we have "Profile" table with over 60 columns like (Id, fname, lname, gender, profilestate, city, state, degree, ...).
users search other peopel on website. query is like :
WITH TempResult as (
select ROW_NUMBER() OVER(ORDER BY #sortColumn DESC) as RowNum, profile.id from Profile
where
(#a is null or a = #a) and
(#b is null or b = #b) and
...(over 60 column)
)
SELECT profile.* FROM TempResult join profile on TempResult.id = profile.id
WHERE
(RowNum >= #FirstRow)
AND
(RowNum <= #LastRow)
sql server by default use clustered index for execution query. but total execution time is over 300. we test another solution such as multi column index in all columns in where clause but total execution time is over 400.
do you have any solution to make total execution time lower than 100.
we using sql server 2008.
Unfortunately I don't think there is a pure SQL solution to your issue. Here are a couple alternatives:
Dynamic SQL - build up a query that only includes WHERE clause statements for values that are actually provided. Assuming the average search actually only fills in 2-3 fields, indexes could be added and utilized.
Full Text Search - go to something more like a Google keyword search. No individual options.
Lucene (or something else) - Search outside of SQL; This is a fairly significant change though.
One other option that I just remembered implementing in a system once. Create a vertical table that includes all of the data you are searching on and build up a query for it. This is easiest to do with dynamic SQL, but could be done using Table Value Parameters or a temp table in a pinch.
The idea is to make a table that looks something like this:
Profile ID
Attribute Name
Attribute Value
The table should have a unique index on (Profile ID, Attribute Name) (unique to make the search work properly, index will make it perform well).
In this table you'd have rows of data like:
(1, 'city', 'grand rapids')
(1, 'state', 'MI')
(2, 'city', 'detroit')
(2, 'state', 'MI')
Then your SQL will be something like:
SELECT *
FROM Profile
JOIN (
SELECT ProfileID
FROM ProfileAttributes
WHERE (AttributeName = 'city' AND AttributeValue = 'grand rapids')
AND (AttributeName = 'state' AND AttributeValue = 'MI')
GROUP BY ProfileID
HAVING COUNT(*) = 2
) SelectedProfiles ON Profile.ProfileID = SelectedProfiles.ProfileID
... -- Add your paging here
Like I said, you could use a temp table that has attribute name/values:
SELECT *
FROM Profile
JOIN (
SELECT ProfileID
FROM ProfileAttributes
JOIN PassedInAttributeTable ON ProfileAttributes.AttributeName = PassedInAttributeTable.AttributeName
AND ProfileAttributes.AttributeValue = PassedInAttributeTable.AttributeValue
GROUP BY ProfileID
HAVING COUNT(*) = CountOfRowsInPassedInAttributeTable -- calculate or pass in
) SelectedProfiles ON Profile.ProfileID = SelectedProfiles.ProfileID
... -- Add your paging here
As I recall, this ended up performing very well, even on fairly complicated queries (though I think we only had 12 or so columns).
As a single query, I can't think of a clever way of optimising this.
Provided that each column's check is highly selective, however, the following (very long winded) code, might prove faster, assuming each individual column has it's own separate index...
WITH
filter AS (
SELECT
[a].*
FROM
(SELECT * FROM Profile WHERE #a IS NULL OR a = #a) AS [a]
INNER JOIN
(SELECT id FROM Profile WHERE b = #b UNION ALL SELECT NULL WHERE #b IS NULL) AS [b]
ON ([a].id = [b].id) OR ([b].id IS NULL)
INNER JOIN
(SELECT id FROM Profile WHERE c = #c UNION ALL SELECT NULL WHERE #c IS NULL) AS [c]
ON ([a].id = [c].id) OR ([c].id IS NULL)
.
.
.
INNER JOIN
(SELECT id FROM Profile WHERE zz = #zz UNION ALL SELECT NULL WHERE #zz IS NULL) AS [zz]
ON ([a].id = [zz].id) OR ([zz].id IS NULL)
)
, TempResult as (
SELECT
ROW_NUMBER() OVER(ORDER BY #sortColumn DESC) as RowNum,
[filter].*
FROM
[filter]
)
SELECT
*
FROM
TempResult
WHERE
(RowNum >= #FirstRow)
AND (RowNum <= #LastRow)
EDIT
Also, thinking about it, you may even get the same result just by having the 60 individual indexes. SQL Server can do INDEX MERGING...
You've several issues imho. One is that you're going to end up with a seq scan no matter what you do.
