Performance: Subquery or Joining - sql

I got a little question about performance of a subquery / joining another table
INSERT
INTO Original.Person
(
PID, Name, Surname, SID
)
(
SELECT ma.PID_new , TBL.Name , ma.Surname, TBL.SID
FROM Copy.Person TBL , original.MATabelle MA
WHERE TBL.PID = p_PID_old
AND TBL.PID = MA.PID_old
);
This is my SQL, now this thing runs around 1 million times or more.
My question is what would be faster?
If I change TBL.SID to (Select new from helptable where old = tbl.sid)
OR
If I add the 'HelpTable' to the from and do the joining in the where?
edit1
Well, this script runs only as much as there r persons.
My program has 2 modules one that populates MaTabelle and one that transfers data. This program does merge 2 databases together and coz of this, sometimes the same Key is used.
Now I'm working on a solution that no duplicate Keys exists.
My solution is to make a 'HelpTable'. The owner of the key(SID) generates a new key and writes it into a 'HelpTable'. All other tables that use this key can read it from the 'HelpTable'.
edit2
Just got something in my mind:
if a table as a Key that can be null(foreignkey that is not linked)
then this won't work with the from or?


Modern RDBMs, including Oracle, optimize most joins and sub queries down to the same execution plan.
Therefore, I would go ahead and write your query in the way that is simplest for you and focus on ensuring that you've fully optimized your indexes.
If you provide your final query and your database schema, we might be able to offer detailed suggestions, including information regarding potential locking issues.
Edit
Here are some general tips that apply to your query:
For joins, ensure that you have an index on the columns that you are joining on. Be sure to apply an index to the joined columns in both tables. You might think you only need the index in one direction, but you should index both, since sometimes the database determines that it's better to join in the opposite direction.
For WHERE clauses, ensure that you have indexes on the columns mentioned in the WHERE.
For inserting many rows, it's best if you can insert them all in a single query.
For inserting on a table with a clustered index, it's best if you insert with incremental values for the clustered index so that the new rows are appended to the end of the data. This avoids rebuilding the index and often avoids locks on the existing records, which would slow down SELECT queries against existing rows. Basically, inserts become less painful to other users of the system.


Joining would be much faster than a subquery


The main difference betwen subquery and join is
subquery is faster when we have to retrieve data from large number of tables.Because it becomes tedious to join more tables.
join is faster to retrieve data from database when we have less number of tables.
Also, this joins vs subquery can give you some more info


Instead of focussing on whether to use join or subquery, I would focus on the necessity of doing 1,000,000 executions of that particular insert statement. Especially as Oracle's optimizer -as Marcus Adams already pointed out- will optimize and rewrite your statements under the covers to its most optimal form.
Are you populating MaTabelle 1,000,000 times with only a few rows and issue that statement? If yes, then the answer is to do it in one shot. Can you provide some more information on your process that is executing this statement so many times?
EDIT: You indicate that this insert statement is executed for every person. In that case the advice is to populate MATabelle first and then execute once:
INSERT
INTO Original.Person
(
PID, Name, Surname, SID
)
(
SELECT ma.PID_new , TBL.Name , ma.Surname, TBL.SID
FROM Copy.Person TBL , original.MATabelle MA
WHERE TBL.PID = MA.PID_old
);
Regards,
Rob.

Related

Will a SQL DELETE with a sub query execute inefficiently if there are many rows in the source table?

I am looking at an application and I found this SQL:
DELETE FROM Phrase
WHERE PhraseId NOT IN(SELECT Id FROM PhraseSource)
The intention of the SQL is to delete rows from Phrase that are not in the PhraseSource table.
The two tables are identical and have the following structure
Id - GUID primary key
...
...
...
Modified int
the ... columns are about ten columns containing text and numeric data. The PhraseSource table may or may not contain more recent rows with a higher number in the Modified column and different text and numeric data.
Can someone tell me will this query execute the SELECT Id from PhraseSource for every row in the Phrase table? If so is there a more efficient way that this could be coded.

