Is the time complexity of the Oracle MAX function O(1), O(log n) or O(n) with respect to the number of rows in a table?
If you have a B-tree index on the column then finding the maximum value is O(log(n)) because the answer will be the last (or first) row of the index. Values are stored in the deepest nodes of the B-tree which has a height O(log(n)).
Without an index it is O(n) because all rows must be read to determine the maximum value.
Note: The O(n) notation ignores constants but in the real world these constants cannot be ignored. The difference between reading from disk and reading from memory is several orders of magnitude. Accessing the first value of an index is likely to be performed mostly in RAM, whereas a full table scan of a huge table will need to read mostly from disk.
Realistically, it's hard to say without specifying a query, a table definition, and a query plan.
If you have a table that has no index on the column you're computing the MAX on, Oracle will have to do a full table scan. That is going to be O(n) since you've got to scan every block in the table. You can see that by looking at the query plan.
We'll generate a table with 100,000 rows and ensure that the rows are reasonably large using a CHAR(1000) column
SQL> create table foo( col1 number, col2 char(1000) );
Table created.
SQL> insert into foo
2 select level, lpad('a',1000)
3 from dual
4 connect by level <= 100000;
100000 rows created.
Now, we can look at the plan for the basic MAX operation. This is doing a full table scan (an O(n) operation)
SQL> set autotrace on;
SQL> select max(col1)
2 from foo;
MAX(COL1)
----------
100000
Execution Plan
----------------------------------------------------------
Plan hash value: 1342139204
---------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
---------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 13 | 4127 (1)| 00:00:50 |
| 1 | SORT AGGREGATE | | 1 | 13 | | |
| 2 | TABLE ACCESS FULL| FOO | 106K| 1350K| 4127 (1)| 00:00:50 |
---------------------------------------------------------------------------
Note
-----
- dynamic sampling used for this statement (level=2)
Statistics
----------------------------------------------------------
29 recursive calls
1 db block gets
14686 consistent gets
0 physical reads
176 redo size
527 bytes sent via SQL*Net to client
523 bytes received via SQL*Net from client
2 SQL*Net roundtrips to/from client
0 sorts (memory)
0 sorts (disk)
1 rows processed
If you create an index on the column you're computing the MAX of, Oracle can do a MIN/MAX scan on the index. That is an O(log n) operation if that's the plan the optimizer chooses. Of course, as a practical matter, this is functionally an O(1) operation because the height of an index is never realistically going to exceed 4 or 5-- the constant terms here are going to dominate.
SQL> create index idx_foo_col1
2 on foo( col1 );
Index created.
SQL> select max(col1)
2 from foo;
MAX(COL1)
----------
100000
Execution Plan
----------------------------------------------------------
Plan hash value: 817909383
-------------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
-------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 13 | 2 (0)| 00:00:01 |
| 1 | SORT AGGREGATE | | 1 | 13 | | |
| 2 | INDEX FULL SCAN (MIN/MAX)| IDX_FOO_COL1 | 1 | 13 | 2 (0)| 00:00:01 |
-------------------------------------------------------------------------------------------
Note
-----
- dynamic sampling used for this statement (level=2)
Statistics
----------------------------------------------------------
5 recursive calls
0 db block gets
83 consistent gets
1 physical reads
0 redo size
527 bytes sent via SQL*Net to client
523 bytes received via SQL*Net from client
2 SQL*Net roundtrips to/from client
0 sorts (memory)
0 sorts (disk)
1 rows processed
But then things get harder. Both MIN and MAX have the same O(log n) behavior individually. But if you have both MIN and MAX in the same query, suddenly you're back to an O(n) operation. Oracle (as of 11.2) hasn't implemented an option grab both the first block and the last block of an index
SQL> ed
Wrote file afiedt.buf
1 select min(col1), max(col1)
2* from foo
SQL> /
MIN(COL1) MAX(COL1)
---------- ----------
1 100000
Execution Plan
----------------------------------------------------------
Plan hash value: 1342139204
