The XML (eXtended Markup Language) provides a standard way of tagging data so that the data can be read and interpreted by a variety of Web browsers. Given the enormous proliferation of web hosts and applications on global communications networks such as the Internet, XML documents are used extensively in daily transactions.
Document type definition (DTD) is one technology that defines the document structure of an XML document according to a list of legal elements or building blocks. From a DTD perspective, all XML documents (and HTML documents) are made up of the following simple building blocks: elements, tags (used to markup elements), attributes (used to provide extra information about elements), entities (variables used to define common text), PCDATA (Parsed Character Data), and CDATA (Character Data). Elements are the main building blocks of XML documents. Examples of XML elements could be “note” and “message.” Elements can contain text, other elements, or be empty.
XML Schema is a W3C (World Wide Web Consortium) standard that defines a schema definition language for an XML data model. Schema definitions (e.g., a type definition such as CustomerType that describes the structure of information regarding each Customer) can be used to validate the content and the structure of XML instance documents. The XML schema document is an XML document that is expressed in a different way than the table and column definitions of a relational database system. The type information supplied in an XML schema document can also be used to check XML queries for correctness, and optimize XML queries and XML storage.
XML schema provides a more robust replacement to DTD technology to include the following: XML schema is extensible to future additions to allow extending or restricting a type definition; XML schema is richer and more useful than DTD to allow, for example, the capability to define user-defined types; XML schema is written in XML; XML schema supports data types; and XML schema support namespaces. Unlike DTD, XML schema provides separation between type and element definitions, so that multiple elements (e.g., LocalCustomer and DistantCustomer) of the same type can be defined using a common type definition (e.g., CustomerType). An XML schema document can import other XML schema documents, thereby setting up a type library system.
In one application example, having the capability to store XML schema documents in relational structures can provide significant advantages. Type definitions can be searched efficiently using relational index structures (instead of parsing the XML schema documents), and appropriate pieces of the XML schema documents (e.g., only CustomerType definition) can be selectively loaded into memory buffers for validations of XML instances, which provides a significant performance improvement. Additionally, SQL (Structured Query Language) views could be provided on the relational storage for relational users to know about stored XML schema documents. Thus, there is a substantial unmet need for a mechanism that maps schema data into other database structures.
The following presents a simplified summary in order to provide a basic understanding of some aspects of the disclosed innovation. This summary is not an extensive overview, and it is not intended to identify key/critical elements or to delineate the scope thereof. Its sole purpose is to present some concepts in a simplified form as a prelude to the more detailed description that is presented later.
The subject innovation provides a mechanism by which XML schemas are stored and managed internally within a SQL server metadata component.
In one aspect thereof, architecture is disclosed that facilitates translation between an XML schema and relational structures. The XML schema describes a structure of an XML document. The innovation finds application to a SQL server that supports the XML type system in which XML schema documents are stored in relational tables. Other components of the SQL server, such as an XML query processor and optimizer, can use the XML type system for query compilation and execution. Furthermore, advanced applications related to, for example, a repository can be built on top of the XML type system.
Storing an XML schema document in a relational database system presents new challenges. For example, the identification of the XML schema document (e.g., using its targetnamespace), and type definitions specified within the XML schema document are mapped to relational rows that capture the nature and the type of the definitions (e.g., an element type definition such as CustomerType in the XML schema document—when stored in the relational system—should remember the fact that it is an element type definition). Additionally, a type hierarchy should be recorded, simple type facets provide additional information that can be captured, and it is also possible to reconstruct the XML schema type definitions from the relational structures.
The novelty of this approach is multi-fold. Firstly, searches for specific XML schema components by ID or by Name are fast. All XML schema component searches (by name or by id) utilize index seeks of the relational store, which minimizes the number of I/O operations. Secondly, the derivation chain structure is also indexed. Therefore, determining type relationships is easy and efficient. Thirdly, because shredded schemas are regular relational objects, various relational views of the XML schema components can be exposed. For example, the different XML schema components (e.g., elements, attributes, types, and wildcards) can be exposed to users in one component table. Fourthly, shredding the XML schemas allows users to write any queries they desire.
