BACKGROUND  
       [0001]     Predefined-schema data storage systems, such as relational databases such as SQLServer from Microsoft and Oracle from Oracle, for example, may be based on a relational data model in which the schema of the data model is defined in advance of use (i.e., at “data definition” time, which is separate from and earlier than “data manipulation” time). Applications written to use these systems must be aware of the schema, and changes to that schema are very disruptive because the model is predicated on “data definition” being advance of “data manipulation.” 
         [0002]     There are, however, many applications—such as messaging systems like Exchange from Microsoft Corp, that are not able to describe their full schema in advance of use because the schema (e.g., the “MAPI” data model in the case of Exchange) may be modified at any point in time by any user. For example, it may be known that all “Messages” have a “property” called “PR_SUBJECT” (0x0037001E), but it might not be known that certain messages will be annotated with a new “property” called “PR_FOOBAR” (0x8011001F).  
         [0003]     Applications have typically taken two different approaches to store such “highly flexible” schema data in less flexible database systems. In a first such approach, the data is stored in XML or blobs in the database, i.e., the ‘schema’ of the data is moved to a higher layer in the software stack. The database management system (DBMS) sees a very simple schema largely containing a single “dynamic schema” object. This allows the schema to be stored and manipulated in a consistent manner but robs the data store of the ability to use knowledge of the schema to optimize operations of the data store. In the absence of advanced database features such as XML data processing this approach is practically unusable for commercial applications because of the performance penalty imposed by eliminating the data store&#39;s ability to optimize its operations.  
         [0004]     In a second such approach, some of the data, i.e., the portion that is known at “data definition” time, is stored in the data store as normal “not dynamic” schema objects, and the remainder is stored in either a blob/XML, or normalized into a “property/value” pair table. This allows the data store to know about as much of the schema as possible, and consequently to use that knowledge in operations. But it requires the application to be written knowing which parts of the schema as “normal” database objects and which are stored as blob/XML or property/value pairs.  
         [0005]     The net result of these approaches is that the application writer must choose between exposing their “part structured and part variable” data store schema through their object model, or having a “fully variable” data schema and loose data store level optimization and processing. Consider MAPI as an example. There is no natural and intuitive way for the writer to know that PR_SUBJECT (0x0037001E) maps to Message.Subject in the object model, and column dbo.MessageView.Subject in the data store schema, while PR_FOOBAR (0x8011001F) is not represented in either the object model or data store schema because it is a “new” data property added dynamically.  
         [0006]     It would be desirable, therefore, if a mechanism existed via which applications could be written such that the data store can have a “part structured and part variable” data schema. It would be particularly desirable if such a schema were not exposed through the object model.  
       SUMMARY  
       [0007]     Methods for building data encapsulation layers for a highly variable schema are disclosed and claimed. As described in detail below, such methods allow for applications to be written in such a way that a data store can have a “part structured and part variable” data schema. Such a schema need not be exposed through the object model. Application writers can choose an optimal data store schema design, part of which is structured and part of which is variable, without sacrificing integrity of the exposed object model.  
         [0008]     An “isolation layer” that defines a relationship between object model data fields and data store data fields may be encoded in the source of the data store interface layer using attributes. Reflection may be used, at application start-time, for example, to build a table of mappings that drive interactions with that data. The use of reflection to build the mapping table eliminates the need for hard-coding such relationships. Consequently, the application code need not change merely because the data store structure changes. An example, three-step process for building and using such an isolation layer is described in detail. 
     
    
     BRIEF DESCRIPTION OF THE DRAWINGS  
       [0009]      FIG. 1  is a flowchart of an example method for building data encapsulation layers for a highly variable schema.  
         [0010]      FIG. 2  provides an example of how to build a mapping table.  
         [0011]      FIG. 3  provides an example of how to use a mapping table at run-time.  
         [0012]      FIG. 4  is a block diagram showing an example computing environment in which aspects of the invention may be implemented. 