---------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
---------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 13 | 4127 (1)| 00:00:50 |
| 1 | SORT AGGREGATE | | 1 | 13 | | |
| 2 | TABLE ACCESS FULL| FOO | 106K| 1350K| 4127 (1)| 00:00:50 |
---------------------------------------------------------------------------
Note
-----
- dynamic sampling used for this statement (level=2)
Statistics
----------------------------------------------------------
4 recursive calls
0 db block gets
14542 consistent gets
0 physical reads
0 redo size
601 bytes sent via SQL*Net to client
523 bytes received via SQL*Net from client
2 SQL*Net roundtrips to/from client
0 sorts (memory)
0 sorts (disk)
1 rows processed
Of course, in subsequent versions of Oracle, this optimization might be implemented and this would go back to being an O(log n) operation. Of course, you can also rewrite the query to get a different query plan that goes back to being O(log n)
SQL> ed
Wrote file afiedt.buf
1 select (select min(col1) from foo) min,
2 (select max(col1) from foo) max
3* from dual
SQL>
SQL> /
MIN MAX
---------- ----------
1 100000
Execution Plan
----------------------------------------------------------
Plan hash value: 3561244922
-------------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
-------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | | 2 (0)| 00:00:01 |
| 1 | SORT AGGREGATE | | 1 | 13 | | |
| 2 | INDEX FULL SCAN (MIN/MAX)| IDX_FOO_COL1 | 1 | 13 | 2 (0)| 00:00:01 |
| 3 | SORT AGGREGATE | | 1 | 13 | | |
| 4 | INDEX FULL SCAN (MIN/MAX)| IDX_FOO_COL1 | 1 | 13 | 2 (0)| 00:00:01 |
| 5 | FAST DUAL | | 1 | | 2 (0)| 00:00:01 |
-------------------------------------------------------------------------------------------
Note
-----
- dynamic sampling used for this statement (level=2)
Statistics
----------------------------------------------------------
7 recursive calls
0 db block gets
166 consistent gets
0 physical reads
0 redo size
589 bytes sent via SQL*Net to client
523 bytes received via SQL*Net from client
2 SQL*Net roundtrips to/from client
0 sorts (memory)
0 sorts (disk)
1 rows processed
Related
I executed this query on Oracle 19c where the partitioned table GRID_LTA has been assigned to KEEP POOL buffer and any segment related name has prefix GRID_LTA as well as primary key and indexes:
SQL> set timing on
SQL> set autotrace on
SQL> SELECT count(distinct t.AVG) n FROM MY_SCHEMA.GRID_LTA t;
N
--------------------------------------
308
Elapsed: 00:00:01.80
Execution Plan
----------------------------------------------------------
Plan hash value: 3595206837
--------------------------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes| (%CPU)| Time | Pstart| Pstop |
--------------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 13 |104K (1)| 00:00:05 | | |
| 1 | SORT AGGREGATE | | 1 | 13 | | | | |
| 2 | VIEW | VW_DAG_0 | 308 |4004|104K (1)| 00:00:05 | | |
| 3 | HASH GROUP BY | | 308 | 1232| 104K (1)| 00:00:05 | | |
| 4 | PARTITION LIST ALL | | 4979K| 18M| 104K (1)| 00:00:05 | 1 | 22 |
| 5 | TABLE ACCESS FULL| GRID_LTA | 4979K| 18M| 104K (1)| 00:00:05 | 1 | 22 |
--------------------------------------------------------------------------------------------------------
Statistics
----------------------------------------------------------
3 recursive calls
0 db block gets
**376769 consistent gets
0 physical reads**
0 redo size
581 bytes sent via SQL*Net to client
588 bytes received via SQL*Net from client
2 SQL*Net roundtrips to/from client
0 sorts (memory)
0 sorts (disk)
1 rows processed
After ten second I submitted this query to inspect the content of the V$BH view:
select o.OWNER,o.object_name, count(distinct block#) k1, count(block#) k2
from sys.dba_objects o, SYS.V_$BH b
where b.OBJD = o.OBJECT_ID
and b.status != 'free'
and o.owner = 'MY_SCHEMA'
and instr(o.object_name,'GRID_LTA') > 0
group by o.OWNER,o.object_name;
Statistics
----------------------------------------------------------
27 recursive calls
0 db block gets
1764 consistent gets
0 physical reads
0 redo size
574 bytes sent via SQL*Net to client
577 bytes received via SQL*Net from client
1 SQL*Net roundtrips to/from client
0 sorts (memory)
0 sorts (disk)
**0 rows processed**
Now it appears the table has completely been read from buffer pool but inspecting buffer pool there isn't any block.
