I've created an Oracle Text index like the following:
create index my_idx on my_table (text) indextype is ctxsys.context;
And I can then do the following:
select * from my_table where contains(text, '%blah%') > 0;
But lets say we have a have another column in this table, say group_id, and I wanted to do the following query instead:
select * from my_table where contains(text, '%blah%') > 0 and group_id = 43;
With the above index, Oracle will have to search for all items that contain 'blah', and then check all of their group_ids.
Ideally, I'd prefer to only search the items with group_id = 43, so I'd want an index like this:
create index my_idx on my_table (group_id, text) indextype is ctxsys.context;
Kind of like a normal index, so a separate text search can be done for each group_id.
Is there a way to do something like this in Oracle (I'm using 10g if that is important)?
Edit (clarification)
Consider a table with one million rows and the following two columns among others, A and B, both numeric. Lets say there are 500 different values of A and 2000 different values of B, and each row is unique.
Now lets consider select ... where A = x and B = y
An index on A and B separately as far as I can tell do an index search on B, which will return 500 different rows, and then do a join/scan on these rows. In any case, at least 500 rows have to be looked at (aside from the database being lucky and finding the required row early.
Whereas an index on (A,B) is much more effective, it finds the one row in one index search.
Putting separate indexes on group_id and the text I feel only leaves the query generator with two options.
(1) Use the group_id index, and scan all the resulting rows for the text.
(2) Use the text index, and scan all the resulting rows for the group_id.
(3) Use both indexes, and do a join.
Whereas I want:
(4) Use the (group_id, "text") index to find the text index under the particular group_id and scan that text index for the particular row/rows I need. No scanning and checking or joining required, much like when using an index on (A,B).
Oracle Text
1 - You can improve performance by creating the CONTEXT index with FILTER BY:
create index my_idx on my_table(text) indextype is ctxsys.context filter by group_id;
In my tests the filter by definitely improved the performance, but it was still slightly faster to just use a btree index on group_id.
2 - CTXCAT indexes use "sub-indexes", and seem to work similar to a multi-column index. This seems to be the option (4) you're looking for:
begin
ctx_ddl.create_index_set('my_table_index_set');
ctx_ddl.add_index('my_table_index_set', 'group_id');
end;
/
create index my_idx2 on my_table(text) indextype is ctxsys.ctxcat
parameters('index set my_table_index_set');
select * from my_table where catsearch(text, 'blah', 'group_id = 43') > 0
This is likely the fastest approach. Using the above query against 120MB of random text similar to your A and B scenario required only 18 consistent gets. But on the downside, creating the CTXCAT index took almost 11 minutes and used 1.8GB of space.
(Note: Oracle Text seems to work correctly here, but I'm not familiar with Text and I can't gaurentee this isn't an inappropriate use of these indexes like #NullUserException said.)
Multi-column indexes vs. index joins
For the situation you describe in your edit, normally there would not be a significant difference between using an index on (A,B) and joining separate indexes on A and B. I built some tests with data similar to what you described and an index join required only 7 consistent gets versus 2 consistent gets for the multi-column index.
The reason for this is because Oracle retrieves data in blocks. A block is usually 8K, and an index block is already sorted, so you can probably fit the 500 to 2000 values in a few blocks. If you're worried about performance, usually the IO to read and write blocks is the only thing that matters. Whether or not Oracle has to join together a few thousand rows is an inconsequential amount of CPU time.
However, this doesn't apply to Oracle Text indexes. You can join a CONTEXT index with a btree index (a "bitmap and"?), but the performance is poor.
I'd put an index on group_id and see if that's good enough. You don't say how many rows we're talking about or what performance you need.
Remember, the order in which the predicates are handled is not necessarily the order in which you wrote them in the query. Don't try to outsmart the optimizer unless you have a real reason to.
Short version: There's no need to do that. The query optimizer is smart enough to decide what's the best way to select your data. Just create a btree index on group_id, ie:
CREATE INDEX my_group_idx ON my_table (group_id);
Long version: I created a script (testperf.sql) that inserts 136 rows of dummy data.
