
It then runs same as LIKE query. So, type conversion that was caused by Entity Framework generator was causing this horrible hit in performance.
First, as you can see both queries are identical and neither can use index. CHARINDEX and LIKE perform same with wildcard. Ex: %YourValue%. However, there performance varies when you use wildcard like 'YourValue%'. Here, LIKE operator will likely to perform faster than CHARINDEX because it may allow partial scan of the index.
Now, in your case, both queries are same but there performance is difference because of following possible reason:
Statistics: SQL Server maintains statistics for sub string in string columns which are use by LIKE operator but not fully usable for CHARINDEX. In that case, LIKE operator will work faster than CHARINDEX.
You can force SQL Server to use index for CHARINDEX with proper table hints
Ex: FROM LOCAddress WITH (INDEX (index_name))
Read more Here, which in section "string summary stastics" says:
SQL Server 2008 includes patented technology for estimating the selectivity of LIKE conditions. It builds a statistical summary of
substring frequency distribution for character columns (a string
summary). This includes columns of type text, ntext, char, varchar,
and nvarchar. Using the string summary, SQL Server can accurately
estimate the selectivity of LIKE conditions where the pattern may have
any number of wildcards in any combination.

pl/sql query optimization with function call in where clause

I am trying to optimize a query where I am using a function() call in the where clause.
The function() simply changes the timezone of the date.
When I call the function as part of the SELECT, it executes extremely fast (< 0.09 sec against table of many hundreds of thousands of rows)
select
id,
fn_change_timezone (date_time, 'UTC', 'US/Central') AS tz_date_time,
value
from a_table_view
where id = 'keyvalue'
and date_time = to_date('01-10-2014','mm-dd-yyyy')
However, this version runs "forever" [meaning I stop it after umpteen minutes]
select id, date_time, value
from a_table_view
where id = 'keyvalue'
and fn_change_timezone (date_time, 'UTC', 'US/Central') = to_date('01-10-2014','mm-dd-yyyy')
(I know I'd have to change the date being compared, its just for example)
So my question is two-fold:
If the function is so fast outside of the where clause, why is it so much slower than say using TRUNC() or other functions (obviously trunc() doesnt do a table lookup like my function - but still the function is very very fast outside the where clause)
What are alternate ways of accomplishing this outside of the where clause ?
I tried this as an alternative, which did not seem any better, it still ran until I stopped the query:
select
tz.date_time,
v.id,
v.value
from
(select
fn_change_timezone(to_date('01/10/2014-00:00:00', 'mm/dd/yyyy-hh24:mi:ss'), 'UTC', 'US/Central') as date_time
from dual
) tz
inner join
(
select
id,
fn_change_timezone (date_time, 'UTC', 'US/Central') AS v_date_time,
value
from a_table_view
where id = 'keyvalue'
) v ON
v.tz_date_time = tz.date_time
Hopefully I am explaining the issue well.
There are at least four potential issues with using functions in the WHERE clause:
Functions may prevent indexes. A function-based index can solve this issue.
Functions may prevent partition pruning. Hard-coding values or maybe virtual column partitioning are possible solutions, although neither is likely helpful in this case.
Functions may run slowly. Even if the function is cheap, it is often very expensive to switch between SQL and PL/SQL. Some possible solutions are DETERMINISTIC, PARALLEL_ENABLE, function result caching, defining the logic in purely SQL, or with 12c defining the function in SQL.
Functions may cause bad cardinality estimates. It's hard enough for the optimizer to guess the result of normal conditions, adding procedural code makes it even more difficult. Using ASSOCIATE STATISTICS it is possible to provide some information to the optimizer about the cost and cardinality of the function.
Without more information, such as an explain plan, it is difficult to know what the specific issue is with this query.
Function calls in the WHERE clause are a Bad Thing. The problem is that the function may be called for every row in the table, which may be many more than the selected set. This can be a real performance killer (don't ask me how I know :-). In the first version with the function call in the SELECT list the function will only be called when a row has been chosen and is being added to the result set - in the second version the function may well be called for every row in the table. Also, depending on the version of Oracle you're using there may be significant overhead to calling a user function from SQL, but I think this penalty has been largely eliminated in versions since 10g.
Best of luck.
Share and enjoy.

