UPDATE table1
SET col1 = 'Y'
WHERE col2 in (select col2 from table2)
In the above query, imagine the inner query returns 10000 rows. Does this query with IN clause affect performance?
If so, what can be done for faster execution?
if the subquery returns a large number of rows compared to the number of rows in TABLE1, the optimizer will likely produce a plan like this:
--------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes |TempSpc| Cost (%CPU)| Time
--------------------------------------------------------------------------------
| 0 | UPDATE STATEMENT | | 300K| 24M| | 1581 (1)| 00:0
| 1 | UPDATE | TABLE1 | | | | |
|* 2 | HASH JOIN SEMI | | 300K| 24M| 9384K| 1581 (1)| 00:0
| 3 | TABLE ACCESS FULL| TABLE1 | 300K| 5860K| | 355 (2)| 00:0
| 4 | TABLE ACCESS FULL| TABLE2 | 168K| 10M| | 144 (2)| 00:0
--------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
2 - access("COL2"="COL2")
It will scan both tables once and update only the rows in TABLE1 common to both tables. This is a highly efficient plan if you need to update lots of rows.
Sometimes the inner query will have few rows compared to the number of rows in TABLE1. If you have an index on TABLE1(col2), you could then obtain a plan similar to this one:
-------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
-------------------------------------------------------------------------------
| 0 | UPDATE STATEMENT | | 93 | 4557 | 247 (1)| 00:00:03 |
| 1 | UPDATE | TABLE1 | | | | |
| 2 | NESTED LOOPS | | 93 | 4557 | 247 (1)| 00:00:03 |
| 3 | SORT UNIQUE | | 51 | 1326 | 142 (0)| 00:00:02 |
| 4 | TABLE ACCESS FULL| TABLE2 | 51 | 1326 | 142 (0)| 00:00:02 |
|* 5 | INDEX RANGE SCAN | IDX1 | 2 | 46 | 2 (0)| 00:00:01 |
-------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
5 - access("T1"."COL2"="T2"."COL2")
In that case Oracle will read the rows from TABLE2 and for each (unique) row, perform an index access on TABLE1.
Which access is faster depend upon the selectivity of the inner query and the clustering of the index on TABLE1 (are the rows with similar value of col2 in TABLE1 next to each other or randomly spread?). In any case, performance wise, if you need to perform this update this query is one of the fastest way to do it.
UPDATE table1 outer
SET col1 = 'Y'
WHERE EXISTS (select null
from table2
WHERE col2 = outer.col2)
This could be better
To get the idea which is better - look at the execution plan.
From Oracle:
11.5.3.4 Use of EXISTS versus IN for Subqueries
In certain circumstances, it is better
to use IN rather than EXISTS. In
general, if the selective predicate is
in the subquery, then use IN. If the
selective predicate is in the parent
query, then use EXISTS.
From my experience, I have seen better plans using EXISTS where subquery returns large amount of rows.
See here for more discussion from Oracle
Related
My Oracle query takes over 1.5 min and I do not know if it's because of inefficient query writing, bad choice of indexes or some other database issue that I cannot control.
Some tables and data were changed to protect IP.
