Does SQL performance degrade as the number elements in an "IN" clause increases? - sql
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.
Related
How can I make large IN clauses more efficient in SQL Server?
My current query runs very slow when accessing a DB with pretty large tables
SELECT *
FROM table1
WHERE timestamp BETWEEN 635433140000000000 AND 635433150000000000
AND ID IN ('element1', 'element2', 'element3', ... , 'element 3002');
As you can see the IN clause has several thousand values. This query is executed roughly every second.
Is there another way to write it to improve performance?
Add the elements of the IN to an indexed temporary (if the elements change) or permanent table (if the elements are static) and inner join on them.
This is your query:
SELECT *
FROM table1
WHERE timestamp BETWEEN 635433140000000000 AND 635433150000000000 AND
ID IN ('element1', 'element2', 'element3', ... , 'element 3002');
The query is fine. Add an index on table1(id, timestamp).
The best answer depends on how those element ID listings are selected, but it all comes down to one thing: getting them into a table somewhere that you can join against. That will help performance tremendously. But again, the real question here is how best to get those items into a table, and that will depend on information not yet included in the question.
You should check your execution plan, I guess you could have a parameter sniffing problem caused by your between. Check if the actual rows are way off you expected values. And you can rewrite your IN to a EXISTS, which works inside like a INNER JOIN.
Oracle: How can I find tablespace fragmentation?
I've a JOIN beween two tables. It's really really slow and I can't find why.
The query takes hours in a PRODUCTION environment on a very big Client.
Can you ask me what you need to understand why it doesn't work well?
I can add indexes, partition the table, etc. It's Oracle 10g.
I expect a few thousand record. Because of the following condition:
f.eif_campo1 != c.fornitura AND and f.field29 = 'New'
Infact it should be always verified for all 18 million records
SELECT c.id_messaggio
,f.campo1
,c.f
FROM
flows c,
tab f
WHERE
f.field198 = c.id_messaggio
AND f.extra_id = c.extra_id
and f.field1 != c.ExampleF
and f.field29 = 'New'
and c.processtype in ('Example1')
and c.flag_ann = 'N';
Selectivity for the following record expressed as number of distinct values:
COUNT (DISTINCT extra_id) =>17*10^6,
COUNT (DISTINCT (extra_id || field20)) =>17*10^6,
COUNT (DISTINCT field198) =>36*10^6,
COUNT (DISTINCT (field19 || field20)) =>45*10^6,
COUNT (DISTINCT (field1)) =>18*10^6,
COUNT (DISTINCT (field20)) =>47
This is the execution plan [See large image][1]
![enter image description here][2]
Extra details:
I have relaxed one contition to see how many records are taken. 300 thousand.
![enter image description here][7]
--03:57 mins with parallel execution /*+ parallel(c 8) parallel(f 24) */
--395.358 rows
SELECT count(1)
FROM
flows c,
flet f
WHERE
f.field19 = c.id_messaggio
AND f.extra_id = c.extra_id
and f.field20 = 'ExampleF'
and c.process_type in ('ExampleP')
and c.flag_ann = 'N';
Your explain plan shows the following.
The database uses an index to retrieve rows from ENI_FLUSSI_HUB where
flh_tipo_processo_cod in ('VT','VOLTURA_ENI','CC')
It then winnows the rows
where flh_flag_ann = 'N'
This produces a result set which is used to access
rows from ETL_ELAB_INTERF_FLAT on the basis of f.idde_identif_dati_ext_id =
c.idde_identif_dati_ext_id
Finally those rows are filtered on the basis of the
remaining parts of the WHERE clause.
Now, the starting point is a good one if flh_tipo_processo_cod is a selective
column: that is, if it contains hundreds of different values, or if the values in
your list are relatively rare. It might even be a good path of the flag column
identifies relatively few columns with a value of 'N'. So you need to understand
both the distribution of your data - how many distinct values you have - and its
skew - which values appear very often or hardly at all. The overall
performance suggests that the distribution and/or skew of the
flh_tipo_processo_cod and flh_flag_ann columns is not good.
So what can you do? One approach is to follow Ben's suggestion, and use full
table scans. If you have an Enterprise Edition licence and plenty of CPU capacity
you could try parallel query to improve things. That might still be too slow, or it might be too disruptive for other users.
An alternative approach would be to use better indexes. A composite index on
eni_flussi_hub(flh_tipo_processo_cod,flh_flag_ann,idde_identif_dati_ext_id,
flh_fornitura,flh_id_messaggio) would avoid the need to read that table. Whether
this would be a new index or a replacement for ENI_FLK_IDX3 depends on the other
activity against the table. You might be able to benefit from index compression.
All the columns in the query projection are referenced in the WHERE clause. So
you could also use a composite index on the other table to avoid table reads. Agsin you need to understand the distribution and skew of the data. But you should probably lead with the least selective columns. Something like etl_elab_interf_flat(etl_elab_interf_flat,eif_campo200,dde_identif_dati_ext_id,eif_campo1,eif_campo198). Probably this is a new index. It's unlikely you would want to replace ETL_EIF_FK_IDX4 with this (especially if that really is an index on a foreign key constraint)..
