Patent Publication Number: US-7904487-B2

Title: Translating data access requests

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This Application is related to the following U.S. Patent Applications: U.S. patent application Ser. No. 09/998,908, “Support for Multiple Data Stores,” filed on Nov. 30, 2001; U.S. patent application Ser. No. 10/314,888, “Support for Multiple Mechanisms for Accessing Data Stores,” filed on Dec. 9, 2002; “Support for RDBMS in an LDAP System”, by Sanjay P. Ghatare, U.S. patent application Ser. No. 10/682,575, filed the same day as the present application; and “Partitioning Data Access Requests,” by Sanjay P. Ghatare, U.S. patent application Ser. No. 10/682,330, filed the same day as the present application. The four above listed patent applications are incorporated herein by reference in their entirety. 
     BACKGROUND OF THE INVENTION 
     1. Field of the Invention 
     The present invention is directed to technology for translating data access requests. 
     2. Description of the Related Art 
     With the growth of the Internet, the use of networks and other information technologies, Identity Systems have become more popular. In general, an Identity System provides for the creation, removal, editing and other managing of identity information stored in various types of data stores. The identity information pertains to users, groups, organizations and/or things. For each entry in the data store, a set of attributes are stored. For example, the attributes stored for a user may include name, address, employee number, telephone number, email address, user ID and password. 
     The Identity System can also manage access privileges that govern what an entity can view, create, modify or use in the Identity System. Often, this management of access privileges is based on one or more specific attributes, membership in a group and/or association with an organization. Some users of Identity Systems also use Access Systems. An Access System provides for the authentication and authorization of users attempting to access resources. For efficiency purposes, there is an advantage to integrating the Identity System and the Access System. For example, both systems can share the same set of data stores. 
     Some systems are designed for a particular type of data store. For example, some Identity Systems are designed to work with LDAP directories. However, some organization that desire to use an Identity System may already have a relational database populated with data in use for other systems. Thus, there is a desire for supporting the use of relational databases for systems designed to work with other types of data stores. 
     Some prior solutions have provided for the use of relational databases by systems designed to work with other types of data stores. However, these prior solutions required that the relational database employ a specific predetermined schema. Requiring a specific predetermined schema may be acceptable for a new database that is not to be used with other applications. Existing databases, however, have already been implemented with a schema. Additionally, some databases may also need to interface with other applications that may not work with the specific predetermined schema. Thus, there is a need to support the use of relational databases for systems designed to work with other types of data stores, where the relational database is not required to be of a specific schema. 
     SUMMARY OF THE INVENTION 
     The present invention, roughly described, pertains to technology for translating access requests between a format suitable for a relational database and a different format used by an application. One embodiment of the present invention includes receiving a request to access data for one or more attributes, where the request identifies the attributes in a first data format. A mapping catalog customizable for a relational database schema is accessed. The mapping catalog identifies one or more portions of one or more tables in a relational database that stores the data for the one or more attributes. At least a portion of the request to access data is translated from the first data format to a form suitable for the relational database. The step of translating is performed by using the mapping catalog. The translated request is provided to the relational database. 
     One implementation of the present invention includes a data source interface in communication with business logic, a mapping catalog and a translation module. The translation modules receives access request information from the data source interface and mapping information from the mapping catalog. The access request information pertains to data for one or more attributes. The translation module translates the request information from a first form to a second form suitable for a relational database based on the mapping information from the mapping catalog. 
     In one embodiment, the present invention is implemented as part of an Identity System, or an integrated Identity and Access System. However, the present invention is not limited to Identity Systems and can be implemented as part of many other types of systems. 
     The present invention can be accomplished using hardware, software, or a combination of both hardware and software. The software used for the present invention is stored on one or more processor readable storage devices including hard disk drives, CD-ROMs, DVDs, optical disks, floppy disks, tape drives, RAM, ROM, flash memory or other suitable storage devices. In alternative embodiments, some or all of the software can be replaced by dedicated hardware including custom integrated circuits, gate arrays, FPGAs, PLDs, and special purpose processors. In one embodiment, software implementing the present invention is used to program one or more processors. The one or more processors can be in communication with one or more storage devices, peripherals and/or communication interfaces. 
     These and other objects and advantages of the present invention will appear more clearly from the following description in which the preferred embodiment of the invention has been set forth in conjunction with the drawings. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a block diagram depicting the components of one embodiment of the present invention. 
         FIG. 2  is a flow chart describing one embodiment of a process for authenticating and authorizing. 
         FIG. 3  is an example of a directory tree structure. 
         FIG. 4  is a block diagram of one embodiment of an architecture for supporting multiple data stores. 
         FIG. 5  is a flow chart describing one embodiment of a process for creating a mapping catalog. 
         FIG. 6  is a flow chart describing one embodiment of a process for using a mapping catalog to support translation of requests from a logical object class format to SQL format. 
         FIG. 7  is an example of an ER diagram. 
         FIG. 8  graphically depicts an example of an RDBMS schema. 
         FIG. 9  is a flow chart describing one embodiment of a process for translating and performing SEARCH requests. 
         FIG. 10  is a flow chart describing one embodiment of a process used when combining sub-filters. 
         FIG. 10A  depicts an example of an expression tree. 
         FIG. 11  is a flow chart describing one embodiment of a process used when combining sub-filters. 
         FIG. 12  is a flow chart describing one embodiment of simple node combining process. 
         FIG. 13  is a flow chart describing one embodiment of NOT type combining process. 
         FIG. 14  is a flow chart describing one embodiment of AND type combining process. 
         FIG. 15  is a flow chart describing one embodiment of OR type combining process. 
         FIG. 16  is a flow chart describing one embodiment of a process for translating and performing ADD requests. 
         FIG. 17  is a flow chart describing one embodiment of a process for translating and performing a DELETE operation. 
         FIG. 18  is a flow chart describing one embodiment of a process for translating and performing a MODIFY operation. 
         FIG. 19  is a flow chart describing one embodiment of a process for partitioning a data access request. 
         FIG. 20  is a flow chart describing one embodiment of a process for evaluating a partition expression against a filter expression. 
         FIG. 21  depicts an example of a partition expression tree 
         FIG. 22  is a flow chart describing one embodiment of a process for a partition function. 
         FIG. 23  is a flow chart describing one embodiment of a process for combining results for child sub-filters. 
     
