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Step 2: Deciding Upon NTP Topology at Deployment Site 104 The Number of NTP Clients 104 The Level of Network Redundancy 104 Impact of Network Physical Topology and Geography on NTP Topology 106 Step 3: Determining NTP Features to Configure 106 Basic NTP Configuration 107 Basic Dedicated Timeserver Configuration 107 Basic Unix/Linux NTP Client Configuration 108 Basic Unix/Linux NTP Primary Timeserver Configuration 110 Typical Unix/Linux Client Configuration 111 Basic Cisco Router/Switch NTP Configuration 113 Basic Juniper Router NTP Configuration 116 NTP Security Features 116 NTP Security in Unix/Linux Environments 117 NTP Security on Cisco Routers and Switches 119 Redundant NTP Time Sources 123 NTP Operational Modes 124 Additional NTP Configuration Options 126 Step 4: Monitoring and Managing NTP Operations 126 NTP Deployment on Networks with and without Internet Access 127 NTP Deployment Guidelines for Small, Medium, and Large Networks 128 Small NTP Networks 129 Medium-Size NTP Networks .

Where primary_key = :primary_key And decode( column1, :old_column1, 1 ) = 1 And decode( column2, :old_column2, 1 ) = 1 .. Here, we are optimistic that the data doesn t get changed In this case, if our update updates one row, we got lucky; the data didn t change between the time we read it and the time we got around to submitting the update If we update zero rows, we lose; someone else changed the data and now we must figure out what we want to do to continue in the application.

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Should we make the end user re-key the transaction after querying the new values for the row (potentially causing the user frustration, as there is a chance the row will have changed yet again) Should we try to merge the values of the two updates by performing update conflict-resolution based on business rules (lots of code) The preceding UPDATE will, in fact, avoid a lost update, but it does stand a chance of being blocked, hanging while it waits for an UPDATE of that row by another session to complete If all of your applications use optimistic locking, then using a straight UPDATE is generally OK since rows are locked for a very short duration as updates are applied and committed.

Deferred deletion occurs when the business object is loaded into memory and the UI calls a method on the object to mark it for deletion. Then when the Save() method is called, the object is deleted rather than being inserted or updated. The sequence of events flows like this: 1. The object is loaded by the UI. 2. The UI calls a method to mark the object for deletion (that method must call MarkDeleted()).

However, if some of your applications use pessimistic locking, which will hold locks on rows for relatively long periods of time, or if there is any application (such as a batch process) that might lock rows for a long period of time (more than a second or two is considered long!), then you should consider using a SELECT FOR UPDATE NOWAIT instead to verify the row was not changed, and lock it immediately prior to the UPDATE to avoid getting blocked by another session..

There are many methods of implementing optimistic concurrency control. We ve discussed one whereby the application will store all of the before images of the row in the application itself. In the following sections, we ll explore two others, namely: Using a special column that is maintained by a database trigger or application code to tell us the version of the record Using a checksum or hash that was computed using the original data

3. The UI calls the object s Save() or BeginSave() method. 4. The save method invokes the data portal just like it does when doing an insert or an update (as discussed earlier in this chapter). 5. The data portal does one of the following: When not using an ObjectFactory attribute, typically, the DataPortal_DeleteSelf() method calls the object s DataPortal_Delete() method, which contains the code needed to delete the object s data (and any related child data, and so on). When using an ObjectFactory attribute, the data portal creates an instance of the specified object factory class and invokes the specified delete method. This delete method contains the code needed to delete the business object s data, along with any related child data. When not using an ObjectFactory attribute, from the business object s perspective, one method is called: DataPortal_DeleteSelf(). Earlier in the chapter, Figure 4-12 showed the process of saving a root object; it also depicts deferred deletion. When an ObjectFactory attribute is specified on the business class, the business developer must provide both a factory class and the business class. The factory class must implement a delete method that removes the business object s data, along with any child object data. The CSLA .NET framework supports both deletion models to provide flexibility for the UI developer. It is up to the business object author to decide which model to support by implementing either a Shared or instance delete method on the object.

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