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In Internet-based cloud table storage, the simplest way to update a single entity is to replace it with a completely new object. This means deleting it from the table and inserting a new entity object with updated values. In other words, we want to update data in buckets. The price we have to pay is that we need to make double trips for each update action. This will challenge relational cloud tables to maintain data integrity. To meet the requirements of Internet-scaleable data storage, updating data in buckets is sensible, since cloud storage is designed to be Internet scaleable, and the cost is not a concern. To update data in buckets should tremendously simplify the effort for the development team when dealing with relational data

Note One of my goals here is to get you thinking outside of the box just a bit. The rest of the book has

To create an equation from scratch, position the insertion point where you want the equation to appear. Click the top portion of the Equation button in the Symbols group. An equation text box will be inserted at the location of the insertion point, and you can begin entering the equation using the options in the Symbols and Structures groups on the Equation Design Tools tab. The Tools group (see Figure 5-79) includes the Equation command and options for formatting the equation layout.

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infrastructures. As we know, with traditional database structures inserting, updating, or deleting a record from a relational database applies to the record's dependencies too. We should design and implement our data storage and data access approaches for cloud storage differently from the traditional approaches for databases we are used to. We are going to focus on the topic of how to handle relational cloud tables next.

Before we discuss updating data in buckets, let us spend a little time talking about best practices in using the DataServiceContext object , since we are going to apply these rules in our example. The following are best practices recommended for using DataServiceContext. Make the DataServiceContext object thread-safe, since the DataServiceContext does not support thread-safe access. Instantiate an instance of the DataServiceContext object every time you need to use it, since there is no mechanism for a DataServiceContext instance to persist its state in a thread. For instance, using the same DataServiceContext instance across all inserts, updates, and deletes may cause a failure. Each of these actions requires invoking the SaveChanges() method to commit the changes. If the same instance is used to do all these activities, the internal trace of the instance to the actual object may be lost when the instance is used across the different actions. DataServiceContext has MergeOption, which is used to control how the DataServiceContext handles the tracked entities. We covered this topic in the last section. Call AttachTo() before calling Insert(), Update(), or Delete() as the following snippet shows. This will cause the server to track the data entity with an ETag and make sure the action is applied to the correct entity. If the MergeOption of the context object is set to the value of AppendOnly and the entity is already being tracked by a previous action with the same DataServiceContext object instance, then a failure may occur and you may get the error message saying that the data have been tracked already.

been pretty straightforward and operated well within the bounds of how most people will use Workflow in Office 2007. This chapter specifically is an attempt to push that envelope a little. I hope you ll find the information here a little thought provoking. You may even find yourself thinking, That s pretty cool as you make your way through one or two sections.

_dataTableContext.AttachTo(_dataTableContext.TableName, entity, "*"); Now it is the time for us to back to our topic of handling updating and deleting data from cloud storage in buckets.

As we mentioned in 1, Azure table storage is not relational data storage. In the real world, the solution Microsoft has comes up with to handle relational data structures is SQL Azure (covered in 8). The following example is based on an assumption that the relational data structure in the cloud environment for an application to access is relatively simple and that the number of objects in the data model is small. This example proves the concept of dealing with such types of cloud relational data structures without using SQL Azure. This approach may add value to a development team as an alternate design option.

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