    
    
     DETAILED DESCRIPTION 
     I. Access Management System 
     The present invention can be used with an Identity System, an Access System, or an integrated Identity and Access System (“an Access Management System”). The present invention can also be used with other systems.  FIG. 1  depicts an example of an Access Management System that provides identity management services and/or access management services for a network. The identity management portion of the system manages identity profiles, while the access management portion of the system provides security for resources across one or more Web Servers (or other components). Although the system of  FIG. 1  includes an integrated Identity System and Access System, other embodiments may only include an Identity System or only include an Access System. 
       FIG. 1  is a block diagram depicting one embodiment for deploying an integrated Identity System and Access System.  FIG. 1  shows web browsers  12  and  14  accessing Web Server  18  and/or Web Server  20  via network  16 . One example of a network is the Internet. In one embodiment, web browsers  12  and  14  are standard web browsers known in the art running on any suitable type of computer.  FIG. 1  depicts web browsers  12  and  14  communicating with Web Server  18  and Web Server  20  using HTTP over the Internet; however, other protocols and networks can also be used. 
     Web Server  18  is a standard Web Server known in the art and provides an end user with access to various resources via network  16 . One embodiment includes two firewalls. A first firewall (see dotted lines) is connected between network  16  and Web Server  18 . A second firewall (see dotted lines) is connected between Web Servers  16  and  18  and Access Server  34 /Identity Server  40 . 
       FIG. 1  shows two types of resources: resource  22  and resource  24 . Resource  22  is external to Web Server  18  but can be accessed through Web Server  18 . Resource  24  is located on Web Server  18 . A resource can be anything that is possible to address with a uniform resource locator (URL, see RFC 1738). A resource can include a web page, software application, file, database, directory, data unit, etc. In one embodiment, a resource is anything accessible to a user via a network. The network could be the Internet, a LAN, a WAN, or any other type of network. 
       FIG. 1  shows Web Server  18  including Web Gate  28 , which is a software module. In one embodiment, Web Gate  28  is a plug-in to Web Server  18 . Web Gate  28  communicates with Access Server  34 . Access Server  34  communicates with Directory  36 . 
     The Access System includes Access Server  34 , Web Gate  28 , and Directory  36 . Access Server  34  provides authentication, authorization, auditing and logging services. It further provides for identity profiles to be used across multiple domains and for access based on a single web-based authentication (sign-on). Web Gate  28  acts as an interface between Web Server  18  and Access Server  34 . Web Gate  28  intercepts requests from users for resources  22  and  24 , and authorizes them via Access Server  34 . Access Server  34  is able to provide centralized authentication, authorization, and auditing services for resources hosted on or available to Web Server  18  and other Web Servers. 
     The Identity System includes Web Pass  38 , Identity Server  40  and Directory  36 . Identity Server  40  manages identity profiles. An identity profile is a set of information associated with a particular entity (e.g., user, group, organization, thing, etc.). The data elements of the identity profile are called attributes. An attribute can be a characteristic, quality or element of information about something. In one embodiment, an attribute may include a name, a value and access criteria. Other embodiments may include more or less information. The Identity Server includes three main applications, which effectively handle the identity profiles and privileges of the user population: User Manager  42 , Group Manager  44 , and Organization Manager (also called Object Manager)  46 . User Manager  42  manages the identity profiles for individual users. Group Manager  44  manages identity profiles for groups. Organization Manager  46  manages identity profiles for organizations and/or can manage any object. Identity Server  40  also includes Publisher  48 , an application that enables entities to quickly locate and graphically view information stored by Directory  36 . In one embodiment, Web Pass  38  is a Web Server plug-in that sends information back and forth between Identity Server  40  and the Web Server  20 , creating a three-tier architecture. The Identity System also provides a Certificate Processing Server (not shown in  FIG. 1 ) for managing digital certificates. 
     User Manager  42  handles the functions related to user identities and access privileges, including creation and deletion of user identity profiles, modification of user identity profile data, determination of access privileges, and credentials management of both passwords and digital certificates. With User Manager  42 , the create, delete, and modify functions of user identity management can be set as flexible, multi-step workflows. Each business can customize its own approval, setup, and management processes and have multiple processes for different kinds of users. 
     Group Manager  44  allows entities to create, delete and manage groups of users who need identical access privileges to a specific resource or set of resources. Managing and controlling privileges for a group of related people—rather than handling their needs individually—yield valuable economies of scale. Group Manager  44  meets a wide range of e-business needs: easy creation, maintenance, and deletion of permanent and ad hoc groups of users who may be allowed or denied access to particular resources; modification and adaptation of groups and their access privileges with minimal disruption to the directory server&#39;s underlying schema; efficient addition and deletion of users from established groups; and delegation of administrative responsibility for group membership and subscription requests and approvals. 
     With Group Manager  44 , companies (or other entities) can allow individual users to do the following: (1) self-subscribe to and unsubscribe from groups, (2) view the groups that they are eligible to join or have joined, and (3) request subscription to groups that have access to the applications they need. Multi-step workflows can then define which users must obtain approval before being added to a group and which can be added instantly. Group Manager  44  also lets organizations form dynamic groups specified by an LDAP filter. The ability to create and use dynamic groups is extremely valuable because it eliminates the administrative headache of continually keeping individual, static membership up-to-date. With dynamic group management features, users can be automatically added or removed if they meet the criteria specified by the LDAP filter. Dynamic groups also greatly enhance security since changes in user identities that disqualify someone from membership in a group are automatically reflected in the dynamic group membership. 
     The third application in the Identity System, Organization Manager  46 , streamlines the management of large numbers of organizations and/or other objects within an e-business network, including partners, suppliers, or even major internal organizations such as sales offices and business units. Certain infrastructure security and management operations are best handled at the highest organizational unit level rather than at the individual or group level. Like User Manager and Group Manager, this application relies on multi-step workflow and delegation capabilities. Organization Manager handles the following administrative tasks: (1) organization lifecycle management, whereby companies can create, register, and delete organizations in their systems using customizable workflows; (2) maintenance of organization profiles on an attribute-by-attribute basis through self-service, delegated administration and system-initiated activities; (3) organization self-registration, whereby organizations such as business partners, customers and suppliers can self-generate a request to be added to the e-business network; and (4) creation of reusable rules and processes through multi-step workflows. 
     The various components of  FIG. 1  can be implemented by software running on computing devices. Many different types of computing devices can be used, including servers, mainframes, minicomputers, personal computers, mobile computing devices, handheld devices, mobile telephones, etc. Typically, such computing devices will have one or more processors that are programmed by code that is stored in one or more processor readable storage devices. The one or more processors are in communication with the processor readable storage devices, peripherals (e.g., keyboards, monitors, pointing devices, printers, etc.) and communication interfaces (e.g., network interfaces, modems, wireless transmitters/receivers, etc.). 
     The system of  FIG. 1  is scalable. There can be one or many Web Servers, one or many Access Servers, and one or many Identity Servers. In one embodiment, Directory  36  is a Directory Server and communicates with other servers/modules using LDAP or LDAP over SSL. In other embodiments, Directory  36  can implement other protocols or can be other types of data repositories (e.g., relational database using SQL, etc.). Many variations of the system of  FIG. 1  can be used with the present invention. For example, instead of accessing the system with a web browser, an API can be used. Alternatively, portions of functionality of the system at  FIG. 1  can be separated into independent programs that can be accessed with a URL. 
     To understand how the system of  FIG. 1  protects a resource, first consider the operation regarding unprotected resources. First, an end user causes his or her browser to send a request to a Web Server. The request is usually an HTTP request, which includes a URL. The Web Server then translates, or maps, the URL into a file system&#39;s name space and locates the matching resource. The resource is then returned to the browser. 
