I want to index this query clause -- note that the text is static.
SELECT * FROM tbl where flags LIKE '%current_step: complete%'
To re-iterate, the current_step: complete never changes in the query. I want to build an index that will effectively pre-calculate this boolean value, thereby preventing full table scans...
I would prefer not to add a boolean column to store the pre-calculated value as this would necessitate code changes in the application....
If you don't want to change the query, and it isn't just an issue of nor changing the data maintenance (in which case a virtual column and/or index would do the job), you could use a materialised view that applies the filter, and let query rewrite take case of using that instead of the real table. Which may well be overkill but is an option.
The original plan for a mocked-up version:
explain plan for
SELECT * FROM tbl where flags LIKE '%current_step: complete%';
select * from table(dbms_xplan.display);
--------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
--------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 2 | 60 | 3 (0)| 00:00:01 |
|* 1 | TABLE ACCESS FULL| TBL | 2 | 60 | 3 (0)| 00:00:01 |
--------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
1 - filter("FLAGS" IS NOT NULL AND "FLAGS" LIKE '%current_step:
complete%')
A materialised view that will only hold the records your query is interested in (this is a simple example but you'd need to decide how to refresh and add a log if needed):
create materialized view mvw
enable query rewrite as
SELECT * FROM tbl where flags LIKE '%current_step: complete%';
Now your query hits the materialised view, thanks to query rewrite:
explain plan for
SELECT * FROM tbl where flags LIKE '%current_step: complete%';
select * from table(dbms_xplan.display);
-------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
-------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 2 | 60 | 3 (0)| 00:00:01 |
| 1 | MAT_VIEW REWRITE ACCESS FULL| MVW | 2 | 60 | 3 (0)| 00:00:01 |
-------------------------------------------------------------------------------------
But any other query will still use the original table:
explain plan for
SELECT * FROM tbl where flags LIKE '%current_step: working%';
select * from table(dbms_xplan.display);
--------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
--------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 27 | 3 (0)| 00:00:01 |
|* 1 | TABLE ACCESS FULL| TBL | 1 | 27 | 3 (0)| 00:00:01 |
--------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
1 - filter("FLAGS" LIKE '%current_step: success%' AND "FLAGS" IS NOT
NULL)
Of course a virtual index would be simpler if you are allowed to modify the query...
A full text search index might be what you are looking for.
There are a few ways you can implement this:
Oracle has Oracle Text where you can define which type of full text index you want.
Lucene is a Java full text search framework.
Solr is a server product that provides full text search.
I would prefer not to add a boolean column to store the pre-calculated value as this would necessitate code changes in the application
There are two ways I can suggest :
1.
If you are on 11g and up, you could have a VIRTUAL COLUMN always generated as 1 when the value is complete else 0. All you need to do then :
select * from table where virtual_column = 1
To improve performance, you could have an index over it, which is equivalent to a function-based index.
2.
Update : Perhaps, I should be more clear with my second point : source
There are instances where Oracle will use an index to resolve a like with the pattern of '%text%'. If the query can be resolved without having to go back to the table (rowid lookup), the index may be chosen. Example:
select distinct first_nm from person where first_nm like '%EV%';
And in above case, Oracle will do an index fast full scan - a full scan of the smaller index.
Related
I created an index called Z7 and I want to use it in a SELECT statement like this:
SELECT * FROM Employees WITH (INDEX(Z7)) WHERE First_Name NOT LIKE ('J%');
But it shows me this error:
ORA-00933: SQL command not properly ended
Contrary to the LIKE predicate that can be resolved with a index range scan there is no index access path in Oracle that would implement a NOT LIKE that would need to do two range scans before and after your LIKE value.
