SELECT DISTINCT a.*, b.*
FROM current_tbl a
LEFT JOIN import_tbl b
ON ( a.user_id = b.user_id
OR ( a.f_name||' '||a.l_name = b.f_name||' '||b.l_name)
)
Two tables that are basically the same
I don't have access to the table structure or data input (thus no cleaning up primary keys)
Sometimes the user_id is populated in one and not the other
Sometimes names are equal, sometimes they are not
I've found that I can get the most of the data by matching on user_id or the first/last names. I'm using the ' ' between the names to avoid cases where one user has the same first name as another's last name and both are missing the other field (unlikely, but plausible).
This query runs in 33000ms, whereas individualized they are each about 200ms.
I've been up late and can't think straight right now
I'm thinking that I could do a UNION and only query by name where a user_id does not exist (the default join is the user_id, if a user_id doesn't exist then I want to join by the name)
Here is some free points to anyone that wants to help
Please don't ask for the execution plan.
Looks like you can easily avoid the string concatenation:
OR ( a.f_name||' '||a.l_name = b.f_name||' '||b.l_name)
Change it to:
OR ( a.f_name = b.f_name AND a.l_name = b.l_name)
Rather than concatenating first and last name and comparing them, try comparing them individually instead. Assuming you have them (and you should create them if you don't), this should improve your chances of using indexes on the first name and last name columns.
SELECT DISTINCT a.*, b.*
FROM current_tbl a
LEFT JOIN import_tbl b
ON ( a.user_id = b.user_id
OR (a.f_name = b.f_name and a.l_name = b.l_name)
)
If people's suggestions don't provide a major speed increase, there is a possibility that your real problem is that the best query plan for your two possible join conditions is different. For that situation you would want to do two queries and merge results in some way. This is likely to make your query much, much uglier.
One obscure trick that I have used for that kind of situation is to do a GROUP BY off of a UNION ALL query. The idea looks like this:
SELECT a_field1, a_field2, ...
MAX(b_field1) as b_field1, MAX(b_field2) as b_field2, ...
FROM (
SELECT a.field_1 as a_field1, ..., b.field1 as b_field1, ...
FROM current_tbl a
LEFT JOIN import_tbl b
ON a.user_id = b.user_id
UNION ALL
SELECT a.field_1 as a_field1, ..., b.field1 as b_field1, ...
FROM current_tbl a
LEFT JOIN import_tbl b
ON a.f_name = b.f_name AND a.l_name = b.l_name
)
GROUP BY a_field1, a_field2, ...
And now the database can do each of the two joins using the most efficient plan.
(Warning of a drawback in this approach. If a row in current_tbl joins to multiple rows in import_tbl, then you'll wind up merging data in a very odd way.)
Incidental random performance tip. Unless you have reason to believe that there are potential duplicate rows, avoid DISTINCT. It forces an implicit GROUP BY, which can be expensive.
I don't really understand why you're concatenating those strings. Seems like that's where your slowdown would be. Does this work instead?
SELECT DISTINCT a.*, b.*
FROM current_tbl a
LEFT JOIN import_tbl b
ON ( a.user_id = b.user_id
OR ( a.f_name = b.f_name AND a.l_name = b.l_name)
)
Here is Yet Another Ugly Way To Do It.
SELECT a.*
, CASE WHEN b.user_id IS NULL THEN c.field1 ELSE b.field1 END as b_field1
, CASE WHEN b.user_id IS NULL THEN c.field2 ELSE b.field2 END as b_field2
...
FROM current_tbl a
LEFT JOIN import_tbl b
ON a.user_id = b.user_id
LEFT JOIN import_tbl c
ON a.f_name = c.f_name AND a.l_name = c.l_name;
This avoids any GROUP BY, and also handles conflicting matches in a somewhat reasonable way.
Try using JOIN hints:
http://msdn.microsoft.com/en-us/library/ms173815.aspx
We were encountering the same type of behavior with one of our queries. As a last resort we added the LOOP hint, and the query ran much much faster.