     With the system of  FIG. 1  deployed, Web Server  18  (enabled by Web Gate  28 , Access Server  34 , and Directory  36 ) can make informed decisions based on default and/or specific rules about whether to return requested resources to an end user. The rules are evaluated based on the end user&#39;s identity profile, which is managed by the Identity System. In one embodiment of the present invention, the general method proceeds as follows. An end user enters a URL or an identification of a requested resource residing in a protected policy domain. The user&#39;s browser sends the URL as part of an HTTP request to Web Server  18 . Web Gate  28  intercepts the request. If the end user has not already been authenticated, Web Gate  28  causes Web Server  18  to issue a challenge to the browser for log-on information. The received log-on information is then passed back to Web Server  18  and on to Web Gate  28 . Web Gate  28  in turn makes an authentication request to Access Server  34 , which determines whether the user&#39;s supplied log-on information is authentic or not. Access Server  34  performs the authentication by accessing attributes of the user&#39;s identity profile and the resource&#39;s authentication criteria stored on Directory  36 . If the user&#39;s supplied log-on information satisfies the authentication criteria, the process flows as described below; otherwise, the end user is notified that access to the requested resource is denied and the process halts. After authenticating the user, Web Gate  28  queries Access Server  34  about whether the user is authorized to access the resource requested. Access Server  34  in turn queries Directory  36  for the appropriate authorization criteria for the requested resource. Access Server  34  retrieves the authorization criteria for the resource and answers Web Gate  28 &#39;s authorization query, based on the resource&#39;s authorization criteria and the user&#39;s identity profile. If the user is authorized, the user is granted access to the resource; otherwise, the user&#39;s request is denied. Various alternatives to the above described flow are also within the spirit and scope of the present invention. 
     Authentication and Authorization decisions are based on policy domains and policies. A policy domain is a logical grouping of Web Server host ID&#39;s, host names, URL prefixes, and rules. Host names and URL prefixes specify the course-grain portion of the web name space a given policy domain protects. Rules specify the conditions in which access to requested resources is allowed or denied, and to which end users these conditions apply. Policy domains contain two levels of rules: first level default rules and second level rules contained in policies. First level default rules apply to any resource in a policy domain not associated with a policy. 
     A policy is a grouping of a URL pattern, resource type, operation type (such as a request method), and policy rules. These policy rules are the second level rules described above. Policies are always attached to a policy domain and specify the fine-grain portion of a web name space that a policy protects. In practice, the host names and URL prefixes from the policy&#39;s policy domain are logically concatenated with the policy&#39;s URL pattern. The resulting overall pattern is compared to the incoming URL. If there is a match, then the policy&#39;s various rules are evaluated to determine whether the request should be allowed or denied; if there is not a match, then default policy domain rules are used. 
       FIG. 2  provides a flow chart for one embodiment of a method for authenticating and authorizing. In step  50 , a user&#39;s browser  12  requests a web-enabled resource  22  or  24 . The request is intercepted by Web Gate  28  in step  52 . The method then determines whether the requested resource is protected by an authentication and/or authorization rule in step  53 . If the resource is not protected, then access is granted to the requested resource in step  95 . If the requested resource is protected, however, the method proceeds to step  54 . If the user has previously authenticated for a protected resource in the same domain, a valid authentication cookie is passed by browser  12  with the request in step  50 . The authentication cookie is intercepted by Web Gate in step  52 . If a valid cookie is received (step  54 ), the method attempts to authorize the user in step  56 . If no valid authentication cookie is received (step  54 ), the method attempts to authenticate the user for the requested resource (step  60 ). 
     If the user successfully authenticates for the requested resource (step  62 ), then the method proceeds to step  74 . Otherwise, the unsuccessful authentication is logged in step  64 . After step  64 , the system then performs authentication failure actions and Web Gate  28  denies the user access to the requested resource in step  66 . In step  74 , the successful authentication of the user for the resource is logged. The method then performs authentication success actions in step  76 . In response to the successful authentication, Web Gate  28  then passes a valid authentication cookie to browser  12  (step  80 ), which stores the cookie. After passing the cookie in step  80 , the system attempts to authorize in step  56 . 
     In step  56 , the method determines whether the user is authorized to access the requested resource. If the user is authorized (step  90 ), the method proceeds to step  92 . Otherwise, the unsuccessful authorization is logged in step  96 . After step  96 , the method performs authorization failure actions (step  98 ) and Web Gate.  28  denies the user access to the requested resource. If authorization is successful (step  90 ), then the successful authorization of the user is logged in step  92 . Authorization success actions are performed in step  94 . The user is granted access to the requested resource in step  95 . In one embodiment of step  95 , some or all of HTTP request information is provided to the resource. In one or more scenarios, the resource being accessed is the Identity System. Other scenarios include accessing other resources. 
     More information about authorization, authentication, an Access System and an Identity System can be found in U.S. patent application Ser. No. 09/998,908, “Support for Multiple Data Stores,” filed on Nov. 30, 2001, which is incorporated herein by reference in its entirety. 
     Both the Identity System and the Access System make use of Directory  36 . A unit of information stored in Directory  36  is called an entry or identity profile, which is a collection of information about an object. The information in an entry often describes a real-world object such as a person, but this is not required. A typical directory includes many entries that correspond to people, departments, groups and other objects in the organization served by the directory. An entry is composed of a set of attributes, each of which describes one particular trait, characteristic, quality or element of the object. In one embodiment, each attribute has a type, one or more values, and associated access criteria. The type describes the kind of information contained in the attribute, and the value contains the actual data. 
     An entry in the directory may have a set of attributes that are required and a set of attributes that are allowed. For example, an entry describing a person may be required to have a cn (common name) attribute and a sn (surname) attribute. One example of an allowed attribute may be a nickname. In one embodiment, any attribute not explicitly required or allowed is prohibited. 
     Examples of attributes stored in a user identity profile include: first name, middle name, last name, title, email address, telephone number, fax number, mobile telephone number, pager number, pager email address, identification of work facility, building number, floor number, mailing address, room number, mail stop, manager, direct reports, administrator, organization that the user works for, region, department number, department URL, skills, projects currently working on, past projects, home telephone, home address, birthday, previous employers and anything else desired to be stored by an administrator. Examples of attributes stored in a group identity profile include: owner, name, description, static members, dynamic member rule, subscription policies, etc. Examples of attributes stored in a user organization identity profile include: owner, name, description, business category, address, country, etc. In other embodiments, less or more than the above-listed information is stored. 
     In one embodiment, each identity profile is based on a logical object class definition. Each logical object class may include single and multi-valued attributes. The attributes can be mandatory or optional. Each attribute can also have a data type and a semantic type. A semantic type is a behavior associated with an attribute. For example, the semantic type of a telephone number is to dial the telephone number. 
       FIG. 3  depicts an exemple directory tree that can be stored in Directory  36 . Each node on the tree is an entry in the directory structure that includes an identity profile. In one embodiment, the entity can be a user, group or organization. Node  230  is the highest node on the tree and represents an entity responsible for the directory structure. In one example, an entity may set up an Extranet and grant Extranet access to many different companies. The entity setting up the Extranet is node  230 . Each of the companies with Extranet access would have a node at a level below node  230 . For example, company A (node  232 ) and company B (node  234 ) are directly below node  230 . Each company may be broken up into organizations. The organizations could be departments in the company or logical groups to help manage the users. For example,  FIG. 3  shows company A broken up into two organizations: organization A with node  236  and organization B with node  238 . Company B is shown to be broken up into two organizations: organization C with node  240  and organization D with node  242 .  FIG. 5  shows organization A having two end users: employee  1  with node  250  and employee  2  with node  252 . Organization B is shown with two end users: employee  3  with node  254  and employee  4  with node  256 . Organization C is shown with two end users: employee  5  with node  258  and employee  6  with node  260 . Organization D is shown with two end users: employee  7  with node  262  and employee  8  with node  264 . 
     Each entity has a distinguished name (DN), which uniquely identifies the node. In one embodiment, each entry also has a relative name, which is different from all other relevant names on the same level of the hierarchy. In one implementation, the distinguished name (DN) comprises a union of the relative names up the tree. For example, the distinguished name of employee  1  (node  250 ) is 
     DN=CN=Empl, OU=OrgA, O=CompanyA, DC=entity, where:
         DC=Domain Component   O=Organization   OU=Organizational Unit   CN=common name.       