DESC my_table;
Name Null Type
-------- -------- ---------
ID NOT NULL NUMBER(4)
GROUP_ID NUMBER(4)
TEXT CLOB
There is a btree index on group_id. To ensure the index will actually be used, run this as a dba user:
EXEC DBMS_STATS.GATHER_TABLE_STATS('<YOUR USER HERE>', 'MY_TABLE', cascade=>TRUE);
Here's how many rows each group_id has and the corresponding percentage:
GROUP_ID COUNT PCT
---------------------- ---------------------- ----------------------
1 1 1
2 2 1
3 4 3
4 8 6
5 16 12
6 32 24
7 64 47
8 9 7
Note that the query optimizer will use an index only if it thinks it's a good idea - that is, you are retrieving up to a certain percentage of rows. So, if you ask it for a query plan on:
SELECT * FROM my_table WHERE group_id = 1;
SELECT * FROM my_table WHERE group_id = 7;
You will see that for the first query, it will use the index, whereas for the second query, it will perform a full table scan, since there are too many rows for the index to be effective when group_id = 7.
Now, consider a different condition - WHERE group_id = Y AND text LIKE '%blah%' (since I am not very familiar with ctxsys.context).
SELECT * FROM my_table WHERE group_id = 1 AND text LIKE '%ipsum%';
Looking at the query plan, you will see that it will use the index on group_id. Note that the order of your conditions is not important:
SELECT * FROM my_table WHERE text LIKE '%ipsum%' AND group_id = 1;
Generates the same query plan. And if you try to run the same query on group_id = 7, you will see that it goes back to the full table scan:
SELECT * FROM my_table WHERE group_id = 7 AND text LIKE '%ipsum%';
Note that stats are gathered automatically by Oracle every day (it's scheduled to run every night and on weekends), to continually improve the effectiveness of the query optimizer. In short, Oracle does its best to optimize the optimizer, so you don't have to.
I do not have an Oracle instance at hand to test, and have not used the full-text indexing in Oracle, but I have generally had good performance with inline views, which might be an alternative to the sort of index you had in mind. Is the following syntax legit when contains() is involved?
This inline view gets you the PK values of the rows in group 43:
(
select T.pkcol
from T
where group = 43
)
If group has a normal index, and doesn't have low cardinality, fetching this set should be quick. Then you would inner join that set with T again:
select * from T
inner join
(
select T.pkcol
from T
where group = 43
) as MyGroup
on T.pkcol = MyGroup.pkcol
where contains(text, '%blah%') > 0
Hopefully the optimizer would be able to use the PK index to optimize the join and then appy the contains predicate only to the group 43 rows.
Related
The problem
Using PostgreSQL 13, I ran into a performance issue selecting the highest id from a view that joins two tables, depending on the select statement I execute.
Here's a sample setup:
CREATE TABLE test1 (
id BIGSERIAL PRIMARY KEY,
joincol VARCHAR
);
CREATE TABLE test2 (
joincol VARCHAR
);
CREATE INDEX ON test1 (id);
CREATE INDEX ON test1 (joincol);
CREATE INDEX ON test2 (joincol);
CREATE VIEW testview AS (
SELECT test1.id,
test1.joincol AS t1charcol,
test2.joincol AS t2charcol
FROM test1, test2
WHERE test1.joincol = test2.joincol
);
What I found out
I'm executing two statements which result in completely different execution plans and runtimes. The following statement executes in less than 100ms. As far as I understand the execution plan, the runtime is independent of the rowcount, since Postgres iterates the rows one by one (starting at the highest id, using the index) until a join on a row is possible and immediately returns.
SELECT id FROM testview ORDER BY ID DESC LIMIT 1;
However, this one takes over 1 second on average (depending on rowcount), since the two tables are "joined completely", before Postgres uses the index to select the highest id.
SELECT MAX(id) FROM testview;
Please refer to this sample on dbfiddle to check the explain plans:
https://www.db-fiddle.com/f/bkMNeY6zXqBAYUsprJ5eWZ/1
My real environment
On my real environment test1 contains only a hand full of rows (< 100), having unique values in joincol. test2 contains up to ~10M rows, where joincol always matches a value of test1's joincol. test2's joincol is not nullable.
The actual question
Why does Postgres not recognize that it could use an Index Scan Backward on row basis for the second select? Is there anything I could improve on the tables/indexes?
Queries not strictly equivalent
why does Postgres not recognize that it could use a Index Scan Backward on row basis for the second select?
To make the context clear:
max(id) excludes NULL values. But ORDER BY ... LIMIT 1 does not.