It's important to note that Microsoft says this about JOIN hints:
Because the SQL Server query optimizer typically selects the best execution plan for a query, we recommend that hints, including , be used only as a last resort by experienced developers and database administrators.
my boss at my last job.. I swear.. he thought that using UNIONS was ALWAYS FASTER THAN OR.
For example.. instead of writing
Select * from employees Where Employee_id = 12 or employee_id = 47
he would write (and have me write)
Select * from employees Where employee_id = 12
UNION
Select * from employees Where employee_id = 47
SQL Sever optimizer said that this was the right thing to do in SOME situations.. I have a friend who works on the SQL Server team at Microsoft, I emailed him about this and he told me that my stats were out of date or something along those lines.
I never really got a good answer on WHY the unions are faster, it seems REALLY counter-intuitive.
I'm not recommending you DO this, but in some situations it can help.
Also two more things-- GET RID OF THE DISTINCT CLAUSE unless you absolutely need it.. n
and more importantly, you can easily get rid of the concatenation in your join, like this for example (pardon my lack of mySQL knowledge)
SELECT DISTINCT a., b.
FROM current_tbl a
LEFT JOIN import_tbl b
ON ( a.user_id = b.user_id
OR ( a.f_name = b.f_name and a.l_name = b.l_name)
)
I've had some tests at work in a similiar situation that show 10x performance improvement by getting rid of the simple concatenation in your join
Related
How I can add two fields that belong to an inner join?
I have this code:
select
SUM(ACT.NumberOfPlants ) AS NumberOfPlants,
SUM(ACT.NumOfJornales) AS NumberOfJornals
FROM dbo.AGRMastPlanPerformance MPR (NOLOCK)
INNER JOIN GENRegion GR ON (GR.intGENRegionKey = MPR.intGENRegionLink )
INNER JOIN AGRDetPlanPerformance DPR (NOLOCK) ON
(DPR.intAGRMastPlanPerformanceLink =
MPR.intAGRMastPlanPerformanceKey)
INNER JOIN vwGENPredios P โโ(NOLOCK) ON ( DPR.intGENPredioLink =
P.intGENPredioKey )
INNER JOIN AGRSubActivity SA (NOLOCK) ON (SA.intAGRSubActivityKey =
DPR.intAGRSubActivityLink)
LEFT JOIN (SELECT RA.intGENPredioLink, AR.intAGRActividadLink,
AR.intAGRSubActividadLink, SUM(AR.decNoPlantas) AS
intPlantasTrabajads, SUM(AR.decNoPersonas) AS NumOfJornales,
SUM(AR.decNoPlants) AS NumberOfPlants
FROM AGRRecordActivity RA WITH (NOLOCK)
INNER JOIN AGRActividadRealizada AR WITH (NOLOCK) ON
(AR.intAGRRegistroActividadLink = RA.intAGRRegistroActividadKey AND
AR.bitActivo = 1)
INNER JOIN AGRSubActividad SA (NOLOCK) ON (SA.intAGRSubActividadKey
= AR.intAGRSubActividadLink AND SA.bitEnabled = 1)
WHERE RA.bitActive = 1 AND
AR.bitActive = 1 AND
RA.intAGRTractorsCrewsLink IN(2)
GROUP BY RA.intGENPredioLink,
AR.decNoPersons,
AR.decNoPlants,
AR.intAGRAActivityLink,
AR.intAGRSubActividadLink) ACT ON (ACT.intGENPredioLink IN(
DPR.intGENPredioLink) AND
ACT.intAGRAActivityLink IN( DPR.intAGRAActivityLink) AND
ACT.intAGRSubActivityLink IN( DPR.intAGRSubActivityLink))
WHERE
MPR.intAGRMastPlanPerformanceKey IN(4) AND
DPR.intAGRSubActivityLink IN( 1153)
GROUP BY
P.vchRegion,
ACT.NumberOfFloors,
ACT.NumOfJournals
ORDER BY ACT.NumberOfFloors DESC
However, it does not perform the complete sum. It only retrieves all the values โโof the columns and adds them 1 by 1, instead of doing the complete sum of the whole column.