SELECT /*+ PARALLEL (AUTO) */ COUNT(DISTINCT SUD_USERID)
FROM (
SELECT /*+ PARALLEL (AUTO) */
SUD_USERID ,
CASE WHEN SCH_PAGETYPE = 'Page' AND SUD_EVENTTYPE = 'S'
THEN 'EVENTTYPE1'
WHEN SCH_PAGETYPE = 'Page' AND SUD_EVENTTYPE = 'V'
THEN 'EVENTTYPE2'
WHEN SCH_PAGETYPE = 'Hub' AND SUD_EVENTTYPE = 'S'
THEN 'EVENTTYPE3'
END AS CALC_EVENT_SOURCE,
SUD_EVENT_SOURCE
FROM
(
SELECT /*+ PARALLEL (AUTO) */
UPPER(PAGETYPE)|| '-' || SCH.ID PAGETYPE_ID ,
SCH.PAGETYPE SCH_PAGETYPE
FROM TABLE1 SCH
WHERE SCH.PAGETYPE IN ('Page', 'Hub')
AND SCH.CATEGORY_NAME NOT IN ('archive', 'testcategory')
)
INNER JOIN (
SELECT /*+ PARALLEL (AUTO) */
DISTINCT SUD.TRACEID TRACEID ,
SUD.EVENTTYPE SUD_EVENTTYPE ,
SUD.USERID SUD_USERID,
SUD.EVENT_SOURCE SUD_EVENT_SOURCE
FROM
SOMESCHEMA.USAGE_DETAILS SUD
WHERE
SUD.EVENTTYPE IN ('S', 'V')
)
ON TRACEID = PAGETYPE_ID
INNER JOIN USER_JOB_FAMILY_MAPPING SFD
ON SUD_USERID = SFD.USERID
)
WHERE CALC_EVENT_SOURCE = SUD_EVENT_SOURCE
I could not copy the text of the explain plan (generated via DBeaver)
but here is a screenshot:
USAGE_DETAILS table has 3941810 rows
TABLE1 has 5908 rows
USER_JOB_FAMILY_MAPPING has 578233 rows
There are no keys on any of these tables.
USAGE_DETAILS.TRACEID is VARCHAR2(500) NOT NULL has function index=SUBSTR("TRACEID",1,4) and
another index declared as default but on that column.
USAGE_DETAILS.USERID is VARCHAR2(50) NOT NULL
USAGE_DETAILS.EVENTTYPE is VARCHAR2(10) NOT NULL and has default index
USAGE_DETAILS.EVENT_SOURCE is VARCHAR2(200) NOT NULL and has default index
I have tried doing inner joins on the full tables rather than the parenthetically generated (subselect?) tables, but that did not perform better and also limited my ability to use an alias in the WHERE clause.
I do not know what kind of machine this is running on, just that it's set up for development. I'd like this query to give me accurate answers in under 10s. Some times the query above though still does not return even after 10+ minutes.
Plan hash value: 2784166315
-----------------------------------------------------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes |TempSpc| Cost (%CPU)| Time |
-----------------------------------------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 27 | | 258K (1)| 00:00:11 |
| 1 | SORT AGGREGATE | | 1 | 27 | | | |
| 2 | VIEW | VM_NWVW_1 | 1809K| 46M| | 258K (1)| 00:00:11 |
| 3 | HASH GROUP BY | | 1809K| 745M| | 258K (1)| 00:00:11 |
|* 4 | HASH JOIN | | 1809K| 745M| | 258K (1)| 00:00:11 |
|* 5 | TABLE ACCESS FULL | TABLE1S | 5875 | 172K| | 309 (0)| 00:00:01 |
| 6 | MERGE JOIN SEMI | | 3079K| 1180M| | 257K (1)| 00:00:11 |
| 7 | SORT JOIN | | 3079K| 1139M| | 254K (1)| 00:00:10 |
| 8 | VIEW | | 3079K| 1139M| | 254K (1)| 00:00:10 |
| 9 | HASH UNIQUE | | 3079K| 1139M| 1202M| 254K (1)| 00:00:10 |
| 10 | INLIST ITERATOR | | | | | | |
| 11 | TABLE ACCESS BY INDEX ROWID BATCHED| USAGE_DETAILS | 3079K| 1139M| | 46 (0)| 00:00:01 |
|* 12 | INDEX RANGE SCAN | IDX_UUD_EVENTTYPE | 13704 | | | 46 (0)| 00:00:01 |
|* 13 | SORT UNIQUE | | 578K| 7905K| 22M| 3558 (1)| 00:00:01 |
| 14 | INDEX FAST FULL SCAN | USERID_IDX | 578K| 7905K| | 704 (1)| 00:00:01 |
-----------------------------------------------------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