But I think your more crucial issue here is that you've an unnecessary join:
SELECT profile.* FROM TempResult
WHERE
(RowNum >= #FirstRow)
AND
(RowNum <= #LastRow)
This is a classic "SQL Filter" query problem. I've found that the typical approaches of "(#b is null or b = #b)" & it's common derivatives all yeild mediocre performance. The OR clause tends to be the cause.
Over the years I've done a lot of Perf/Tuning & Query Optimisation. The Approach I've found best is to generate Dynamic SQL inside a Stored Proc. Most times you also need to add "with Recompile" on the statement. The Stored Proc helps reduce potential for SQL injection attacks. The Recompile is needed to force the selection of indexes appropriate to the parameters you are searching on.
Generally it is at least an order of magnitude faster.
I agree you should also look at points mentioned above like :-
If you commonly only refer to a small subset of the columns you could create non-clustered "Covering" indexes.
Highly selective (ie:those with many unique values) columns will work best if they are the lead colum in the index.
If many colums have a very small number of values, consider using The BIT datatype. OR Create your own BITMASKED BIGINT to represent many colums ie: a form of "Enumerated datatyle". But be careful as any function in the WHERE clause (like MOD or bitwise AND/OR) will prevent the optimiser from choosing an index. It works best if you know the value for each & can combine them to use an equality or range query.
While often good to find RoWID's with a small query & then join to get all the other columns you want to retrieve. (As you are doing above) This approach can sometimes backfire. If the 1st part of the query does a Clustred Index Scan then often it is faster to get the otehr columns you need in the select list & savethe 2nd table scan.
So always good to try it both ways & see what works best.
Remember to run SET STATISTICS IO ON & SET STATISTICS TIME ON. Before running your tests. Then you can see where the IO is & it may help you with index selection, for the mose frequent combination of paramaters.
I hope this makes sense without long code samples. (it is on my other machine)
Related
Let us have the following table in SQL Server 2016
-- generating 1M test table with four attributes
WITH x AS
(
SELECT n FROM (VALUES (0),(1),(2),(3),(4),(5),(6),(7),(8),(9)) v(n)
), t1 AS
(
SELECT ones.n + 10 * tens.n + 100 * hundreds.n + 1000 * thousands.n + 10000 * tenthousands.n + 100000 * hundredthousands.n as id
FROM x ones, x tens, x hundreds, x thousands, x tenthousands, x hundredthousands
)
SELECT id,
id % 50 predicate_col,
row_number() over (partition by id % 50 order by id) join_col,
LEFT('Value ' + CAST(CHECKSUM(NEWID()) AS VARCHAR) + ' ' + REPLICATE('*', 1000), 1000) as padding
INTO TestTable
FROM t1
GO
-- setting the `id` as a primary key (therefore, creating a clustered index)
ALTER TABLE TestTable ALTER COLUMN id int not null
GO
ALTER TABLE TestTable ADD CONSTRAINT pk_TestTable_id PRIMARY KEY (id)
-- creating a non-clustered index
CREATE NONCLUSTERED INDEX ix_TestTable_predicate_col_join_col
ON TestTable (predicate_col, join_col)
GO
Ok, and now when I run the following queries having just slightly different predicates (b.predicate_col <= 0 vs. b.predicate_col = 0) I got completely different plans.
-- Q1
select b.id, b.predicate_col, b.join_col, b.padding
from TestTable b
join TestTable a on b.join_col = a.id
where a.predicate_col = 1 and b.predicate_col <= 0
option (maxdop 1)
-- Q2
select b.id, b.predicate_col, b.join_col, b.padding
from TestTable b
join TestTable a on b.join_col = a.id
where a.predicate_col = 1 and b.predicate_col = 0
option (maxdop 1)
If I look on query plans, then it is clear that he chooses to join the key lookup together with non-clustered index seek first and then he does the final join with non-clustered index in the case of Q1 (which is bad). A much better solution is in the case of Q2: he joins the non-clustered indexes first and then he does the final key lookup.
The question is: why is that and can I improve it somehow?
In my intuitive understanding of histograms, it should be easy to estimate the correct result for both variants of predicates (b.predicate_col <= 0 vs. b.predicate_col = 0), therefore, why different query plans?
EDIT:
Actually, I do not want to change the indexes or physical structure of the table. I would like to understand why he picks up such a bad query plan in the case of Q1. Therefore, my question is precisely like this:
Why he picks such a bad query plan in the case of Q1 and can I improve without altering the physical design?
I have checked the result estimations in the query plan and both query plans have exact row number estimations of every operator! I have checked the result memo structure (OPTION (QUERYTRACEON 3604, QUERYTRACEON 8615, QUERYTRACEON 8620)) and rules applied during the compilation (OPTION (QUERYTRACEON 3604, QUERYTRACEON 8619, QUERYTRACEON 8620)) and it seems that he finish the query plan search once he hit the first plan. Is this the reason for such behaviour?
