Can someone explain this to me?
I have two huge tables on which I wish to LEFT JOIN, but I think it would be more efficient to filter at the 'on' rather than the 'where'.
Select * from Table1 t1 left join Table2 t2 on t1.Id = t2.Id and t1.Enabled = 1
Rather than
Select * from Table1 t1 left join Table2 t2 on t1.Id = t2.Id where t1.Enabled = 1
The above results are not the same. No matter what I put in as filtering, it stays unaffected:
Select * from Table1 t1 left join Table2 t2 on t1.Id = t2.Id and t1.Enabled = 1
yields exactly the same results as
Select * from Table1 t1 left join Table2 t2 on t1.Id = t2.Id and t1.Enabled = 0
Also, Table1 might only have a few records where Enabled = 1, so it would be inefficient to join millions of records first and then filter to find only 10.
I can do a sub select first, but I somehow I feel it is not the right way:
Select * from (Select * from Table1 where Enabled = 1) a left join Table2 t2 on a.Id = t2.Id
Types of Joins
Left outer join All rows from the first-named table (the "left"
table, which appears leftmost in the JOIN clause) are included.
Unmatched rows in the right table do not appear.
When you move the condition to the where then t1.Enabled = 1 is applied
Do you have actual performance problems with the first query?
Related
I have three table valued parameters passed into an SP. These all contain data to filter a query. I want to join them to a table as below but only if there is data in a table valued parameter
SELECT DISTINCT TOP (1000)
Person.col1,
Person.col2,
FROM dbo.Person INNER JOIN
#tbl1 t1 ON Person.col3 = t1.val INNER JOIN
#tbl2 t2 ON Person.col4 = t2.val INNER JOIN
#tbl3 t3 ON Person.col5 = t3.val
I am aware I can do a Left Outer Join but I don't want results with NULL values. The top 1000 necessary as there is a lot of data and scanning the whole table causes performance issues
Try use coalesce to cater nulls check
SELECT DISTINCT TOP (1000)
Person.col1,
Person.col2,
FROM dbo.Person INNER JOIN
#tbl1 t1 ON coalesce(Person.col3, '111') = t1.val INNER JOIN
#tbl2 t2 ON coalesce(Person.col4 , '111')= t2.val INNER JOIN
#tbl3 t3 ON coalesce(Person.col5, '111') = t3.val
I have three table, table_1 (id), table_2(id), table_pivot(tbl1_id, tbl2_id). When I use query like this:
select *
from public.table_1 t1
left join public.table_pivot tp on tp.tbl1_id = t1.id and tp.user_id = 1
left join public.table_2 t2 on t2.id = tp.tbl2_id;
Data from table_1 is show. But when I use where condition. Like this:
select *
from public.table_1 t1
left join public.table_pivot tp on tp.tbl1_id = t1.id
left join public.table_2 t2 on t2.id = tp.tbl2_id
where tp.user_id = 1;
Data from table_1 not show.
I hope advance can help explain why?
Thanks.
Including a where clause on an outer joined table, effectively converts the join into an inner join. If there are no matching values in table_pivot, then
you will get no results at all. This is standard sql.
Below sample query is a part of my main query. I found SORT operator in below query is consuming 30% of the cost.
To avoid SORT, there is need of creation of Indexes. Is there any other way to optimize this code.
SELECT TOP 1 CONVERT( DATE, T_Date) AS T_Date
FROM TableA
WHERE ID = r.ID
AND Status = 3
AND TableA_ID >ISNULL((
SELECT TOP 1 TableA_ID
FROM TableA
WHERE ID = r.ID
AND Status <> 3
ORDER BY T_Date DESC
), 0)
ORDER BY T_Date ASC
Looks like you can use not exists rather than the sorts. I think you'll probably get a better performance boost by use a CTE or derived table instead of the a scalar subquery.
select *
from r ... left outer join
(
select ID, min(t_date) as min_date from TableA t1
where status = 3 and not exists (
select 1 from TableA t2
where t2.ID = t1.ID
and t2.status <> 3 and t2.t_date > t1.t_date
)
group by ID
) as md on md.ID = r.ID ...
or
select *
from r ... left outer join
(
select t1.ID, min(t1.t_date) as min_date
from TableA t1 left outer join TableA t2
on t2.ID = t1.ID and t2.status <> 3
where t1.status = 3 and t1.t_date < t2.t_date
group by t1.ID
having count(t2.ID) = 0
) as md on md.ID = r.ID ...
It also appears that you're relying on an identity column but it's not clear what those values mean. I'm basically ignoring it and using the date column instead.
Try this:
SELECT TOP 1 CONVERT( DATE, T_Date) AS T_Date
FROM TableA a1
LEFT JOIN (
SELECT ID, MAX(TableA_ID) AS MaxAID
FROM TableA
WHERE Status <> 3
GROUP BY ID
) a2 ON a2.ID = a1.ID AND a1.TableA_ID > coalesce(a2.MAXAID,0)
WHERE a1.ID = r.ID AND a1.Status = 3
ORDER BY T_Date ASC
The use of TOP 1 in combination with the unexplained r alias concern me. There's almost certainly a MUCH better way to get this data into your results that doesn't involve doing this in a sub query (unless this is for an APPLY operation).
