Selecting from a Large Table SQL 2005 - sql

I have a SQL table it has more than 1000000 rows, and I need to select with the query as you can see below:
SELECT DISTINCT TOP (200) COUNT(1) AS COUNT, KEYWORD
FROM QUERIES WITH(NOLOCK)
WHERE KEYWORD LIKE '%Something%'
GROUP BY KEYWORD ORDER BY 'COUNT' DESC
Could you please tell me how can I optimize it to speed up the execution process? Thank you for useful answers.

I'd first look at the execution plan to see how sql server is trying to access your data. Here is a link to just one of many articles on execution plan analysis.

Asking a question about SQL Server performance without providing a schema is a complete waste of everybody time. I'm going to answer a different question, which is one you should had been ask in the first place:
What schema should I use to
efficiently satisfy a query like
SELECT DISTINCT TOP (200) COUNT(1) AS
COUNT, KEYWORD FROM QUERIES WHERE
KEYWORD LIKE '%Something%'GROUP BY
KEYWORD ORDER BY 'COUNT' DESC when QUERIES table has over 1M rows?
The proper schema depend on the selectivity of KEYWORD. One possible design would be to normalize KEYWORD into a lookup table and have a narrow non-clustered index on the lookup id:
CREATE TABLE KEYWORDS (KeywordId INT NOT NULL IDENTITY(1,1) PRIMARY KEY,
Keyword VARCHAR(...) UNIQUE);
CREATE TABLE QUERIES (...,
KeywordId INT NOT NULL,
CONSTRAINT FK_KEYWORD
FOREIGN KEY KeywordId
REFERENCES KEYWORDS (KeywordId),
...);
CREATE INDEX ndxQueriesKeyword ON Queries (KeywordId);
If the number of distinct keyword is relatively low, the original query can be satisfied quickly by a scan of the Keywqord table followed by a nexted loop range scan of the ndxQueriesKeyword index, which is very narrow and therefore generates low IO.
As the number of distinct keyword increases, this approach may start showing problems due to the high number of range scans on the Queries table, and possible even due to the full scan on the Keywords table.
You may consider using a different WHERE clause, namely one LIKE 'Something%, which is SARGable and can leverage an index on KEYWORK, benefiting from a range reduction and a narrower scan than a full table scan.
If you are on Enterprise Edition you can consider adding an indexes view with the pre-computed aggregates:
CREATE VIEW vwQueryKeywords
WITH SCHEMABINDING
AS SELECT KEYWORD, COUNT_BIG(*) as COUNT
FROM dbo.QUERIES
GROUP BY KEYWORD;
CREATE CLUSTERED INDEX cdxQueryKeywords ON vwQueryKeywords(KEYWORD);
On EE the optimizer will consider the indexed view for the original query. On non-EE you will have to change the query to run against the view with the NOEXPAND hint:
SELECT KEYWORD, COUNT
FROM vwQueryKeywords WITH(NOEXPAND)
WHERE KEYWORD LIKE '%Something%';
Another completely different approach is to ditch the LIKE '%Something%' condition altogether in favor of fullt-text search:
SELECT DISTINCT TOP (200) COUNT(1) AS
COUNT, KEYWORD FROM QUERIES WHERE
CONTAINS (Keyword, Something)
GROUP BY
KEYWORD ORDER BY 'COUNT' DESC
Because the FT search is a reverse-index lookup, it may prove optimal over a traditional WHERE. The only issue is that you'll only be able to search for full words, since FT won't let you search partial matches the way LIKE does. Again, the actual mileage will vary based on Keyword data profile (ie. its statistics and distribution).

