I'm making a sample recent screen that will display a list, it displays the list, with id set as primary key.
I have done the correct query as expected but the table with big amount of data can cause slow performance issues.
This is the sample query below:
SELECT distinct H.id -- (Primary Key),
H.partnerid as PartnerId,
H.partnername AS partner, H.accountname AS accountName,
H.accountid as AccountNo,
FROM myschema.mytransactionstable H
INNER JOIN (
SELECT S.accountid, S.partnerid, S.accountname,
max(S.transdate) AS maxDate
from myschema.mytransactionstable S
group by S.accountid, S.partnerid, S.accountname
) ms ON H.accountid = ms.accountid
AND H.partnerid = ms.partnerid
AND H.accountname =ms.accountname
AND H.transdate = maxDate
WHERE H.accountid = ms.accountid
AND H.partnerid = ms.partnerid
AND H.accountname = ms.accountname
AND H.transdate = maxDate
GROUP BY H.partnerid,H.accountid, H.accountname
ORDER BY H.id DESC
LIMIT 5
In my case, there are values which are similar in the selected columns but differ only in their id's
Below is a link to an image without executing the query above. They are all the records that have not yet been filtered.
Sample result query click here
Since I only want to get the 5 most recent by their id but the other columns can contain similar values
accountname,accountid,partnerid.
I already got the correct query but,
I want to improve the performance of the query. Any suggestions for the improvement of query?
You can try using row_number()
select * from
(
select *,row_number() over(order by transdate desc) as rn
from myschema.mytransactionstable
)A where rn<=5
Don't repeat ON and WHERE clauses. Use ON to say how the tables (or subqueries) are "related"; use WHERE for filtering (that is, which rows to keep). Probably in your case, all the WHERE should be removed.
Please provide SHOW CREATE TABLE
This 'composite' index would probably help because of dealing with the subquery and the JOIN:
INDEX(partnerid, accountid, accountname, transdate)
That would also avoid a separate sort for the GROUP BY.
But then the ORDER BY is different, so it cannot avoid a sort.
This might avoid the sort without changing the result set ordering: ORDER BY partnerid, accountid, accountname, transdate DESC
Please provide EXPLAIN SELECT ... and EXPLAIN FORMAT=JSON SELECT ... if you have further questions.
If we cannot get an index to handle the WHERE, GROUP BY, and ORDER BY, the query will generate all the rows before seeing the LIMIT 5. If the index does work, then the outer query will stop after 5 -- potentially a big savings.
When executed, is there any difference at between the following two sql queries:
SELECT name, count(*) FROM mytable GROUP BY name HAVING count(*) > 1
And:
SELECT * from (SELECT name, count(*) cnt FROM mytable GROUP BY name) x where cnt > 1
In other words, is having more a "convenience" clause to simplify having to do subselect, or does the query engine fundamentally performance different when a having statement is used vs the second approach? Currently in mysql:
Create table:
CREATE TABLE `mytable` (
`name` varchar(20) NOT NULL DEFAULT ''
) ENGINE=InnoDB DEFAULT CHARSET=utf-8;
In almost any other database, the two would be equivalent. For conciseness, HAVING is usually a better choice.
At least historically, MySQL materialized subqueries. So, this query:
SELECT *
FROM (SELECT name, count(*) as cnt
FROM mytable
GROUP BY name
) x
WHERE cnt > 1;
suggests that it is going to write out the derived table, and then re-scan it for the final WHERE. However, this makes little difference to performance because the GROUP BY is already reading and writing the data.
So, these queries are probably quite similar in performance on MySQL. And, they would have the same execution plan on almost any other database. The HAVING clause results in the simpler query.
I have a SQL query (MYSQL) that I would like to go faster. The general problem is to count distinct keys that has an aggregated condition on them. That is, I like to sum the values of a column in the rows with the same key value and then determine if it should be included in the count. The only solution I have come up with is to do a sub-query that do the summing and then count distinct in the outer query using having there. Like:
SELECT COUNT(DISTINCT key), sum1, sum2, categoryid
FROM
(
SELECT SUM(cnt1) AS sum1,
SUM(cnt2) AS sum2,
key,categoryid
FROM table
GROUP BY key,categoryid
) as SUBQUERY
GROUP BY categoryid
HAVING (8*sum1)/sum2 > 0;
The problem (as I see it) is that the query use a sub-query that will produce a temp table. As the data set large (10M rows, 500K distinct keys) it takes a lot of time. It looks like it should be possible to do better as a straight distinct count without the condition takes just a tenth of the time of this query and summing without grouping takes only a fraction of that.