Sqlite view vs plain select statement performance

I have a simple table (with about 8 columns and a LOT of rows) in a SQLite database. There is a single program that runs as a service and performs selects, updates and inserts on the table quite often (approximately every 5 minutes). The selects are used only to determine which rows are to be updated, and they are based on a column that holds boolean values (probably translated to integer internally by SQLite).
There is also a web application that performs selects (always with a GROUP BY clause) whenever a web user wishes to view part of the data.
There are two ways to ask for data through the web application: (a) predefined filters (i.e. the where clause has specific conditions on 3 specific columns) an (b) custom filters (i.e. the user chooses the values for the conditions, but the columns participating in the where clause are the same as in (a)). As mentioned, in both cases there is a GROUP BY operation.
I am wondering whether using a view or a custom function might increase the performance. Currently, a "custom" select may take more than 30 seconds to complete - and that's before any data has been sent back to the user.
EDIT:
Using EXPLAIN QUERY PLAN on a "predefined" select statement yields only one row:
0|0|TABLE mytable
Using EXPLAIN on the same query, yields the following:
0|OpenVirtual|1|4|keyinfo(2,-BINARY,BINARY)
1|OpenVirtual|2|3|keyinfo(1,BINARY)
2|MemInt|0|5|
3|MemInt|0|4|
4|Goto|0|27|
5|MemInt|1|5|
6|Return|0|0|
7|IfMemPos|4|9|
8|Return|0|0|
9|AggFinal|0|0|count(0)
10|AggFinal|2|1|sum(1)
11|MemLoad|0|0|
12|MemLoad|1|0|
13|MemLoad|2|0|
14|MakeRecord|3|0|
15|MemLoad|0|0|
16|MemLoad|1|0|
17|Sequence|1|0|
18|Pull|3|0|
19|MakeRecord|4|0|
20|IdxInsert|1|0|
21|Return|0|0|
22|MemNull|1|0|
23|MemNull|3|0|
24|MemNull|0|0|
25|MemNull|2|0|
26|Return|0|0|
27|Gosub|0|22|
28|Goto|0|82|
29|Integer|0|0|
30|OpenRead|0|2|
31|SetNumColumns|0|9|
32|Rewind|0|48|
33|Column|0|8|
34|String8|0|0|123456789
35|Le|356|39|collseq(BINARY)
36|Column|0|3|
37|Integer|180|0|
38|Gt|100|42|collseq(BINARY)
39|Column|0|7|
40|Integer|1|0|
41|Ne|356|47|collseq(BINARY)
42|Column|0|6|
43|Sequence|2|0|
44|Column|0|3|
45|MakeRecord|3|0|
46|IdxInsert|2|0|
47|Next|0|33|
48|Close|0|0|
49|Sort|2|69|
50|Column|2|0|
51|MemStore|7|0|
52|MemLoad|6|0|
53|Eq|512|58|collseq(BINARY)
54|MemMove|6|7|
55|Gosub|0|7|
56|IfMemPos|5|69|
57|Gosub|0|22|
58|AggStep|0|0|count(0)
59|Column|2|2|
60|Integer|30|0|
61|Add|0|0|
62|ToReal|0|0|
63|AggStep|2|1|sum(1)
64|Column|2|0|
65|MemStore|1|1|
66|MemInt|1|4|
67|Next|2|50|
68|Gosub|0|7|
69|OpenPseudo|3|0|
70|SetNumColumns|3|3|
71|Sort|1|80|
72|Integer|1|0|
73|Column|1|3|
74|Insert|3|0|
75|Column|3|0|
76|Column|3|1|
77|Column|3|2|
78|Callback|3|0|
79|Next|1|72|
80|Close|3|0|
81|Halt|0|0|
82|Transaction|0|0|
83|VerifyCookie|0|1|
84|Goto|0|29|
85|Noop|0|0|
The select I used was as the following
SELECT
COUNT(*) as number,
field1,
SUM(CAST(filter2 +30 AS float)) as column2
FROM
mytable
WHERE
(filter1 > '123456789' AND filter2 > 180)
OR filter3=1
GROUP BY
field1
ORDER BY
number DESC, field1;
Whenever you're going to be doing comparisons of a non-primary-key field, it's a good design idea to add an index into to the field(s). Too many, however, can cause INSERTs to crawl, so plan accordingly.
Also, if you have simple fields such as ones that only hold a boolean value, you may want to consider declaring it as an INTEGER instead of whatever you declared it as. Declaring it as any type not specifically defined by SQLite will cause it to default to a NUMERIC type which will take longer to compare values because it will store it internally as a double and will use the floating-point math processor instead of the integer math processor.
IMO, the GROUP BY sorting directive is sometimes a dead giveaway to an unoptimized query; its methodology involves eliminating redundant data which could have been eliminated beforehand if it hadn't been pulled out of the database to begin with.
EDIT:
I saw your query and saw there are some simple things you can do to optimize it:
SUM(CAST(filter2 +30 AS float)) is inefficient; why are you casting it as a float? Why not just SUM it then add 30 * the COUNT?
filter1 > '123456789' - Why the string comparison? Why not just use integer comparison?