Did I something wrong or is there a possibile explanation ?
How is it possible inspecting the buffer pool in reliable way ?
just solved, using data_object_id instead object_id how I've seen abroad in some examples.
I'm using Oracle 18c but I guess my question would not be bound to the specific version.
I want to fetch rows from a table but I found a complex, ugly solution.
I would like to know if there is better, simple query that can return the same result as following.
First of all, I have a simple table like this.
Note that col is going to store large text.
CREATE TABLE simpletable
(record_id NUMBER,
col CLOB,
PRIMARY KEY (record_id));
I want to retrieve single row from the above table and whichever row is acceptable.
First query came to my mind is as following.
SELECT * FROM (SELECT * FROM simpletable) WHERE rownum <= 1;
Another is as following.
SELECT * FROM (SELECT * FROM simpletableORDER BY record_id) WHERE rownum <= 1;
Unfortunately, neither of above two does not use primary-key index and uses TABLE ACCESS FULL which can take long time when the table grows enough large.
(I'm guessing that oracle preferred the simpler plan because my table is not enough large yet to use index scan.
Oracle might choose different plan if the table grows up further.)
My final solution that uses primary-key index to narrow down the table access is following.
SELECT simpletable.* FROM
(SELECT * FROM
(SELECT record_id, ROWID as id FROM simpletable ORDER BY record_id)
WHERE rownum<=1) a
JOIN simpletable ON a.id = simpletable.ROWID;
If you have a better solution, please let me know.
It would be very appreciated.
P.S.
The first two queries produced the following plan.
------------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 2015 | 4 (25)| 00:00:01 |
|* 1 | COUNT STOPKEY | | | | | |
| 2 | VIEW | | 1 | 2015 | 4 (25)| 00:00:01 |
|* 3 | SORT ORDER BY STOPKEY| | 1 | 2015 | 4 (25)| 00:00:01 |
| 4 | TABLE ACCESS FULL | SIMPLETABLE | 1 | 2015 | 3 (0)| 00:00:01 |
------------------------------------------------------------------------------------------
the final one is:
----------------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
----------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 2039 | 3 (0)| 00:00:01 |
| 1 | NESTED LOOPS | | 1 | 2039 | 3 (0)| 00:00:01 |
| 2 | VIEW | | 1 | 25 | 2 (0)| 00:00:01 |
|* 3 | COUNT STOPKEY | | | | | |
| 4 | VIEW | | 1 | 25 | 2 (0)| 00:00:01 |
| 5 | INDEX FULL SCAN | SYS_C007561 | 1 | 25 | 2 (0)| 00:00:01 |
| 6 | TABLE ACCESS BY USER ROWID| SIMPLETABLE | 1 | 2014 | 1 (0)| 00:00:01 |
----------------------------------------------------------------------------------------------
I think using OFFSET..FETCH method might helps you here -
SELECT *
FROM simpletable
ORDER BY record_id
OFFSET 0 ROWS
FETCH FIRST ROW ONLY;
If the Cost Based Optimizer code has access to reliable statistics, from its dictionary, regarding all the objects available for this query, then it will very likely produce an optimal execution plan. Of course, there are exceptions and you would argue with their support people as to whether or not choosing a suboptimal plan is a bug.