4 - access("TRACEID"=UPPER("PAGETYPE")||'-'||TO_CHAR("SCH"."ID"))
filter("from$_subquery$_004"."SUD_EVENT_SOURCE"=CASE WHEN (("SCH"."PAGETYPE"='Page') AND
("from$_subquery$_004"."SUD_EVENTTYPE"='S')) THEN 'EVENTTYPE1' WHEN (("SCH"."PAGETYPE"='Page') AND
("from$_subquery$_004"."SUD_EVENTTYPE"='V')) THEN 'EVENTTYPE2' WHEN (("SCH"."PAGETYPE"='Hub') AND
("from$_subquery$_004"."SUD_EVENTTYPE"='S')) THEN 'EVENTTYPE3' END )
5 - filter("SCH"."CATEGORY_NAME"<>'archive' AND "SCH"."CATEGORY_NAME"<>'testcategory' AND ("SCH"."PAGETYPE"='Hub' OR
"SCH"."PAGETYPE"='Page'))
12 - access("SUD"."EVENTTYPE"='S' OR "SUD"."EVENTTYPE"='V')
13 - access("from$_subquery$_004"."SUD_USERID"="SFD"."USERID")
filter("from$_subquery$_004"."SUD_USERID"="SFD"."USERID")
Note
-----
- dynamic statistics used: dynamic sampling (level=2)
- automatic DOP: Computed Degree of Parallelism is 1 because of no expensive parallel operation
After running
exec dbms_stats.gather_table_stats(ownname=>'SCHEMA1',tabname=>'USAGE_DETAILS');
exec dbms_stats.gather_table_stats(ownname=>'SCHEMA1',tabname=>'TABLE1');
I have this new plan:
SQL> select plan_table_output from table(dbms_xplan.display());
Plan hash value: 3419946982
----------------------------------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes |TempSpc| Cost (%CPU)| Time |
----------------------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 27 | | 70152 (1)| 00:00:03 |
| 1 | SORT AGGREGATE | | 1 | 27 | | | |
| 2 | VIEW | VM_NWVW_1 | 53144 | 1401K| | 70152 (1)| 00:00:03 |
| 3 | HASH GROUP BY | | 53144 | 21M| 21M| 70152 (1)| 00:00:03 |
|* 4 | HASH JOIN RIGHT SEMI | | 53144 | 21M| 14M| 65453 (1)| 00:00:03 |
| 5 | INDEX FAST FULL SCAN | USERID_IDX | 578K| 7905K| | 704 (1)| 00:00:01 |
|* 6 | HASH JOIN | | 53144 | 20M| | 62995 (1)| 00:00:03 |
| 7 | JOIN FILTER CREATE | :BF0000 | 5503 | 161K| | 309 (0)| 00:00:01 |
|* 8 | TABLE ACCESS FULL | TABLE1 | 5503 | 161K| | 309 (0)| 00:00:01 |
| 9 | VIEW | | 3549K| 1259M| | 62677 (1)| 00:00:03 |
| 10 | HASH UNIQUE | | 3549K| 159M| 203M| 62677 (1)| 00:00:03 |
| 11 | JOIN FILTER USE | :BF0000 | 3549K| 159M| | 21035 (1)| 00:00:01 |
|* 12 | TABLE ACCESS FULL| USAGE_DETAILS | 3549K| 159M| | 21035 (1)| 00:00:01 |
----------------------------------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
4 - access("from$_subquery$_004"."SUD_USERID"="SFD"."USERID")
6 - access("TRACEID"=UPPER("PAGETYPE")||'-'||TO_CHAR("SCH"."ID"))
filter("from$_subquery$_004"."SUD_EVENT_SOURCE"=CASE WHEN (("SCH"."PAGETYPE"='Page') AND
("from$_subquery$_004"."SUD_EVENTTYPE"='S')) THEN 'EVENTTYPE1' WHEN (("SCH"."PAGETYPE"='Page') AND
("from$_subquery$_004"."SUD_EVENTTYPE"='V')) THEN 'EVENTTYPE2' WHEN (("SCH"."PAGETYPE"='Hub') AND
("from$_subquery$_004"."SUD_EVENTTYPE"='S')) THEN 'EVENTTYPE3' END )
8 - filter("SCH"."CATEGORY_NAME"<>'archive' AND "SCH"."CATEGORY_NAME"<>'testcategory' AND
("SCH"."PAGETYPE"='Hub' OR "SCH"."PAGETYPE"='Page'))
12 - filter(("SUD"."EVENTTYPE"='S' OR "SUD"."EVENTTYPE"='V') AND
SYS_OP_BLOOM_FILTER(:BF0000,"SUD"."TRACEID"))
Note
-----
- automatic DOP: Computed Degree of Parallelism is 1 because of no expensive parallel operation
37 rows selected.
