FreeText Query is slow - includes TOP and Order By - sql
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
Related
Will this query load the whole table in memory
If I have a really big table will this query load the whole table in memory before it filters the resets: with parent as ( select * from a101 ) select * from parent where value1 = 159 As you can see the parent query reference the whole table. Will this loaded in memory. This is a very simplified version of the query. The real query has a few joins to other tables. I am evaluating sql server 2012 and postgrsql.
In PostgreSQL (true as of 9.4, at least) CTEs act as optimisation fences. The query optimiser will not flatten CTE terms into the outer query, push down qualifiers, or pull up qualifiers, even in trivial cases. So an unqualified SELECT inside a CTE term will always do a full table scan (or an index-only scan if there's a suitable index). Thus, in PostgreSQL, these two things are very different indeed, as a simple EXPLAIN would show: with parent as ( select * from a101 ) select * from parent where value1 = 159 and SELECT * FROM ( SELECT * FROM a101 ) AS parent WHERE value1 = 159; However, that "will scan the whole table" doesn't necessarily mean "will load the whole table in memory". PostgreSQL will use a TupleStore, which will transparently spill to a tempfile on disk as it gets larger. The original justification was that DML in CTE terms was planned (and later implemented). If there's DML in a CTE term it's vital that its execution be predictable and complete. This may also be true if the CTE calls data-modifying functions. Unfortunately, nobody seems to have thought "... but what if it's just a SELECT and we want to inline it?". Many in the community appear to see this as a feature and regularly promulgate it as a workaround for optimiser issues. I find this attitude utterly perplexing. As a result, it's going to be really hard to fix this later, because people are intentionally using CTEs when they want to prevent the optimiser from altering a query. In other words, PostgreSQL abuses CTEs as pseudo-query-hints (along with the OFFSET 0 hack), because project policy says real query hints aren't desired or supported. AFAIK MS SQL Server may optimise CTE barriers, but may also choose to materialise a result set.
I just made EXPLAIN for this query in PostgreSQL. Surprisingly it does sequence scan instead of index lookup: CTE Scan on parent (cost=123.30..132.97 rows=2 width=1711) Filter: (value1 = 159) CTE parent -> Seq Scan on a101 (cost=0.00..123.30 rows=430 width=2060) I have a primary key index on value1 and it is used for simple select * from a101 where value1 = 159 query. So, the answer is it will scan the whole table. I am surprised, I thought it will work as a view or subquery, but it does not. You can use this to use index: select * from (select * from a101) parent where value1 = 159`
No. Queries are evaluated as a whole. If you look at the execution plan you will see the filter predicate will be applied to the inner search. GIven the triviality of the outer search, I am quite sure it will be optimizd away. Check execution plans - this is baseline knowledge and you better learn how to do that fast. Once you hit a real performance problem you will need to find out the issue and that is where execution plans come in.
CTE are just language syntax to make code more readable , they have no impact on query execution performance . When the query is executed , it will be executed according to predefined SQL Server query execution phases 1. FROM 2. ON 3. OUTER 4. WHERE 5. GROUP BY 6. CUBE | ROLLUP 7. HAVING 8. SELECT 9. DISTINCT 10 ORDER BY 11. TOP So WHERE filter will be applied first and then the records will be selected so complete table would not be fetched in memory.
What is the order of execution for this SQL statement
I have below SQL Query : SELECT TOP 5 C.CustomerID,C.CustomerName,C.CustomerSalary FROM Customer C WHERE C.CustomerSalary > 10000 ORDER BY C.CustomerSalary DESC What will be execution order of the following with proper explanation ? TOP Clause WHERE Clause ORDER BY Clause
Check out the documentation for the SELECT statement, in particular this section: Logical Processing Order of the SELECT statement The following steps show the logical processing order, or binding order, for a SELECT statement. This order determines when the objects defined in one step are made available to the clauses in subsequent steps. For example, if the query processor can bind to (access) the tables or views defined in the FROM clause, these objects and their columns are made available to all subsequent steps. Conversely, because the SELECT clause is step 8, any column aliases or derived columns defined in that clause cannot be referenced by preceding clauses. However, they can be referenced by subsequent clauses such as the ORDER BY clause. Note that the actual physical execution of the statement is determined by the query processor and the order may vary from this list. which gives the following order: FROM ON JOIN WHERE GROUP BY WITH CUBE or WITH ROLLUP HAVING SELECT DISTINCT ORDER BY TOP
WHERE ORDER BY TOP Here is a good article about that: http://blog.sqlauthority.com/2009/04/06/sql-server-logical-query-processing-phases-order-of-statement-execution/
Simply remember this phrase:- Fred Jones' Weird Grave Has Several Dull Owls Take the first letter of each word, and you get this:- FROM (ON) JOIN WHERE GROUP BY (WITH CUBE or WITH ROLLUP) HAVING SELECT DISTINCT ORDER BY TOP Hope that helps.