This is caused by SQL Server's inability to use Index Columns to the Right of the Inequality search.
This code produces the same issue:
SELECT * FROM TestTable WHERE predicate_col <= 0 and join_col = 1
SELECT * FROM TestTable WHERE predicate_col = 0 and join_col <= 1
Inequality queries such as >= or <= put a limitation on SQL, the Optimiser can't use the rest of the columns in the index, so when you put an inequality on [predicate_col] you're rendering the rest of the index useless, SQL can't make full use of the index and produces an alternate (bad) plan. [join_col] is the last column in the Index so in the second query SQL can still make full use of the index.
The reason SQL opts for the Hash Match is because it can't guarantee the order of the data coming out of table B. The inequality renders [join_col] in the index useless so SQL has to prepare for unsorted data on the join, even though the row count is the same.
The only way to fix your problem (even though you don't like it) is to alter the Index so that Equality columns come before Inequality columns.
Ok answer can be from Statistics and histogram point of view also.
Answer can be from index structure arrangement point of view also.
Ok I am trying to answer this from index structure.
Although you get same result in both query because there is no predicate_col < 0 records
When there is Range predicate in composite index ,both the index are not utilise. There can also be so many other reason of index not being utilise.
-- Q1
select b.id, b.predicate_col, b.join_col, b.padding
from TestTable b
join TestTable a on b.join_col = a.id
where a.predicate_col = 1 and b.predicate_col <= 0
option (maxdop 1)
If we want plan like in Q2 then we can create another composite index.
-- creating a non-clustered index
CREATE NONCLUSTERED INDEX ix_TestTable_predicate_col_join_col_1
ON TestTable (join_col,predicate_col)
GO
We get query plan exactly like Q2.
Another way is to define CHECK constraint in predicate_col
Alter table TestTable ADD check (predicate_col>=0)
GO
This also give same query plan as Q2.
Though in real table and data, whether you can create CHECK Constraint or create another composite index or not is another discussion.
I just created a view but it is really slow, since my actual table has something around 800k rows.
Is there something I can change in the actual sql code to make it run faster?
Here is how it looks now:
Select B.*
FROM
(Select A.*, (select count(B.KEY_ID)/77
FROM book_new B
where B.KEY_ID = A.KEY_ID) as COUNT_KEY
FROM
(select *
from book_new
where region = 'US'
and (actual_release_date is null or
actual_release_date >= To_Date( '01/07/16','dd/mm/yy'))
) A
) B
WHERE B.COUNT_KEY = 1
OR (B.COUNT_KEY > 1 AND B.NEW_OLD <> 'Old')
The most obvious things to do are add indexes:
Add an index on book_new(key_id)
Add an index on book_new(region, actual_release_date)
These are probably sufficient. It is possible that rewriting the query would help, but this is a good beginning. If you want to rewrite the query, it would help if you described the logic you are trying to implement.
There are many ways to solve this issue based on your needs
You can create an indexed view
You can create an index in the base tables which are used in this view.
You can use the required columns in the SELECT statement instead of using SELECT * FROM,
If the table contains many columns but you require only few columns, you can create a NON CLUSTERED INDEX with INCLUDE COLUMNS option which will reduce the LOGICAL READS.
For starters, replace the scalar subquery for COUNT_KEY with a windowed COUNT(*).
SELECT * FROM
(
select book_new.*, COUNT(*) OVER ( PARTITION BY book_new.key_id)/77 COUNT_KEY
from book_new
where region = 'US'
and (actual_release_date is null or
actual_release_date >= To_Date( '01/07/16','dd/mm/yy'))
)
WHERE count_key = 1 OR ( count_key > 1 AND new_old <> 'Old' )
This way, you only go through the BOOK_NEW table one time.
BTW, I agree with other comments that this query makes little sense.
I have the following table:
id symbol_01 symbol_02
1 abc xyz
2 kjh okd
3 que qid
I need a query that ensures symbol_01 and symbol_02 are both contained in a list of valid symbols. In other words I would needs something like this:
select *
from mytable
where symbol_01 in (
select valid_symbols
from somewhere)
and symbol_02 in (
select valid_symbols
from somewhere)
The above example would work correctly, but the subquery used to determine the list of valid symbols is identical both times and is quite large. It would be very innefficient to run it twice like in the example.
Is there a way to do this without duplicating two identical sub queries?