In this specific case, if you are querying a single table and the CBO could choose between a full table scan and some other scan and then chose a full table scan, then chances were good that the CBO determined that the number of blocks scanned (buffer gets) would have been smaller using a full table scan.
You can expose the truth of the matter by tracing the execution of multiple versions of the statement, each one using a different set of hints to force a particular execution plan. You should consider the execution with the fewest buffer gets to be the winner. Alternatively, if the execution plan is of a serial nature, then you can use response time as measure. If the winner is not automatically chosen by the CBO, then it's probably because the statistics it used were not accurate and you should make them accurate. If the statistics are indeed accurate then Oracle support will probably give you a very long homework assignment.
Similar to the Horror Vacui, some database developers suffer under the Horror FULL TABLE SCAN by simply assuming index access good, full scan bad.
But this is not true, FULL TABLE SCAN is a normal access method, that is preferred in some situation.
Let's illustrate it on a simple example with 10K rows in your table
insert into simpletable (record_id, col)
select rownum, rpad('x',3998,'y')
from dual connect by level <= 10000
To get one arbitrary row from the table you simple use the following query
select * from simpletable where rownum = 1;
Here is the output (edited for brevity) you get from SQL*Plus with setting set autotrace traceonly to see the execution plan and the statistics.
Execution Plan
----------------------------------------------------------
Plan hash value: 1007892724
--------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time
--------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 2015 | 2 (0)| 00:00:01
|* 1 | COUNT STOPKEY | | | | |
| 2 | TABLE ACCESS FULL| SIMPLETABLE | 10188 | 19M| 2 (0)| 00:00:01
--------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
1 - filter(ROWNUM=1)
Statistics
----------------------------------------------------------
5 consistent gets
2 physical reads
1 rows processed
The most important information is the statistics consistent gets - there were only 5 blocks accessed - the table is much larger.
What is the explanation? See the operation COUNT STOPKEY above the TABLE ACCESS FULL this ensures that the scan is terminated after the first row is found.
If you want to get a specific row, e.g. the one with the highest ID, the prefered approach is using the row_limiting_clause
SELECT *
FROM simpletable
ORDER BY record_id DESC
OFFSET 0 ROWS FETCH NEXT 1 ROW ONLY;
You will see the execution plan below, that performs first the INDEX FULL SCAN DESCENDING. The complete (full) index will be red in the descending order, but again due to STOPKEY you break after reading the highest key (which is the first entry due to the descending order).
---------------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
---------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 10188 | 19M| 613 (0)| 00:00:01 |
|* 1 | VIEW | | 10188 | 19M| 613 (0)| 00:00:01 |
|* 2 | WINDOW NOSORT STOPKEY | | 10188 | 19M| 613 (0)| 00:00:01 |
| 3 | TABLE ACCESS BY INDEX ROWID| SIMPLETABLE | 10188 | 19M| 613 (0)| 00:00:01 |
| 4 | INDEX FULL SCAN DESCENDING| SYS_C008793 | 10188 | | 29 (0)| 00:00:01 |
---------------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
1 - filter("from$_subquery$_002"."rowlimit_$$_rownumber"<=CASE WHEN (0>=0) THEN
0 ELSE 0 END +1 AND "from$_subquery$_002"."rowlimit_$$_rownumber">0)
2 - filter(ROW_NUMBER() OVER ( ORDER BY
INTERNAL_FUNCTION("SIMPLETABLE"."RECORD_ID") DESC )<=CASE WHEN (0>=0) THEN 0 ELSE 0
END +1)
Note if the table is empty or contains very few rows, you will se even here a TABLE ACCESS FULL because the optimizer recognises that it is more effective that to first go to the index and that access the table.
I'm making a proof of concept and I'm experimenting a strange behaviour.
I have a table partitioned by range by a date field and the cost of a query changes a lot if I set a fixed date or one created by SYSDATE.