Let's illustrate it in this setup with a table that has only one row satisfying your not like predicate.
create table Employees as
select 'J'||rownum as First_Name, lpad('x',1000,'y') pad from dual connect by level <= 10000
union all
select 'Xname', 'zzzzz' from dual;
create index Z7 on Employees (First_Name);
The query
SELECT * FROM Employees WHERE First_Name NOT LIKE ('J%');
performs as expected a FULL TABLE SCAN
-------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
-------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 37 | 37259 | 398 (1)| 00:00:01 |
|* 1 | TABLE ACCESS FULL| EMPLOYEES | 37 | 37259 | 398 (1)| 00:00:01 |
-------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
1 - filter("FIRST_NAME" NOT LIKE 'J%')
You may hint Oracle to use index as follows (note that your syntax FROM Employees WITH (INDEX(Z7)) WHERE is wrong and causing your error!)
SELECT /*+ index(Employees Z7) */ * FROM Employees WHERE First_Name NOT LIKE ('J%');
This will indeed cause the index usage, but not in the sence you probablly intended.
If you examines the execution plan you'll see the INDEX FULL SCAN, that means, Oracle walks through the complete index from A to Z, filter the entires in the index that are not like your predicates (see the FILTER in the plan below) and for the selected keys access the table.
So generally you'll be not happy with this plan for a large index as it will take substantially longer that the full table scan.
-------------------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
-------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 9433 | 9276K| 2912 (1)| 00:00:01 |
| 1 | TABLE ACCESS BY INDEX ROWID BATCHED| EMPLOYEES | 9433 | 9276K| 2912 (1)| 00:00:01 |
|* 2 | INDEX FULL SCAN | Z7 | 9433 | | 25 (0)| 00:00:01 |
-------------------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
2 - filter("FIRST_NAME" NOT LIKE 'J%')
See here how to produce the execution plan for the query
I am trying to optimize the performance of a query. The problem is:
Say we have view X. And it has attr A, B, C.
C is a calculated field.
Say I want to try to optimize by querying "Select A,B from X where A = 'some condition'" then if I need C I can calculate that later on with the much smaller subset of data to enhance performance.
My question is will this help? Or does an Oracle view calculate C anyways when I make the initial query, regardless of whether I am querying for that attr or not? Therefore to optimize I would have to remove these calculated from the view?
The short answer is yes it helps to select only the limited column list from a view - both in means of the CPU (value calculation) and storage.
In cases when it is possible Oracle optimizer completely eliminates the view definition and merges it in the underlining tables.
So the view columns not referenced in the query are not accessed at all.
Here a simple example
create table t as
select rownum a, rownum b, rownum c from dual
connect by level = 10;
create or replace view v1 as
select a, b, c/0 c from t;
I'm simulation the complex calculation with a zero divide to see if the value is caclulated at all.
The best way to check is to run the query and to see the execution plan
select a, b from v1
where a = 1;
--------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
--------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 26 | 3 (0)| 00:00:01 |
|* 1 | TABLE ACCESS FULL| T | 1 | 26 | 3 (0)| 00:00:01 |
--------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
1 - filter("A"=1)
Column Projection Information (identified by operation id):
-----------------------------------------------------------
1 - "A"[NUMBER,22], "B"[NUMBER,22]
In the Project Information is visible, that only columns A and B are refrenced - so no calculation on the C column is done.
Even the other way around work; if you first materialize the view and afterward you make the row filtering. I'm simulating it with the folowing query - not ethat teh MATERALIZE hint materializes all the view rows in a temporary table, that is used in the query.