Anyone with ideas on how to improve on performance?
Thanks in advance!
Lasse
I actually was able to cut the response time myself by moving the count distinct to the inner query. Don't know why I didn't see that earlier. Obviously makes the temp table smaller. However it is still a factor 4-5 slower than the distinct count without a condition.
The new select looks like:
SELECT dist_cnt, sum1, sum2, categoryid
FROM
(
SELECT COUNT(DISTINCT key) AS dist_cnt,
SUM(cnt1) AS sum1,
SUM(cnt2) AS sum2,
key,categoryid
FROM table
GROUP BY key,categoryid
) as SUBQUERY
WHERE (8*sum1)/sum2 > 0
GROUP BY categoryid
Anyway, I think it should be possible to get it at least a factor 2 faster.
Lasse
I am trying to optimize queries to my database. I have the following query:
select date, (
select count(user_id)
from myTable
where logdate = date
) as value
from myTable;
As far as I can see, the second value is computed efficiently. However, is there any common practice to optimize this kind of query in MySQL?
I believe you can avoid writing a subquery and preform the same query using aggregation, which may run faster:
SELECT date, COUNT(user_id) AS numRecords
FROM myTable
GROUP BY date;
Here is a reference on aggregate functions.
you do not have to put group functions in a separate select. Just do
select date, count(user_id) from myTable group by date;
There is no hard and fast. In this query, it was a matter of one select being more efficient than 2. But here is some tips for beginners on optimizing queries.
If I have a table
CREATE TABLE users (
id int(10) unsigned NOT NULL auto_increment,
name varchar(255) NOT NULL,
profession varchar(255) NOT NULL,
employer varchar(255) NOT NULL,
PRIMARY KEY (id)
)
and I want to get all unique values of profession field, what would be faster (or recommended):
SELECT DISTINCT u.profession FROM users u
or
SELECT u.profession FROM users u GROUP BY u.profession
?
They are essentially equivalent to each other (in fact this is how some databases implement DISTINCT under the hood).
If one of them is faster, it's going to be DISTINCT. This is because, although the two are the same, a query optimizer would have to catch the fact that your GROUP BY is not taking advantage of any group members, just their keys. DISTINCT makes this explicit, so you can get away with a slightly dumber optimizer.
When in doubt, test!
If you have an index on profession, these two are synonyms.
If you don't, then use DISTINCT.
GROUP BY in MySQL sorts results. You can even do:
SELECT u.profession FROM users u GROUP BY u.profession DESC
and get your professions sorted in DESC order.
DISTINCT creates a temporary table and uses it for storing duplicates. GROUP BY does the same, but sortes the distinct results afterwards.
So
SELECT DISTINCT u.profession FROM users u
is faster, if you don't have an index on profession.
All of the answers above are correct, for the case of DISTINCT on a single column vs GROUP BY on a single column.
Every db engine has its own implementation and optimizations, and if you care about the very little difference (in most cases) then you have to test against specific server AND specific version! As implementations may change...
BUT, if you select more than one column in the query, then the DISTINCT is essentially different! Because in this case it will compare ALL columns of all rows, instead of just one column.
So if you have something like:
// This will NOT return unique by [id], but unique by (id,name)
SELECT DISTINCT id, name FROM some_query_with_joins
// This will select unique by [id].
SELECT id, name FROM some_query_with_joins GROUP BY id
It is a common mistake to think that DISTINCT keyword distinguishes rows by the first column you specified, but the DISTINCT is a general keyword in this manner.
So people you have to be careful not to take the answers above as correct for all cases... You might get confused and get the wrong results while all you wanted was to optimize!
Go for the simplest and shortest if you can -- DISTINCT seems to be more what you are looking for only because it will give you EXACTLY the answer you need and only that!
well distinct can be slower than group by on some occasions in postgres (dont know about other dbs).
tested example:
postgres=# select count(*) from (select distinct i from g) a;
count
10001
(1 row)
Time: 1563,109 ms
postgres=# select count(*) from (select i from g group by i) a;
count
10001
(1 row)
Time: 594,481 ms
http://www.pgsql.cz/index.php/PostgreSQL_SQL_Tricks_I
so be careful ... :)
Group by is expensive than Distinct since Group by does a sort on the result while distinct avoids it. But if you want to make group by yield the same result as distinct give order by null ..