This is exact execution order, with your case. 1-FROM 2-WHERE 3-SELECT 4-ORDER BY 5-TOP
TOP, WHERE, and ORDER BY are not "executed" - they simply describe the desired result and the database query optimizer determines (hopefully) the best plan for the actual execution. The separation between "declaring the desired result" and how it is physically achieved is what makes SQL a "declarative" language. Assuming there is an index on CustomerSalary, and the table is not clustered, your query will likely be executed as an index seek + table heap access, as illustrated in this SQL Fiddle (click on View Execution Plan at the bottom): As you can see, first the correct CustomerSalary value is found through the Index Seek, then the row that value belongs to is retrieved from the table heap through RID Lookup (Row ID Lookup). The Top is just for show here (and has 0% cost), as is the Nested Loops for that matter - the starting index seek will return (at most) one row in any case. The whole query is rather efficient and will likely cost only a few I/O operations. If the table is clustered, you'll likely have another index seek instead of the table heap access, as illustrated in this SQL Fiddle (note the lack of NONCLUSTERED keyword in the DDL SQL): But beware: I was lucky this time to get the "right" execution plan. The query optimizer might have chosen a full table scan, which is sometimes actually faster on small tables. When analyzing query plans, always try to do that on realistic amounts of data!
Visit https://msdn.microsoft.com/en-us/library/ms189499.aspx for a better explanation. The following steps show the logical processing order, or binding order, for a SELECT statement. This order determines when the objects defined in one step are made available to the clauses in subsequent steps. For example, if the query processor can bind to (access) the tables or views defined in the FROM clause, these objects and their columns are made available to all subsequent steps. Conversely, because the SELECT clause is step 8, any column aliases or derived columns defined in that clause cannot be referenced by preceding clauses. However, they can be referenced by subsequent clauses such as the ORDER BY clause. Note that the actual physical execution of the statement is determined by the query processor and the order may vary from this list. FROM ON JOIN WHERE GROUP BY WITH CUBE or WITH ROLLUP HAVING SELECT DISTINCT ORDER BY TOP
My $0,02 here. There's two different concepts in action here: the logical execution order and the plan of query execution. An other was to see it is who answers the following questions: How MSSQL understood my SQL Query? What it'll do to execute it in the best possible way given the current schema and data? The first question is answered by the logical execution order. Brian's answer show what it is. It's the way SQL understood your command: "FROM Customer table (aliased as C) consider only the rows WHERE the C.CustomerSalary > 10000, ORDER them BY C.CustomerSalary in descendent order and SELECT the columns listed for the TOP 5 rows". The resultset will obey that meaning The second question's answer is the query execution plan - and it depends on your schema (table definitions, selectivity of data, quantity of rows in the customer table, defined indexes, etc) since is heavily dependant of SQL Server optimizer internal workings.
Here is the complete sequence for sql server : 1. FROM 2. ON 3. JOIN 4. WHERE 5. GROUP BY 6. WITH CUBE or WITH ROLLUP 7. HAVING 8. SELECT 9. DISTINCT 10. ORDER BY 11. TOP So from the above list, you can easily understand the execution sequence of TOP, WHERE and ORDER BY which is : 1. WHERE 2. ORDER BY 3. TOP Get more information about it from Microsoft