performance of rand()

I have heard that I should avoid using 'order by rand()', but I really need to use it. Unlike what I have been hearing, the following query comes up very fast.
select
cp1.img_id as left_id,
cp1.img_filename as left_filename,
cp1.facebook_name as left_facebook_name,
cp2.img_id as right_id,
cp2.img_filename as right_filename,
cp2.facebook_name as right_facebook_name
from
challenge_photos as cp1
cross join
challenge_photos as cp2
where
(cp1.img_id < cp2.img_id)
and
(cp1.img_id,cp2.img_id) not in ((0,0))
and
(cp1.img_status = 1 and cp2.img_status = 1)
order by rand() limit 1
is this query considered 'okay'? or should I use queries that I can find by searching "alternative to rand()" ?
It's usually a performance thing. You should avoid, as much as possible, per-row functions since they slow down your queries.
That means things like uppercase(name), salary * 1.1 and so on. It also includes rand(). It may not be an immediate problem (at 10,000 rows) but, if you ever want your database to scale, you should keep it in mind.
The two main issues are the fact that you're performing a per-row function and then having to do a full sort on the output before selecting the first row. The DBMS cannot use an index if you sort on a random value.
But, if you need to do it (and I'm not making judgement calls there), then you need to do it. Pragmatism often overcomes dogmatism in the real world :-)
A possibility, if performance ever becomes an issue, is to get a count of the records with something like:
select count(*) from ...
then choose a random value on the client side and use a:
limit <start>, <count>
clause in another select, adjusting for the syntax used by your particular DBMS. This should remove the sorting issue and the transmission of unneeded data across the wire.