SELECT DISTINCT u.profession FROM users u
is equal to
SELECT u.profession FROM users u GROUP BY u.profession order by null
It seems that the queries are not exactly the same. At least for MySQL.
Compare:
describe select distinct productname from northwind.products
describe select productname from northwind.products group by productname
The second query gives additionally "Using filesort" in Extra.
In MySQL, "Group By" uses an extra step: filesort. I realize DISTINCT is faster than GROUP BY, and that was a surprise.
After heavy testing we came to the conclusion that GROUP BY is faster
SELECT sql_no_cache
opnamegroep_intern
FROM telwerken
WHERE opnemergroep IN (7,8,9,10,11,12,13) group by opnamegroep_intern
635 totaal 0.0944 seconds
Weergave van records 0 - 29 ( 635 totaal, query duurde 0.0484 sec)
SELECT sql_no_cache
distinct (opnamegroep_intern)
FROM telwerken
WHERE opnemergroep IN (7,8,9,10,11,12,13)
635 totaal 0.2117 seconds ( almost 100% slower )
Weergave van records 0 - 29 ( 635 totaal, query duurde 0.3468 sec)
(more of a functional note)
There are cases when you have to use GROUP BY, for example if you wanted to get the number of employees per employer:
SELECT u.employer, COUNT(u.id) AS "total employees" FROM users u GROUP BY u.employer
In such a scenario DISTINCT u.employer doesn't work right. Perhaps there is a way, but I just do not know it. (If someone knows how to make such a query with DISTINCT please add a note!)
Here is a simple approach which will print the 2 different elapsed time for each query.
DECLARE #t1 DATETIME;
DECLARE #t2 DATETIME;
SET #t1 = GETDATE();
SELECT DISTINCT u.profession FROM users u; --Query with DISTINCT
SET #t2 = GETDATE();
PRINT 'Elapsed time (ms): ' + CAST(DATEDIFF(millisecond, #t1, #t2) AS varchar);
SET #t1 = GETDATE();
SELECT u.profession FROM users u GROUP BY u.profession; --Query with GROUP BY
SET #t2 = GETDATE();
PRINT 'Elapsed time (ms): ' + CAST(DATEDIFF(millisecond, #t1, #t2) AS varchar);
OR try SET STATISTICS TIME (Transact-SQL)
SET STATISTICS TIME ON;
SELECT DISTINCT u.profession FROM users u; --Query with DISTINCT
SELECT u.profession FROM users u GROUP BY u.profession; --Query with GROUP BY
SET STATISTICS TIME OFF;
It simply displays the number of milliseconds required to parse, compile, and execute each statement as below:
SQL Server Execution Times:
CPU time = 0 ms, elapsed time = 2 ms.
SELECT DISTINCT will always be the same, or faster, than a GROUP BY. On some systems (i.e. Oracle), it might be optimized to be the same as DISTINCT for most queries. On others (such as SQL Server), it can be considerably faster.
This is not a rule
For each query .... try separately distinct and then group by ... compare the time to complete each query and use the faster ....
In my project sometime I use group by and others distinct
If you don't have to do any group functions (sum, average etc in case you want to add numeric data to the table), use SELECT DISTINCT. I suspect it's faster, but i have nothing to show for it.
In any case, if you're worried about speed, create an index on the column.
If the problem allows it, try with EXISTS, since it's optimized to end as soon as a result is found (And don't buffer any response), so, if you are just trying to normalize data for a WHERE clause like this
SELECT FROM SOMETHING S WHERE S.ID IN ( SELECT DISTINCT DCR.SOMETHING_ID FROM DIFF_CARDINALITY_RELATIONSHIP DCR ) -- to keep same cardinality
A faster response would be:
SELECT FROM SOMETHING S WHERE EXISTS ( SELECT 1 FROM DIFF_CARDINALITY_RELATIONSHIP DCR WHERE DCR.SOMETHING_ID = S.ID )
This isn't always possible but when available you will see a faster response.
in mySQL i have found that GROUP BY will treat NULL as distinct, while DISTINCT does not.
Took the exact same DISTINCT query, removed the DISTINCT, and added the selected fields as the GROUP BY, and i got many more rows due to one of the fields being NULL.
So.. I tend to believe that there is more to the DISTINCT in mySQL.