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, 151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216,217,218,219,220,221,222,223,224,225,226,227,228,229,230,231,232,233,234,235,236,237,238,239,240,241,242,243,244,245,246,247,248,249,250,251,252,253,254,255,256,257,258,259,260,261,262,263,264,265,266,267,268,269,270,271,272,273,274,275,276,277,278,279,280,281,282,283,284,285,286,287,288,289,290,291,292,293,294,295,296,297,298,299,300,301,302,303,304,305,306,307,308,309,310,311,312,313,314,315,316,317,318,319,320,321,322,323,324,325,326,327,328,329,330,331,332,333,334,335,336,337,338,339,340,341,342,343,344,345,346,347,348,349,350,351,352,353,354,355,356,357,358,359,360,361,362,363,364,365,366,367,368,369,370,371,372,373,374,375,376,377,378,379,380,381,382,383,384,385,386,387,388,389,390,391,392,393,394,395,396,397,398,399,400,401,402,403,404,405,406,407,408,409,410,411,412,413,414,415,416,417,418,419,420,421,422,423,424,425,426,427,428,429,430,431,432,433,434,435,436,437,438,439,440,441,442,443,444,445,446,447,448,449,450,451,452,453,454,455,456,457,458,459,460,461,462,463,464,465,466,467,468,469,470,471,472,473,474,475,476,477,478,479,480,481,482,483,484,485,486,487,488,489,490,491,492,493,494,495,496,497,498,499,500,501,502,503,504,505,506,507,508,509,510,511,512,513,514,515,516,517,518,519,520,521,522,523,524,525,526,527,528,529,530,531,532,533,534,535,536,537,538,539,540,541,542,543,544,545,546,547,548,549,550,551,552,553,554,555,556,557,558,559,560,561,562,563,564,565,566,567,568,569,570,571,572,573,574,575,576,577,578,579,580,581,582,583,584,585,586,587,588,589,590,591,592,593,594,595,596,597,598,599,600,601,602,603,604,605,606,607,608,609,610,611,612,613,614,615,616,617,618,619,620,621,622,623,624,625,626,627,628,629,630,631,632,633,634,635,636,637,638,639,640,641,642,643,644,645,646,647,648,649,650,651,652,653,654,655,656,657,658,659,660,661,662,663,664,665,666,667,668,669,670,671,672,673,674,675,676,677,678,679,680,681,682,683,684,685,686,687,688,689,690,691,692,693,694,695,696,697,698,699,700,701,702,703,704,705,706,707,708,709,710,711,712,713,714,715,716,717,718,719,720,721,722,723,724,725,726,727,728,729,730,731,732,733,734,735,736,737,738,739,740,741,742,743,744,745,746,747,748,749,750,751,752,753,754,755,756,757,758,759,760,761,762,763,764,765,766,767,768,769,770,771,772,773,774,775,776,777,778,779,780,781,782,783,784,785,786,787,788,789,790,791,792,793,794,795,796,797,798,799,800,801,802,803,804,805,806,807,808,809,810,811,812,813,814,815,816,817,818,819,820,821,822,823,824,825,826,827,828,829,830,831,832,833,834,835,836,837,838,839,840,841,842,843,844,845,846,847,848,849,850,851,852,853,854,855,856,857,858,859,860,861,862,863,864,865,866,867,868,869,870,871,872,873,874,875,876,877,878,879,880,881,882,883,884,885,886,887,888,889,890,891,892,893,894,895,896,897,898,899,900,901,902,903,904,905,906,907,908,909,910,911,912,913,914,915,916,917,918,919,920,921,922,923,924,925,926,927,928,929,930,931,932,933,934,935,936,937,938,939,940,941,942,943,944,945,946,947,948,949,950,951,952,953,954,955,956,957,958,959,960,961,962,963,964,965,966,967,968,969,970,971,972,973,974,975,976,977,978,979,980,981,982,983,984,985,986,987,988,989,990,991,992,993,994,995,996,997,998,999,1000,1001,1002,1003,1004,1005,1006,1007,1008,1009,1010,1011,1012,1013,1014,1015,1016,1017,1018,1019,1020,1021,1022,1023,1024,1025,1026,1027,1028,1029,1030,1031,1032,1033,1034,1035,1036,1037,1038,1039,1040,1041,1042,1043,1044,1045,1046,1047,1048,1049,1050,1051,1052,1053,1054,1055,1056,1057,1058,1059,1060,1061,1062,1063,1064,1065,1066,1067,1068,1069,1070,1071,1072,1073,1074,1075,1076,1077,1078,1079,1080,1081,1082,1083,1084,1085,1086,1087,1088,1089,1090,1091,1092,1093,1094,1095,1096,1097,1098,1099,1100,1101,1102,1103,1104,1105,1106,1107,1108,1109,1110,1111,1112,1113,1114,1115,1116,1117,1118,1119,1120,1121,1122,1123,1124,1125,1126,1127,1128,1129,1130,1131,1132,1133,1134,1135,1136,1137,1138,1139,1140,1141,1142,1143,1144,1145,1146,1147,1148,1149,1150,1151,1152,1153,1154,1155,1156,1157,1158,1159,1160,1161,1162,1163,1164,1165,1166,1167,1168,1169,1170,1171,1172,1173,1174,1175,1176,1177,1178,1179,1180,1181,1182,1183,1184,1185,1186,1187,1188,1189,1190,1191,1192,1193,1194,1195,1196,1197,1198,1199,1200,1201,1202,1203,1204,1205,1206,1207,1208,1209,1210,1211,1212,1213,1214,1215,1216,1217,1218,1219,1220,1221,1222,1223,1224,1225,1226,1227,1228,1229,1230,1231,1232,1233,1234,1235,1236,1237,1238,1239,1240,1241,1242,1243,1244,1245,1246,1247,1248,1249,1250,1251,1252,1253,1254,1255,1256,1257,1258,1259,1260,1261,1262,1263,1264,1265,1266,1267,1268,1269,1270,1271,1272,1273,1274,1275,1276,1277,1278,1279,1280,1281,1282,1283,1284,1285,1286,1287,1288,1289,1290,1291,1292,1293,1294,1295,1296,1297,1298,1299,1300,1301,1302,1303,1304,1305,1306,1307,1308,1309,1310,1311,1312,1313,1314,1315,1316,1317,1318,1319,1320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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.
Selecting from a Large Table SQL 2005
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).