Is it more likely that the compute statistics massively helped this query or that someone did something else that I was not aware of? Yes, the query ran much better, but I'd feel better too if I knew why.
Hy,
after reviewing your SQL I noticed your statements are full of string comparisons and searches. For example
SELECT /*+ PARALLEL (AUTO) */
UPPER(PAGETYPE)|| '-' || SCH.ID PAGETYPE_ID ,
SCH.PAGETYPE SCH_PAGETYPE
FROM TABLE1 SCH
WHERE SCH.PAGETYPE IN ('Page', 'Hub')
AND SCH.CATEGORY_NAME NOT IN ('archive', 'testcategory')
This can be indexed int 2 ways.
First: Create table that has 'Page', 'Hub', and other types that you need, create for the a column Index and then "replace" basically adapt your query to resolve those indexes instead of string compare.
Tables can have multiple indices on columns those have to be treated with caution because they create problems in regards of database size.
Also I would check if what are the biggest tables and reorder their selections to the last. Meaning:
if one table has 12 rows and the other 100. First put the 12 row table then the 100 row. This will multiply in your case since the tables and nested and chained.
I made 1 more review and realized I made an oversight.
USAGE_DETAILS table has 3941810 rows
TABLE1 has 5908 rows
USER_JOB_FAMILY_MAPPING has 578233 rows
First filter the table 1, this is costly already, then Inner join raw USAGE_DETAILS and then select the join ID-s.
Then inner join USER_JOB_FAMILY_MAPPING, and select after that. The reason is that the joins are done on the ID which is probably int type.
Gather statistics on the relevant objects like this:
begin
dbms_stats.gather_table_stats(ownname => user, tabname => 'TABLE1');
dbms_stats.gather_table_stats(ownname => 'SOMESCHEMA', tabname => 'USAGE_DETAILS');
end;
/
This line in the execution plan implies that one of the tables is missing statistics:
- dynamic statistics used: dynamic sampling (level=2)
Not all uses of dynamic sampling imply missing statistics, but level 2 is highly suspicious. That sampling level is usually intended to "Apply dynamic sampling to all unanalyzed tables."
Optimizer statistics are necessary for Oracle to make good execution plans. The algorithms and access paths for joining small amounts of data are different than the algorithms and access paths for joining large amounts of data. The optimizer statistics help Oracle estimate the size of the results and build good plans.
If this solves your problem, you should also investigate the root cause. Optimizer statistics should always be gathered manually after a large change, and automatically by the system every night. If you have a large ETL process that significantly changes a table, it should include a call to DBMS_STATS at the end. The database by default gathers stats at 10PM every night, unless a DBA foolishly disabled the autotask.
If that doesn't solve the problem, then regenerate the execution plan with actual numbers using DBMS_SQLTUNE or the GATHER_PLAN_STATISTICS_HINT. SQL tuning is about optimizing the operations. Your SQL statement has 14 operations, each of which is like a miniature program. We need to know which one of the operations is causing the problem. Finding actual cardinalities and actual run times, and comparing them to estimates, helps tremendously with diagnosing SQL problems.
How do we know that gathering stats was what fixed the performance?
We can't be 100% sure. But it's a safe bet that gathering statistics was responsible for the improvement, for several reasons.
Bad or missing statistics are responsible for a large percentage of all Oracle performance problems. Ask any DBA and they'll have plenty of stories about missing statistics.