These are the explain plans:
SQL> SELECT *
2 FROM TP_TEST_ELEMENTO_TRAZABLE ET
3 WHERE ET.FEC_RECEPCION
4 BETWEEN TRUNC(SYSDATE-2) AND TRUNC(SYSDATE-1)
5 ;
5109 filas seleccionadas.
Plan de Ejecuci¾n
----------------------------------------------------------
Plan hash value: 1151442660
------------------------------------------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | Pstart| Pstop |
------------------------------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 5008 | 85136 | 4504 (8)| 00:00:55 | | |
|* 1 | FILTER | | | | | | | |
| 2 | PARTITION RANGE ITERATOR| | 5008 | 85136 | 4504 (8)| 00:00:55 | KEY | KEY |
|* 3 | TABLE ACCESS FULL | TP_TEST_ELEMENTO_TRAZABLE | 5008 | 85136 | 4504 (8)| 00:00:55 | KEY | KEY |
------------------------------------------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
1 - filter(TRUNC(SYSDATE#!-2)<=TRUNC(SYSDATE#!-1))
3 - filter("ET"."FEC_RECEPCION">=TRUNC(SYSDATE#!-2) AND "ET"."FEC_RECEPCION"<=TRUNC(SYSDATE#!-1))
EstadÝsticas
----------------------------------------------------------
1 recursive calls
0 db block gets
376 consistent gets
0 physical reads
0 redo size
137221 bytes sent via SQL*Net to client
4104 bytes received via SQL*Net from client
342 SQL*Net roundtrips to/from client
0 sorts (memory)
0 sorts (disk)
5109 rows processed
Using fixed dates:
SQL> SELECT *
2 FROM TP_TEST_ELEMENTO_TRAZABLE ET
3 WHERE ET.FEC_RECEPCION
4 BETWEEN TO_DATE('26/02/2017', 'DD/MM/YYYY') AND TO_DATE('27/02/2017', 'DD/MM/YYYY')
5 ;
5109 filas seleccionadas.
Plan de Ejecuci¾n
----------------------------------------------------------
Plan hash value: 3903280660
-----------------------------------------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | Pstart| Pstop |
-----------------------------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 5008 | 85136 | 11 (0)| 00:00:01 | | |
| 1 | PARTITION RANGE ITERATOR| | 5008 | 85136 | 11 (0)| 00:00:01 | 607 | 608 |
|* 2 | TABLE ACCESS FULL | TP_TEST_ELEMENTO_TRAZABLE | 5008 | 85136 | 11 (0)| 00:00:01 | 607 | 608 |
-----------------------------------------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
2 - filter("ET"."FEC_RECEPCION"<=TO_DATE(' 2017-02-27 00:00:00', 'syyyy-mm-dd hh24:mi:ss'))
EstadÝsticas
----------------------------------------------------------
1 recursive calls
0 db block gets
376 consistent gets
0 physical reads
0 redo size
137221 bytes sent via SQL*Net to client
4104 bytes received via SQL*Net from client
342 SQL*Net roundtrips to/from client
0 sorts (memory)
0 sorts (disk)
5109 rows processed
What's the difference that produces a cost of 4504 and a cost of 11?
Thanks in advance :)
The difference is because when you use SYSDATE, it has the potential to need any partition. For example, if you are daily partitioned, then the partition you need to access will be different between today and tomorrow. As such, the plan is KEY:KEY, meaning that the actual partition is resolved at runtime.
With a fixed date, we know at compile time which partition it resolves to. And since it resolves to a single partition, it's more "accurately" costed.
I have two queries which return the same result set, but when reviewing the execution plans they have different values of cardinality.