Finally, because XML schemas are shredded into tables, XML instance validation loads only the necessary components to perform validation. During validation, only parts of the schema that are used are loaded and cached. A schema cache stores an in-memory representation of XML schema components optimized for XML instance validation. XML schema components are loaded from metadata tables into main memory as read-only objects such that multiple users can use the in-memory objects for validation. If the XML schema is changed during the operation, the schema cache entries are invalidated. Additionally, if the database server is under heavy load, unused schema cache entries are unloaded. In view of the above novel capabilities, a scalable system is provided that can operate in large enterprise environments involving thousands of XML schema components and supporting many concurrent users.
In another aspect, a view component facilitates viewing internal data in a read-only manner. Catalog views provide a tabular representation of the SQL server's internal metadata structures. Users can query the views, but not modify them directly.
To the accomplishment of the foregoing and related ends, certain illustrative aspects of the disclosed innovation are described herein in connection with the following description and the annexed drawings. These aspects are indicative, however, of but a few of the various ways in which the principles disclosed herein can be employed and is intended to include all such aspects and their equivalents. Other advantages and novel features will become apparent from the following detailed description when considered in conjunction with the drawings.
The innovation is now described with reference to the drawings, wherein like reference numerals are used to refer to like elements throughout. In the following description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding thereof. It may be evident, however, that the innovation can be practiced without these specific details. In other instances, well-known structures and devices are shown in block diagram form in order to facilitate a description thereof.
As used in this application, the terms “component” and “system” are intended to refer to a computer-related entity, either hardware, a combination of hardware and software, software, or software in execution. For example, a component can be, but is not limited to being, a process running on a processor, a processor, a hard disk drive, multiple storage drives (of optical and/or magnetic storage medium), an object, an executable, a thread of execution, a program, and/or a computer. By way of illustration, both an application running on a server and the server can be a component. One or more components can reside within a process and/or thread of execution, and a component can be localized on one computer and/or distributed between two or more computers.
The XML (eXtended Markup Language) Schema specification describes the structure of an XML document, and it is verbose and complicated. The innovation finds application to a SQL (Structured Query Language) server that supports the XML type system in which XML schema documents are stored in relational tables, for example. However, this is but one exemplary application, and should not be construed as limiting, since the invention finds application in translation between any two disparate data structures. The disclosed innovation shows that a schema definition language need not necessarily be stored in the format in which it is provided, but can be stored in a different format that still captures all the information about schema components. A relational representation is one such possibility; others include object-relational, object-oriented, or even some other XML format, for example. Other components of the SQL server, such as an XML query processor and optimizer, use the XML type system for query compilation and execution. Furthermore, advanced applications, such as related to a repository, can be built on top of the XML type system.
Storing an XML Schema document in a relational database system, for example, can present challenges. For example, the identification of the XML schema document (e.g., using its targetnamespace), and type definitions specified within the XML schema document are mapped to relational rows that capture the nature and the type of the definitions (e.g., an element type definition such as CustomerType in the XML schema document—when stored in the relational system—should remember the fact that it is an element type definition). Additionally, a type hierarchy should be recorded, simple type facets provide additional information that can be captured, and it is also possible to reconstruct the XML schema type definitions from the relational structures.
The novelty of this approach is multi-fold. Firstly, searches for specific components by ID or by Name are fast. All XML Schema component searches (by name or by id) utilize index seeks of the relational store, which minimizes the number of I/O operations. Secondly, the derivation chain structure is also indexed. Therefore, determining type relationships is easy and efficient. Thirdly, because shredded schemas are regular relational objects various relational views of the XML schema components can be exposed. For example, the different XML schema components (e.g., elements, attributes, types, and wildcards) can be exposed to users in one component table. Fourthly, shredding the XML schemas allows users to write any queries they desire.
Finally, because XML schemas are shredded into tables, XML instance validation loads only the necessary components to perform validation. During validation, only parts of the schema that are used are loaded and cached. The “Schema Cache” stores the in-memory representation of XML schema optimized for XML instance validation. XML schema components are loaded from metadata into main memory as read-only objects such that multiple users can use the in-memory objects for validation. If the XML schema is changed during the operation, the schema cache entries are invalidated. Additionally, if the database server is under heavy load, unused schema cache entries are unloaded. In view of the above novel capabilities, a scalable system is provided that can operate in large enterprise environments involving thousands of XML schema components and supporting many concurrent users.