The Note section changes strongly imply there are no other weird things happening behind the scenes. There are lots of tricks to silently fix queries, like SQL profiles, baselines, adaptive reoptimization, dynamic sampling (shows up in the first plan, but not the second one, because stats are better), etc. But if those tricks were used they would show up in the Note section.
I'm joining a table with itself but although I expect this operation to use index, it seems it doesn't. There are 1 million records on the table(MY_TABLE) and the query I run is executing on about 10 thousand records.(So it is lower than %1 of whole table.)
Test Case:
explain plan for
SELECT *
FROM SCHM.MY_TABLE A1, SCHM.MY_TABLE A2
WHERE (A1.K_ID = '123abc')
AND A1.HDT = A2.HDT
AND A2.C_DATE BETWEEN A1.SYSDATE - 0.0004
AND A1.SYSDATE + 0.0004
AND A1.GKID = A2.GKID;
Plan hash value: 1210306805
----------------------------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
----------------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 3 | 81 | 28 (0)| 00:00:01 |
|* 1 | FILTER | | | | | |
|* 2 | HASH JOIN | | 3 | 81 | 28 (0)| 00:00:01 |
| 3 | TABLE ACCESS BY INDEX ROWID BATCHED| MY_TABLE | 3 | 45 | 7 (0)| 00:00:01 |
|* 4 | INDEX RANGE SCAN | IX_MY_TABLE_C_DATE | 3 | | 4 (0)| 00:00:01 |
| 5 | TABLE ACCESS BY INDEX ROWID BATCHED| MY_TABLE | 17 | 204 | 21 (0)| 00:00:01 |
|* 6 | INDEX RANGE SCAN | IX_MY_TABLE_K_ID | 17 | | 4 (0)| 00:00:01 |
----------------------------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
1 - filter(SYSDATE#!+0.00004>=SYSDATE#!-0.00004)
2 - access("A1"."HDT"="A2"."HDT" AND
"A1"."GKID"="A2"."GKID")
4 - access("A2"."C_DATE">=SYSDATE#!-0.00004 AND
"A2"."C_DATE"<=SYSDATE#!+0.00004)
6 - access("A1"."K_ID"=U'123abc')
In the above statement, it can be seen that the index on C_DATE is used.
However, in the below statement, the index on C_DATE is not used. So, the query runs really slow.
Real Case:
explain plan for
SELECT *
FROM SCHM.MY_TABLE A1, SCHM.MY_TABLE A2
WHERE (A1.K_ID = '123abc')
AND A1.HDT = A2.HDT
AND A2.C_DATE BETWEEN A1.C_DATE - 0.0004
AND A1.C_DATE + 0.0004
AND A1.GKID = A2.GKID;
Plan hash value: 1063167343
----------------------------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
----------------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 4187K| 998M| 6549K (1)| 00:04:16 |
|* 1 | HASH JOIN | | 4187K| 998M| 6549K (1)| 00:04:16 |
| 2 | JOIN FILTER CREATE | :BF0000 | 17 | 2125 | 21 (0)| 00:00:01 |
| 3 | TABLE ACCESS BY INDEX ROWID BATCHED| MY_TABLE | 17 | 2125 | 21 (0)| 00:00:01 |
|* 4 | INDEX RANGE SCAN | IX_MY_TABLE_K_ID | 17 | | 4 (0)| 00:00:01 |
| 5 | JOIN FILTER USE | :BF0000 | 1429M| 166G| 6546K (1)| 00:04:16 |
|* 6 | TABLE ACCESS STORAGE FULL | MY_TABLE | 1429M| 166G| 6546K (1)| 00:04:16 |
----------------------------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
1 - access(A1.HDT=A2.HDT AND
A1.GKID=A2.GKID)
filter(A2.C_DATE>=INTERNAL_FUNCTION(A1.C_DATE)-0.00004 AND
A2.C_DATE<=INTERNAL_FUNCTION(A1.C_DATE)+0.00004)
4 - access(A1.K_ID=U'123abc')
6 - storage(SYS_OP_BLOOM_FILTER(:BF0000,A2.HDT,A2.HDT))
filter(SYS_OP_BLOOM_FILTER(:BF0000,A2.HDT,A2.HDT))
If I use the hint /*+index(A2,IX_MY_TABLE_C_DATE )*/, everthing is fine, the index is used and the query runs fast as I want.
