How to otimize select from several tables with millions of rows
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?
First I assume that your University and SecurityGroup tables are rather small. You posted the size of the large tables but it's really the other sizes that are part of the problem
Your problem is from the fact that you can't join the smallest tables first. Your join order should be from small to large. But because your mapping tables don't include a securitygroup-to-university table, you can't join the smallest ones first. So you wind up starting with one or the other, to a big table, to another big table and then with that large intermediate result you have to go to a small table.
If you always have current_univ and current_secgrp and root as inputs you want to use them to filter as soon as possible. The only way to do that is to change your schema some. In fact, you can leave the existing tables in place if you have to but you'll be adding to the space with this suggestion.
You've normalized the data very well. That's great for speed of update... not so great for querying. We denormalize to speed querying (that's the whole reason for datawarehouses (ok that and history)). Build a single mapping table with the following columns.
Univ_id, SecGrp_ID, Root, catalog_id. Make it an index organized table of the first 3 columns as pk.
Now when you query that index with all three PK values, you'll finish that index scan with a complete list of allowable catalog Id, now it's just a single join to the cat table to get the cat item details and you're off an running.
The indexes that can be useful and should be considered deal with
WHERE c.root = 100
AND cs.catalog = c.id
AND cs.securitygroup = 200
AND cu.catalog = c.id
AND cu.university = 300
So the following fields can be interesting for indexes
c: id, root
cs: catalog, securitygroup
cu: catalog, university
So, try creating
(catalog_securitygroup.catalog, catalog_securitygroup.securitygroup)
and
(catalog_university.catalog, catalog_university.university)
EDIT: I missed the ORDER BY - these fields should also be considered, so
(catalog.name, catalog.id)
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:
test=# SELECT (SELECT COUNT(*) FROM catalog), (SELECT COUNT(*) FROM catalog_securitygroup), (SELECT COUNT(*) FROM catalog_university);
?column? | ?column? | ?column?
----------+----------+----------
500000 | 1497501 | 500000
(1 row)
Database is postgres 8.4, default ubuntu install, hardware i5, 4GRAM
First I rewrote the query to
SELECT c.id, c.name, c.owner
FROM catalog c, catalog_securitygroup cs, catalog_university cu
WHERE c.root < 50
AND cs.catalog = c.id
AND cu.catalog = c.id
AND cs.securitygroup < 200
AND cu.university < 200
ORDER BY c.name
LIMIT 50 OFFSET 100
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:
CREATE INDEX test1 ON catalog (name, id);
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
The Oracle cost-based optimizer makes use of all the information that it has to decide what the best access paths are for the data and what the least costly methods are for getting that data. So below are some random points related to your question.
The first three tables that you've listed all have primary keys. Do the other tables (catalog_university and catalog_securitygroup) also have primary keys on them?? A primary key defines a column or set of columns that are non-null and unique and are very important in a relational database.
Oracle generally enforces a primary key by generating a unique index on the given columns. The Oracle optimizer is more likely to make use of a unique index if it available as it is more likely to be more selective.
If possible an index that contains unique values should be defined as unique ( CREATE UNIQUE INDEX... ) and this will provide the optimizer with more information.
The additional indexes that you have provided are no more selective than the existing indexes. For example, the index on (catalog.id, catalog.name, catalog.owner) is unique but is less useful than the existing primary key index on (catalog.id). If a query is written to select on the catalog.name column, it is possible to do and index skip scan but this starts being costly (and most not even be possible in this case).
Since you are trying to select based in the catalog.root column, it might be worth adding an index on that column. This would mean that it could quickly find the relevant rows from the catalog table. The timing for the second query could be a bit misleading. It might be taking 2 seconds to find 50 matching rows from catalog, but these could easily be the first 50 rows from the catalog table..... finding 50 that match all your conditions might take longer, and not just because you need to join to other tables to get them. I would always use create table as select without restricting on rownum when trying to performance tune. With a complex query I would generally care about how long it take to get all the rows back... and a simple select with rownum can be misleading
Everything about Oracle performance tuning is about providing the optimizer enough information and the right tools (indexes, constraints, etc) to do its job properly. For this reason it's important to get optimizer statistics using something like DBMS_STATS.GATHER_TABLE_STATS() . Indexes should have stats gathered automatically in Oracle 10g or later.
Somehow this grew into quite a long answer about the Oracle optimizer. Hopefully some of it answers your question. Here is a summary of what is said above:
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