     
    
     DETAILED DESCRIPTION  
       [0013]      FIG. 1  depicts a method  200  for building data encapsulation layers for a highly variable schema. At  202 , a variable relationship between one or more application object model data fields and one or more data store data fields may be encoded in the source of the data store interface layer of an application. The relationship may be encoded using annotations, such as Microsoft .NET Framework Attributes. For example, to represent that “PR_SUBJECT” in MAPI is “Subject” in the internal object model, and column “subject” in the data store, the data model object could be coded as follows:  
                                   [MapiUnnamedProperty(PropIds.PropId_SUBJECT, PropType.Unicode)]       [ViewMappingColumn(“subject”)]       internal string Subject       { get; set; }.                    
 In the foregoing example, “[MapiUnnamedProperty(PropIds.PropId_SUBJECT, PropType. Unicode)]” represents a property that the application uses, i.e., the object model data fields, “[ViewMappingColumn(‘subject’)]” refers to the data store column that the property maps to, i.e., the data store data fields, and “internal string Subject” represents a “data store interface” or “isolation” layer. Thus, the isolation layer, which may define the relationship between the object model data fields and the data store data fields, may be encoded in the source of the data store interface layer using attributes. 
 
         [0014]     It should be understood that many types of mapping relationships may be supported. The foregoing is an example of a 1-to-1-to-1 mapping from end-user, to object-model, to data store. The following is an example of a 1-to-1-to-many mapping from end-user, to object-model, to data store:  
                                   [MapiUnnamedProperty(PropIds.PropId_MessageId, PropType.Unicode]       [ViewMappingColumn(“MIDGuid”, “MIDCounter”)]       internal ExchangeId MID       { get; set; }                  
 
         [0015]     The following is an example of a 1-to-1-to-function mapping:  
                                   [MapiUnnamedProperty(PropIds.PropId_Unread, PropType.Unicode]       [ViewMappingFunction(“UnreadItems+UnreadAppointments”)]       internal UnreadCount       { get; set; }                  
 
 A host of others are possible. 
 
         [0016]     At  204 , a mapping table may be built. The mapping table may be derived from the variable relationship encoded into the data store interface layer of the application, and may map a specific relationship between the object model data fields and the data store data fields that exists at start-up time. Thus, the application code need not change merely because the data store structure changes.  
         [0017]     Such a mapping table may be built using a technique that is commonly referred to as “reflection,” such as Microsoft .NET Framework Reflection, for example. That is, the executable code associated with an application may “look at” the source code associated with the application (e.g., the source code from which the executable code was compiled) and identify certain relationships from the source code.  
         [0018]      FIG. 2  provides example code for building a mapping table. As shown, the code may build a mapping table at start-up time for methods and properties. It should be understood that, although such a table may be built at start-up time, it can be built at any desirable time, such as at compilation time or on an as-needed basis during runtime. Such methods may include statics and instance methods. Accordingly, the code may find “ViewMappingFunction”s. Properties may include instance properties only. Accordingly, the code may find property mappings and “ViewMappingColumn”s. The method by which the mapping table is built may, of course, differ depending on the nature of the mapping and the data store schema.  
         [0019]     At  206 , the mapping table may be used at run-time. That is, when there is a request for a property, the table may be used to determine how to get the data and to invoke the correct mechanism for obtaining the value of the requested property.  FIG. 3  provides an example of how to use a mapping table at run-time. As shown, the program loops through the request array and fills the property values.  
         [0020]     It should be apparent that a user can invoke “MapiGetProps” to retrieve the desired data from the data store. Thus, the user may be totally shielded from the physical realization of those properties in the object model, or data store. In fact, the “MapiGetProps” function itself may also be shielded. It knows there are two types of properties: those that are handled in the object model and represented in the data store schema, and those that are represented as “property/value” pairs (or XML, or blob). It need not be aware of which properties fall into which set, or why. This logical isolation allows the underlying object model, or data store physical realization, to change without affecting the end-user application.  