NULL values sort last in ascending sort order, and first in descending. So an Index Scan Backward might not find the greatest value (according to max()) first, but any number of NULL values.
The formal equivalent of:
SELECT max(id) FROM testview;
is not:
SELECT id FROM testview ORDER BY id DESC LIMIT 1;
but:
SELECT id FROM testview ORDER BY id DESC NULLS LAST LIMIT 1;
The latter query doesn't get the fast query plan. But it would with an index with matching sort order: (id DESC NULLS LAST).
That's different for the aggregate functions min() and max(). Those get a fast plan when targeting table test1 directly using the plain PK index on (id). But not when based on the view (or the underlying join-query directly - the view is not the blocker). An index sorting NULL values in the right place has hardly any effect.
We know that id in this query can never be NULL. The column is defined NOT NULL. And the join in the view is effectively an INNER JOIN which cannot introduce NULL values for id.
We also know that the index on test.id cannot contain NULL values.
But the Postgres query planner is not an AI. (Nor does it try to be, that could get out of hands quickly.) I see two shortcomings:
min() and max() get the fast plan only when targeting the table, regardless of index sort order, an index condition is added: Index Cond: (id IS NOT NULL)
ORDER BY ... LIMIT 1 gets the fast plan only with the exactly matching index sort order.
Not sure, whether that might be improved (easily).
db<>fiddle here - demonstrating all of the above
Indexes
Is there anything I could improve on the tables/indexes?
This index is completely useless:
CREATE INDEX ON "test" ("id");
The PK on test.id is implemented with a unique index on the column, that already covers everything the additional index might do for you.
There may be more, waiting for the question to clear up.
Distorted test case
The test case is too far away from actual use case to be meaningful.
In the test setup, each table has 100k rows, there is no guarantee that every value in joincol has a match on the other side, and both columns can be NULL
Your real case has 10M rows in table1 and < 100 rows in table2, every value in table1.joincol has a match in table2.joincol, both are defined NOT NULL, and table2.joincol is unique. A classical one-to-many relationship. There should be a UNIQUE constraint on table2.joincol and a FK constraint t1.joincol --> t2.joincol.
But that's currently all twisted in the question. Standing by till that's cleaned up.
This is a very good problem, and good testcase.
I tested it in postgres 9.3 perhaps 13 is can it more more fast.
I used Occam's Razor and i excluded some possiblities
View (without view is slow to)
JOIN can filter some rows (unfortunatly in your test not, but more length md5 5-6 yes)
Other basic equivalent select statements not solve yout problem (inner query or exists)
I achieved to use just index, but because the tables isn't bigger than indexes it was not the solution.
I think
CREATE INDEX on "test" ("id");
is useless, because PK!
If you change this
CREATE INDEX on "test" ("joincol");
to this
CREATE INDEX ON TEST (joincol, id);
Than the second query use just indexes.
After you run this
REINDEX table test;
REINDEX table test2;
VACUUM ANALYZE test;
VACUUM ANALYZE test2;
you can achive some performance tuning. Because you created indexes before inserts.
I think the reason is the two aim of DB.
First aim optimalize just some row. So run Nested Loop. You can force it with limit x.
Second aim optimalize whole table. Run this query fast for whole table.
In this situation postgres optimalizer didn't notice that simple MAX can run with NESTED LOOP. Or perhaps postgres cannot use limit in aggregate clause (can run on whole partial select, what is filtered with query).
And this is very expensive. But you have possiblities to write there other aggregates, like SUM, MIN, AVG stb.
Perhaps can help you the Window functions too.
My first time working with indexes in database and so far I've learn that if you have a multi-column index such as index('col1', 'col2', 'col3'), and if you do a query that uses where col2='col2' and col3='col3', that index would not be use.
I also learn that if a column is very low selectivity column. Indexing is useless.
However, from my test, it seems none of the above is true at all. Can someone explain more on this?
I have a table with more than 16 million records. Let's say claimID is the primary key, then there're a historynumber column that only have 3 distinct values (1,2,3), and a last column with storeNumber that has about 1 million distinct values.
I have an index for claimID alone, another index(historynumber, claimID), and other index with index(historynumber, storeNumber), and finally index(storeNumber, historynumber).