with vv as (
select /*+ MATERIALIZE */ a,b from v1)
select a, b from vv
where a = 1;
----------------------------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
----------------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 26 | 5 (0)| 00:00:01 |
| 1 | TEMP TABLE TRANSFORMATION | | | | | |
| 2 | LOAD AS SELECT | SYS_TEMP_0FD9D6605_5E8CE554 | | | | |
| 3 | TABLE ACCESS FULL | T | 1 | 26 | 3 (0)| 00:00:01 |
|* 4 | VIEW | | 1 | 26 | 2 (0)| 00:00:01 |
| 5 | TABLE ACCESS FULL | SYS_TEMP_0FD9D6605_5E8CE554 | 1 | 26 | 2 (0)| 00:00:01 |
----------------------------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
4 - filter("A"=1)
Column Projection Information (identified by operation id):
-----------------------------------------------------------
1 - "A"[NUMBER,22], "B"[NUMBER,22]
2 - SYSDEF[4], SYSDEF[0], SYSDEF[1], SYSDEF[96], SYSDEF[0]
3 - "A"[NUMBER,22], "B"[NUMBER,22]
4 - "A"[NUMBER,22], "B"[NUMBER,22]
5 - "C0"[NUMBER,22], "C1"[NUMBER,22]
Again you see in the Projection Information the column C is not referenced.
What doesn't work and you should avoid is to materialize the view with a select * .. - this of course fails.
with vv as (
select /*+ MATERIALIZE */ * from v1)
select a, b from vv
where a = 1;
SQL is a descriptive language not a procedural language. The database optimizer actually determines the execution.
For your scenario, there are two reasonable options for the optimizer:
Filter the rows and then calculate the value after filtering.
Calculate the value first and then filter.
Oracle has a good optimizer, so I would expect it to consider both possibilities. It chooses the one that would have the best performance for your query.
If you still need c only for some of the rows returned, then delaying the computation might be worthwhile if it is really really expensive. However, that would be an unusual optimization.
There is a table which has trades and its row count is 220 million, one of column is counterparty. The column is indexed. If I run a normal query like:
select *
from <table>
where counterparty = 'X'
The plan shows it uses index. Where as if I use group by on same column, it doesn't use index and does table scan. i.e.: for below query:
select counterparty, count(*)
from <table>
group by counterparty
Could you please advise, why it's not using the index for group by? FYI - I have already run the db stats.
FYI - the plan for 1st and second query is shown below:
Note - we are migrating data from Sybase to oracle, when I use same group by in Sybase with same indexes. The query uses indexes, but not in oracle.
First
Plan hash value: 350128866
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
| 0 | SELECT STATEMENT | | 2209 | 1469K| 914 (0)| 00:00:01 |
| 1 | TABLE ACCESS BY INDEX ROWID| FXCASHTRADE | 2209 | 1469K| 914 (0)| 00:00:01 |
|* 2 | INDEX RANGE SCAN | SCB_FXCASHTRADE_002 | 2209 | | 11 (0)| 00:00:01 |
Predicate Information (identified by operation id):
2 - access("COUNTERPARTY"='test')
Second
> Plan hash value: 2920872612
| Id | Operation | Name | Rows | Bytes |TempSpc| Cost (%CPU)| Time |
| 0 | SELECT STATEMENT | | 100K| 2151K| | 6558K (1)| 00:00:38 |
| 1 | HASH GROUP BY | | 100K| 2151K| 6780M| 6558K (1)| 00:00:38 |
| 2 | TABLE ACCESS FULL| FXCASHTRADE | 221M| 4643M| | 6034K (1)| 00:00:35 |
I am going to make an educated guess and say that counterparty is defined as a nullable column. As such, Oracle can't solely rely on the index to generate the results of your group by query, since null values need to be included in the results, but (Oracle) indexes don't include null values. With that in mind, a full table scan makes sense.
If there is no good reason for counterparty to be nullable, go ahead and make it not null. The execution plan should then change to use the index as expected.
Alternatively, if you can't make that change, but you don't care about null values for this particular query, you can tweak the query to filter our null values explicitly. This should also result in a better execution plan.
select counterparty, count(*)
from tbl
where counterparty is not null -- add this filter
group by counterparty
Note: I'm no Sybase expert, but I assume that indexes include null values. Oracle indexes do not include null values. That would explain the difference in execution plan between both databases.
