I'm having a problem with a slow query. Consider the table tblVotes - and it has two columns - VoterGuid, CandidateGuid. It holds votes cast by voters to any number of candidates.
There are over 3 million rows in this table - with about 13,000 distinct voters casting votes to about 2.7 million distinct candidates. The total number of rows in the table is currently 6.5 million.
What my query is trying to achieve is getting - in the quickest and most cache-efficient way possible (we are using SQL Express) - the top 1000 candidates based on the number of votes they have received.
The code is:
SELECT CandidateGuid, COUNT(*) CountOfVotes
FROM dbo.tblVotes
GROUP BY CandidateGuid
HAVING COUNT(*) > 1
ORDER BY CountOfVotes DESC
... but this takes a scarily long time to run on SQL express when there is a very full table.
Can anybody suggest a good way to speed this up and get it running in quick time? CandidateGuid is indexed individually - and there is a composite primary key on CandidateGuid+VoterGuid.
If you have only two columns in a table, a "normal" index on those two fields won't help you much, because it is in fact a copy of your entire table, only ordered. First check in execution plan, if your index is being used at all.
Then consider changing your index to clustered index.
Try using a top n, instead of a having clause - like so:
SELECT TOP 1000 CandidateGuid, COUNT(*) CountOfVotes
FROM dbo.tblVotes
GROUP BY CandidateGuid
ORDER BY CountOfVotes DESC
I don't know if SQL Server is able to use the composite index to speed this query, but if it is able to do so you would need to express the query as SELECT CandidateGUID, COUNT(VoterGUID) FROM . . . in order to get the optimization. This is "safe" because you know VoterGUID is never NULL, since it's part of a PRIMARY KEY.
If your composite primary key is specified as (CandidateGUID, VoterGUID) you will not get any added benefit of a separate index on just CandidateGUID -- the existing index can be used to optimize any query that the singleton index would assist in.
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.
I have a table
Books(BookId, Name, ...... , PublishedYear)
I do have about 30 fields in my Books table, where BookId is the primary key (Identity column). I have about 2 million records for this table.
I know select * is evil performance killer..
I have a situation to select range of rows or all the rows having all the columns in it.
Select * from Books;
this query takes more than 2 seconds to scan through the data page and get all the records. On checking the execution it still uses the Clustered index scan.
Obviously 2 seconds my not be that bad, however when this table has to be joined with other tables which is executed in batch is taking time over 15 minutes (There are no duplicate records though on the final result at completion as the count is matching). The join criteria is pretty simple and yields no duplication.
Excluding this table alone has the batch execution completed in sub seconds.
Is there a way to optimize this having said that I will have to select all the columns :(
Thanks in advance.
I've just run a batch against my developer instance, one SELECT specifying all Columns and one using *. There is no evidence (nor should there) that there is any difference aside from the raw parsing of my input. If I remember correctly, that old saying really means: Do not SELECT columns you are not using, they use up resources without benefit.
When you try to improve performance in your code, always check your assumptions, they might only apply to some older version (of sql server etc) or other method.
I've got a table with huge amount of data. Lets say 10GB of lines, containing bunch of crap. I need to select for example X rows (X is usually below 10) with highest amount column.
Is there any way how to do it without sorting the whole table? Sorting this amount of data is extremely time-expensive, I'd be OK with one scan through the whole table and selecting X highest values, and letting the rest untouched. I'm using SQL Server.
Create an index on amount then SQL Server can select the top 10 from that and do bookmark lookups to retrieve the missing columns.
SELECT TOP 10 Amount FROM myTable ORDER BY Amount DESC
if it is indexed, the query optimizer should use the index.
If not, I do no see how one could avoid scanning the whole thing...
Wether an index is usefull or not depends on how often you do that search.
You could also consider putting that query into an indexed view. I think this will give you the best benefit/cost ration.
I've always just used "SELECT COUNT(1) FROM X" but perhaps this is not the most efficient. Any thoughts? Other options include SELECT COUNT(*) or perhaps getting the last inserted id if it is auto-incremented (and never deleted).
How about if I just want to know if there is anything in the table at all? (e.g., count > 0?)
The best way is to make sure that you run SELECT COUNT on a single column (SELECT COUNT(*) is slower) - but SELECT COUNT will always be the fastest way to get a count of things (the database optimizes the query internally).