The query in the real case cannot be changed because it is created by application.
Index Information:
K_ID, not unique, position 1
HDT, not unique, position 1
C_DATE, not unique, position 1
ID Unique and Primary Key, position 1
What do I have to change in order the query in the real case to use index?
Well, the second query is slower since it's quite different from the first one. It has an extra join between tables:
AND A2.C_DATE BETWEEN A1.C_DATE - 0.0004
AND A1.C_DATE + 0.0004
and on a million rows this takes a toll.
The first query doesn't have this join condition and both tables are:
Filtered first. This is fast using indexes: only 3 rows and 17 rows.
Joining them second. Joining 3 and 17 rows doesn't take any time.
The second query needs to perform:
A huge (hash) join first, that returns probably 100K+ rows.
A filtering later.
This is way slower.
I suggest adding the following indexes, and try again:
create index ix_1 (k_id);
create index ix_2 (hdt, gkid, c_date);
You have three join criteria (HDT, GKID, C_DATE) and 1 non-join criteria (K_ID) in your self-join. So for me it would seem natural, if the DBMS started with the records matching K_ID and then looked up all matching other records.
For this case I'd suggest the following indexes:
create index idx1 on my_table(k_id, hdt, gkid, c_date);
create index idx2 on my_table(hdt, gkid, c_date);
If there are just few records per k_id, I am sure that Oracle will use the indexes. If there are many, Oracle may still use the second one for a hash join.
Just to add, whenever you have a case where you
have a slow SQL,
have identified a hint that would make it
faster
cannot change the SQL because the source is not available
then this is a perfect case for SQL Plan Baselines. These let you lock a "good" plan against an existing SQL without touching the SQL statement itself.
The entire series describing SPM is at the links below, but thelinke to "part 4" walks through an exact example of what you want to achieve.
https://blogs.oracle.com/optimizer/sql-plan-management-part-1-of-4-creating-sql-plan-baselines
https://blogs.oracle.com/optimizer/sql-plan-management-part-2-of-4-spm-aware-optimizer
https://blogs.oracle.com/optimizer/sql-plan-management-part-3-of-4:-evolving-sql-plan-baselines
https://blogs.oracle.com/optimizer/sql-plan-management-part-4-of-4:-user-interfaces-and-other-features
Following this question, suppose now I've set up the indexes, and now I want only to return certain field, without duplicates:
Select distinct A.cod
from A join B
on A.id1=B.id1 and
A.id2=B.id2
where A.year=2016
and B.year=2016
the problem now is I'm getting something like 150k cod, with only 1000 distinct values, so my query is very inefficient.
Question: how can I improve that? i.e, how can I tell the DB, for every row on A, to stop joining that row as soon as a match is found?
Thank you in advance!
I'm basing my answer on your question:
how can I tell the DB, for every row on A, to stop joining that row as soon as a match is found?
with the EXISTS clause, once it sees a match it will stop and check for the next record to be checked.
adding the DISTINCT will filter out any duplicate CODs (in case there is one).