       FIG. 3  shows a hierarchical tree. Some organizations employ fat or flat trees for ease of maintenance. A flat directory tree is a directory information tree that does not have any hierarchy. All of the nodes are leaf nodes (nodes without any child nodes). A fat directory tree is a tree that has a large number of nodes at any given level in a directory information tree. One advantage of a fat or flat tree is user maintenance. For example, if an employee moves to a new group, the node must be moved to a new container if the tree is not flat or fat. By moving the node to a new container, the distinguished name for the node changes and all certificates become void. One drawback of flat or fat trees is that the organization loses the benefits of having a logical directory, such as using the logical directory to determine who has access to which nodes. To remedy this, the Identity System includes partition support for fat and flat tree directories using filters. From a configuration page, an attribute can be configured to be accessible (read, modify, etc.,) based on a two part filter. The first component in the filter identifies a top node in the directory. The filter will only apply to those entities at or below that top node. The second component of the filter is an LDAP filter which defines who can access the attribute. This two component filter can be applied on an attribute by attribute basis. 
     There are many ways for an entity to access and use the Identity System. In one embodiment, the entity can access the Identity System&#39;s services using a browser. In other embodiments, XML documents and API&#39;s can be used to access the services of the Identity System. For example, an entity can use a browser by pointing the browser to Identity Server  40 . The user will then be provided with a login page to enter the user&#39;s ID, password, type of user and application requested (optional). Upon filling out that information, the user will be authenticated and authorized (by the Access System) to use the Identity System. Alternatively, the Access System can be bypassed (or there may be no Access System) and the Identity System authenticates the user. 
     II. Supporting Multiple Data Stores 
     The above description of the Identity and Access Systems assumes that the data store is a LDAP directory. In other embodiments, other types of data stores can be used. For example, a relational database can also be used. In one embodiment, the Identity and/or Access Systems can be used with both a LDAP directory and a relational database. In one implementation, the Identity and Access Systems will internally treat all data as LDAP type data and convert data to the appropriate formats upon access to the various data stores. In another embodiment, the Identity and Access Systems will use a logical object class format for data and upon accessing a data store, the data will be translated between the formats in the data store and the logical object class. The logical object class format is a predetermined format for storing data. One embodiment of a logical object class format has a one-to-one correspondence with an LDAP data type; therefore, the logical object class is the same as the LDAP format. In other embodiments, the logical object class format will differ slightly from the LDAP data type. In yet other embodiments, the logical object class can differ significantly from the LDAP data type. There are many different formats for a logical object class that can be used with the present invention. No particular format is required. 
     Table 1 provides a mapping of compatible data types for LDAP and RDBMS (Relational Database Management System). 
     
       
         
           
               
             
               
                 TABLE 1 
               
             
            
               
                   
               
               
                 Compatible data types for LDAP and RDBMS. 
               
            
           
           
               
               
            
               
                 LDAP data types 
                 Compatible RDBMS data type 
               
               
                   
               
               
                 Case exact match string (ces) 
                 Char, varchar 
               
               
                 Case insensitive string (cis) 
                 Char, varchar 
               
               
                 Telephone (tel) 
                 Char, varchar (spaces and hyphens 
               
               
                   
                 ignored in comparison) 
               
               
                 Integer (int) 
                 Integer, number, numeric 
               
               
                 Distinguished Name (dn) 
                 Char, varchar 
               
               
                 Binary (bin) 
                 Blob 
               
               
                   
               
            
           
         
       
     