For example, the query returns these results:
What I expect is the final sums. In NumberOfPlants the result of the sum would be 163,237 and of NumberJornales would be 61.
How can I do this?
First of all the (nolock) hints are probably not accomplishing the benefit you hope for. It's not an automatic "go faster" option, and if such an option existed you can be sure it would be already enabled. It can help in some situations, but the way it works allows the possibility of reading stale data, and the situations where it's likely to make any improvement are the same situations where risk for stale data is the highest.
That out of the way, with that much code in the question we're better served with a general explanation and solution for you to adapt.
The issue here is GROUP BY. When you use a GROUP BY in SQL, you're telling the database you want to see separate results per group for any aggregate functions like SUM() (and COUNT(), AVG(), MAX(), etc).
So if you have this:
SELECT Sum(ColumnB) As SumB
FROM [Table]
GROUP BY ColumnA
You will get a separate row per ColumnA group, even though it's not in the SELECT list.
If you don't really care about that, you can do one of two things:
Remove the GROUP BY If there are no grouped columns in the SELECT list, the GROUP BY clause is probably not accomplishing anything important.
Nest the query
If option 1 is somehow not possible (say, the original is actually a view) you could do this:
SELECT SUM(SumB)
FROM (
SELECT Sum(ColumnB) As SumB
FROM [Table]
GROUP BY ColumnA
) t
Note in both cases any JOIN is irrelevant to the issue.
I have three tables:
articles(id,title,message)
comments(id,article_id,commentedUser_id,comment)
comment_likes(id, likedUser_id, comment_id, action_like, action_dislike)
I want to show comments.id, comments.commentedUser_id, comments.comment, ( Select count(action_like) where action_like="like") as likes and comment_id=comments.id where comments.article_id=article.id
Actually I want to count all action_likes that related to any comment. And show all all comments of articles.
action_likes having only two values null or like
SELECT c.id , c.CommentedUser_id , c.comment , (cl.COUNT(action_like) WHERE action_like='like' AND comment_id='c.id') as likes
FROM comment_likes as cl
LEFT JOIN comments as c ON c.id=cl.comment_id
WHERE c.article_id=article.id
It shows nothing, I know I'm doing wrong way, that was just that I want say
I guess you are looking for something like below. This will return Article/Comment wise LIKE count.
SELECT
a.id article_id,
c.id comment_id,
c.CommentedUser_id ,
c.comment ,
COUNT (CASE WHEN action_like='like' THEN 1 ELSE NULL END) as likes
FROM article a
INNER JOIN comments C ON a.id = c.article_id
LEFT JOIN comment_likes as cl ON c.id=cl.comment_id
GROUP BY a.id,c.id , c.CommentedUser_id , c.comment
IF you need results for specific Article, you can add WHERE clause before the GROUP BY section like - WHERE a.id = N
I would recommend a correlated subquery for this:
SELECT a.id as article_id, c.id as comment_id,
c.CommentedUser_id, c.comment,
(SELECT COUNT(*)
FROM comment_likes cl
WHERE cl.comment_id = c.id AND
cl.action_like = 'like'
) as num_likes
FROM article a INNER JOIN
comments c
ON a.id = c.article_id;
This is a case where a correlated subquery often has noticeably better performance than an outer aggregation, particularly with the right index. The index you want is on comment_likes(comment_id, action_like).
Why is the performance better? Most databases will implement the group by by sorting the data. Sorting is an expensive operation that grows super-linearly -- that is, twice as much data takes more than twice as long to sort.
The correlated subquery breaks the problem down into smaller pieces. In fact, no sorting should be necessary -- just scanning the index and counting the matching rows.
How can we reduce the Execution time of the below query?
Need help in rewriting below SQL query in a more efficient way?