My guess was that if I do:
select * from my_table where claimId='123456' and historynumber = 1
would be much faster than
select * from my_table where historynumber = 1 and claimId = '123456'
However, the 2 have exactly the same performance (instant). So I thought the primary key index can work on any column order. Therefore, I tried the same thing but on historynumber and storeNumber instead. The result is exactly the same. Then I start trying out on columns that has no indexes and of course the result is the same also.
Finally, I do a
select * from my_table where historynumber = 1
and the query takes so long I had to cancel it.
So my conclusion is that the column order in where clause is completely useless, and so is the column order in the index definition since it seems like the database is smart enough to tell which column is the highest selectivity column.
Could someone give me an example that could prove otherwise?
Index explanation is a huge topic.
Don't worry about the sequence of different attributes in the SQL - it has no effect whether you specify
...where claimId='123456' and historynumber = 1
or the other way round. Each SQL is checked and optimized by the optimizer. To proove how the data gets accessed you could do a EXPLAIN. Check the documentation for more details.
For your other problem
select * from my_table where historynumber = 1
with an index of (storeNumber, historynumber).
Have you ever tried to lookup the name of a caller (having the telephone number) in a telephone book?
Well it is pretty much the same for an index - so the column order when creatin the index matters!
There are techniques which could help - i.e. index jump scan - but there is no guarantee.
Check out following sites to learn a little bit more about DB2 indexes:
http://db2commerce.com/2013/09/19/db2-luw-basics-indexes/
http://use-the-index-luke.com/sql/where-clause/the-equals-operator/concatenated-keys
I have to do a SELECT on a table like this:
id
username
speed
is_running
The statement is like:
SELECT *
FROM mytable
WHERE username = 'foo'
AND is_running = 1
I have an index on "username". If I'm running the above statement, do I need to also index "is_running" for best performance? Or does only the first column of the select make a difference? I'm using mysql 5.0.
It depends on the type of data you're storing. If it's bool, you may not see a gain from an index on that column alone. You may want to try to add a composite index on the two columns:
ALTER TABLE mytable ADD INDEX `IDX_USERNAME_IS_RUNNING` ( `username` , `is_running` );
It will ultimately depend on the amount of data in the table as to if you require the index. In many cases, the engine might just do a table scan and omit your index all together if it thinks that is faster. Do you have 100 users, or 100,000 users?
On a bit/bool column you are not going to utilize a ton of storage space for the index, so it probably won't hurt unless you have a really high insertion rate.
If you have a table with 1 million users and only 1 or 2 is running at any one time - sure, index by is_running and it will give you fantastic performance. This specific use case would do best to have 2 indexes individually on columns - username, isrunning. The reason for 2 indexes is if you are asking for is_running=0, in which case it uses the username index instead.
Otherwise, there is 0% chance of a composite index on (username, isrunning) helping anything. Stick to a single index on username.
Finally, do you really need to whole record? Select *? In some scenarios close to the tipping point (when MySQL thinks the index+lookups becomes less efficient than a straight scan), you can make this query run faster than the original. Have an index on (username,id)
SELECT mytable.*
FROM (
SELECT id
FROM mytable
WHERE username = 'foo'
AND is_running = 1
) X
INNER JOIN mytable on mytable.id = X.id
I'm reading about indexes in my database book and I was wondering if I was correct in my assumption that a WHERE clause with a non-constant expression in it will not use the index.
So if i have
SELECT * FROM statuses WHERE app_user_id % 10 = 0;
This would not use an index created on app_user_id. But
SELECT * FROM statuses WHERE app_user_id = 5;
would use the index on app_user_id.
Usually (there are other options) a database index is a B-Tree, which means that you can do range scans on it (including equality scans).
The condition app_user_id % 10 = 0 cannot be evaluated with a single range scan, which is why a database will probably not use an index.
It could still decide to use the index in another way, namely for a full scan: Reading the whole table takes more time than just reading the whole index. On the other hand, after reading the index you may still get back to the table, so the overall cost may end up being higher.
This is up to the database query optimizer to decide.
A few examples:
select app_user_id from t where app_user_id % 10 = 0
Here, you do not need the table at all, all necessary data is in the index. The database will most likely do a full index scan.
select count(*) from t where app_user_id % 10 = 0
Same. Full index scan.
select count(*) from t
Only if app_user_id is NOT NULL can this be done with the index (because NULL data is not in the index, at least on Oracle, at least on single column indexes, your database may handle this differently).
