Have the following tables (Oracle 10g):
catalog (
id NUMBER PRIMARY KEY,
name VARCHAR2(255),
owner NUMBER,
root NUMBER REFERENCES catalog(id)
...
)
university (
id NUMBER PRIMARY KEY,
...
)
securitygroup (
id NUMBER PRIMARY KEY
...
)
catalog_securitygroup (
catalog REFERENCES catalog(id),
securitygroup REFERENCES securitygroup(id)
)
catalog_university (
catalog REFERENCES catalog(id),
university REFERENCES university(id)
)
Catalog: 500 000 rows, catalog_university: 500 000, catalog_securitygroup: 1 500 000.
I need to select any 50 rows from catalog with specified root ordered by name for current university and current securitygroup. There is a query:
SELECT ccc.* FROM (
SELECT cc.*, ROWNUM AS n FROM (
SELECT c.id, c.name, c.owner
FROM catalog c, catalog_securitygroup cs, catalog_university cu
WHERE c.root = 100
AND cs.catalog = c.id
AND cs.securitygroup = 200
AND cu.catalog = c.id
AND cu.university = 300
ORDER BY name
) cc
) ccc WHERE ccc.n > 0 AND ccc.n <= 50;
Where 100 – some catalog, 200 – some securitygroup, 300 – some university. This query return 50 rows from ~ 170 000 in 3 minutes.
But next query return this rows in 2 sec:
SELECT ccc.* FROM (
SELECT cc.*, ROWNUM AS n FROM (
SELECT c.id, c.name, c.owner
FROM catalog c
WHERE c.root = 100
ORDER BY name
) cc
) ccc WHERE ccc.n > 0 AND ccc.n <= 50;
I build next indexes: (catalog.id, catalog.name, catalog.owner), (catalog_securitygroup.catalog, catalog_securitygroup.index), (catalog_university.catalog, catalog_university.university).
Plan for first query (using PLSQL Developer):
http://habreffect.ru/66c/f25faa5f8/plan2.jpg
Plan for second query:
http://habreffect.ru/f91/86e780cc7/plan1.jpg
What are the ways to optimize the query I have?
Best Answer
The indexes that can be useful and should be considered deal with
So the following fields can be interesting for indexes
So, try creating
and
EDIT: I missed the ORDER BY - these fields should also be considered, so
might be beneficial (or some other composite index that could be used for sorting and the conditions - possibly (catalog.root, catalog.name, catalog.id))
EDIT2 Although another question is accepted I'll provide some more food for thought. I have created some test data and run some benchmarks.
The test cases are minimal in terms of record width (in catalog_securitygroup and catalog_university the primary keys are (catalog, securitygroup) and (catalog, university)). Here is the number of records per table:
Database is postgres 8.4, default ubuntu install, hardware i5, 4GRAM
First I rewrote the query to
note: the conditions are turned into less then to maintain comparable number of intermediate rows (the above query would return 198,801 rows without the LIMIT clause)
If run as above, without any extra indexes (save for PKs and foreign keys) it runs in 556 ms on a cold database (this is actually indication that I oversimplified the sample data somehow - I would be happier if I had 2-4s here without resorting to less then operators)
This bring me to my point - any straight query that only joins and filters (certain number of tables) and returns only a certain number of the records should run under 1s on any decent database without need to use cursors or to denormalize data (one of these days I'll have to write a post on that).
Furthermore, if a query is returning only 50 rows and does simple equality joins and restrictive equality conditions it should run even much faster.
Now let's see if I add some indexes, the biggest potential in queries like this is usually the sort order, so let me try that:
This makes execution time on the query - 22ms on a cold database.
And that's the point - if you are trying to get only a page of data, you should only get a page of data and execution times of queries such as this on normalized data with proper indexes should take less then 100ms on decent hardware.
I hope I didn't oversimplify the case to the point of no comparison (as I stated before some simplification is present as I don't know the cardinality of relationships between catalog and the many-to-many tables).
So, the conclusion is