As Jeremy stated, you need to look at the execution plan and client statistics to see what is faster. However, a couple of suggestions. First, do you really need a prefixing wildcard on your search? I.e., LIKE '%Something%' will not be able to use an index whereas LIKE 'Something%' will. Second, you might try a CTE to see if will be faster. So, something like:
;With NumberedItems As
(
Select Keyword, Count(*) As [Count]
, ROW_NUMBER() OVER ( ORDER BY Keyword, Count(*) DESC ) As ItemRank
From Queries WITH (NOLOCK)
Where Keyword LIKE '%Something%'
Group By Keyword
)
Select Keyword, [Count]
From NumberedItems
Where ItemRank <= 200

It's rather hard to guess what may be causing the performance issues with just a query and no schema or execution plan. You should definitely read-up on them as all performance tuning of SQL queries is ultimately driven by the execution plan.
If you really want to delve into it, you can also read up on the query optimizer which attempts to execute your query using the most optimal plan. Understanding the optimizer is important to ensure you are taking full advantage of the indexes, etc. you have on the database. Microsoft also has several helpful documents such as this on troubleshooting performance issue.
For your particular case, the bottleneck is most likely in the WHERE clause. LIKE comparisons tend to be inefficient, especially when surrounded by percent signs as the query tends to be unable to take advantage of indexes on the column, etc. Depending on how you've stored data, full-text indexing may be a useful option, as that can frequently outperform LIKE '%SOMEVALUE%'.

If you can't use a full-text search engine from a third party, create an inverted index from your text periodically and search that instead. A naive implementation would beat your current strategy.
http://en.wikipedia.org/wiki/Inverted_index

Your query is not optimizable (without implementing some form of full-text indexing, itself expensive) because you have a leading wildcard in your keyword match. You would need to split the keywords out into separate column values (probably in a separate, related table) and search on an exact match or, at least, a match with the wildcard not at the beginning of the text.
Additionally the results you're getting may not be accurate if you have some keywords that are nested in others (eg "cart" will match a keyword search on "car", which is not what you want).

Related

difference b/w where column='' and column like '' in sql [duplicate]