Of course these are just guesses on my part. Tuning is a science and to do it properly requires lots of data. Use the Wait Interface to investigate where the database is spending its time. Use the 10053 event to understand why the Optimizer makes the choices it does. But above all, don't implement partitioning unless you really know the ramifications.
The simple answer seems to be your explain plan. You're accessing both tables by index rowid. Whilst to select a single row you cannot - to my knowledge - get faster, in your case you're selecting a lot more than a single row. This means that for every single row you, you're going into both tables one row at a time, which when you're looking a significant proportion of a table or index is not what you want to do. My suggestion would be to force a full scan of one or both of your tables. Try to use the smaller as a driver first: SELECT /*+ full(c) */ c.flh_id_messaggio , f.eif_campo1 , c.f FROM flows c, JOIN flet f ON f.field19 = c.flh_id_messaggio AND f.extra_id = c.extra_id AND f.field1 <> c.f WHERE ... But you may have to change /*+ full(c) */ to /*+ full(c) full(f) */. Your indexes seem to be separate column indexes as well. For this, and if possible, I would have indexes on: flows of id_messaggio, extra_id, f and on flet of field19, extra_id, field1. This will only really matter if you do not use as full scan. Or, if you have everything you're returning and selecting is in one index.
What is the most efficient way to count rows in a table in SQLite?
I've always just used "SELECT COUNT(1) FROM X" but perhaps this is not the most efficient. Any thoughts? Other options include SELECT COUNT(*) or perhaps getting the last inserted id if it is auto-incremented (and never deleted). How about if I just want to know if there is anything in the table at all? (e.g., count > 0?)
The best way is to make sure that you run SELECT COUNT on a single column (SELECT COUNT(*) is slower) - but SELECT COUNT will always be the fastest way to get a count of things (the database optimizes the query internally). If you check out the comments below, you can see arguments for why SELECT COUNT(1) is probably your best option.
To follow up on girasquid's answer, as a data point, I have a sqlite table with 2.3 million rows. Using select count(*) from table, it took over 3 seconds to count the rows. I also tried using SELECT rowid FROM table, (thinking that rowid is a default primary indexed key) but that was no faster. Then I made an index on one of the fields in the database (just an arbitrary field, but I chose an integer field because I knew from past experience that indexes on short fields can be very fast, I think because the index is stored a copy of the value in the index itself). SELECT my_short_field FROM table brought the time down to less than a second.
If you are sure (really sure) that you've never deleted any row from that table and your table has not been defined with the WITHOUT ROWID optimization you can have the number of rows by calling: select max(RowId) from table; Or if your table is a circular queue you could use something like select MaxRowId - MinRowId + 1 from (select max(RowId) as MaxRowId from table) JOIN (select min(RowId) as MinRowId from table); This is really really fast (milliseconds), but you must pay attention because sqlite says that row id is unique among all rows in the same table. SQLite does not declare that the row ids are and will be always consecutive numbers.
The fastest way to get row counts is directly from the table metadata, if any. Unfortunately, I can't find a reference for this kind of data being available in SQLite. Failing that, any query of the type SELECT COUNT(non-NULL constant value) FROM table should optimize to avoid the need for a table, or even an index, scan. Ideally the engine will simply return the current number of rows known to be in the table from internal metadata. Failing that, it simply needs to know the number of entries in the index of any non-NULL column (the primary key index being the first place to look). As soon as you introduce a column into the SELECT COUNT you are asking the engine to perform at least an index scan and possibly a table scan, and that will be slower.
I do not believe you will find a special method for this. However, you could do your select count on the primary key to be a little bit faster.
sp_spaceused 'table_name' (exclude single quote) this will return the number of rows in the above table, this is the most efficient way i have come across yet. it's more efficient than select Count(1) from 'table_name' (exclude single quote) sp_spaceused can be used for any table, it's very helpful when the table is exceptionally big (hundreds of millions of rows), returns number of rows right a way, whereas 'select Count(1)' might take more than 10 seconds. Moreover, it does not need any column names/key field to consider.
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
Slow distinct query in SQL Server over large dataset
We're using SQL Server 2005 to track a fair amount of constantly incoming data (5-15 updates per second). We noticed after it has been in production for a couple months that one of the tables has started to take an obscene amount of time to query. The table has 3 columns: id -- autonumber (clustered) typeUUID -- GUID generated before the insert happens; used to group the types together typeName -- The type name (duh...) One of the queries we run is a distinct on the typeName field: SELECT DISTINCT [typeName] FROM [types] WITH (nolock); The typeName field has a non-clusted, non-unique ascending index on it. The table contains approximately 200M records at the moment. When we run this query, the query took 5m 58s to return! Perhaps we're not understanding how the indexes work... But I didn't think we mis-understood them that much. To test this a little further, we ran the following query: SELECT DISTINCT [typeName] FROM (SELECT TOP 1000000 [typeName] FROM [types] WITH (nolock)) AS [subtbl] This query returns in about 10 seconds, as I would expect, it's scanning the table. Is there something we're missing here? Why does the first query take so long? Edit: Ah, my apologies, the first query returns 76 records, thank you ninesided. Follow up: Thank you all for your answers, it makes more sense to me now (I don't know why it didn't before...). Without an index, it's doing a table scan across 200M rows, with an index, it's doing an index scan across 200M rows... SQL Server does prefer the index, and it does give a little bit of a performance boost, but nothing to be excited about. Rebuilding the index did take the query time down to just over 3m instead of 6m, an improvement, but not enough. I'm just going to recommend to my boss that we normalize the table structure. Once again, thank you all for your help!!