     Note that some of the data types (e.g, CIS, telephone) require special comparison functions. The support for CIS can be easily executed in RDBMS server using either UPPER( ) or LOWER( ) function. Support for telephone number requires existence of comparison functions in the database server that ignores spaces and hyphens. Since each function may not exist in the RDBMS, it may need to be implemented as a user defined function. Case insensitive search or telephone number search results in a sequential search of data in a RDBMS server, unless the functional index is built into the database. 
     The LDAP protocol operations include SEARCH, ADD, DELETE and MODIFY. Other operations can also be used. In one embodiment, a LDAP SEARCH operation maps to a SQL SELECT operation, a LDAP ADD operation maps to a SQL INSERT operation, a LDAP DELETE operation maps to a SQL DELETE operation, and a LDAP MODIFY operation maps to a SQL UPDATE operation. 
     The logical name space is a system of names used for defining logical object classes and their attributes. To add support for RDBMS, and other data sources, the logical object class will be mapped to columns of tables in the relational database, object classes in the LDAP data store, or other structures in other types of data stores. 
       FIG. 4  depicts a high level architecture for supporting multiple types of data stores.  FIG. 4  depicts User Interface layer  402 , Business Logic layer  404 , and Data Source layer  406 . Business Logic layer  404  sits below User Interface layer  402  and above Data Source layer  406 . User Interface layer  402  is used to interface with the user. Business Logic layer  404  performs the core logic of the Identity System and Access System described above. In other embodiments, Business Logic layer  404  can perform other types of business logic for other applications. Business Logic layer  404  is in communication with User Interface layer  402  and Data Source layer  406 . When Business Logic layer  404  needs to access data (including reading data, writing data, modifying data, deleting data, etc.), Business Logic layer  404  will communicate with Data Source layer  406  for the data access. In one embodiment, regardless of the type of data store being accessed, Business Logic layer  404  will send data to Data Source layer  406  and receive data from Data Source layer  406  in the same format. In one embodiment, that format is the logical object class format. 
     Data Source layer  406  includes Data Source Layer Interface  420 , Partitioning Module  422 , Merge Module  424 , and Transaction Module  430 . Transaction Module  430  includes a first sub-module  432  for communicating with relational database server  450  and a second sub-module  434  for communicating with LDAP server  452 . If the system were to include additional data stores, additional sub-modules would also be included. Data Source Layer Interface  420  is used to provide an interface for Business Logic layer  406 . Upon receiving a data access request from Business Logic layer  406 , Data Source Layer Interface  420  will provide the access request to Partitioning Module  422 . Partitioning module  422  will determine which data store should receive the request. In some embodiments, the request can be broken into sub-requests and different sub-requests can be provided to different data stores. The data access request can be partitioned based on manually created partition rules for data or by other criteria. For example, in some systems, data will be partitioned by the day of the week the request was received. In other embodiments, other rules can be used. More information about partitioning is discussed below. Upon partitioning, the appropriate request will be sent to the appropriate one or more sub-modules (e.g.,  432  or  434 ). If the data request is for relational database server  450 , then the request is sent to sub-module  432 . If the request is intended for LDAP server  452 , then the request is sent to sub-module  434 . A data access request can be for one data store or multiple data stores (including one, two or more relational databases). Sub-module  432  translates the request from an LDAP operation on logical object classes to one or more operations on RDBMS tables using the RDBMS Mapping Catalog  438 . For example, an LDAP query is translated to a select statement. An LDAP modify can be translated to an insert, delete or update operation on a RDBMS system. Sub-module  434  translates operations on logical object classes to operations on LDAP record entries in LDAP server  452 , based, on LDAP Mapping Catalog  440 . 
     Note that the data sources (e.g.,  450  and  452 ) can be implemented on separate computing devices from user interface  402 , business logic  404  and data source layer  606 . Alternatively, the data sources (e.g.,  450  and  452 ) can be implemented on the same computing devices as one or more of user interface  402 , business logic  404  and data source layer  606 . 
     LDAP filters support operators AND, OR, NOT, equal, approx, greater than, less than, present, sub-string and extensible. The extensible operator is not supported in RDBMS. The approx (sounds like) operator may not have the equivalent operator/function in all databases. In other embodiments, other operators can also be used. 
     Upon translating the data access request to the appropriate format for database server  450  or LDAP server  452 , the translated request is then sent to the appropriate data store. After the operation is performed on the appropriate data store, one or more results are sent back to sub-module  432  or sub-module  434 . Those results are then translated back to the logical object class format and provided to merge module  424 . Merge module  424  will merge all the results for a single request (because the partitioning module may have partitioned data request into multiple sub-requests) and then provide the merge results back to Data Source Layer Interface  420 . The merge results are then sent from Data Source Layer Interface  420  back to Business Logic layer  404 . 
       FIG. 5  is a flowchart describing a high level process for setting up RDBMS Mapping Catalog  438  and/or LDAP Mapping Catalog  440 . In one embodiment, the process of  FIG. 5  is performed once for RDBMS Mapping Catalog  438  and once for LDAP Mapping Catalog  440 . 
     In step  502  of  FIG. 5 , the logical object class (or classes) is determined. In one embodiment, the logical object class is determined by an administrator or designer of the system. In other embodiments, the logical object class can be determined automatically by a computer. In step  504 , each of the attributes of the logical object class are classified. In one embodiment, all attributes are classified into one of eight classes. More detail about the classification will be described below. These classes are used for translating data between logical object class and RDBMS or LDAP. Each classification is translated differently. In other embodiments, more or less than eight classes are used. In Step  506 , the Mapping Catalog is created based on the classification of attributes. More detail about the Mapping Catalog will be explained below. In step  508 , the Mapping Catalog is stored. 
     Once the Mapping Catalog is stored, the system is now configured so that data can be translated between an RDBMS system and the business logic that uses the logical object class. Note that one of the advantages of the present invention is that the business logic is able to adapt to an existing RDBMS schema by using the Mapping Catalog. That is, in one embodiment, the mapping catalog is customizable for any normalized relational database schema. 
       FIG. 6  depicts a flow chart describing a high level description of how data is accessed using a logical object class and the RDBMS server (and/or other type of data store). In step  600 , Data Source Layer Interface  420  receives a data access request from Business Logic layer  404 . In step  602 , Partitioning Module  422  will determine the appropriate data source(s) for the request. In step  604 , the request is sent to the appropriate sub-modules in translation module  430 . The data request is translated based on the Mapping Catalogs in step  606 . The translated data request is then communicated to the appropriate data store (e.g., relational database server  450  or LDAP server  452 ) in step  610 . In step  612 , the results form the data store, received by the transaction module  430 , are translated back to the logical object class format. The results are then merged in step  614 . The merged results are provided to Business Logic layer  404  in step  616 . 
     As described above, the present invention provides for mapping between the logical object class and RDBMS. This mapping is based on the Mapping Catalog. To understand the mapping and the Mapping Catalog, it is important to understand how database schemas are designed. Database schema design involves identifying entities (a group of attributes that describes things like objects, persons, places, etc.) and their relationship in the problem domain. The relationship is generally depicted using Entity Relationship (ER) diagrams. The cardinality of the relationship between entities can be one-to-one, one-to-many, and many-to-many. Database schemas do not generally support many-to-many entity relationships; therefore, many-to-many entity relationships can be resolved by introducing another associative entity. A relation can connect two different instances of the same entity. Such relation is called recursive relationship. 
       FIG. 7  shows an ER diagram for Employees. The many-to-many relationship between Employees and Projects is broken by introducing Project Participants as an associative entity.  FIG. 7  shows five entities: Employees  650 , Department  652 , Employee Projects  654 , Project  656  and HR  658 . The RDBMS schema definition (table, columns of table, primary key, foreign key) captures the entity definitions in the ER diagram. Each of the boxes in  FIG. 7  corresponds to a table. Each of the lines  660 ,  662 ,  664 ,  666 ,  668  and  670  refer to a relationship between data and the tables. Line  660  refers to a one to zero or one relationship. Line  664  refers to a zero or one to one-or-many relationship. Line  666  refers to a zero or one to one-or-many relationship. Line  668  refers to a zero or one to one-or-many relationship. Line  670  refers to a one to one relationship. 
       FIG. 8  shows the RDBMS table definitions corresponding to the ER diagram of  FIG. 7 . Each box in  FIG. 8  is a table, which can have primary keys, foreign keys, and column names.  FIG. 8  shows table  680  for employee information, table  682  for storing department information, table  684  for storing project participant information, table  686  for storing project information, and table  690  for storing human resources salary information. Employee table  680  has five columns. The first column is identification (ID), which serves as the primary key for employee table  680 . Employee table  680  also includes a Name column (Name), department identification (DeptID), manager identification (MgrID), and Login name. Department table  682  includes identification (ID), which serves as the primary key and a Name column. Project Participants table  684  (also called Employee Project Table) includes a primary key that consists of an employee ID (EID) and a project ID (PID). Projects Table  686  includes identification (ID), which serves as the primary key, and a name (Name). The department ID (DeptID) stored in employee table  680  is a foreign key that points to the ID in the department table  682 . A first employee will also have a MgrID and that will be a pointer to a second employee&#39;s ID, where that second employee is the manager of the first employee. In the employee-project table, the employee ID (EID) is a key to the employee table, pointing to the ID (primary key). The project ID (PID) is a key to the project table  686  and points to the ID column in project table  686 . HR table  688  uses the employee ID (EID) as its primary key and also includes a column for employee salary. The EID of HR table  688  points to the same as the ID of Employee table  680 . 
     For the above example, consider the following logical object class (employee) and its mapping to the example schema described above: 
     