1. Will this query execute the SELECT Id from PhraseSource for every row?
No.
In SQL you express what you want to do, not how you want it to be done1. The engine will create an execution plan to do what you want in the most performant way it can.
For your query, executing the query for each row is not necessary. Instead the engine will create an execution plan that executes the subquery once, then does a left anti-semi join to determine what IDs are not present in the PhraseSource table.
You can verify this when you include the Actual Execution Plan in SQL Server Management Studio.
2. Is there a more efficient way that this could be coded?
A little bit more efficient, as follows:
DELETE
p
FROM
Phrase AS p
WHERE
NOT EXISTS (
SELECT
1
FROM
PhraseSource AS ps
WHERE
ps.Id=p.PhraseId
);
This has been shown in tests done by user Aaron Bertrand on sqlperformance.com: Should I use NOT IN, OUTER APPLY, LEFT OUTER JOIN, EXCEPT, or NOT EXISTS?:
Conclusion
[...] for the pattern of finding all rows in table A where some condition does not exist in table B, NOT EXISTS is typically going to be your best choice.
Another benefit of using NOT EXISTS with a correlated subquery is that it does not have problems when PhraseSource.Id can be NULL. I suggest you read up on IN/NOT IN vs NULL values in the subquery. E.g. you can read more about that on sqlbadpractices.com: Using NOT IN operator with null values.
The PhraseSource.Id column is probably not nullable in your schema, but I prefer using a method that is resilient in all possible schemas.
1. Exceptions exist when forcing the engine to use a specific path, e.g. with Table Hints or Query Hints. The engine doesn't always get things right.

In this case the sub-query could be evaluated for each row if the database system is not smart enough (but in case of MS SQL Server, I suppose it should be able to recognize the fact that you don't need to evaluate the subquery more than once).
Still there is a better solution:
DELETE p
FROM Phrase p
LEFT JOIN PhraseSource ps ON ps.Id = p.PhraseId
WHERE ps.Id IS NULL
This uses the LEFT JOIN which matches the rows of both tables, but in case there is no match it leaves the ps entry NULL. Now you just check for NULLs on the left side to see which Phrases do not have a match and will delete those.
All types of JOIN statements are very nicely described in this answer.
Here you can see three different approaches for a similar issue compared on MySQL. As #Drammy mentions, to actually see the performance of a given approach, you could see the execution plan on your target database and do performance testing on different approaches of the same problem.

That query should optimise into a join. Have you looked at the execution plan?
If you're experiencing poor performance it is likely because of the guid primary keys.
A primary key is clustered by default. If the guid primary key is clustered on your table that means the data in the tables is ordered by the primary key. The problem with guids as clustered keys is that when you delete one record the table has to be reordered and shuffled around on disk.
This article is a good read on the topic..
https://blog.codinghorror.com/primary-keys-ids-versus-guids/

Exclude Certain Records with Certain Values SQL Select

I've used the solution (by AdaTheDev) from the thread below as it relates to the same question:
How to exclude records with certain values in sql select
But when applying the same query to over 40,000 records, the query takes too long to process (>30mins). Is there another way that's efficient in querying for certain records with certain values (the same question as in the above stackoverflow thread). I've attempted to use this below and still no luck:
SELECT StoreId
FROM sc
WHERE StoreId NOT IN (
SELECT StoreId
FROM StoreClients
Where ClientId=5
);
Thanks --

You could use EXISTS:
SELECT StoreId
FROM sc
WHERE NOT EXISTS (
SELECT 1
FROM StoreClients cl
WHERE sc.StoreId = cl.StoreId
AND cl.ClientId = 5
)
Make sure to create an index on StoreId column. Your query could also benefit from an index on ClientId.

40,000 rows isn't too big for SQL server. The other thread is suggesting some good queries too. If I understand correctly, your problem right now is the performance.
To improve the performance, you may need to add a new index to your table, or just update the statistics on your table.
If you are running this query in SQL server management studio for testing and performance tuning, make sure that you are selecting "Include Actual Execution Plan". This will make the query to take longer to execute, but the execution plan result can help you on where the time is spent.
It usually suggests adding some indexes to improve the performance, which is easy to follow.
If adding new indexes are not possible, then you have to spend some time reading on how to understand the execution plan's diagram and finding the slow areas.