Another approach:
select *
from mytable t1
where 2 = (select count(distinct symbol)
from valid_symbols vs
where vs.symbol in (t1.symbol_01, t1.symbol_02));
This assumes that the valid symbols are stored in a table valid_symbols that has a column named symbol. The query would also benefit from an index on valid_symbols.symbol
You could try use a CTE like;
WITH ValidSymbols AS (
SELECT DISTINCT valid_symbol
FROM somewhere
)
SELECT mt.*
FROM MyTable mt
INNER JOIN ValidSymbols v1
ON mt.symbol_01 = v1.valid_symbol
INNER JOIN ValidSymbols v2
ON mt.symbol_02 = v2.valid_symbol
From a performance perspective, your query is the right way to do this. I would write it as:
select *
from mytable t
where exists (select 1
from valid_symbols vs
where t.symbol_01 = vs.valid_symbol
) and
exists (select 1
from valid_symbols vs
where t.symbol_02 = vs.valid_symbol
) ;
The important component is that you need an index on valid_symbols(valid_symbol). With this index, the lookup should be pretty fast. Appropriate indexes can even work if valid_symbols is a view, although the effect depends on the complexity of the view.
You seem to have a situation where you have two foreign key relationships. If you explicitly declare these relationships, then the database will enforce that the columns in your table match the valid symbols.
I have a component that retrieves data from database based on the keys provided.
However I want my java application to get all the data for all keys in a single database hit to fasten up things.
I can use 'in' clause when I have only one key.
While working on more than one key I can use below query in oracle
SELECT * FROM <table_name>
where (value_type,CODE1) IN (('I','COMM'),('I','CORE'));
which is similar to writing
SELECT * FROM <table_name>
where value_type = 1 and CODE1 = 'COMM'
and
SELECT * FROM <table_name>
where value_type = 1 and CODE1 = 'CORE'
together
However, this concept of using 'in' clause as above is giving below error in 'SQL server'
ERROR:An expression of non-boolean type specified in a context where a condition is expected, near ','.
Please let know if their is any way to achieve the same in SQL server.
This syntax doesn't exist in SQL Server. Use a combination of And and Or.
SELECT *
FROM <table_name>
WHERE
(value_type = 1 and CODE1 = 'COMM')
OR (value_type = 1 and CODE1 = 'CORE')
(In this case, you could make it shorter, because value_type is compared to the same value in both combinations. I just wanted to show the pattern that works like IN in oracle with multiple fields.)
When using IN with a subquery, you need to rephrase it like this:
Oracle:
SELECT *
FROM foo
WHERE
(value_type, CODE1) IN (
SELECT type, code
FROM bar
WHERE <some conditions>)
SQL Server:
SELECT *
FROM foo
WHERE
EXISTS (
SELECT *
FROM bar
WHERE <some conditions>
AND foo.type_code = bar.type
AND foo.CODE1 = bar.code)
There are other ways to do it, depending on the case, like inner joins and the like.
If you have under 1000 tuples you want to check against and you're using SQL Server 2008+, you can use a table values constructor, and perform a join against it. You can only specify up to 1000 rows in a table values constructor, hence the 1000 tuple limitation. Here's how it would look in your situation:
SELECT <table_name>.* FROM <table_name>
JOIN ( VALUES
('I', 'COMM'),
('I', 'CORE')
) AS MyTable(a, b) ON a = value_type AND b = CODE1;
This is only a good idea if your list of values is going to be unique, otherwise you'll get duplicate values. I'm not sure how the performance of this compares to using many ANDs and ORs, but the SQL query is at least much cleaner to look at, in my opinion.
You can also write this to use EXIST instead of JOIN. That may have different performance characteristics and it will avoid the problem of producing duplicate results if your values aren't unique. It may be worth trying both EXIST and JOIN on your use case to see what's a better fit. Here's how EXIST would look,
SELECT * FROM <table_name>
WHERE EXISTS (
SELECT 1
FROM (
VALUES
('I', 'COMM'),
('I', 'CORE')
) AS MyTable(a, b)
WHERE a = value_type AND b = CODE1
);
In conclusion, I think the best choice is to create a temporary table and query against that. But sometimes that's not possible, e.g. your user lacks the permission to create temporary tables, and then using a table values constructor may be your best choice. Use EXIST or JOIN, depending on which gives you better performance on your database.
Normally you can not do it, but can use the following technique.