The queries are:
select acq_cod
, prp
, df_val
, descr
from acqdefprp
where (prp like '%pswd%' or prp like '%Pswd%')
and prp not like '%kno%'
and prp not like '%encr%';
and
select acq_cod
, prp
, df_val
, descr
from acqdefprp
where regexp_instr(prp, 'pswd', 1,1,0,'i' ) > 0
and regexp_instr(prp, '(encr)|(kno)', 1,1,0,'i' ) = 0;
The first query has the following explain plan:
--------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
--------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 65 | 4485 | 6 (0)| 00:00:01 |
|* 1 | TABLE ACCESS FULL| acqdefprp | 65 | 4485 | 6 (0)| 00:00:01 |
--------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
1 - filter(("PRP" LIKE '%pswd%' OR "PRP" LIKE '%Pswd%')
AND "PRP" NOT LIKE '%kno%'
AND "PRP" NOT LIKE '%encr%')
And the explain plan for the second query is:
--------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
--------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 69 | 6 (0)| 00:00:01 |
|* 1 | TABLE ACCESS FULL| acqdefprp | 1 | 69 | 6 (0)| 00:00:01 |
--------------------------------------------------------------------------------
1 - filter(REGEXP_INSTR ("PRP",'(encr)|(kno)',1,1,0,'i') = 0
AND REGEXP_INSTR ("PRP",'pswd',1,1,0,'i') > 0 )
My question is why is the cardinality different between the two execution plans? For the first plan the cardinality (rows) is 65 and for the second it's 1?
My assumption is that this cardinality is the maximum number of rows that will be returned by each condition, if each condition was evaluated separately, and all of this based on table statistics. And that is why for my first query this assumed maximum is 65, since the WHERE conditions are a little more permissive.
And also that is why for the second query the cardinality is 1, since the regexp_instr is more restrictive.
If my assumptions are not correct, I'd really like to know what determines this cardinality number.
Thank you in advance for any help
In your case the expression are too complex for the optimizer to use basic statistics to estimate the cardinality. In these cases (it doesn't seem that you use histograms that might affect LIKE predicates) a fixed selectivity is used:
equality operator: 1%
inequality operator: 5%
So your
LIKE example is approximately (5 % + 5 % - (5 % * 5 %)) * 95 % * 95 % => 8.8 % of total table rows. - (5 % * 5 %) is the intersection because of OR operator.
REGEX example is 1 % * 5 % => 0.05 % of total table rows.
Oracle also supports extended statistics where you can compute statistics and histograms for specific expressions or correlated columns.
You comapare plans with direct WHERE conditions and with REGEXP_INSTR functions. Actually there is no difference which function to use, for oracle very difficult to give a real estimate without function execution.
For example we can create function -
CREATE OR REPLACE FUNCTION f_check(str IN VARCHAR2)
RETURN NUMBER IS
BEGIN
IF str LIKE 'A%' THEN
RETURN 1;
END IF;
RETURN -1;
END;
/
First select -
SELECT *
FROM tmptxt
WHERE dsc LIKE 'A%'
Plan hash value: 2928917536
----------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
----------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 121 | 4356 | 4 (0)| 00:00:01 |
|* 1 | TABLE ACCESS FULL| TMPTXT | 121 | 4356 | 4 (0)| 00:00:01 |
----------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
1 - filter("DSC" LIKE 'A%')
and with function -
SELECT *
FROM tmptxt
WHERE f_check(dsc) = 1
Plan hash value: 2928917536
----------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
----------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 36 | 4 (0)| 00:00:01 |
|* 1 | TABLE ACCESS FULL| TMPTXT | 1 | 36 | 4 (0)| 00:00:01 |
----------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
1 - filter("F_CHECK"("DSC")=1)
This two queries give the same result, but plan estimate has some difference. It is not too important (fullscan in first way and fullscan in the second), just need to evaluate the whole plan, didn't dwell on the numbers.
My assumption is that this cardinality is the maximum number of rows that will be returned by each condition....
No, cardinality is the estimation of the CBO how many rows will be returned in the operation. (technicaly always >= 1).
The cardinality is calculated either from the object statistics stored in data dictionary or by dynaming sampling (details here).
Dynamic sampling are more costly (as they are calculated in each parse) but can return much precise results.