If you check out the comments below, you can see arguments for why SELECT COUNT(1) is probably your best option.
To follow up on girasquid's answer, as a data point, I have a sqlite table with 2.3 million rows. Using select count(*) from table, it took over 3 seconds to count the rows. I also tried using SELECT rowid FROM table, (thinking that rowid is a default primary indexed key) but that was no faster. Then I made an index on one of the fields in the database (just an arbitrary field, but I chose an integer field because I knew from past experience that indexes on short fields can be very fast, I think because the index is stored a copy of the value in the index itself). SELECT my_short_field FROM table brought the time down to less than a second.
If you are sure (really sure) that you've never deleted any row from that table and your table has not been defined with the WITHOUT ROWID optimization you can have the number of rows by calling:
select max(RowId) from table;
Or if your table is a circular queue you could use something like
select MaxRowId - MinRowId + 1 from
(select max(RowId) as MaxRowId from table) JOIN
(select min(RowId) as MinRowId from table);
This is really really fast (milliseconds), but you must pay attention because sqlite says that row id is unique among all rows in the same table. SQLite does not declare that the row ids are and will be always consecutive numbers.
The fastest way to get row counts is directly from the table metadata, if any. Unfortunately, I can't find a reference for this kind of data being available in SQLite.
Failing that, any query of the type
SELECT COUNT(non-NULL constant value) FROM table
should optimize to avoid the need for a table, or even an index, scan. Ideally the engine will simply return the current number of rows known to be in the table from internal metadata. Failing that, it simply needs to know the number of entries in the index of any non-NULL column (the primary key index being the first place to look).
As soon as you introduce a column into the SELECT COUNT you are asking the engine to perform at least an index scan and possibly a table scan, and that will be slower.
I do not believe you will find a special method for this. However, you could do your select count on the primary key to be a little bit faster.
sp_spaceused 'table_name' (exclude single quote)
this will return the number of rows in the above table, this is the most efficient way i have come across yet.
it's more efficient than select Count(1) from 'table_name' (exclude single quote)
sp_spaceused can be used for any table, it's very helpful when the table is exceptionally big (hundreds of millions of rows), returns number of rows right a way, whereas 'select Count(1)' might take more than 10 seconds. Moreover, it does not need any column names/key field to consider.
I have a SQL table readings something like:
id int
client_id int
device_id int
unique index(client_id, device_id)
I do not understand why the following query is so slow:
SELECT client_id FROM `readings` WHERE device_id = 10 ORDER BY client_id DESC LIMIT 1
My understanding with the index is that mysql keeps an ordered list (one property of a btree) of each row in the table sorted first by client_id and then by device_id. When I execute an explain on this query it says that it will use the index, but that it will need to look at every row. This makes sense since in the worst case, there may only be one row with device_id = 10 and that may also be the row with the smallest client_id and thus at the end of it's search. However, in practice, this is not true. My table has ~10 million rows, and rows with device_id = 10 are spread fairly evenly throughout that table. Why then doesn't MySQL start at the end of the index and scan until it finds the first row with device_id = 10, stop and return that value? It does not seem possible that this is what is happening since the query takes ~30 seconds to execute.
Is it that my unique key is implemented as a hash somehow and thus not accessible in a list form? PHPMyAdmin is telling me that it is implemented as a b-tree, which makes me think that it should be able to do the scan as I mentioned above and quit with the first instance.
Where is my error and how can I make this query execute more quickly?
Thanks
Try switching the column order in the index:
unique index(device_id, client_id)
Since you are filtering on device_id, you would want that to be the first column in the index.
First, I'm assuming that you have good statistics for this table. If not, you'll want to analyze the table to make sure the optimizer can figure out what the best option is.
Here's another approach you could try that might work better. I could be that MySQL is not understanding your intent well enough to optimize correctly:
SELECT MAX(client_id) from readings where device_id = 10
Otherwise you could modify the index to be by device_id first, then client_id. Or you could add another index by just device_id.
You have a compound index on (client_id, device_id), these will(more or less) be concatenated for the purpose of indexing and the index will only be considered if you use the
first of the column(s). Your query is using 'device_id' which is the last of them, you could provide a separate index on that column, or swap the columns around in the index.
Also, check the output of EXPLAIN on your queries.