Join to SELECT vs. Join to Tableset

For the DB gurus out there, I was wondering if there is any functional/performance difference between Joining to the results a SELECT statement and Joining to a previously filled table variable. I'm working in SQL Server 2008 R2.
Example (TSQL):
-- Create a test table
DROP TABLE [dbo].[TestTable]
CREATE TABLE [dbo].[TestTable](
[id] [int] NOT NULL,
[value] [varchar](max) NULL
) ON [PRIMARY]
-- Populate the test table with a few rows
INSERT INTO [dbo].[TestTable]
SELECT 1123, 'test1'
INSERT INTO [dbo].[TestTable]
SELECT 2234, 'test2'
INSERT INTO [dbo].[TestTable]
SELECT 3345, 'test3'
-- Create a reference table
DROP TABLE [dbo].[TestRefTable]
CREATE TABLE [dbo].[TestRefTable](
[id] [int] NOT NULL,
[refvalue] [varchar](max) NULL
) ON [PRIMARY]
-- Populate the reference table with a few rows
INSERT INTO [dbo].[TestRefTable]
SELECT 1123, 'ref1'
INSERT INTO [dbo].[TestRefTable]
SELECT 2234, 'ref2'
-- Scenario 1: Insert matching results into it's own table variable, then Join
-- Create a table variable
DECLARE #subset TABLE ([id] INT NOT NULL, [refvalue] VARCHAR(MAX))
INSERT INTO #subset
SELECT * FROM [dbo].[TestRefTable]
WHERE [dbo].[TestRefTable].[id] = 1123
SELECT t.*, s.*
FROM [dbo].[TestTable] t
JOIN #subset s
ON t.id = s.id
-- Scenario 2: Join directly to SELECT results
SELECT t.*, s.*
FROM [dbo].TestTable t
JOIN (SELECT * FROM [dbo].[TestRefTable] WHERE id = 1123) s
ON t.id = s.id
In the "real" world, the tables and table variable are pre-defined. What I'm looking at is being able to have the matched reference rows available for further operations, but I'm concerned that the extra steps will slow the query down. Are there technical reasons as to why one would be faster than the other? What sort of performance difference may be seen between the two approaches? I realize it is difficult (if not impossible) to give a definitive answer, just looking for some advice for this scenario.

The database engine has an optimizer to figure out the best way to execute a query. There is more under the hood than you probably imagine. For instance, when SQL Server is doing a join, it has a choice of at least four join algorithms:
Nested Loop
Index Lookup
Merge Join
Hash Join
(not to mention the multi-threaded versions of these.)
It is not important that you understand how each of these works. You just need to understand two things: different algorithms are best under different circumstances and SQL Server does its best to choose the best algorithm.
The choice of join algorithm is only one thing the optimizer does. It also has to figure out the ordering of the joins, the best way to aggregate results, whether a sort is needed for an order by, how to access the data (via indexes or directly), and much more.
When you break the query apart, you are making an assumption about optimization. In your case, you are making the assumption that the first best thing is to do a select on a particular table. You might be right. If so, your result with multiple queries should be about as fast as using a single query. Well, maybe not. When in a single query, SQL Server does not have to buffer all the results at once; it can stream results from one place to another. It may also be able to take advantage of parallelism in a way that splitting the query prevents.
In general, the SQL Server optimizer is pretty good, so you are best letting the optimizer do the query all in one go. There are definitely exceptions, where the optimizer may not choose the best execution path. Sometimes fixing this is as easy as being sure that statistics are up-to-date on tables. Other times, you can add optimizer hints. And other times you can restructure the query, as you have done.
For instance, one place where loading data into a local table is useful is when the table comes from a different server. The optimizer may not have full information about the size of the table to make the best decisions.
In other words, keep the query as one statement. If you need to improve it, then focus on optimization after it works. You generally won't have to spend much time on optimization, because the engine is pretty good at it.

This would give the same result?
SELECT t.*, s.*
FROM dbo.TestTable AS t
JOIN dbo.TestRefTable AS s ON t.id = s.id AND s.id = 1123
Basically, this is a cross join of all records from TestTable and TestRefTable with id = 1123.

Joining to table variables will also result in bad cardinality estimates by the optimizer. Table variables are always assumed by the optimizer to contain only a single row. The more rows it actually has the worse that estimate becomes. This causes the optimizer to assume the wrong number of rows for the table itself, but in other places, for operators that might then join to that result, it can result in wrong estimations of the number executions for that operation.
Personally I think Table parameters should be used for getting data into and out of the server conveniently using client apps (C# .Net apps make good use of them), or for passing data between Stored Procs, but should not be used too much within the proc itself. The importance of getting rid of them within the Proc code itself increases with the expected number of rows to be carried by the parameter.
Sub Selects will perform better, or immediately copying into a temp table will work well. There is overhead for copying into the temp table, but again, the more rows you have the more worth it that overhead becomes because the estimates by the optimizer get worse and worse.

In general a derived table in the query is probably going to be faster than joining to a table variable because it can make use of indexes and they are not available in table variables. However, temp tables can also have indexes creted and that might solve the potential performance difference.
Also if the number of table variable records is expected to be small, then indexes won't make a great deal of difference anyway and so there would be little or no differnce.
As alawys you need to test on your own system as number of records and table design and index design havea great deal to do with what works best.

I'd expect the direct Table join to be faster than the Table to TableVariable, and use less resources.

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.