Referring now to
Referring now to
Translation from XML to a relational representation of the XML schema can consist of several phases. At 200, in a first phase, XML schema data is consumed in preparation for the translation process. At 202, a symbol table is created in memory (in-memory representation of the XML schema). In a second phase, at 204, the symbol table is traversed and the structure of the XML schema is validated. In a final phase, at 206, the in-memory representation of the XML schema is persisted in a relational format.
During the final phase of persisting data, the novel code populates metadata tables that describe the structure of the XML Schema types.
Accordingly,
A new concept called XML schema collection can be used for management of XML schemas in the SQL Server 2005 database, and is described in a previous pending U.S. patent application Ser. No. 10/726,080 entitled “XML Schema Collections and Corresponding Systems and Methods” filed Dec. 1, 2003, by the assignee of this application. The collection is a metadata object into which one or more XML schemas may be loaded at the same time the XML schema collection is created using a statement CREATE XML SCHEMA COLLECTION.
Once the XML schema collection has been created, more XML schemas may be loaded into it by altering the XML schema collection using a statement ALTER XML SCHEMA COLLECTION. The XML schema collection can be removed from the system using the statement DROP XML SCHEMA COLLECTION.
Following is an example of creating an XML schema collection and loading the XML schema for books into it.
Following is an example of adding an XML schema for DVDs to an existing XML schema collection.
Following is an example of dropping the XML schema collection.
With respect to internal cache storage of XML schemas, an XSD (XML Schema Definition) type cache (also called herein a schema cache) is implemented in support of performance and resource utilization needs. Compiling content models is extremely memory and I/O intensive. For example, a type with several facets, few elements and few attributes would require a lookup to many (e.g., 20-50) metadata objects. While loading parts of XSD is already an improvement over most commercial applications, caching improves data access due to high concurrency requirements placed on the server (e.g., an SQL Server). Note that although the following description is in the context of an SQL server, it is to be understood that other suitable server architectures can benefit from the disclosed cache management mechanism.
The input schemas (e.g., XML) are shredded into many relational tables and only the most frequently used pieces of schema can be selectively loaded and cached. Furthermore, since the relational layout includes several primary and secondary indexes, the loading of schemas will also be fast. Because XML schemas are shredded into tables, XML instance validation loads only the necessary components to perform validation. During validation, only parts of the schema that are used are loaded and cached. The schema cache stores the in-memory representation of XML schema optimized for XML instance validation. XML schema components are loaded from metadata into main memory as read-only objects such that multiple users can use the in-memory objects for validation. If the XML schema is changed during the operation, the schema cache entries are invalidated. Additionally, if the database server is under heavy load, unused schema cache entries are unloaded. In view of the above novel capabilities, a scalable system is provided that can operate in large enterprise environments involving thousands of XML schema components and supporting many concurrent users.
Once the required schemas are located in relational tables, only the parts relevant to Type, Attribute, or Element definition will be added to the XSD type cache. In implementation, a reverse mechanism from the schema import is used: first, a symbol table is created, and then, validation structures are derived that are cached.
For caching, the SQL Server caching framework can be used which keeps the most active entries in memory while less frequently used entries are removed periodically. In addition, the mechanism for cache cleanup is driven by the memory pressure currently present on the system. If the system is overloaded, entries will be more aggressively removed from the cache. The algorithm for cache cleanup also takes into consideration the number of I/O reads required to compute the entry and the total memory required to compute the cache entry.
A final property of relational representation of XML schemas is a performance benefit due to the indexes built on XML schema component tables and other schema tables. Inheritance can be efficiently checked. Inheritance checking is used in several parts of SQL Server, mainly during data import and for XQuery casting.
During DDL (Data Definition Language) (CREATE, ALTER and DROP XML SCHEMA COLLECTION) the namespace version is changed during DDL import or DDL drop. This will invalidate any existing cache entries. In one implementation, if a database version change is detected the whole cache is flushed.