         [0000]     Example Computing Environment  
         [0021]      FIG. 4  and the following discussion are intended to provide a brief general description of a suitable computing environment in which an example embodiment of the invention may be implemented. It should be understood, however, that handheld, portable, and other computing devices of all kinds are contemplated for use in connection with the present invention. While a general purpose computer is described below, this is but one example. The present invention also may be operable on a thin client having network server interoperability and interaction. Thus, an example embodiment of the invention may be implemented in an environment of networked hosted services in which very little or minimal client resources are implicated, e.g., a networked environment in which the client device serves merely as a browser or interface to the World Wide Web.  
         [0022]     Although not required, the invention can be implemented via an application programming interface (API), for use by a developer or tester, and/or included within the network browsing software which will be described in the general context of computer-executable instructions, such as program modules, being executed by one or more computers (e.g., client workstations, servers, or other devices). Generally, program modules include routines, programs, objects, components, data structures and the like that perform particular tasks or implement particular abstract data types. Typically, the functionality of the program modules may be combined or distributed as desired in various embodiments. Moreover, those skilled in the art will appreciate that the invention may be practiced with other computer system configurations. Other well known computing systems, environments, and/or configurations that may be suitable for use with the invention include, but are not limited to, personal computers (PCs), automated teller machines, server computers, hand-held or laptop devices, multi-processor systems, microprocessor-based systems, programmable consumer electronics, network PCs, minicomputers, mainframe computers, and the like. An embodiment of the invention may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network or other data transmission medium. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.  
         [0023]      FIG. 4  thus illustrates an example of a suitable computing system environment  100  in which the invention may be implemented, although as made clear above, the computing system environment  100  is only one example of a suitable computing environment and is not intended to suggest any limitation as to the scope of use or functionality of the invention. Neither should the computing environment  100  be interpreted as having any dependency or requirement relating to any one or combination of components illustrated in the exemplary operating environment  100 .  
         [0024]     With reference to  FIG. 4 , an example system for implementing the invention includes a general purpose computing device in the form of a computer  110 . Components of computer  110  may include, but are not limited to, a processing unit  120 , a system memory  130 , and a system bus  121  that couples various system components including the system memory to the processing unit  120 . The system bus  121  may be any of several types of bus structures including a memory bus or memory controller, a peripheral bus, and a local bus using any of a variety of bus architectures. By way of example, and not limitation, such architectures include Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, Video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus (also known as Mezzanine bus).  
         [0025]     Computer  110  typically includes a variety of computer readable media. Computer readable media can be any available media that can be accessed by computer  110  and includes both volatile and nonvolatile, removable and non-removable media. By way of example, and not limitation, computer readable media may comprise computer storage media and communication media. Computer storage media includes both volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Computer storage media includes, but is not limited to, random access memory (RAM), read-only memory (ROM), Electrically-Erasable Programmable Read-Only Memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CDROM), digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by computer  110 . Communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media. The term “modulated data signal” means a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal. By way of example, and not limitation, communication media includes wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, radio frequency (RF), infrared, and other wireless media. Combinations of any of the above should also be included within the scope of computer readable media.  
         [0026]     The system memory  130  includes computer storage media in the form of volatile and/or nonvolatile memory such as ROM  131  and RAM  132 . A basic input/output system  133  (BIOS), containing the basic routines that help to transfer information between elements within computer  110 , such as during start-up, is typically stored in ROM  131 . RAM  132  typically contains data and/or program modules that are immediately accessible to and/or presently being operated on by processing unit  120 . By way of example, and not limitation,  FIG. 4  illustrates operating system  134 , application programs  135 , other program modules  136 , and program data  137 . RAM  132  may contain other data and/or program modules.  