This question skirts around what I'm wondering, but the answers don't exactly address it.
It would seem that in general '=' is faster than 'like' when using wildcards. This appears to be the conventional wisdom. However, lets suppose I have a column containing a limited number of different fixed, hardcoded, varchar identifiers, and I want to select all rows matching one of them:
select * from table where value like 'abc%'
and
select * from table where value = 'abcdefghijklmn'
'Like' should only need to test the first three chars to find a match, whereas '=' must compare the entire string. In this case it would seem to me that 'like' would have an advantage, all other things being equal.
This is intended as a general, academic question, and so should not matter which DB, but it arose using SQL Server 2005.
See https://web.archive.org/web/20150209022016/http://myitforum.com/cs2/blogs/jnelson/archive/2007/11/16/108354.aspx
Quote from there:
the rules for index usage with LIKE
are loosely like this:
If your filter criteria uses equals =
and the field is indexed, then most
likely it will use an INDEX/CLUSTERED
INDEX SEEK
If your filter criteria uses LIKE,
with no wildcards (like if you had a
parameter in a web report that COULD
have a % but you instead use the full
string), it is about as likely as #1
to use the index. The increased cost
is almost nothing.
If your filter criteria uses LIKE, but
with a wildcard at the beginning (as
in Name0 LIKE '%UTER') it's much less
likely to use the index, but it still
may at least perform an INDEX SCAN on
a full or partial range of the index.
HOWEVER, if your filter criteria uses
LIKE, but starts with a STRING FIRST
and has wildcards somewhere AFTER that
(as in Name0 LIKE 'COMP%ER'), then SQL
may just use an INDEX SEEK to quickly
find rows that have the same first
starting characters, and then look
through those rows for an exact match.
(Also keep in mind, the SQL engine
still might not use an index the way
you're expecting, depending on what
else is going on in your query and
what tables you're joining to. The
SQL engine reserves the right to
rewrite your query a little to get the
data in a way that it thinks is most
efficient and that may include an
INDEX SCAN instead of an INDEX SEEK)
It's a measureable difference.
Run the following:
Create Table #TempTester (id int, col1 varchar(20), value varchar(20))
go
INSERT INTO #TempTester (id, col1, value)
VALUES
(1, 'this is #1', 'abcdefghij')
GO
INSERT INTO #TempTester (id, col1, value)
VALUES
(2, 'this is #2', 'foob'),
(3, 'this is #3', 'abdefghic'),
(4, 'this is #4', 'other'),
(5, 'this is #5', 'zyx'),
(6, 'this is #6', 'zyx'),
(7, 'this is #7', 'zyx'),
(8, 'this is #8', 'klm'),
(9, 'this is #9', 'klm'),
(10, 'this is #10', 'zyx')
GO 10000
CREATE CLUSTERED INDEX ixId ON #TempTester(id)CREATE CLUSTERED INDEX ixId ON #TempTester(id)
CREATE NONCLUSTERED INDEX ixTesting ON #TempTester(value)
Then:
SET SHOWPLAN_XML ON
Then:
SELECT * FROM #TempTester WHERE value LIKE 'abc%'
SELECT * FROM #TempTester WHERE value = 'abcdefghij'
The resulting execution plan shows you that the cost of the first operation, the LIKE comparison, is about 10 times more expensive than the = comparison.
If you can use an = comparison, please do so.
You should also keep in mind that when using like, some sql flavors will ignore indexes, and that will kill performance. This is especially true if you don't use the "starts with" pattern like your example.
You should really look at the execution plan for the query and see what it's doing, guess as little as possible.
This being said, the "starts with" pattern can and is optimized in sql server. It will use the table index. EF 4.0 switched to like for StartsWith for this very reason.
If value is unindexed, both result in a table-scan. The performance difference in this scenario will be negligible.
If value is indexed, as Daniel points out in his comment, the = will result in an index lookup which is O(log N) performance. The LIKE will (most likely - depending on how selective it is) result in a partial scan of the index >= 'abc' and < 'abd' which will require more effort than the =.
Note that I'm talking SQL Server here - not all DBMSs will be nice with LIKE.
You are asking the wrong question. In databases is not the operator performance that matters, is always the SARGability of the expression, and the coverability of the overall query. Performance of the operator itself is largely irrelevant.
So, how do LIKE and = compare in terms of SARGability? LIKE, when used with an expression that does not start with a constant (eg. when used LIKE '%something') is by definition non-SARGabale. But does that make = or LIKE 'something%' SARGable? No. As with any question about SQL performance the answer does not lie with the query of the text, but with the schema deployed. These expression may be SARGable if an index exists to satisfy them.
So, truth be told, there are small differences between = and LIKE. But asking whether one operator or other operator is 'faster' in SQL is like asking 'What goes faster, a red car or a blue car?'. You should eb asking questions about the engine size and vechicle weight, not about the color... To approach questions about optimizing relational tables, the place to look is your indexes and your expressions in the WHERE clause (and other clauses, but it usually starts with the WHERE).
A personal example using mysql 5.5: I had an inner join between 2 tables, one of 3 million rows and one of 10 thousand rows.
When using a like on an index as below(no wildcards), it took about 30 seconds:
where login like '12345678'
using 'explain' I get:
When using an '=' on the same query, it took about 0.1 seconds:
where login ='12345678'
Using 'explain' I get:
As you can see, the like completely cancelled the index seek, so query took 300 times more time.
= is much faster than LIKE, even without wildcard. I tested on MySQL with 11GB of data and more than 100 million of records, the f_time column is indexed.
SELECT * FROM XXXXX WHERE f_time = '1621442261'
#took 0.00sec and return 330 records
SELECT * FROM XXXXX WHERE f_time LIKE '1621442261'
#took 44.71sec and return 330 records
Besides all the answers, there this to consider:
'like' is case insensitive, so every character needs to be compared twice, whereas the '=' only compares once for identical characters.
This issue arises with or without indexes.
Maybe you are looking about Full Text Search.
In contrast to full-text search, the LIKE Transact-SQL predicate works on
character patterns only. Also, you cannot use the LIKE predicate to
query formatted binary data. Furthermore, a LIKE query against a large
amount of unstructured text data is much slower than an equivalent
full-text query against the same data. A LIKE query against millions
of rows of text data can take minutes to return; whereas a full-text
query can take only seconds or less against the same data, depending
on the number of rows that are returned.
I was working with a huge database that has more then 400M records and I put LIKE in search query. Here is the final results.
There were three tables tb1, tb2 and tb3. When I use EQUAL for in all tables QUERY the response time was 193ms. and when I put LIKE in one of he table the response time was 19.22 sec. and for all table LIKE response time was 112 Sec

What are the performance implications of Oracle IN Clause with no joins?