You do misunderstand the index. Even if it did use the index it would still do an index scan across 200M entries. This is going to take a long time, plus the time it takes to do the DISTINCT (causes a sort) and it's a bad thing to run. Seeing a DISTINCT in a query always raises a red flag and causes me to double check the query. In this case, perhaps you have a normalization issue?
There is an issue with the SQL Server optimizer when using the DISTINCT keyword. The solution was to force it to keep the same query plan by breaking out the distinct query separately. So we took queries such as: SELECT DISTINCT [typeName] FROM [types] WITH (nolock); and break it up into the following: SELECT typeName INTO #tempTable1 FROM types WITH (NOLOCK) SELECT DISTINCT typeName FROM #tempTable1 Another way to get around it is to use a GROUP BY, which gets a different optimization plan.
I doubt SQL Server will even try to use the index, it'd have to do practically the same amount of work (given the narrow table), reading all 200M rows regardless of whether it looks at the table or the index. If the index on typeName was clustered it may reduce the time taken as it shouldn't need to sort before grouping. If the cardinality of your types is low, how about maintaining a summary table which holds the list of distinct type values? A trigger on insert/update of the main table would do a check on the summary table and insert a new record when a new type is found.
As others have already pointed out - when you do a SELECT DISTINCT (typename) over your table, you'll end up with a full table scan no matter what. So it's really a matter of limiting the number of rows that need to be scanned. The question is: what do you need your DISTINCT typenames for? And how many of your 200M rows are distinct? Do you have only a handful (a few hundred at most) distinct typenames?? If so - you could have a separate table DISTINCT_TYPENAMES or something and fill those initially by doing a full table scan, and then on inserting new rows to the main table, just always check whether their typename is already in DISTINCT_TYPENAMES, and if not, add it. That way, you'd have a separate, small table with just the distinct TypeName entries, which would be lightning fast to query and/or to display. Marc
A looping approach should use multiple seeks (but loses some parallelism). It might be worth a try for cases with relatively few distinct values compared to the total number of rows (low cardinality). Idea was from this question: select typeName into #Result from Types where 1=0; declare #t varchar(100) = (select min(typeName) from Types); while #t is not null begin set #t = (select top 1 typeName from Types where typeName > #t order by typeName); if (#t is not null) insert into #Result values (#t); end select * from #Result; And looks like there are also some other methods (notably the recursive CTE #Paul White): different-ways-to-find-distinct-values-faster-methods sqlservercentral Topic873124-338-5
My first thought is statistics. To find last updated:
SELECT
name AS index_name,
STATS_DATE(object_id, index_id) AS statistics_update_date
FROM
sys.indexes
WHERE
object_id = OBJECT_ID('MyTable');
Edit: Stats are updated when indexes are rebuilt, which I see are not maintained
My second thought is that is the index still there? The TOP query should still use an index.
I've just tested on one of my tables with 57 million rows and both use the index.
An indexed view can make this faster. create view alltypes with schemabinding as select typename, count_big(*) as kount from dbo.types group by typename create unique clustered index idx on alltypes (typename) The work to keep the view up to date on each change to the base table should be moderate (depending on your application, of course -- my point is that it doesn't have to scan the whole table each time or do anything insanely expensive like that.) Alternatively you could make a small table holding all values: select distinct typename into alltypes from types alter table alltypes add primary key (typename) alter table types add foreign key (typename) references alltypes The foreign key will make sure that all values used appear in the parent alltypes table. The trouble is in ensuring that alltypes does not contain values not used in the child types table.
I should try something like this: SELECT typeName FROM [types] WITH (nolock) group by typeName; And like other i would say you need to normalize that column.
An index helps you quickly find a row. But you're asking the database to list all unique types for the entire table. An index can't help with that. You could run a nightly job which runs the query and stores it in a different table. If you require up-to-date data, you could store the last ID included in the nightly scan, and combine the results: select type from nightlyscan union select distinct type from verybigtable where rowid > lastscannedid Another option is to normalize the big table into two tables: talbe1: id, guid, typeid type table: typeid, typename This would be very beneficial if the number of types was relatively small.
I could be missing something but would it be more efficient if an overhead on load to create a view with distinct values and query that instead? This would give almost instant responses to the select if the result set is significantly smaller with the overhead over populating it on each write though given the nature of the view that might be trivial in itself. It does ask the question how many writes compared to how often you want the distinct and the importance of the speed when you do.