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When deciding to use out-of-process session state, keep in mind that only SQL Server provides a solution for n+1 reliability If you re using the NT State Server and that box goes down, your session information is unavailable, which will, in all likelihood, severely impair (or take down) an application that s dependent on this information Also be aware that session state in ASP NET is application specific ASP NET provides no solution out of the box for sharing session information across IIS applications, which is unfortunate, because this is a common need If you find yourself needing this type of information sharing, you ll have to code your own solution If it s entirely untenable to move session information out of process, there is one other option Load balancers support an option called client affinity, or sticky sessions.

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Being a careful employee, Adam even queries the record back to verify his changes: adam@ORA10G> select ename, sal from emp where ename='MARTIN'; ENAME SAL ---------- ---------MARTIN 1375.

As a second example of how you can abstract control using functions, let s consider the common pattern of timing the execution of an operation (measured in wall-clock time). First let s explore how to use System.DateTime.Now to get the wall-clock time:

Satisfied that all is well, Adam commits his changes: adam@ORA10G> commit; Blake s phone call is over and he returns to his desk His screen still shows Martin s old salary information Unaware of Adam s changes, Blake proceeds to give Martin a bonus of $100 based on his (now old) salary of $1,250, wiping out the changes made by Adam earlier: blake@ORA10G> update emp set sal = 1350 where ename='MARTIN'; 1 row updated blake@ORA10G> commit; Commit complete The final row for Martin s record looks as follows: martin@ORA10G> select * from emp where ename='MARTIN'; EMPNO ENAME JOB MGR HIREDATE SAL COMM DEPTNO ---------- ---------- --------- ---------- --------- ---------- ------- --------7654 MARTIN SALESMAN 7698 28-SEP-81 1350 1400 30 As you can see, the update done by Adam has been overwritten by Blake s changes and is the lost update Martin expected to see a total salary of $1,475 (1,250 1.

This means that once a load balancer sends a given user to a specific server, it continues to send that user to that server for the duration of the user s session (it sticks the user to that server) While this allows you to use in-process session information and still have an application that can scale out, it s not the most efficient load balancing algorithm you can employ It s possible that some servers in the Farm will be under significantly more load than others It depends on how long users stuck to a particular server use the application If more users stuck to server A stick around, and those stuck to server B leave the application, server A could be under much more load than server B This solution also doesn t provide for redundant availability of the application.

> open System;; > let start = DateTime.Now;; val start : DateTime > http "http://www.newscientist.com";; val it : string = "<html>...</html>" > let finish = DateTime.Now;; val finish : DateTime > let elapsed = finish - start;; val elapsed : TimeSpan > elapsed;; val it : TimeSpan = 00:00:01.9799671 Note the type TimeSpan has been inferred from the use of the overloaded operator in the expression finish - start. We discuss overloaded operators in depth in 6. You can now wrap up this technique as a function time that acts as a new control operator: open System let time f = let start = DateTime.Now let res = f() let finish = DateTime.Now (res, finish - start) This function runs the input function f but takes the time on either side of the call. It then returns both the result of the function and the elapsed time. The inferred type is as follows:

10 + 100), whereas his salary is only $1,350 In the preceding example, both updates were changing the same column The problem can occur even if different columns of the same row are being updated by two different transactions This happens when the application performing updates is written such that instead of updating only the changed columns of a record (it takes more work to detect which column changed), all (nonprimary key) columns are updated For example, let s consider an application screen that allows the end user to update the salary and commission of an employee in our emp table Adam, in session 1, is updating the comm column of the emp table for Martin s record In a different session, Blake is changing the sal column of the same record.

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