I have a query in this form that will on average take ~100 in clause elements, and at some rare times > 1000 elements. If greater than 1000 elements, we will chunk the in clause down to 1000 (an Oracle maximum).
The SQL is in the form of
SELECT * FROM tab WHERE PrimaryKeyID IN (1,2,3,4,5,...)
The tables I am selecting from are huge and will contain millions more rows than what is in my in clause. My concern is that the optimizer may elect to do a table scan (our database does not have up to date statistics - yeah - I know ...)
Is there a hint I can pass to force the use of the primary key - WITHOUT knowing the index name of the primary Key, perhaps something like ... /*+ DO_NOT_TABLE_SCAN */?
Are there any creative approaches to pulling back the data such that
We perform the least number of round-trips
We we read the least number of blocks (at the logical IO level?)
Will this be faster ..
SELECT * FROM tab WHERE PrimaryKeyID = 1
UNION
SELECT * FROM tab WHERE PrimaryKeyID = 2
UNION
SELECT * FROM tab WHERE PrimaryKeyID = 2
UNION ....
If the statistics on your table are accurate, it should be very unlikely that the optimizer would choose to do a table scan rather than using the primary key index when you only have 1000 hard-coded elements in the WHERE clause. The best approach would be to gather (or set) accurate statistics on your objects since that should cause good things to happen automatically rather than trying to do a lot of gymnastics in order to work around incorrect statistics.
If we assume that the statistics are inaccurate to the degree that the optimizer would be lead to believe that a table scan would be more efficient than using the primary key index, you could potentially add in a DYNAMIC_SAMPLING hint that would force the optimizer to gather more accurate statistics before optimizing the statement or a CARDINALITY hint to override the optimizer's default cardinality estimate. Neither of those would require knowing anything about the available indexes, it would just require knowing the table alias (or name if there is no alias). DYNAMIC_SAMPLING would be the safer, more robust approach but it would add time to the parsing step.
If you are building up a SQL statement with a variable number of hard-coded parameters in an IN clause, you're likely going to be creating performance problems for yourself by flooding your shared pool with non-sharable SQL and forcing the database to spend a lot of time hard parsing each variant separately. It would be much more efficient if you created a single sharable SQL statement that could be parsed once. Depending on where your IN clause values are coming from, that might look something like
SELECT *
FROM table_name
WHERE primary_key IN (SELECT primary_key
FROM global_temporary_table);
or
SELECT *
FROM table_name
WHERE primary_key IN (SELECT primary_key
FROM TABLE( nested_table ));
or
SELECT *
FROM table_name
WHERE primary_key IN (SELECT primary_key
FROM some_other_source);
If you got yourself down to a single sharable SQL statement, then in addition to avoiding the cost of constantly re-parsing the statement, you'd have a number of options for forcing a particular plan that don't involve modifying the SQL statement. Different versions of Oracle have different options for plan stability-- there are stored outlines, SQL plan management, and SQL profiles among other technologies depending on your release. You can use these to force particular plans for particular SQL statements. If you keep generating new SQL statements that have to be re-parsed, however, it becomes very difficult to use these technologies.

Getting RID Lookup instead of Table Scan?