I am trying to use a correlated subquery, but I am trying to limit it to the "best" record. When I use SQL very similiar to what follows, I get two rows per BigTable.identifier, and I wish to have only one. In the 'UNION' statement, the second half is more desirable than the first half. However, sometimes the first half will be needed. Any ideas? Here's the code:
select
BigTable.identifier,
Correlated.ID,
Correlated.Effective_Date,
Correlated.Period_Number
from
BigTable
inner join
(
select
TOP 2147483647
Table3.identifier,
Table4.Effective_Date,
Table4.Period_Number
from
Table3
inner join Table4 on Table3.matching_key = Table4.matching_key
where
Table4.Period_Number = 0
order by Table4.Effective_Date desc
UNION
select
TOP 2147483647
Table3.Identifer,
Table4.Effective_Date,
Table4.Period_Number
from
Table3
inner join Table5 on Table3.matching-key = Table5.matching-key
inner join Table4 on Table5.key1 = Table4.key1 and
Table5.key2 = Table4.key2
where
Table4.period_number = 1
order by Table4.Effective_Date desc
) as Correlated
on BigTable.identifier = Correlated.identifier
If each sub-query in that UNION had some condition which EXCLUDED the row if it was less-preferred, you would never see the less-preferred rows in the UNION.
So, if each were to have a NOT EXISTS (.... a better row in the other side of the union ....), you would eliminate less-preferred rows at the root.
I'm not clear on how you want to use effective date. Assuming you mean that you prefer Period=1 but if the Effective date is less you prefer Period=0, then something like this might work.
select
BigTable.identifier,
Correlated.ID,
Correlated.Effective_Date,
Correlated.Period_Number
from
BigTable
inner join
(
select
TOP 2147483647
Table3.identifier,
Table4.Effective_Date,
Table4.Period_Number
from
Table3
inner join Table4 on Table3.matching_key = Table4.matching_key
where
Table4.Period_Number = 0
AND NOT EXISTS
(select 1
from Table5 T5 inner join Table4 T4
on T5.key1 = T4.key1 and T5.key2 = T4.key2
where Table3.matching-key = T5.matching-key
and (T4.Effective_Date >= Table4.Effective_Date and T4.Period_Number = 1)
)
order by Table4.Effective_Date desc
UNION
select
TOP 2147483647
Table3.Identifer,
Table4.Effective_Date,
Table4.Period_Number
from
Table3
inner join Table5 on Table3.matching-key = Table5.matching-key
inner join Table4 on Table5.key1 = Table4.key1 and
Table5.key2 = Table4.key2
where
Table4.period_number = 1
AND NOT EXISTS
(select 1
from Table4 T4
where Table3.matching-key = T4.matching-key
and (T4.Period_Number > 0)
and (T4.Effective_Date > Table4.Effective_Date and T4.Period_Number = 0)
)
order by Table4.Effective_Date desc
) as Correlated
on BigTable.identifier = Correlated.identifier
I have a db schema and I am quite not so familiar with T-SQL, I know, ORM's ruined me. Developers :)
This is the schema.
Table1 1 - 1 to three tables (Table2, Table3, Table4) and each Table(2,3,4) 1 - 1 to a Table5.
Graph (try) representation:
Table1 1<->1 Table2 1<->1 Table5
1<->1 Table3 1<->1 Table5
1<->1 Table4 1<->1 Table5
I need a query to retrieve all Table1 records and their corresponding relationship data, Table1,Table2,Table3 and their relationship data to Table5.
Any help appreciated.
Thank you.
Without seeing your full table structure and the column names you should be able to join the tables in a similar manner as this:
select *
from table1 t1
left join table2 t2
on t1.id = t2.id
left join table3 t3
on t1.id = t3.id
left join table4 t4
on t1.id = t4.id
left join table5 t5
on t2.id = t5.id
or t3.id = t5.id
or t4.id = t5.id
What I actually needed was this:
SELECT F.*, DE.Title as EnergyDrinkTitle, DE.[Picture] AS EnergyPicture, DI.Title AS InspDrinkTitle, DR.Title AS RelaxDrinkTitle
FROM
(Select M.*, E.DescriptionTitle, I.[DescriptionTitle], R.DescriptionTitle,
E.[DrinkId] as EnergyDrink, I.DrinkId as InspDrink, R.[DrinkId] as RelaxDrink
FROM [Member] M
LEFT JOIN [Energy] E
ON M.[_id] = E.[MemberId]
LEFT JOIN [Inspiration] I
ON M.[_id] = I.[MemberId]
LEFT JOIN [Relax] R
ON M.[_id] = R.[MemberId]
) AS F JOIN Drink DE ON F.EnergyDrink = DE._id
JOIN Drink DI ON F.InspDrink = DI._id
JOIN Drink DR ON F.RelaxDrink = DR._id