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    <p>I have provided three different approaches for solving this problem:</p> <ol> <li>Using Pivots</li> <li>Using Case Statements</li> <li>Using inline queries in the where clause</li> </ol> <p>All of the solutions assume we are determining the "most recent" order based on the <code>orderId</code> column. Using the <code>createDate</code> column would add complexity due to timestamp collisions and seriously hinder performance since <code>createDate</code> is probably not part of the indexed key. I have only tested these queries using MS SQL Server 2005, so I have no idea if they will work on your server.</p> <p>Solutions (1) and (2) perform almost identically. In fact, they both result in the same number of reads from the database. </p> <p>Solution (3) is <strong>not</strong> the preferred approach when working with large data sets. It consistently makes hundreds of logical reads more than (1) and (2). When filtering for one specific user, approach (3) is comparable to the other methods. In the single user case, a drop in the cpu time helps to counter the significantly higher number of reads; however, as the disk drive becomes busier and cache misses occur, this slight advantage will disappear.</p> <h2>Conclusion</h2> <p>For the presented scenario, use the pivot approach if it is supported by your DBMS. It requires less code than the case statement and simplifies adding order types in the future.</p> <p>Please note, in some cases, PIVOT is not flexible enough and characteristic value functions using case statements are the way to go.</p> <h2>Code</h2> <p>Approach (1) using PIVOT:</p> <pre><code>select ud.userId, ud.fullname, od1.orderId as orderId1, od1.createDate as createDate1, od1.orderType as orderType1, od2.orderId as orderId2, od2.createDate as createDate2, od2.orderType as orderType2 from userData ud inner join ( select userId, [1] as typeOne, [2] as typeTwo from (select userId, orderType, orderId from orderData) as orders PIVOT ( max(orderId) FOR orderType in ([1], [2]) ) as LatestOrders) as LatestOrders on LatestOrders.userId = ud.userId inner join orderData od1 on od1.orderId = LatestOrders.typeOne inner join orderData od2 on od2.orderId = LatestOrders.typeTwo </code></pre> <p>Approach (2) using Case Statements:</p> <pre><code>select ud.userId, ud.fullname, od1.orderId as orderId1, od1.createDate as createDate1, od1.orderType as orderType1, od2.orderId as orderId2, od2.createDate as createDate2, od2.orderType as orderType2 from userData ud -- assuming not all users will have orders use outer join inner join ( select od.userId, -- can be null if no orders for type max (case when orderType = 1 then ORDERID else null end) as maxTypeOneOrderId, -- can be null if no orders for type max (case when orderType = 2 then ORDERID else null end) as maxTypeTwoOrderId from orderData od group by userId) as maxOrderKeys on maxOrderKeys.userId = ud.userId inner join orderData od1 on od1.ORDERID = maxTypeTwoOrderId inner join orderData od2 on OD2.ORDERID = maxTypeTwoOrderId </code></pre> <p>Approach (3) using inline queries in the where clause (based on Steve K.'s response):</p> <pre><code>select ud.userId,ud.fullname, order1.orderId, order1.orderType, order1.createDate, order2.orderId, order2.orderType, order2.createDate from userData ud, orderData order1, orderData order2 where ud.userId = order1.userId and ud.userId = order2.userId and order1.orderId = (select max(orderId) from orderData od1 where od1.userId = ud.userId and od1.orderType = 1) and order2.orderId = (select max(orderId) from orderData od2 where od2.userId = ud.userId and od2.orderType = 2) </code></pre> <p>Script to generate tables and 1000 users with 100 orders each:</p> <pre><code>CREATE TABLE [dbo].[orderData]( [orderId] [int] IDENTITY(1,1) NOT NULL, [createDate] [datetime] NOT NULL, [orderType] [tinyint] NOT NULL, [userId] [int] NOT NULL ) CREATE TABLE [dbo].[userData]( [userId] [int] IDENTITY(1,1) NOT NULL, [fullname] [nvarchar](50) NOT NULL ) -- Create 1000 users with 100 order each declare @userId int declare @usersAdded int set @usersAdded = 0 while @usersAdded &lt; 1000 begin insert into userData (fullname) values ('Mario' + ltrim(str(@usersAdded))) set @userId = @@identity declare @orderSetsAdded int set @orderSetsAdded = 0 while @orderSetsAdded &lt; 10 begin insert into orderData (userId, createDate, orderType) values ( @userId, '01-06-08', 1) insert into orderData (userId, createDate, orderType) values ( @userId, '01-02-08', 1) insert into orderData (userId, createDate, orderType) values ( @userId, '01-08-08', 1) insert into orderData (userId, createDate, orderType) values ( @userId, '01-09-08', 1) insert into orderData (userId, createDate, orderType) values ( @userId, '01-01-08', 1) insert into orderData (userId, createDate, orderType) values ( @userId, '01-06-06', 2) insert into orderData (userId, createDate, orderType) values ( @userId, '01-02-02', 2) insert into orderData (userId, createDate, orderType) values ( @userId, '01-08-09', 2) insert into orderData (userId, createDate, orderType) values ( @userId, '01-09-01', 2) insert into orderData (userId, createDate, orderType) values ( @userId, '01-01-04', 2) set @orderSetsAdded = @orderSetsAdded + 1 end set @usersAdded = @usersAdded + 1 end </code></pre> <p>Small snippet for testing query performance on MS SQL Server in addition to SQL Profiler:</p> <pre><code>-- Uncomment these to clear some caches --DBCC DROPCLEANBUFFERS --DBCC FREEPROCCACHE set statistics io on set statistics time on -- INSERT TEST QUERY HERE set statistics time off set statistics io off </code></pre>
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    1. COWow, I definitely appreciate the length and detail of your answer.
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