SQL Fiddle: http://sqlfiddle.com/#!3/23cf8
In this query, when I have an In clause on an Id, and then also select other columns, the In is evaluated first, and then the Details column and other columns are pulled in via a RID Lookup:
--In production and in SQL Fiddle, Details is grabbed via a RID Lookup after the In clause is evaluated
SELECT [Id]
,[ForeignId]
,Details
--Generate a numbering(starting at 1)
--,Row_Number() Over(Partition By ForeignId Order By Id Desc) as ContactNumber --Desc because older posts should be numbered last
FROM SupportContacts
Where foreignId In (1,2,3,5)
With this query, the Details are being pulled in via a Table Scan.
With NumberedContacts AS
(
SELECT [Id]
,[ForeignId]
--Generate a numbering(starting at 1)
,Row_Number() Over(Partition By ForeignId Order By Id Desc) as ContactNumber --Desc because older posts should be numbered last
FROM SupportContacts
Where ForeignId In (1,2,3,5)
)
Select nc.[Id]
,nc.[ForeignId]
,sc.[Details]
From NumberedContacts nc
Inner Join SupportContacts sc on nc.Id = sc.Id
Where nc.ContactNumber <= 2 --Only grab the last 2 contacts per ForeignId
;
In SqlFiddle, the second query actually gets a RID Lookup, whereas in production with a million records it produces a Table Scan (the IN clause eliminates 99% of the rows)
Otherwise the query plan shown in SQL Fiddle is identical, the only difference being that for the second query the RID Lookup in SQL Fiddle, is a Table Scan in production :(
I would like to understand possibilities that would cause this behavior? What kinds of things would you look at to help determine the cause of it using a table scan here?
How can I influence it to use a RID Lookup there?
From looking at operation costs in the actual execution plan, I believe I can get the second query very close in performance to the first query if I can get it to use a RID Lookup. If I don't select the Detail column, then the performance of both queries is very close in production. It is only after adding other columns like Detail that performance degrades significantly for the second query. When I put it in SQL Fiddle and saw that the execution plan used an RID Lookup, I was surprised but slightly confused...
It doesn't have a clustered index because in testing with different clustered indexes, there was slightly worse performance for this and other queries. That was before I began adding other columns like Details though, and I can experiment with that more, but would like to have a understanding of what is going on now before I start shooting in the dark with random indexes.
What if you would change your main index to include the Details column?
If you use:
CREATE NONCLUSTERED INDEX [IX_SupportContacts_ForeignIdAsc_IdDesc]
ON SupportContacts ([ForeignId] ASC, [Id] DESC)
INCLUDE (Details);
then neither a RID lookup nor a table scan would be needed, since your query could be satisfied from just the index itself....
The differences in the query plans will be dependent on the types of indexes that exist and the statistics of the data for those tables in the different environments.
The optimiser uses the statistics (histograms of data frequency, mostly) and the available indexes to decide which execution plan is going to be the quickest.
So, for example, you have noticed that the performance degrades when the 'Details' column is included. This is an almost sure sign that either the 'Details' column is not part of an index, or if it is part of an index, the data in that column is mostly unique such that the index accesses would be equivalent (or almost equivalent) to a table scan.
Often when this situation arises, the optimiser will choose a table scan over the index access, as it can take advantage of things like block reads to access the table records faster than perhaps a fragmented read of an index.
To influence the path that will be chose by the optimiser, you would need to look at possible indexes that could be added/modified to make an index access more efficient, but this should be done with care as it can adversely affect other queries as well as possibly degrading insert performance.
The other important activity you can do to help the optimiser is to make sure the table statistics are kept up to date and refreshed at a frequency that is appropriate to the rate of change of the frequency distribution in the table data
If it's true that 99% of the rows would be omitted if it performed the query using the relevant index + RID then the likeliest problem in your production environment is that your statistics are out of date and the optimiser doesn't realise that ForeignID in (1,2,3,5) would limit the result set to 1% of the total data.
Here's a good link for discovering more about statistics from Pinal Dave: http://blog.sqlauthority.com/2010/01/25/sql-server-find-statistics-update-date-update-statistics/
As for forcing the optimiser to follow the correct path WITHOUT updating the statistics, you could use a table hint - if you know the index that your plan should be using which contains the ID and ForeignID columns then stick that in your query as a hint and force SQL optimiser to use the index:
http://msdn.microsoft.com/en-us/library/ms187373.aspx
FYI, if you want the best performance from your second query, use this index and avoid the headache you're experiencing altogether:
create index ix1 on SupportContacts(ForeignID, Id DESC) include (Details);

Does SQL performance degrade as the number elements in an "IN" clause increases?