I'm wondering why cost of this query
select * from address a
left join name n on n.adress_id=a.id
where a.street='01';
is higher than
select * from address a
left join name n on n.adress_id=a.id
where a.street=N'01';
where address table looks like this
ID NUMBER
STREET VARCHAR2(255 CHAR)
POSTAL_CODE VARCHAR2(255 CHAR)
and name table looks like this
ID NUMBER
ADDRESS_ID NUMBER
NAME VARCHAR2(255 CHAR)
SURNAME VARCHAR2(255 CHAR)
These are costs returned by explain plan
Explain plan for '01'
-----------------------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
-----------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 3591 | 1595K| 87 (0)| 00:00:02 |
| 1 | NESTED LOOPS OUTER | | 3591 | 1595K| 87 (0)| 00:00:02 |
|* 2 | TABLE ACCESS FULL | ADDRESS | 3 | 207 | 3 (0)| 00:00:01 |
| 3 | TABLE ACCESS BY INDEX ROWID| NAME | 1157 | 436K| 47 (0)| 00:00:01 |
|* 4 | INDEX RANGE SCAN | NAME_HSI | 1157 | | 1 (0)| 00:00:01 |
-----------------------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
2 - filter("A"."STREET"='01')
4 - access("N"."ADDRESS_ID"(+)="A"."ID")
Explain plan for N'01'
-----------------------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
-----------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 347 | 154K| 50 (0)| 00:00:01 |
| 1 | NESTED LOOPS OUTER | | 347 | 154K| 50 (0)| 00:00:01 |
|* 2 | TABLE ACCESS FULL | ADDRESS | 1 | 69 | 3 (0)| 00:00:01 |
| 3 | TABLE ACCESS BY INDEX ROWID| NAME | 1157 | 436K| 47 (0)| 00:00:01 |
|* 4 | INDEX RANGE SCAN | NAME_HSI | 1157 | | 1 (0)| 00:00:01 |
-----------------------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
2 - filter(SYS_OP_C2C("A"."STREET")=U'01')
4 - access("N"."ADDRESS_ID"(+)="A"."ID")
As you can see cost for N'01' query is lower than cost for '01'. Any idea why? N'01' needs additionally convert varchar to nvarchar so cost should be higher (SYS_OP_C2C()). The other question is why rows processed by N'01' query is lower than '01'?
[EDIT]
Table address has 30 rows.
Table name has 19669 rows.
SYS_OP_C2C is an internal function which does an implicit conversion of varchar2 to national character set using TO_NCHAR function. Thus, the filter completely changes as compared to the filter using normal comparison.
I am not sure about the reason why the number of rows are less, but I can guarantee it could be more too. Cost estimation won't be affected.
Let's try to see step-by-step in a test case.
SQL> CREATE TABLE t AS SELECT 'a'||LEVEL col FROM dual CONNECT BY LEVEL < 1000;
Table created.
SQL>
SQL> EXPLAIN PLAN FOR SELECT * FROM t WHERE col = 'a10';
Explained.
SQL> SELECT * FROM TABLE(dbms_xplan.display);
PLAN_TABLE_OUTPUT
----------------------------------------------------------------------------------------------------
Plan hash value: 1601196873
--------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
--------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 5 | 3 (0)| 00:00:01 |
|* 1 | TABLE ACCESS FULL| T | 1 | 5 | 3 (0)| 00:00:01 |
--------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
PLAN_TABLE_OUTPUT
----------------------------------------------------------------------------------------------------
1 - filter("COL"='a10')
13 rows selected.
SQL>
So far so good. Since there is only one row with value as 'a10', optimizer estimated one row.
Let's see with the national characterset conversion.
SQL> EXPLAIN PLAN FOR SELECT * FROM t WHERE col = N'a10';
Explained.
SQL> SELECT * FROM TABLE(dbms_xplan.display);
PLAN_TABLE_OUTPUT
----------------------------------------------------------------------------------------------------
Plan hash value: 1601196873
--------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
--------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 10 | 50 | 3 (0)| 00:00:01 |
|* 1 | TABLE ACCESS FULL| T | 10 | 50 | 3 (0)| 00:00:01 |
--------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
PLAN_TABLE_OUTPUT
----------------------------------------------------------------------------------------------------
1 - filter(SYS_OP_C2C("COL")=U'a10')
13 rows selected.
