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Queries are prebuilt definitions of data retrieval statements that you can easily adapt at runtime using their properties. A query consists of one or more data sources and methods that are executed when the query is run. The aspects of queries worth looking into here are the controls or object subtypes contained by the data properties: Table: Represents a property of each data source that designates the primary source of data for the query Fields: Defines the fields from the specified table to retrieve from the data source table Sorting: Allows you to specify how to sort the results of the query Ranges: Allows you to specify a range of values to limit the result set to Relations: Enables you to create joined queries; you define joined data sources within the master data source node.

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If referenced objects aren t serializable, the serialization attempt will result in a runtime error Alternatively, any non-serializable object references can be marked as [NotUndoable()], so that the undo process simply ignores them The code to do the serialization is fairly straightforward: // serialize the state and stack it using (MemoryStream buffer = new MemoryStream()) { BinaryFormatter formatter = new BinaryFormatter(); formatterSerialize(buffer, state); _stateStackPush(bufferToArray()); } This code is quite comparable to the cloning code implemented in the ObjectCloner class, earlier The BinaryFormatter object serializes the Hashtable (and any objects to which it refers) into a stream of bytes in an in-memory buffer The byte stream is simply extracted from the in-memory buffer and pushed onto the stack: _stateStackPush(bufferToArray()); Converting a MemoryStream to a byte array is not an issue, since the MemoryStream is implemented to store its data in a byte array.

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DML statement submitted Does cursor exist in session cache No Yes Found error Yes Give error message and exit No Check syntax and semantics

Queries are typically used in reports and in X++ code and occasionally in forms, where they can actually be created fully in code.

The ToArray() method simply returns a reference to that existing array, so no data is copied The act of conversion to a byte array is important, however, because a byte array is serializable, while a MemoryStream object is not If the business object is passed across the network by value while it is being edited, the stack of states needs to be serializable..

Figure 5-1. The steps Oracle takes to process and execute a DML statement (see http://asktom.oracle.com and 5 of Tom Kyte s Effective Oracle by Design [Osborne McGraw-Hill, ISBN: 0-07-223065-7] for a detailed explanation of this algorithm) The goal when writing SQL statements in Oracle is to avoid repeated hard parsing and to minimize soft parsing. In this chapter, we ll focus on how to avoid hard parsing in JDBC programs. In 14, we ll cover techniques for minimizing soft parsing.

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s Passing objects across the network while they re being edited is not anticipated, but since business objects Tip are [Serializable()], you can t prevent the business developer from doing just that. If the stack were to reference a MemoryStream, the business application would get a runtime error as the serialization failed, and that s not acceptable. Converting the data to a byte array avoids accidentally crashing the application on the off chance that the business developer does decide to pass an object across the network as it s being edited.

Jobs resemble classes with a single static main method. They are purely code and have no properties of major interest. They are used typically for administrative purposes and quickand-dirty prototyping.

You re now ready to enter the exciting world of statements in JDBC. Recall that the standard JDBC API consists of two packages (see the section Overview of JDBC API in 3): java.sql: Contains the core JDBC API to access and manipulate information stored in a database, which includes the Statement interface and those that inherit from it (e.g., PreparedStatement and CallableStatement) javax.sql: Contains APIs for accessing server-side data sources from JDBC clients

At this point, we re a third of the way through implementing n-level undo support. It is now possible to create a stack of snapshots of an object s data. It is time to move on and discuss the undo and accept operations.

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