I have a query like this,
SELECT Name FROM Customers WHERE Id IN (1,4,3,6,7)
There might be millions of customers in the DataBase. Will there be an efficiency problem with this query ? When the number of Ids inside IN statement are more ? If so, Why and Any workaround ?
I Use SQLServer. Below is my table Structure
Id|Name|Designation
Id is the primary key -non clustered index.
This query is as basic as it can get.
If you need to find the name of 5 customers, there is simply no other sane way of writing it.
It will perform well if you have an index on ID. The performance is almost instantaneous, directly related to the number of items in the IN clause.
If you don't it will scan the table, and the performance becomes directly related to the number of records in the table.
Assuming you have properly indexed the Id column, there should be no problem. That is the correct method, and if it does not work, you need a new database. (Millions shouldn't be an issue with most regular pieces of software; if you make it to multiple billions you might need to investigate clustered databases).
If you execute the following query:
select * from sys.objects where object_id in (
1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,
31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,
58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,
85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,
109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,
130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,
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5761,5762,5763,5764,5765,5766,5767,5768,5769,5770,5771,5772,5773,5774,5775,5776)
(I'm not going to break up all the lines).
In the resulting query, approximately 5% of the cost of the query is taken up with a constant scan (which is effectively turning all of those numbers into a temp table internally and that table is then passed to a join operator).
But, this is a remarkably simple query overall. For any more complex query, I'd expect that the cost, as a percentage, will go down (since I expect the absolute cost to remain the same)
I know this isn't the question that was asked, but, say your list of IDs came from another query:
SELECT Name FROM Customers WHERE Id IN (SELECT ID FROM X WHERE X.FIELD = COND)
Then this is cause to rewrite your query using EXISTS:
SELECT Name
FROM CUSTOMERS
WHERE EXISTS
(
SELECT *
FROM X
WHERE X.FIELD = COND
AND X.ID = CUSTOMERS.ID
);
This is efficient because EXISTS gives more opportunity for the optimizer to determine an efficient execution path, whereas IN forces the subquery to be fully evaluated.
The query you specified didn't have a subsquery. It just has a list of constants which has little opportunity to be further optimized. As is, you have to do with the best you got, i.e. index the ID column as recommended by #zebediah49.