So one possible workaround to get better estimation is to use dynamic sampling. Here small demo with level 10 (which is extrem and demo only as the whole table is scanned in parsing step; but it is not a problem with 779 rows table and the cardinatlity is exact)
create table tst as
select ltrim(to_char(rownum,'09999')) prp from dual connect by level <= 999999;
select count(*) from tst where prp like '%999%';
280
select count(*) from tst where regexp_instr(prp, '999', 1,1,0,'i' ) > 0;
280
Alter session set optimizer_dynamic_sampling=10;
EXPLAIN PLAN SET STATEMENT_ID = 'jara1' into plan_table FOR
select * from tst where prp like '%999%';
SELECT * FROM table(DBMS_XPLAN.DISPLAY('plan_table', 'jara1','ALL'));
--------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
--------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 280 | 1400 | 467 (2)| 00:00:06 |
|* 1 | TABLE ACCESS FULL| TST | 280 | 1400 | 467 (2)| 00:00:06 |
--------------------------------------------------------------------------
1 - filter("PRP" IS NOT NULL AND "PRP" LIKE '%999%')
EXPLAIN PLAN SET STATEMENT_ID = 'jara1' into plan_table FOR
select * from tst where regexp_instr(prp, '999', 1,1,0,'i' ) > 0;
SELECT * FROM table(DBMS_XPLAN.DISPLAY('plan_table', 'jara1','ALL'));
--------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
--------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 280 | 1400 | 479 (5)| 00:00:06 |
|* 1 | TABLE ACCESS FULL| TST | 280 | 1400 | 479 (5)| 00:00:06 |
--------------------------------------------------------------------------
1 - filter( REGEXP_INSTR ("PRP",'999',1,1,0,'i')>0)
There is example of using a function-based indexes in the documentation Concepts Oracle 11G:
A function-based index is also useful for indexing only specific rows
in a table. For example, the cust_valid column in the sh.customers
table has either I or A as a value. To index only the A rows, you
could write a function that returns a null value for any rows other
than the A rows.
I can imagine only this use case: the reducing size of index, by eliminating some rows by condition. Is there other use cases when this possibility is useful?
Let's take a look at function-based indexes:
SQL> create table tab1 as select object_name from all_objects;
Table created.
SQL> exec dbms_stats.gather_table_stats(user, 'TAB1');
PL/SQL procedure successfully completed.
SQL> set autotrace traceonly
SQL> select count(*) from tab1 where lower(object_name) = 'all_tables';
Execution Plan
----------------------------------------------------------
Plan hash value: 1117438016
---------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
---------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 19 | 18 (0)| 00:00:01 |
| 1 | SORT AGGREGATE | | 1 | 19 | | |
|* 2 | TABLE ACCESS FULL| TAB1 | 181 | 3439 | 18 (0)| 00:00:01 |
---------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
2 - filter(LOWER("OBJECT_NAME")='all_tables')
Statistics
----------------------------------------------------------
1 recursive calls
0 db block gets
63 consistent gets
...
As you know, all the objects have unique names, but oracle has to analyze all 181 rows and performs 63 consistent gets (physical or logical block reads)
Let's create a function-based index:
SQL> create index tab1_obj_name_idx on tab1(lower(object_name));
Index created.
SQL> select count(*) from tab1 where lower(object_name) = 'all_tables';
Execution Plan
----------------------------------------------------------
Plan hash value: 707634933
---------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
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| 0 | SELECT STATEMENT | | 1 | 17 | 1 (0)| 00:00:01 |
| 1 | SORT AGGREGATE | | 1 | 17 | | |
|* 2 | INDEX RANGE SCAN| TAB1_OBJ_NAME_IDX | 181 | 3077 | 1 (0)| 00:00:01 |
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Predicate Information (identified by operation id):
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2 - access(LOWER("OBJECT_NAME")='all_tables')
Statistics
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1 recursive calls
0 db block gets
2 consistent gets
...
As you can see the cost cuts down (from 18 to 1) dramatically and there are only 2 consistent gets.
So function-based indexes can increase the performance of your application very well.