Query with a UNION sub-query takes a very long time

I've been having an odd problem with some queries that depend on a sub query. They run lightning fast, until I use a UNION statement in the sub query. Then they run endlessly, I've given after 10 minutes. The scenario I'm describing now isn't the original one I started with, but I think it cuts out a lot of possible problems yet yields the same problem. So even though it's a pointless query, bear with me!
I have a table:
tblUser - 100,000 rows
tblFavourites - 200,000 rows
If I execute:
SELECT COUNT(*)
FROM tblFavourites
WHERE userID NOT IN (SELECT uid FROM tblUser);
… then it runs in under a second. However, if I modify it so that the sub query has a UNION, it will run for at least 10 minutes (before I give up!)
SELECT COUNT(*)
FROM tblFavourites
WHERE userID NOT IN (SELECT uid FROM tblUser UNION SELECT uid FROM tblUser);
A pointless change, but it should yield the same result and I don't see why it should take any longer?
Putting the sub-query into a view and calling that instead has the same effect.
Any ideas why this would be? I'm using SQL Azure.
Problem solved. See my answer below.

UNION generate unique values, so the DBMS engine makes sorts.
You can use safely UNION ALL in this case.

UNION is really doing a DISTINCT on all fields in the combined data set. It filters out dupes in the final results.
Is Uid indexed? If not it may take a long time as the query engine:
Generates the first result set
Generates the second result set
Filters out all the dupes (which is half the records) in a hash table
If duplicates aren't a concern (and using IN means they won't be) then use UNION ALL which removes the expensive Sort/Filter step.

UNION's are usually implemented via temporary in-memory tables. You're essentially copying your tblUser two times into memory, WITH NO INDEX. Then every row in tblFavourites incur a complete table scan over 200,000 rows - that's 200Kx200K=40 billion double-row scans (because the query engine must get the uid from both table rows)
If your tblUser has an index on uid (which is definitely true because all tables in SQL Azure must have a clustered index), then each row in tblFavourites incurs a very fast index lookup, resulting in only 200Kxlog(100K) =200Kx17 = 200K row scans, each with 17 b-tree index comparisons (which is much faster than reading the uid from a row on a data page), so it should equate to roughly 200Kx(3-4) or 1 million double-row scans. I believe newer versions of SQL server may also build a temp hash table containing just the uid's, so essentially it gets down to 200K row scans (assuming hash table lookup to be trivial).
You should also generate your query plan to check.
Essentially, the non-UNION query runs around 500,000 times faster if tblUser has an index (should be on SQL Azure).

It turns out the problem was due to one of the indexes ... tblFavourites contained two foreign keys to the primary key (uid) in tblUser:
userId
otherUserId
both columns had the same definition and same indexes, but I discovered that swapping userId for otherUserId in the original query solved the problem.
I ran:
ALTER INDEX ALL ON tblFavourites REBUILD
... and the problem went away. The query now executes almost instantly.
I don't know too much about what goes on behind the scenes in Sql Server/Azure ... but I can only imagine that it was a damaged index or something? I update statistics frequently, but that had no effect.
Thanks!
---- UPDATE
The above was not fully correct. It did fix the problem for around 20 minutes, then it returned. I have been in touch with Microsoft support for several days and it seems the problem is to do with the tempDB. They are working on a solution at their end.

I just ran into this problem. I have about 1million rows to go through and then I realized that some of my IDs were in another table, so I unioned to get the same information in one "NOT EXISTS." I went from the query taking about 7 sec to processing only 5000 rows after a minute or so. This seemed to help. I absolutely hate the solution, but I've tried a multitude of things that all end up w/the same extremely slow execution plan. This one got me what I needed in about 18 sec.
DECLARE #PIDS TABLE ([PID] [INT] PRIMARY KEY)
INSERT INTO #PIDS SELECT DISTINCT [ID] FROM [STAGE_TABLE] WITH(NOLOCK)
INSERT INTO #PIDS SELECT DISTINCT [OTHERID] FROM [PRODUCTION_TABLE] WITH(NOLOCK)
WHERE NOT EXISTS(SELECT [PID] FROM #PIDS WHERE [PID] = [OTHERID]
SELECT (columns needed)
FROM [ORDER_HEADER] [OH] WITH(NOLOCK)
INNER JOIN #PIDS ON [OH].[SOME_ID] = [PID]
(And yes I tried "WHERE EXISTS IN..." for the final select... inner join was faster)
Please let me say again, I personaly feel this is really ugly, but I actually use this join twice in my proc, so it's going to save me time in the long run. Hope this helps.

Doesn't it make more sense to rephrase the questions from
"UserIds that aren't on the combined list of all the Ids that apper in this table and/or that table"
to
"UserIds that aren't on this table AND aren't on that table either
SELECT COUNT(*)
FROM tblFavourites
WHERE userID NOT IN (SELECT uid FROM tblUser)
AND userID NOT IN (SELECT uid FROM tblUser);