Boolean Field in Oracle

Yesterday I wanted to add a boolean field to an Oracle table. However, there isn't actually a boolean data type in Oracle. Does anyone here know the best way to simulate a boolean? Googling the subject discovered several approaches
Use an integer and just don't bother assigning anything other than 0 or 1 to it.
Use a char field with 'Y' or 'N' as the only two values.
Use an enum with the CHECK constraint.
Do experienced Oracle developers know which approach is preferred/canonical?
I found this link useful.
Here is the paragraph highlighting some of the pros/cons of each approach.
The most commonly seen design is to imitate the many Boolean-like
flags that Oracle's data dictionary views use, selecting 'Y' for true
and 'N' for false. However, to interact correctly with host
environments, such as JDBC, OCCI, and other programming environments,
it's better to select 0 for false and 1 for true so it can work
correctly with the getBoolean and setBoolean functions.
Basically they advocate method number 2, for efficiency's sake, using
values of 0/1 (because of interoperability with JDBC's getBoolean() etc.) with a check constraint
a type of CHAR (because it uses less space than NUMBER).
Their example:
create table tbool (bool char check (bool in (0,1));
insert into tbool values(0);
insert into tbool values(1);`
Oracle itself uses Y/N for Boolean values. For completeness it should be noted that pl/sql has a boolean type, it is only tables that do not.
If you are using the field to indicate whether the record needs to be processed or not you might consider using Y and NULL as the values. This makes for a very small (read fast) index that takes very little space.
To use the least amount of space you should use a CHAR field constrained to 'Y' or 'N'. Oracle doesn't support BOOLEAN, BIT, or TINYINT data types, so CHAR's one byte is as small as you can get.
The best option is 0 and 1 (as numbers - another answer suggests 0 and 1 as CHAR for space-efficiency but that's a bit too twisted for me), using NOT NULL and a check constraint to limit contents to those values. (If you need the column to be nullable, then it's not a boolean you're dealing with but an enumeration with three values...)
Advantages of 0/1:
Language independent. 'Y' and 'N' would be fine if everyone used it. But they don't. In France they use 'O' and 'N' (I have seen this with my own eyes). I haven't programmed in Finland to see whether they use 'E' and 'K' there - no doubt they're smarter than that, but you can't be sure.
Congruent with practice in widely-used programming languages (C, C++, Perl, Javascript)
Plays better with the application layer e.g. Hibernate
Leads to more succinct SQL, for example, to find out how many bananas are ready to eat select sum(is_ripe) from bananas instead of select count(*) from bananas where is_ripe = 'Y' or even (yuk) select sum(case is_ripe when 'Y' then 1 else 0) from bananas
Advantages of 'Y'/'N':
Takes up less space than 0/1
It's what Oracle suggests, so might be what some people are more used to
Another poster suggested 'Y'/null for performance gains. If you've proven that you need the performance, then fair enough, but otherwise avoid since it makes querying less natural (some_column is null instead of some_column = 0) and in a left join you'll conflate falseness with nonexistent records.
Either 1/0 or Y/N with a check constraint on it. ether way is fine. I personally prefer 1/0 as I do alot of work in perl, and it makes it really easy to do perl Boolean operations on database fields.
If you want a really in depth discussion of this question with one of Oracles head honchos, check out what Tom Kyte has to say about this Here
The database I did most of my work on used 'Y' / 'N' as booleans. With that implementation, you can pull off some tricks like:
Count rows that are true:
SELECT SUM(CASE WHEN BOOLEAN_FLAG = 'Y' THEN 1 ELSE 0) FROM X
When grouping rows, enforce "If one row is true, then all are true" logic:
SELECT MAX(BOOLEAN_FLAG) FROM Y
Conversely, use MIN to force the grouping false if one row is false.
A working example to implement the accepted answer by adding a "Boolean" column to an existing table in an oracle database (using number type):
ALTER TABLE my_table_name ADD (
my_new_boolean_column number(1) DEFAULT 0 NOT NULL
CONSTRAINT my_new_boolean_column CHECK (my_new_boolean_column in (1,0))
);
This creates a new column in my_table_name called my_new_boolean_column with default values of 0. The column will not accept NULL values and restricts the accepted values to either 0 or 1.
In our databases we use an enum that ensures we pass it either TRUE or FALSE. If you do it either of the first two ways it is too easy to either start adding new meaning to the integer without going through a proper design, or ending up with that char field having Y, y, N, n, T, t, F, f values and having to remember which section of code uses which table and which version of true it is using.

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