The CLR 804 has a second component, the GC memory, which can be considered as a heap. CLR objects can be allocated out of this heap. This heap could be shrunk through a mechanism called garbage collection, that is, reclaiming back unusable memory. The size of GC heap is limited by virtual and physical memory size. In one implementation, there are as many GC heaps as a number of CPUs in the system. In one instance, the CLR is allocated externally to the SQL server's memory management mechanism. In another instance, the CLR can be converted to the disclosed memory management mechanism. A costing mechanism can be based on GC heaps sizes and their usage. The GC heap cannot be discarded, but only can be shrunk.
With respect to network libraries page pool, to perform network reads and writes, network libraries can require memory pages that are multiples of OS page sizes. Page size can be different depending on the client configuration. The pool size can depend on the activity of the clients, and the page size configuration. In one instance, network libraries allocate a page directly from the OS and keep a pool of free pages. The pages are usually affinitized to either a scheduler or a network card. There is no real costing. Under memory pressure, network libraries can shrink their pools. The lifetime of the page in the free pool can be defined by current memory pressure. An XML schema cache is about 256-2 KB in entry data size, has an unlimited cache size, the allocation mechanism is memory object per type, costing is by CPU+disk I/O+network I/O, and the lifetime can be cost+usage.
A sys.xml_schema_collections catalog view 1002 can include a row per XML schema collection. An XML schema collection is a named set of XSD definitions. The XML schema collection itself can be contained in a relational schema, and it is identified by a schema-scoped SQL name. The values xml_collection_id and (schema_id, name) are unique for this view.
Example: Rows in sys.xml_schema_collections after the XML schema collection myCollection are created.
A sys.xml_schema_namespaces catalog view 1004 contains one row per XSD-defined XML Namespace. The (collection_id, namespace_id) and (collection_id, name) values are unique within the view.
Example: Rows in sys.xml_schema_namespaces after the XML schema collection myCollection are created.
A sys.xml_schema_components catalog view 1006 contains one row per component of an XML schema. The pair (collection_id, namespace_id) is a compound foreign key to the containing namespace. xml_component_id is unique. For named components, (symbol_space, name, scoping_xml_component_id, is_qualified, xml_namespace_id, xml_collection_id) is also unique. There are two recursive relationships. The first is determined by the base_xml_component_id foreign key. If not NULL, then it is a reference to the parent component in an inheritance hierarchy. The other is determined by scoping_xml_component_id foreign key. If NULL, the component has a global scope. If not NULL, then it is a reference to some other XML component that forms the scoping namespace.
A sys.xml_schema_types catalog view 1008 contains one row per xml-component that is a Type (symbol_Space of T).
A sys.xml_schema_facets catalog view 1010 contains one row per facet (restriction) of an xml-type definition (corresponds to sys.xml_schema_types).
Example: Rows in sys.xml_Schema_facets after the XML schema collection myCollection are created.
A sys.xml_schema_elements catalog view 1012 contains one row per xml-component that is an element (symbol_Space of E).
A sys.xml_schema_model_groups catalog view 1014 contains one row per xml-component that is a Model-Group (symbol_Space of M).
A sys.xml_schema_attributes catalog view 1016 contains one row per xml-component that is an Attribute (symbol_Space of A).
A sys.xml_schema_wildcards catalog view 1018 contains one row per xml-component that is an Attribute-Wildcard (kind of V) or Element-Wildcard (kind of W), both with symbol_Space of N.
Example: Rows in sys.xml_schema_wildcards after the XML schema collection myCollection are created. Since the “books” XML schema does not have a wildcard, no entries for wildcards are created.
A sys.xml_schema_wildcard_namespaces catalog view 1020 contains one row per enumerated namespace for an xml-wildcard.
Example: Rows in sys.xml_Schema_wildcard_namespaces after the XML schema collection myCollection are created. Since the “books” XML schema does not have a wildcard, no entries for the namespace of wildcards are created.
A sys.xml_schema_component_placements catalog view 1022 contains one row per placement for xml-components.
Example: Rows in sys.xml_schema_component_placements after the XML schema collection myCollection are created.
Referring now to
Generally, program modules include routines, programs, components, data structures, etc., that perform particular tasks or implement particular abstract data types. Moreover, those skilled in the art will appreciate that the inventive methods can be practiced with other computer system configurations, including single-processor or multiprocessor computer systems, minicomputers, mainframe computers, as well as personal computers, hand-held computing devices, microprocessor-based or programmable consumer electronics, and the like, each of which can be operatively coupled to one or more associated devices.