SQL>
What happened here? We can see filter(SYS_OP_C2C("COL")=U'a10'), which means an internal function is applied and it converts the varchar2 value to nvarchar2. The filter now found 10 rows.
This will also suppress any index usage, since now a function is applied on the column. We can tune it by creating a function-based index to avoid full table scan.
SQL> create index nchar_indx on t(to_nchar(col));
Index created.
SQL>
SQL> EXPLAIN PLAN FOR SELECT * FROM t WHERE to_nchar(col) = N'a10';
Explained.
SQL> SELECT * FROM TABLE(dbms_xplan.display);
PLAN_TABLE_OUTPUT
----------------------------------------------------------------------------------------------------
Plan hash value: 1400144832
--------------------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
--------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 10 | 50 | 2 (0)| 00:00:01 |
| 1 | TABLE ACCESS BY INDEX ROWID BATCHED| T | 10 | 50 | 2 (0)| 00:00:01 |
|* 2 | INDEX RANGE SCAN | NCHAR_INDX | 4 | | 1 (0)| 00:00:01 |
--------------------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
PLAN_TABLE_OUTPUT
----------------------------------------------------------------------------------------------------
---------------------------------------------------
2 - access(SYS_OP_C2C("COL")=U'a10')
14 rows selected.
SQL>
However, will this make the execution plans similar? No. i think with two different charactersets , the filter will not be applied alike. Thus, the difference lies.
My research says,
Usually, such scenarios occur when the data coming via an application
is nvarchar2 type, but the table column is varchar2. Thus, Oracle
applies an internal function in the filter operation. My suggestion
is, to know your data well, so that you use similar data types during
design phase.
When worrying about explain plans, it matters whether there are current statistics on the tables. If the statistics do not represent the actual data reasonably well, then the optimizer will make mistakes and estimate cardinalities incorrectly.
You can check how long ago statistics were gathered by querying the data dictionary:
select table_name, last_analyzed
from user_tables
where table_name in ('ADDRESS','NAME');
You can gather statistics for the optimizer to use by calling DBMS_STATS:
begin
dbms_stats.gather_table_stats(user, 'ADDRESS');
dbms_stats.gather_table_stats(user, 'NAME');
end;
So perhaps after gathering statistics you will get different explain plans. Perhaps not.
The difference in your explain plans is primarily because the optimizer estimates how many rows it will find in address table differently in the two cases.
In the first case you have an equality predicate with same datatype - this is good and the optimizer can often estimate cardinality (row count) reasonably well for cases like this.
In the second case a function is applied to the column - this is often bad (unless you have function based indexes) and will force the optimizer to take a wild guess. That wild quess will be different in different versions of Oracle as the developers of the optimizer tries to improve upon it. Some versions the wild guess will simply be something like "I guess 5% of the number of rows in the table."
When comparing different datatypes, it is best to avoid implicit conversions, particularly when like this case the implicit conversion makes a function on the column rather than the literal. If you have cases where you get a value as datatype NVARCHAR2 and need to use it in a predicate like above, it can be a good idea to explicitly convert the value to the datatype of the column.
select * from address a
left join name n on n.adress_id=a.id
where a.street = CAST( N'01' AS VARCHAR2(255));
In this case with a literal it does not make sense, of course. Here you would just use your first query. But if it was a variable or function parameter, maybe you could have use cases for doing something like this.
As I can see the first query returns 3591 rows, the second one returns 347 rows. So Oracle needs less I/O operation that's why the cost is less.
Don't be confused with
N'01' needs additionally convert varchar to nvarchar
Oracle does one hard parse and then uses soft parse for the same queries. So the longer your oracle works the faster it becomes.
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);