SELECT A.*, C.*, F.*, D.*
FROM TABLE1 A INNER JOIN
TABLE2 C
ON A.CODE = C.CODE INNER JOIN
TABLE3 D
ON A.CODE = D.CODE INNER JOIN
TABLE4 F
ON A.CODE = F.CODE
WHERE D.IND1 = 'N' AND
D.IND2 = 'N' AND
D.EFF_DATE = (SELECT MAX(X.EFF_DATE)
FROM TABLE3 X
WHERE X.CODE = D.CODE AND X.EFF_DATE <= A.EFFECTIVE_DATE
) AND
F.EFF_DATE = (SELECT MAX(Z.EFF_DATE)
FROM TABLE4 Z
WHERE Z.DETAIL_CODE = F.DETAIL_CODE AND Z.EFF_DATE <= A.EFFECTIVE_DATE
)
For performance, I would start with indexes on:
TABLE3(IND1, IND2, CODE, EFF_DATE)
TABLE3(CODE, EFF_DATE)
TABLE1(CODE, EFF_DATE)
TABLE2(CODE)
TABLE4(CODE)
TABLE4(DETAIL_CODE, EFF_DATE)
If you have performance issues, though, I suspect your code may be generating unexpected Cartesian products. Debugging that requires much more information. I might suggest asking another question.
If you can find out where the bottlenecks in your query are -- i.e. sub-queries, joins -- that will give you a better idea of what to look at. In the absence of that, take a look at:
modify your column projections (i.e. A., C., F., D.) to only return the columns you need
look at table partitioning for the queries accessing rows based on DATE values (TABLE3.EFF_DATE, TABLE4.EFF_DATE) (http://www.oracle.com/technetwork/issue-archive/2006/06-sep/o56partition-090450.html)
look at adding materialized view(s) either on the entire query OR the sub-queries (https://oracle-base.com/articles/misc/materialized-views)
look at statistic generation if the query plan is not optimal (https://docs.oracle.com/cd/A97630_01/server.920/a96533/stats.htm#26713)
If you can provide an EXPLAIN plan (or Oracle's equivalent), that would be helpful.
Note that because of the conditions on the two sub-queries all the records in your result will have D.EFF_DATE <= A.EFFECTIVE_DATE and F.EFF_DATE <= A.EFFECTIVE_DATE, so I would suggest to put those conditions in the JOIN clauses.
Secondly, analytic functions may give better performance than subqueries:
SELECT *
FROM (
SELECT A.*,C.*,F.*,D.*,
RANK() OVER (PARTITION BY D.CODE
ORDER BY D.EFF_DATE DESC) AS D_RANK,
RANK() OVER (PARTITION BY F.DETAIL_CODE
ORDER BY F.EFF_DATE DESC) AS F_RANK
FROM TABLE1 A
INNER JOIN TABLE2 C
ON A.CODE = C.CODE
INNER JOIN TABLE3 D
ON A.CODE = D.CODE
AND D.EFF_DATE <= A.EFFECTIVE_DATE
INNER JOIN TABLE4 F
ON A.CODE = F.CODE
AND F.EFF_DATE <= A.EFFECTIVE_DATE
WHERE D.IND1 = 'N'
AND D.IND2 = 'N'
)
WHERE D_RANK = 1 AND F_RANK = 1
Evidently you need to have the right indexes to optimise the execution plan.
Another thing to consider is the total number of columns your query returns, you seem to be selecting all the columns from 4 tables.
We found that our complex queries ran in under a second when selecting only a few columns but took orders of magnitude longer when selecting many columns.
Question why you need so many columns in your result set.
I'm trying to count authors who don't have any articles in our system, which aggregates authorship across sites. I've got a query working, but it isn't performant.
The best query I have thus far is this:
select count(*) as count_all
from (
select authors.id
from authors
left outer join site_authors on site_authors.author_id = authors.id
left outer join articles on articles.site_author_id = site_authors.id
group by authors.id
having count(articles.id) = 0
) a;
However, the subquery is rather inefficient. I was hoping there's a way to flatten this. I have several similar queries that add extra conditions on the left outer joins, so adding a count column to my schema isn't really an option here.