The illustrated aspects of the invention may also be practiced in distributed computing environments where certain tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules can be located in both local and remote memory storage devices.
A computer typically includes a variety of computer-readable media. Computer-readable media can be any available media that can be accessed by the computer and includes both volatile and nonvolatile media, removable and non-removable media. By way of example, and not limitation, computer readable media can 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, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital video disk (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 the computer.
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, RF, infrared and other wireless media. Combinations of the any of the above should also be included within the scope of computer-readable media.
With reference again to
The system bus 1108 can be any of several types of bus structure that may further interconnect to a memory bus (with or without a memory controller), a peripheral bus, and a local bus using any of a variety of commercially available bus architectures. The system memory 1106 includes read only memory (ROM) 1110 and random access memory (RAM) 1112. A basic input/output system (BIOS) is stored in a non-volatile memory 1110 such as ROM, EPROM, EEPROM, which BIOS contains the basic routines that help to transfer information between elements within the computer 1102, such as during start-up. The RAM 1112 can also include a high-speed RAM such as static RAM for caching data.
The computer 1102 further includes an internal hard disk drive (HDD) 1114 (e.g., EIDE, SATA), which internal hard disk drive 1114 may also be configured for external use in a suitable chassis (not shown), a magnetic floppy disk drive (FDD) 1116, (e.g., to read from or write to a removable diskette 1118) and an optical disk drive 1120, (e.g., reading a CD-ROM disk 1122 or, to read from or write to other high capacity optical media such as the DVD). The hard disk drive 1114, magnetic disk drive 1116 and optical disk drive 1120 can be connected to the system bus 1108 by a hard disk drive interface 1124, a magnetic disk drive interface 1126 and an optical drive interface 1128, respectively. The interface 1124 for external drive implementations includes at least one or both of Universal Serial Bus (USB) and IEEE 1394 interface technologies.
The drives and their associated computer-readable media provide nonvolatile storage of data, data structures, computer-executable instructions, and so forth. For the computer 1102, the drives and media accommodate the storage of any data in a suitable digital format. Although the description of computer-readable media above refers to a HDD, a removable magnetic diskette, and a removable optical media such as a CD or DVD, it should be appreciated by those skilled in the art that other types of media which are readable by a computer, such as zip drives, magnetic cassettes, flash memory cards, cartridges, and the like, may also be used in the exemplary operating environment, and further, that any such media may contain computer-executable instructions for performing the methods of the invention.
A number of program modules can be stored in the drives and RAM 1112, including an operating system 1130, one or more application programs 1132, other program modules 1134 and program data 1136. All or portions of the operating system, applications, modules, and/or data can also be cached in the RAM 1112. It is appreciated that the invention can be implemented with various commercially available operating systems or combinations of operating systems.
A user can enter commands and information into the computer 1102 through one or more wired/wireless input devices, e.g., a keyboard 1138 and a pointing device, such as a mouse 1140. Other input devices (not shown) may include a microphone, an IR remote control, a joystick, a game pad, a stylus pen, touch screen, or the like. These and other input devices are often connected to the processing unit 1104 through an input device interface 1142 that is coupled to the system bus 1108, but can be connected by other interfaces, such as a parallel port, an IEEE 1394 serial port, a game port, a USB port, an IR interface, etc.
A monitor 1144 or other type of display device is also connected to the system bus 1108 via an interface, such as a video adapter 1146. In addition to the monitor 1144, a computer typically includes other peripheral output devices (not shown), such as speakers, printers, etc.
The computer 1102 may operate in a networked environment using logical connections via wired and/or wireless communications to one or more remote computers, such as a remote computer(s) 1148. The remote computer(s) 1148 can be a workstation, a server computer, a router, a personal computer, portable computer, microprocessor-based entertainment appliance, a peer device or other common network node, and typically includes many or all of the elements described relative to the computer 1102, although, for purposes of brevity, only a memory storage device 1150 is illustrated. The logical connections depicted include wired/wireless connectivity to a local area network (LAN) 1152 and/or larger networks, e.g., a wide area network (WAN) 1154. Such LAN and WAN networking environments are commonplace in offices, and companies, and facilitate enterprise-wide computer networks, such as intranets, all of which may connect to a global communication network, e.g., the Internet.