       
         
           
               
               
             
               
                   
                   
               
             
            
               
                   
                 Requires 
               
               
                   
                 ID 
               
               
                   
                 NAME 
               
               
                   
                 DEPARTMENT 
               
               
                   
                 LOGIN 
               
               
                   
                 May have 
               
               
                   
                 MANAGER 
               
               
                   
                 TEAM (multi-valued) 
               
               
                   
                 PROJECTS (multi-valued) 
               
               
                   
                 SALARY 
               
               
                   
                   
               
            
           
         
       
     
     During the configuration phase of the process depicted in  FIG. 5 , the Mapping Catalog will be defined. The logical object class is mapped to a master table and other tables linked to the master table through various key relationships. In the above example, the Employee table is a master table, since this is the first table accessed with any data access request. In one embodiment, an administrator configuring the system would determine which table is the master table. 
     The first step in creating the Mapping Catalog is to classify each of the attributes. Table 2, below, provides eight classifications (A-H). Table 2 uses the following abbreviations:
     OC=Object Class (e.g., Employee)   PTOC=Primary table for object class (e.g., Employee table)   PK=Primary Key   PKC=Primary Key column   KC=Key Column   LT=Linking Table   LLT=Second level linking table (table linked with primary table through another table)   Ci=Columns   

     
       
         
           
               
             
               
                 TABLE 2 
               
             
            
               
                   
               
               
                 LOC Attribute Mappings to columns of table in RDBMS 
               
            
           
           
               
               
               
               
               
               
            
               
                 Attribute 
                   
                   
                   
                   
                   
               
               
                 Mapping Kind 
                   
                   
                 Linking 
                 Cardinality of 
               
               
                 (Example 
                   
                 Example 
                 Expression with 
                 mapped column 
               
               
                 logical object 
                 Mapped 
                 of mapped 
                 parent table 
                 wrt master table 
               
               
                 class attribute) 
                 Column 
                 column 
                 primary key 
                 primary key 
                 Description 
               
               
                   
               
               
                 A 
                 PTOC.PKC 
                 E.ID 
                 — 
                 Single (1-1) 
                 Primary key 
               
               
                 (ID) 
                   
                   
                   
                   
                 from master table 
               
               
                 B 
                 PTOC.C1 
                 E.NAME 
                 — 
                 Single (1-1) 
                 Column from master table 
               
               
                 (NAME) 
                   
                   
                   
                   
                 (directly dependent on 
               
               
                   
                   
                   
                   
                   
                 primary key value) 
               
               
                 C (Manager 
                 PTOC.C1 
                 E.NAME 
                 (PTOC.C3 = LT.PKC) 
                 Single (1-1) 
                 Unique column 
               
               
                 Name or 
                 (Unique) 
                 Or 
                 [master-link- 
                   
                 (C1) from a table 
               
               
                 Department 
                   
                 D.NAME 
                 column = master- 
                   
                 dependent on 
               
               
                 Name) 
                   
                   
                 linked-column] 
                   
                 non-primary key 
               
               
                   
                   
                   
                   
                   
                 column value of 
               
               
                   
                   
                   
                   
                   
                 master row. 
               
               
                 D 
                 LT.C1 
                 HRInfo.SALARY 
                 (PTOC.PKC = LT.PKC) 
                 Single (1-1) 
                 The primary key 
               
               
                 (Employee 
                 (non unique) 
                   
                 [master-link- 
                   
                 of master table is 
               
               
                 Salary 
                   
                   
                 column = master- 
                   
                 the linking attribute 
               
               
                 stored in 
                   
                   
                 linked-column] 
                   
                 with primary key of 
               
               
                 HR table) 
                   
                   
                   
                   
                 the linking table 
               
               
                   
                   
                   
                   
                   
                 and the mapped 
               
               
                   
                   
                   
                   
                   
                 attribute is not 
               
               
                   
                   
                   
                   
                   
                 unique column in 
               
               
                   
                   
                   
                   
                   
                 the linked table. 
               