Some databases do not need to do access table or index for this, they maintain row counts in the metadata.
select * from t where app_user_id = 5
This is the classic scenario for an index. The database can look at the small section of the index tree, retrieve a small (just one if this was a unique or primary index) number of rowids and fetch those selectively from the table.
select * from t where app_user_id between 5 and 10
Another classic index case. Range scan in the tree returns a small number of rowids to fetch from the table.
select * from t where app_user_id between 5 and 10 order by app_user_id
Since index scans return ordered data, you even get the sorting for free.
select * from t where app_user_id between 5 and 1000000000
Maybe here you should not be using an index. It seems to match too many records. This is a case where having bind variables hide the range from the database could actually be detrimental.
select * from t where app_user_id between 5 and 1000000000
order by app_user_id
But here, since sorting would be very expensive (even taking up temporary swap disk space), maybe iterating in index order is good. Maybe.
select * from t where app_user_id % 10 = 0
This is difficult to decide. We need all columns, so ultimately the query needs to touch the table. The question is whether to go through an index first. The query returns approximately 10% of the whole table. That is probably too much for an index access path to be efficient. If the optimizer has reason to believe that the query returns much less than 10% of the table, an index scan followed by accessing the table might be good. Same if the table is very fragmented (lots of deleted rows eating up space).
If I have an table
create table sv ( id integer, data text )
and an index:
create index myindex_idx on sv (id,text)
would this still be usefull if I did a query
select * from sv where id = 10
My reason for asking is that i'm looking through a set of tables with out any indexes, and seeing different combinations of select queries. Some uses just one column other has more than one. Do I need to have indexes for both sets or is an all-inclusive-index ok?
I am adding the indexes for faster lookups than full table scans.
Example (based on the answer by Matt Huggins):
select * from table where col1 = 10
select * from table where col1 = 10 and col2=12
select * from table where col1 = 10 and col2=12 and col3 = 16
could all be covered by index table (co1l1,col2,col3) but
select * from table where col2=12
would need another index?
It should be useful since an index on (id, text) first indexes by id, then text respectively.
If you query by id, this index will be used.
If you query by id & text, this index will be used.
If you query by text, this index will NOT be used.
Edit: when I say it's "useful", I mean it's useful in terms of query speed/optimization. As Sune Rievers pointed out, it will not mean you will get a unique record given just ID (unless you specify ID as unique in your table definition).
Oracle supports a number of ways of using an index, and you ought to start by understanding all of them so have a quick read here: http://download.oracle.com/docs/cd/B19306_01/server.102/b14211/optimops.htm#sthref973
Your query select * from table where col2=12 could usefully leverage an index skip scan if the leading column is of very low cardinality, or a fast full index scan if it is not. These would probably be fine for running reports, however for an OLTP query it is likely that you would do better to create an index with col2 as the leading column.
I assume id is primary key. There is no point in adding a primary key to the index, as this will always be unique. Adding something unique to something else will also be unique.
Add a unique index to text, if you really need it, otherwise just use id is uniqueness for the table.
If id is not your primary key, then you will not be guaranteed to get a unique result from your query.
Regarding your last example with lookup on col2, I think you could need another index. Indexes are not a cure-all solution for performance problems though, sometimes your database design or your queries needs to be optimized, for instance rewritten into stored procedures (while I'm not totally sure Oracle has them, I'm sure there's an Oracle equivalent).
If the driver behind your question is that you have a table with several columns and any combination of these columns may be used in a query, then you should look at BITMAP indexes.
Looking at your example:
select * from mytable where col1 = 10 and col2=12 and col3 = 16
You could create 3 bitmap indexes:
create bitmap index ix_mytable_col1 on mytable(col1);
create bitmap index ix_mytable_col2 on mytable(col2);
create bitmap index ix_mytable_col3 on mytable(col3);
These bitmap indexes have the great benefit that they can be combined as required.
So, each of the following queries would use one or more of the indexes:
select * from mytable where col1 = 10;
select * from mytable where col2 = 10 and col3 = 16;
select * from mytable where col3 = 16;
So, bitmap indexes may be an option for you. However, as David Aldridge pointed out, depending on your particular data set a single index on (col1,col2,col3) might be preferable. As ever, it depends. Take a look at your data, the likely queries against that data, and make sure your statistics are up to date.
Hope this helps.