When used in a LAN networking environment, the computer 1102 is connected to the local network 1152 through a wired and/or wireless communication network interface or adapter 1156. The adaptor 1156 may facilitate wired or wireless communication to the LAN 1152, which may also include a wireless access point disposed thereon for communicating with the wireless adaptor 1156.
When used in a WAN networking environment, the computer 1102 can include a modem 1158, or is connected to a communications server on the WAN 1154, or has other means for establishing communications over the WAN 1154, such as by way of the Internet. The modem 1158, which can be internal or external and a wired or wireless device, is connected to the system bus 1108 via the serial port interface 1142. In a networked environment, program modules depicted relative to the computer 1102, or portions thereof, can be stored in the remote memory/storage device 1150. It will be appreciated that the network connections shown are exemplary and other means of establishing a communications link between the computers can be used.
The computer 1102 is operable to communicate with any wireless devices or entities operatively disposed in wireless communication, e.g., a printer, scanner, desktop and/or portable computer, portable data assistant, communications satellite, any piece of equipment or location associated with a wirelessly detectable tag (e.g., a kiosk, news stand, restroom), and telephone. This includes at least Wi-Fi and Bluetooth™ wireless technologies. Thus, the communication can be a predefined structure as with a conventional network or simply an ad hoc communication between at least two devices.
Wi-Fi, or Wireless Fidelity, allows connection to the Internet from a couch at home, a bed in a hotel room, or a conference room at work, without wires. Wi-Fi is a wireless technology similar to that used in a cell phone that enables such devices, e.g., computers, to send and receive data indoors and out; anywhere within the range of a base station. Wi-Fi networks use radio technologies called IEEE 802.11(a, b, g, etc.) to provide secure, reliable, fast wireless connectivity. A Wi-Fi network can be used to connect computers to each other, to the Internet, and to wired networks (which use IEEE 802.3 or Ethernet). Wi-Fi networks operate in the unlicensed 2.4 and 5 GHz radio bands, at an 11 Mbps (802.11a) or 54 Mbps (802.11b) data rate, for example, or with products that contain both bands (dual band), so the networks can provide real-world performance similar to the basic 10BaseT wired Ethernet networks used in many offices.
Referring now to
The system 1200 also includes one or more server(s) 1204. The server(s) 1204 can also be hardware and/or software (e.g., threads, processes, computing devices). The servers 1204 can house threads to perform transformations by employing the invention, for example. One possible communication between a client 1202 and a server 1204 can be in the form of a data packet adapted to be transmitted between two or more computer processes. The data packet may include a cookie and/or associated contextual information, for example. The system 1200 includes a communication framework 1206 (e.g., a global communication network such as the Internet) that can be employed to facilitate communications between the client(s) 1202 and the server(s) 1204.
Communications can be facilitated via a wired (including optical fiber) and/or wireless technology. The client(s) 1202 are operatively connected to one or more client data store(s) 1208 that can be employed to store information local to the client(s) 1202 (e.g., cookie(s) and/or associated contextual information). Similarly, the server(s) 1204 are operatively connected to one or more server data store(s) 1210 that can be employed to store information local to the servers 1204.
What has been described above includes innovative examples. It is, of course, not possible to describe every conceivable combination of components or methodologies for purposes of describing the subject invention, but one of ordinary skill in the art may recognize that many further combinations and permutations are possible. Accordingly, the invention is intended to embrace all such alterations, modifications and variations that fall within the spirit and scope of the appended claims. Furthermore, to the extent that the term “includes” is used in either the detailed description or the claims, such term is intended to be inclusive in a manner similar to the term “comprising” as “comprising” is interpreted when employed as a transitional word in a claim.
This application claims the benefit of U.S. Provisional Patent application Ser. No. 60/619,043 entitled “MAPPING OF XML SCHEMA DATA INTO RELATIONAL DATABASE STRUCTURES” and filed Oct. 15, 2004, the entirety of which is incorporated by reference herein.
Number | Date | Country | |
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60619043 | Oct 2004 | US |