               
                 E 
                 LT.KC1 
                 EP.PID 
                 (PTOC.PKC = LT.KC2) 
                 Multi-valued 
                 Column part of 
               
               
                 (Project Ids) 
                   
                   
                 [master-link- 
                 (1-m) 
                 primary key in 
               
               
                   
                   
                   
                 column = master- 
                   
                 another table, 
               
               
                   
                   
                   
                 linked-column] 
                   
                 whose another 
               
               
                   
                   
                   
                   
                   
                 key part is linked 
               
               
                   
                   
                   
                   
                   
                 to the primary key 
               
               
                   
                   
                   
                   
                   
                 value of master row. 
               
               
                 F 
                 LLT.C1 
                 P.NAME 
                 (PTOC.PKC = LT.KC2) 
                 Multi-valued 
                 Unique column 
               
               
                 (Project 
                 (Unique) 
                   
                 and (LLT.PKC = LT.KC1) 
                 (1-m) 
                 value in another 
               
               
                 Names) 
                   
                   
                 [(master-link- 
                   
                 table dependent 
               
               
                   
                   
                   
                 column = master- 
                   
                 on E values. 
               
               
                   
                   
                   
                 linked-column) and 
               
               
                   
                   
                   
                 (table-link-column = 
               
               
                   
                   
                   
                 table-linked-column)] 
               
               
                 G 
                 PTOC.PKC 
                 E.ID 
                 (PTOC.C3 = PTOC.PKC) 
                 Multi-valued 
                 Primary key column 
               
               
                 (Team 
                   
                   
                 [master-link- 
                 (1-m) 
                 values from table 
               
               
                 Member 
                   
                   
                 column = master- 
                   
                 whose non-primary key 
               
               
                 IDs) 
                   
                   
                 linked-column] 
                   
                 column matches 
               
               
                   
                   
                   
                   
                   
                 master rows 
               
               
                   
                   
                   
                   
                   
                 primary key value. 
               
               
                 H 
                 PTOC.C1 
                 E.NAME 
                 (PTOC.C3 = PTOC.PKC) 
                 Multi-valued 
                 Unique column 
               
               
                 (Team 
                 (Unique) 
                   
                 [master-link- 
                 (1-m) 
                 value from table 
               
               
                 Member 
                   
                   
                 column = master- 
                   
                 dependent on G values. 
               
               
                 Names) 
                   
                   
                 linked-column] 
               
               
                   
               
            
           
         
       
     
     Table 2 is used to classify each attribute into one of the eight classes (also called attribute mapping kind). Table 2 includes six columns. The first column (attribute mapping kind) lists the name of the classification and provides an example. The last column of Table 2 provides a Description of each of the classifications. Based on this Description, an administrator or computer program (in which case the classification is automatically done by a computer) is performed. For example, the first classification, Class A, pertains to attributes which are the primary keys in the master table. In this example, the ID is the primary key and is a Class A attribute. Using the last column of Table 3, all of the attributes are classified (see step  504  of  FIG. 5 ). 
     Step  506  in  FIG. 5  includes creating the Mapping Catalog. In one embodiment, the Mapping Catalog is created based on the information in Table 2. One embodiment of the Mapping Catalog includes a table with six columns: (1) Attribute Column, (2) Mapped-Column, (3) Master-Link-Column, (4) Master-Linked-Column, (5) Mapped-Table-Link-Column, and (6) Mapped-Table-Linked-Column. Other embodiments can implement the Mapping Catalog with different data structures and/or based on different data. The Attribute Column of the Mapping Catalog stores the name of the attribute from the logical object class. The second column of Table 2 (titled “Mapped-Column”) indicates what information should be placed in the Mapped-Column of the Mapping Catalog. 
     Table 3, below provides an example of a Mapping Catalog created based on Table 2 and the example above. 
     
       
         
           
               
             
               
                 TABLE 3 
               
             
            
               
                   
               
               
                 Employee LOC Attribute Mapping 
               
            
           
           
               
               
               
               
               
               
            
               
                   
                 Mapped-Column 
                 Master 
                   
                 Mapped- 
                 Mapped- 
               
               
                   
                 (* - Multiple 
                 -Link- 
                 Master- 
                 Table-link- 
                 Table-linked- 
               
               
                 Attribute 
                 values) 
                 Col. 
                 linked-column 
                 column 
                 column 
               
               
                   
               
               
                 ID 
                 Employee.ID 
                 — 
                 — 
                 — 
                 — 
               
               
                 NAME 
                 Employee.Name 
                 — 
                 — 
                 — 
                 — 
               
               
                 LOGIN 
                 Employee.Login 
                 — 
                 — 
                 — 
                 — 
               
               
                 MANAGER 
                 Employee.Name 
                 MgrId 
                 Employee.ID 
                 — 
                 — 
               
               
                 DEPART. 
                 Department.Name 
                 DeptId 
                 Department.ID 
                 — 
                 — 
               
               
                 PROJECTS 
                 Projects.Name 
                 ID 
                 Emp_projects.EID 
                 Projects.ID 
                 Emp_projects.PID 
               
               
                 TEAM 
                 Employee.Name 
                 MgrId 
                 Employee.ID 
               
               
                   
               
            
           
         
       
     
     The last four columns of the Mapping Catalog are filled in based on information in the fourth column (“Linking Expression with Parent Table Primary Key”) of Table 2. Note that Table 3 includes a row for seven attributes in the logical object class Employee, described above. The first attribute, ID, is a Class A attribute. The Mapped Column in Table 3 is PTOC.PKC, which is the primary key for the master table—Employee.ID. The fourth column of Table 2 indicates that no information should be added to the last four columns of Table 3 for this entry. 
     The second attribute in Table 3 is the NAME attribute, which is a Class B attribute. The Mapped Column in Table 2 indicates that the Mapped Column in the Mapping Catalog should indicate the appropriate column for the attribute in the master table Employee. In this case, the mapped column is Employee.Name. The fourth column of Table 2 indicates that no information should be added to the last four columns of Table 3 for this entry. 
     The third attribute is LOGIN (which is not shown in the schema or ER drawings of  FIGS. 7 and 8 ). LOGIN is a Class B attribute. The Mapped Column in Table 2 indicates that the Mapped Column in the Mapping Catalog should indicate the appropriate column for the attribute in the master table. In this case, the mapped column is Employee.Login. The fourth column of Table 2 indicates that no information should be added to the last four columns of Table 3 for this entry. 
     The fourth attribute is MANAGER, which is a Class C attribute. The second column of Table 2 indicates that the Mapped Column for the Mapping Catalog should indicate the appropriate column in the master table, which in this case is Employee.Name. The fourth column of Table 2 indicates that the Master-Link-Column of the Mapping Catalog should include the appropriate column of the master table, which is MgrId. This is the attribute which is the source of the link/key. The Master-Linked-Column should include the primary key column of the linking table, which in this case is Employee.ID and is the destination of the link/key. 
     The fifth attribute is DEPARTMENT name, which is also a Class C attribute. The Master-Link-Column is equal to the appropriate column in the master table and the Master-Linked-Column is equal to the column in the linking table for the primary key. The linking table is the Department Table. 
     The sixth attribute is PROJECTS, which is a Class F attribute. Note that Class E, F, G and H are multi-valued attributes. The mapped column for a Class F attribute is the appropriate column of the second level linking table (e.g., Project Table  686 ). For a Class F attribute, data is populated in the Master-Link-Column, Master-Linked-Column, Mapped-Table-Link-Column, and Mapped-Table-Linked-Column. The Master-Link-Column is populated with the primary key column of the master table and the Master-Link-Column is the appropriate key column for the linking table, for example, Employee.ID and Emp_projects.empid, respectively. The Mapped-Table-Link Column is the primary key column for the second level linking table (e.g., Projects.ID) and the Mapped-Table-Link Column is the appropriate key column for the linking table (e.g., EMP_Projects.PID). 
     III. Translating Data Access Requests 
     Step  606  of  FIG. 6  includes translating data access requests. In one embodiment, an access request may be in the following format:
 