FreeText Query is slow - includes TOP and Order By

The Product table has 700K records in it. The query:
SELECT TOP 1 ID,
Name
FROM Product
WHERE contains(Name, '"White Dress"')
ORDER BY DateMadeNew desc
takes about 1 minute to run. There is an non-clustered index on DateMadeNew and FreeText index on Name.
If I remove TOP 1 or Order By - it takes less then 1 second to run.
Here is the link to execution plan.
http://screencast.com/t/ZDczMzg5N
Looks like FullTextMatch has over 400K executions. Why is this happening? How can it be made faster?
UPDATE 5/3/2010
Looks like cardinality is out of whack on multi word FreeText searches:
Optimizer estimates that there are 28K records matching 'White Dress', while in reality there is only 1.
http://screencast.com/t/NjM3ZjE4NjAt
If I replace 'White Dress' with 'White', estimated number is '27,951', while actual number is '28,487' which is a lot better.
It seems like Optimizer is using only the first word in phrase being searched for cardinality.
Looks like FullTextMatch has over 400K executions. Why is this happening?
Since you have an index combined with TOP 1, optimizer thinks that it will be better to traverse the index, checking each record for the entry.
How can it be made faster?
If updating the statistics does not help, try adding a hint to your query:
SELECT TOP 1 *
FROM product pt
WHERE CONTAINS(name, '"test1"')
ORDER BY
datemadenew DESC
OPTION (HASH JOIN)
This will force the engine to use a HASH JOIN algorithm to join your table and the output of the fulltext query.
Fulltext query is regarded as a remote source returning the set of values indexed by KEY INDEX provided in the FULLTEXT INDEX definition.
Update:
If your ORM uses parametrized queries, you can create a plan guide.
Use Profiler to intercept the query that the ORM sends verbatim
Generate a correct plan in SSMS using hints and save it as XML
Use sp_create_plan_guide with an OPTION USE PLAN to force the optimizer always use this plan.
Edit
From http://technet.microsoft.com/en-us/library/cc721269.aspx#_Toc202506240
The most important thing is that the
correct join type is picked for
full-text query. Cardinality
estimation on the FulltextMatch STVF
is very important for the right plan.
So the first thing to check is the
FulltextMatch cardinality estimation.
This is the estimated number of hits
in the index for the full-text search
string. For example, in the query in
Figure 3 this should be close to the
number of documents containing the
term ‘word’. In most cases it should
be very accurate but if the estimate
was off by a long way, you could
generate bad plans. The estimation for
single terms is normally very good,
but estimating multiple terms such as
phrases or AND queries is more complex
since it is not possible to know what
the intersection of terms in the index
will be based on the frequency of the
terms in the index. If the cardinality
estimation is good, a bad plan
probably is caused by the query
optimizer cost model. The only way to
fix the plan issue is to use a query
hint to force a certain kind of join
or OPTIMIZE FOR.
So it simply cannot know from the information it stores whether the 2 search terms together are likely to be quite independent or commonly found together. Maybe you should have 2 separate procedures one for single word queries that you let the optimiser do its stuff on and one for multi word procedures that you force a "good enough" plan on (sys.dm_fts_index_keywords might help if you don't want a one size fits all plan).
NB: Your single word procedure would likely need the WITH RECOMPILE option looking at this bit of the article.
In SQL Server 2008 full-text search we have the ability to alter the plan that is generated based on a cardinality estimation of the search term used. If the query plan is fixed (as it is in a parameterized query inside a stored procedure), this step does not take place. Therefore, the compiled plan always serves this query, even if this plan is not ideal for a given search term.
Original Answer
Your new plan still looks pretty bad though. It looks like it is only returning 1 row from the full text query part but scanning all 770159 rows in the Product table.
How does this perform?
CREATE TABLE #tempResults
(
ID int primary key,
Name varchar(200),
DateMadeNew datetime
)
INSERT INTO #tempResults
SELECT
ID, Name, DateMadeNew
FROM Product
WHERE contains(Name, '"White Dress"')
SELECT TOP 1
*
FROM #tempResults
ORDER BY DateMadeNew desc
I can't see the linked execution plan, network police are blocking that, so this is just a guess...
if it is running fast without the TOP and ORDER BY, try doing this:
SELECT TOP 1
*
FROM (SELECT
ID, Name, DateMadeNew
FROM Product
WHERE contains(Name, '"White Dress"')
) dt
ORDER BY DateMadeNew desc
A couple of thoughts on this one:
1) Have you updated the statistics on the Product table? It would be useful to see the estimates and actual number of rows on the operations there too.
2) What version of SQL Server are you using? I had a similar issue with SQL Server 2008 that turned out to be nothing more than not having Service Pack 1 installed. Install SP1 and a FreeText query that was taking a couple of minutes (due to a huge number of actual executions against actual) went down to taking a second.
I had the same problem earlier.
The performance depends on which unique index you choose for full text indexing.
My table has two unique columns - ID and article_number.
The query:
select top 50 id, article_number, name, ...
from ARTICLE
CONTAINS(*,'"BLACK*" AND "WHITE*"')
ORDER BY ARTICLE_NUMBER
If the full text index is connected to ID then it is slow depending on the searched words.
If the full text index is connected to ARTICLE_NUMBER UNIQUE index then it was always fast.
I have better solution.
I. Let's first overview proposed solutions as they also may be used in some cases:
OPTION (HASH JOIN) - is not good as you may get error "Query processor could not produce a query plan because of the hints defined in this query. Resubmit the query without specifying any hints and without using SET FORCEPLAN."
SELECT TOP 1 * FROM (ORIGINAL_SELECT) ORDER BY ... - is not good, when you need to use paginating results from you ORIGINAL_SELECT
sp_create_plan_guide - is not good, as to use plan_guide you have to save plan for specific sql statement, this won't work for dynamic sql statements (e.g. generated by ORM)
II. My Solution contains of two parts
1. Self join table used for Full Text search
2. Use MS SQL HASH Join Hints MSDN Join Hints
Your SQL :
SELECT TOP 1 ID, Name FROM Product WHERE contains(Name, '"White Dress"')
ORDER BY DateMadeNew desc
Should be rewritten as :
SELECT TOP 1 p.ID, p.Name FROM Product p INNER HASH JOIN Product fts ON fts.ID = p.ID
WHERE contains(fts.Name, '"White Dress"')
ORDER BY p.DateMadeNew desc
If you are using NHibernate with/without Castle Active Records, I've replied in post how to write interceptor to modify your query to replace INNER JOIN by INNER HASH JOIN