         [0027]     The computer  110  may also include other removable/non-removable, volatile/nonvolatile computer storage media. By way of example only,  FIG. 4  illustrates a hard disk drive  141  that reads from or writes to non-removable, nonvolatile magnetic media, a magnetic disk drive  151  that reads from or writes to a removable, nonvolatile magnetic disk  152 , and an optical disk drive  155  that reads from or writes to a removable, nonvolatile optical disk  156 , such as a CD ROM or other optical media. Other removable/non-removable, volatile/nonvolatile computer storage media that can be used in the example operating environment include, but are not limited to, magnetic tape cassettes, flash memory cards, digital versatile disks, digital video tape, solid state RAM, solid state ROM, and the like. The hard disk drive  141  is typically connected to the system bus  121  through a non-removable memory interface such as interface  140 , and magnetic disk drive  151  and optical disk drive  155  are typically connected to the system bus  121  by a removable memory interface, such as interface  150 .  
         [0028]     The drives and their associated computer storage media discussed above and illustrated in  FIG. 4  provide storage of computer readable instructions, data structures, program modules and other data for the computer  110 . In  FIG. 4 , for example, hard disk drive  141  is illustrated as storing operating system  144 , application programs  145 , other program modules  146 , and program data  147 . Note that these components can either be the same as or different from operating system  134 , application programs  135 , other program modules  136 , and program data  137 . Operating system  144 , application programs  145 , other program modules  146 , and program data  147  are given different numbers here to illustrate that, at a minimum, they are different copies. A user may enter commands and information into the computer  110  through input devices such as a keyboard  162  and pointing device  161 , commonly referred to as a mouse, trackball or touch pad. Other input devices (not shown) may include a microphone, joystick, game pad, satellite dish, scanner, or the like. These and other input devices are often connected to the processing unit  120   a - f  through a user input interface  160  that is coupled to the system bus  121 , but may be connected by other interface and bus structures, such as a parallel port, game port or a universal serial bus (USB).  
         [0029]     A monitor  191  or other type of display device is also connected to the system bus  121  via an interface, such as a video interface  190 . In addition to monitor  191 , computers may also include other peripheral output devices such as speakers  197  and printer  196 , which may be connected through an output peripheral interface  195 .  
         [0030]     The computer  110  may operate in a networked environment using logical connections to one or more remote computers, such as a remote computer  180 . The remote computer  180  may be a personal computer, a server, a router, a network PC, a peer device or other common network node, and typically includes many or all of the elements described above relative to the computer  110 , although only a memory storage device  181  has been illustrated in  FIG. 4 . The logical connections depicted in  FIG. 4  include a local area network (LAN)  171  and a wide area network (WAN)  173 , but may also include other networks. Such networking environments are commonplace in offices, enterprise-wide computer networks, intranets and the Internet.  
         [0031]     When used in a LAN networking environment, the computer  110  is connected to the LAN  171  through a network interface or adapter  170 . When used in a WAN networking environment, the computer  110  typically includes a modem  172  or other means for establishing communications over the WAN  173 , such as the Internet. The modem  172 , which may be internal or external, may be connected to the system bus  121  via the user input interface  160 , or other appropriate mechanism. In a networked environment, program modules depicted relative to the computer  110 , or portions thereof, may be stored in the remote memory storage device. By way of example, and not limitation,  FIG. 4  illustrates remote application programs  185  as residing on memory device  181 . It will be appreciated that the network connections shown are exemplary and other means of establishing a communications link between the computers may be used.  
         [0032]     One of ordinary skill in the art can appreciate that a computer  110  or other client devices can be deployed as part of a computer network. In this regard, the present invention pertains to any computer system having any number of memory or storage units, and any number of applications and processes occurring across any number of storage units or volumes. An embodiment of the present invention may apply to an environment with server computers and client computers deployed in a network environment, having remote or local storage. The present invention may also apply to a standalone computing device, having programming language functionality, interpretation and execution capabilities.
The relationships between physical data store schema, object model, and end-user property may be encoded in the source of the object model using attributes. Reflection may be used to build the table of those relationships so that changes to the relationships between those three layers can be easily and quickly made without impacting higher levels in the software stack.