select DISTINCT cod
from A ax
where year = 2016
and exists ( select 1
from B bx
WHERE Ax.ID1 = Bx.ID1
AND Ax.ID2 = Bx.ID2
AND Ax.YEAR = Bx.YEAR);
EDIT: Was curious which solution (IN or EXISTS) will give me a better Explain plan
Create the 1st Table Definition
Create table A
(
ID1 number,
ID2 number,
cod varchar2(100),
year number
);
insert 4000000 sequential numbers
BEGIN
FOR i IN 1..4000000 loop
insert into A (id1, id2, cod, year)
values (i, i , i, i);
end loop;
END;
commit;
Create Table B and insert the same data into to it
Create table B
as
select *
from A;
Reinsert Data from Table A to make duplicates
insert into B
select *
from A
Build the Indexes mentioned in the Previous Post Index on join and where
CREATE INDEX A_IDX ON A(year, id1, id2);
CREATE INDEX B_IDX ON B(year, id1, id2);
Update a bunch of rows to make it fetch multiple rows with the year 2016:
update B
set year = 2016
where rownum < 20000;
update A
set year = 2016
where rownum < 20000;
commit;
Check Explain plan using EXISTS
Plan hash value: 1052726981
----------------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
----------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 44 | 7 (15)| 00:00:01 |
| 1 | HASH UNIQUE | | 1 | 44 | 7 (15)| 00:00:01 |
| 2 | NESTED LOOPS SEMI | | 1 | 44 | 6 (0)| 00:00:01 |
| 3 | TABLE ACCESS BY INDEX ROWID| A | 1 | 26 | 4 (0)| 00:00:01 |
|* 4 | INDEX RANGE SCAN | A_IDX | 1 | | 3 (0)| 00:00:01 |
|* 5 | INDEX RANGE SCAN | B_IDX | 2 | 36 | 2 (0)| 00:00:01 |
----------------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
4 - access("YEAR"=2016)
5 - access("BX"."YEAR"=2016 AND "AX"."ID1"="BX"."ID1" AND "AX"."ID2"="BX"."ID2")
filter("AX"."YEAR"="BX"."YEAR")
Check Explain plan using IN
Plan hash value: 3002464630
----------------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
----------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 44 | 7 (15)| 00:00:01 |
| 1 | HASH UNIQUE | | 1 | 44 | 7 (15)| 00:00:01 |
| 2 | NESTED LOOPS | | 1 | 44 | 6 (0)| 00:00:01 |
| 3 | TABLE ACCESS BY INDEX ROWID| A | 1 | 26 | 4 (0)| 00:00:01 |
|* 4 | INDEX RANGE SCAN | A_IDX | 1 | | 3 (0)| 00:00:01 |
|* 5 | INDEX RANGE SCAN | B_IDX | 1 | 18 | 2 (0)| 00:00:01 |
----------------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
4 - access("YEAR"=2016)
5 - access("YEAR"=2016 AND "ID1"="ID1" AND "ID2"="ID2")
Although my test case is limited, i'm guessing that both the IN and EXISTS clause have nearly the same execution.
On the face of it, what you are actually trying to do should be done like this:
select distinct cod
from A
where year = 2016
and (id1, id2) in (select id1, id2 from B where year = 2016)
The subquery in the WHERE condition is a non-correlated query, so it will be evaluated only once. And the IN condition is evaluated using short-circuiting; instead of a complete join, it will search through the results of the subquery only until a match is found.
EDIT: As Migs Isip points out, there may be duplicate codes in the original table, so a "distinct" may still be needed. I edited my code to add it back after Migs posted his answer.
Not sure about your existing indexes but you can improve your query a bit by adding another JOIN condition like
Select distinct A.cod
from A join B
on A.id1=B.id1 and
A.id2=B.id2 and
A.year = B.year // this one
where A.year=2016;
I have a query that is taking 10 secs of time to run currently(about 300 lines). Now I add a where condition table_a.column_a ='XXX' like in the below query. The amount of time it takes to run it now has increased to 300 secs.
When I ran the explain plan. I see that this new where condition has some impact, looks like a sort operation(plan result below). I did not mention sort anywhere in the sql. Why is this piece so significant?
QUERY:
SELECT * from TABLE_A,TABLE_B WHERE TABLE_A.ID = TABLE_B.SOMEID AND TABLE_A.COLUMN_A='XXX';
EXPLAINPLAN RESULT:(REMOVED THE UNNECESSARY PART)
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
| 0 | SELECT STATEMENT | | 1 | 2878 | 154 (2)| 00:00:02 |
--removed lines here--
| 124 | BUFFER SORT | | 1 | 24 | 126 (1)| 00:00:02 |
| 125 | TABLE ACCESS BY INDEX ROWID | TABLE_A | 1 | 24 | 3 (0)| 00:00:01 |
|*126 | INDEX RANGE SCAN | COLUMN_A | 1 | | 2 (0)| 00:00:01 |
It looks like the sort operation is in place to allow for an index scan for your where condition rather than a generally more expensive sequential scan. It could be that, in this instance, the sort plus index scan is more expensive than the sequential scan would be. You could try changing this behavior by dropping the operative index, or by using hints to dictate the access method.