SELECT * FROM <table_name>
where (value_type+'/'+CODE1) IN (('I'+'/'+'COMM'),('I'+'/'+'CORE'));
A better solution is to avoid hardcoding your values and put then in a temporary or persistent table:
CREATE TABLE #t (ValueType VARCHAR(16), Code VARCHAR(16))
INSERT INTO #t VALUES ('I','COMM'),('I','CORE')
SELECT DT. *
FROM <table_name> DT
JOIN #t T ON T.ValueType = DT.ValueType AND T.Code = DT.Code
Thus, you avoid storing data in your code (persistent table version) and allow to easily modify the filters (without changing the code).
I think you can try this, combine and and or at the same time.
SELECT
*
FROM
<table_name>
WHERE
value_type = 1
AND (CODE1 = 'COMM' OR CODE1 = 'CORE')
What you can do is 'join' the columns as a string, and pass your values also combined as strings.
where (cast(column1 as text) ||','|| cast(column2 as text)) in (?1)
The other way is to do multiple ands and ors.
I had a similar problem in MS SQL, but a little different. Maybe it will help somebody in futere, in my case i found this solution (not full code, just example):
SELECT Table1.Campaign
,Table1.Coupon
FROM [CRM].[dbo].[Coupons] AS Table1
INNER JOIN [CRM].[dbo].[Coupons] AS Table2 ON Table1.Campaign = Table2.Campaign AND Table1.Coupon = Table2.Coupon
WHERE Table1.Coupon IN ('0000000001', '0000000002') AND Table2.Campaign IN ('XXX000000001', 'XYX000000001')
Of cource on Coupon and Campaign in table i have index for fast search.
Compute it in MS Sql
SELECT * FROM <table_name>
where value_type + '|' + CODE1 IN ('I|COMM', 'I|CORE');
I need to calculate a total of a column up to a specified date on a table that currently has over 400k rows and is poised to grow further. I found the SUM() aggregate function to be too slow for my purpose, as I couldn't get it faster than about 1500ms for a sum over 50k rows.
Please note that the code below is the fastest implementation I have found so far. Notably filtering the data from CustRapport and storing it in a temporary table brought me a 3x performance increase. I also experimented with indexes, but they usually made it slower.
I would however like the function to be at least an order of magnitude faster. Any idea on how to achieve that? I have stumbled upon http://en.wikipedia.org/wiki/Fenwick_tree. However, I would rather have the storage and calculation processed within SQL Server.
CustRapport and CustLeistung are Views with the following definition:
ALTER VIEW [dbo].[CustLeistung] AS
SELECT TblLeistung.* FROM TblLeistung
WHERE WebKundeID IN (SELECT WebID FROM XBauAdmin.dbo.CustKunde)
ALTER VIEW [dbo].[CustRapport] AS
SELECT MainRapport.* FROM MainRapport
WHERE WebKundeID IN (SELECT WebID FROM XBauAdmin.dbo.CustKunde)
Thanks for any help or advice!
ALTER FUNCTION [dbo].[getBaustellenstunden]
(
#baustelleID int,
#datum date
)
RETURNS
#ret TABLE
(
Summe float
)
AS
BEGIN
declare #rapport table
(
id int null
)
INSERT INTO #rapport select WebSourceID from CustRapport
WHERE RapportBaustelleID = #baustelleID AND RapportDatum <= #datum
INSERT INTO #ret
SELECT SUM(LeistungArbeit)
FROM CustLeistung INNER JOIN #rapport as r ON LeistungRapportID = r.id
WHERE LeistungArbeit is not null
AND LeistungInventarID is null AND LeistungArbeit > 0
RETURN
END
Execution plan:
http://s23.postimg.org/mxq9ktudn/execplan1.png
http://s23.postimg.org/doo3aplhn/execplan2.png
General advice I can provide now until you provide more information.
Updated my query since it was pulling from views to pull straight from the tables.
INSERT INTO #ret
SELECT
SUM(LeistungArbeit)
FROM (
SELECT DISTINCT WebID FROM XBauAdmin.dbo.CustKunde
) Web
INNER JOIN dbo.TblLeistung ON TblLeistung.WebKundeID=web.webID
INNER JOIN dbo.MainRapport ON MainRapport.WebKundeID=web.webID
AND TblLeistung.LeistungRapportID=MainRapport.WebSourceID
AND MainRapport.RapportBaustelleID = #baustelleID
AND MainRapport.RapportDatum <= #datum
WHERE TblLeistung.LeistungArbeit is not null
AND TblLeistung.LeistungInventarID is null
AND TblLeistung.LeistungArbeit > 0
Get rid of the table variable. They have their use, but I switch to temp tables when I get over a 100 records; indexed temp tables simply perform better in my experience.
Update your select to the above query and retest performance
Check and ensure there are indexes on every column references in the query. If you use the show actual execution plan, SQL Server will help identify where indexes would be useful.