Extra rub: this is a cross-platform query and needs to work against both pgSQL, SQLite, and MySQL.
you can try a little bit different query, but I'm not sure that it will be faster:
select count(*)
from authors as a
where not exists (
select b.id
from site_authors as b
inner join
articles as c
on a.id=b.author_id and b.id=c.site_author_id)
of course I suppose you have proper indexes on tables:
site_authors: unique (author_id, id)
articles: non unique (site_author_id)
Assuming that 'normal' joins are simpler and faster, you could subtract the number of authors with articles from the total number of authors:
SELECT (SELECT COUNT(*)
FROM authors) -
(SELECT COUNT(DISTINCT site_authors.author_id)
FROM site_authors
JOIN articles ON articles.site_author_id = site_authors.id)
Alternatively, try a subquery:
SELECT COUNT(*)
FROM authors
WHERE id NOT IN (SELECT site_authors.author_id
FROM site_authors
JOIN articles ON articles.site_author_id = site_authors.id)
It might be simpler and faster to use NOT IN rather than a join. Sql processors are pretty smart about using indexes even when it looks obtuse. Something like this:
Select count(*)
from authors
where id not in (select author_id from site_authors)
and id not in (select site_author_id from articles);
Be sure that author_id and site_author_id are indexed. The optimizer will notice what your are doing and create an indexed look up for the "NOT IN" clause.
I have this SELECT query:
SELECT Auctions.ID, Users.Balance, Users.FreeBids,
COUNT(CASE WHEN Bids.Burned=0 AND Auctions.Closed=0 THEN 1 END) AS 'ActiveBids',
COUNT(CASE WHEN Bids.Burned=1 AND Auctions.Closed=0 THEN 1 END) AS 'BurnedBids'
FROM (Users INNER JOIN Bids ON Users.ID=Bids.BidderID)
INNER JOIN Auctions
ON Bids.AuctionID=Auctions.ID
WHERE Users.ID=#UserID
GROUP BY Users.Balance, Users.FreeBids, Auctions.ID
My problam is that it returns no rows if the UserID cant be found on the Bids table.
I know it's something that has to do with my
(Users INNER JOIN Bids ON Users.ID=Bids.BidderID)
But i dont know how to make it return even if the user is no on the Bids table.
You're doing an INNER JOIN, which only returns rows if there are results on both sides of the join. To get what you want, change your WHERE clause like this:
Users LEFT JOIN Bids ON Users.ID=Bids.BidderID
You may also have to change your SELECT statement to handle Bids.Burned being NULL.
If you want to return rows even if there's no matching Auction, then you'll have to make some deeper changes to your query.
My problam is that it returns no rows if the UserID cant be found on the Bids table.
Then INNER JOIN Bids/Auctions should probably be left outer joins. The way you've written it, you're filtering users so that only those in bids and auctions appear.
Left join is the simple answer, but if you're worried about performance I'd consider re-writing it a little bit. For one thing, the order of the columns in the group by matters to performance (although it often doesn't change the results). Generally, you want to group by a column that's indexed first.
Also, it's possible to re-write this query to only have one group by, which will probably speed things up.
Try this out:
with UserBids as (
select
a.ID
, b.BidderID
, ActiveBids = count(case when b.Burned = 0 then 1 end)
, BurnedBids = count(case when b.Burned = 0 then 1 end)
from Bids b
join Auctions a
on a.ID = b.AuctionID
where a.Closed = 0
group by b.BidderID, a.AuctionID
)
select
b.ID
, u.Balance
, u.FreeBids
, b.ActiveBids
, b.BurnedBids
from Users u
left join UserBids b
on b.BidderID = u.ID
where u.ID = #UserID;
If you're not familiar with the with UserBids as..., it's called a CTE (common table expression), and is basically a way to make a one-time use view, and a nice way to structure your queries.