I have two tables:
create table big( id number, name varchar2(100));
insert into big(id, name) select rownum, object_name from all_objects;
create table small as select id from big where rownum < 10;
create index big_index on big(id);
On these tables if I execute the following query:
select *
from big_table
where id like '45%'
or id in ( select id from small_table);
it always goes for a Full Table Scan.
Execution Plan
----------------------------------------------------------
Plan hash value: 2290496975
----------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
----------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 3737 | 97162 | 85 (3)| 00:00:02 |
|* 1 | FILTER | | | | | |
| 2 | TABLE ACCESS FULL| BIG | 74718 | 1897K| 85 (3)| 00:00:02 |
|* 3 | TABLE ACCESS FULL| SMALL | 1 | 4 | 3 (0)| 00:00:01 |
----------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
1 - filter("ID"=45 OR EXISTS (SELECT /*+ */ 0 FROM "SMALL" "SMALL"
WHERE "ID"=:B1))
3 - filter("ID"=:B1)
Are there any ways in which we can rewrite the Query So that it always goes for index Scan.
No, no and no.
You do NOT want it to use an index. Luckily Oracle is smarter than that.
ID is numeric. While it might have ID values of 45,450,451,452,4501,45004,4500003 etc, in the indexes these values will be scattered anywhere and everywhere. If you went with a condition such as ID BETWEEN 450 AND 459, then it may be worth using the index.
To use the index it would have to scan it all the way from top to bottom (converting each ID to a character to do the LIKE comparison). Then, for any match, it has to go off to get the NAME column.
It has decided that it is easier to and quicker to scan the table (which, with 75,000 rows isn't that big anyway) rather than mucking about going back and forth between the index and the table.
The others are right, you shouldn't use a numeric column like that.
However, it is actually, the OR <subquery> construct that is causing a (performance) problem in this case. I don't know if it is different in version 11, but up to version 10gr2, it causes a a filter operation with what is basically a nested loop with a correlated subquery. In your case, the use of a numeric column as a varchar also results in a full table scan.
You can rewrite your query like this:
select *
from big
where id like '45%'
union all
select *
from big
join small using(id)
where id not like '45%';
With your test case, I end up with a row count of 174000 rows in big and 9 small.
Running your query takes 7 seconds with 1211399 consistent gets.
Running my query 0,7 seconds and uses 542 consistent gets.
The explain plans for my query is:
--------------------------------------------------------------------
| Id | Operation | Name | Rows | Cost (%CPU)|
---------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 8604 | 154 (6)|
| 1 | UNION-ALL | | | |
|* 2 | TABLE ACCESS FULL | BIG | 8603 | 151 (4)|
| 3 | NESTED LOOPS | | 1 | 3 (0)|
|* 4 | TABLE ACCESS FULL | SMALL | 1 | 3 (0)|
| 5 | TABLE ACCESS BY INDEX ROWID| BIG | 1 | 0 (0)|
|* 6 | INDEX UNIQUE SCAN | BIG_PK | 1 | 0 (0)|
---------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
2 - filter(TO_CHAR("ID") LIKE '45%')
4 - filter(TO_CHAR("SMALL"."ID") NOT LIKE '45%')
6 - access("BIG"."ID"="SMALL"."ID")
Statistics
----------------------------------------------------------
1 recursive calls
0 db block gets
542 consistent gets
0 physical reads
0 redo size
33476 bytes sent via SQL*Net to client
753 bytes received via SQL*Net from client
76 SQL*Net roundtrips to/from client
0 sorts (memory)
0 sorts (disk)
1120 rows processed
Something like this might work:
select *
from big_table big
where id like '45%'
or exists ( select id from small_table where id = big.id);