ldap://[hostname:portnum]/[Searchbase]?[attributes]?[subtype]?[filter]
 
     In one embodiment, only [attributes] and [filter] of the above URL will be applicable to RDBMS data sources. The other components (if specified by callers) can be used by the LDAP data sources. In one embodiment, if an operation involves a logical object class, then hostname and port number for a data source will be used from the Data Source Profile information in the Mapping Catalog. Subtype and Searchbase assumes DIT structure for LDAP. To improve search performance, the LDAP translation module can use a specified searchbase, or derive the searchbase information from an LDAP filter to DN suffix mappings in the Mapping Catalog. 
     A. Search 
       FIG. 9  is a flow chart describing a process for performing steps  606  and  610  of  FIG. 6  for a SEARCH operation. In step  702 , the [attributes] and [filter] of the access request are read. In step  704 , each of the attributes in the [attributes] and [filter] of the access request are mapped to the relational database using the Mapping Catalog. A filter may be composed of sub-filters. For example, the filter (&amp;(manager=Jill)(project_names=HRsystem)) has two sub-filters. The first sub-filter is (manager=Jill) and the second sub-filter is (project_names=HRsystem). In step  708 , each sub-filter is translated into a separate SELECT statement. In step  708 , each of the SELECT statements for the sub-filters are combined into one aggregate SELECT statement. In step  710 , the aggregate SELECT statement built in step  708  is issued to the database in order to get the primary key values of the rows of the master table that store the data being searched for. In step  712 , the requested attributes from [attributes] of the access request are obtained for each primary key value returned in step  710 . These attributes will be translated and returned to the business logic as described above. 
     Step  706  of  FIG. 9  includes translating sub-filters. Table 4 provides the translation templates for translating sub-filters, including providing a template for each class of attribute. Variables in the templates are from the Mapping Catalog. 
     
       
         
           
               
             
               
                 TABLE 4 
               
             
            
               
                   
               
               
                 SQL queries for LDAP 
               
            
           
           
               
               
            
               
                 Attribute 
                   
               
               
                 Class 
                 SQL statement for filter (attribute &lt;op&gt; value) 
               
               
                   
               
               
                 A 
                 mapped-column &lt;op&gt; value 
               
               
                 B 
                 Select master-table.primary-key-column from master-table 
               
               
                   
                 where mapped-column &lt;op&gt; value 
               
               
                 C 
                 Select master. primary-key-column From master-table 
               
               
                   
                 master, mapped-column-table child Where (master.master- 
               
               
                   
                 link-column = child.master-linked-column) and 
               
               
                   
                 (child.mapped-column &lt;op&gt; value) 
               
               
                 D 
                 Select master-linked-column From mapped-column-table 
               
               
                   
                 Where mapped-column &lt;op&gt; value 
               
               
                 E 
                 Select master-linked-column from mapped-column-table 
               
               
                   
                 where mapped-column &lt;op&gt; value 
               
               
                 F 
                 Select master-linked-column From master-linked-column- 
               
               
                   
                 table, mapped-column-table Where (table-link-column = 
               
               
                   
                 table-linked-column) and (mapped-column &lt;op&gt; value) 
               
               
                 G 
                 Select master-link-column From master-table 
               
               
                   
                 Where mapped-column &lt;op&gt; value 
               
               
                 H 
                 Select master-link-column From master-table 
               
               
                   
                 Where mapped-column &lt;op&gt; value 
               
               
                   
               
            
           
         
       
     
     Table 5 provides examples of translating sub-filters using the templates of Table 4. Note that example SQL statements of Table 5 are based on the example above. 
     
       
         
           
               
             
               
                 TABLE 5 
               
             
            
               
                   
               
               
                 Example SQL queries 
               
            
           
           
               
               
            
               
                 Attribute 
                 Example SQL statement for filter 
               
               
                   
               
               
                 ID 
                 Select employee.ID From employee 
               
               
                 Name = John 
                 Select employee.ID From employee 
               
               
                   
                 where (employee.Name=’John’) 
               
               
                 Login = jsmith 
                 Select employee.ID From employee 
               
               
                   
                 where (employee.Login=’jsmith’) 
               
               
                 Department Name = 
                 Select employee.ID employee master, 
               
               
                 Sales 
                 department child Where (master.DeptId = 
               
               
                   
                 child.Id) and (child.Name = ‘Sales’) 
               
               
                 Manager Name = 
                 Select employee.ID From employee master, 
               
               
                 Smith 
                 employee child Where (master.mgrid = 
               
               
                   
                 child.id) and (child.name=‘Smith’) 
               
               
                 Project Names = Big 
                 Select emp_projects.empid From 
               
               
                   
                 emp_projects, projects Where 
               
               
                   
                 (emp_projects.projid = projects.id) and 
               
               
                   
                 (projects.name = ‘Big’) 
               
               
                   
               
            
           
         
       
     
     Step  708  of  FIG. 9  includes combining the sub-filters.  FIG. 10  depicts a flow chart describing the process of combining the sub-filters. In step  800 , an expression tree of is built for the filter. That is, a tree (e.g. a search tree) is set up where each node is an operator, attribute or value from the filter in the access request. The top node, also called the root node, is the highest level operator from a lexical standpoint. For example, the filter (&amp;(manager=Jill)(project_names=HRsystem)) is used to create the expression tree of  FIG. 10A . In step  802 , the root node is accessed. For example, in  FIG. 10A , the node for the AND (&amp;) operator is accessed. In step  804 , the “combination process” is performed. 
       FIG. 11  is a flow chart describing the “combination process” of step  804 . In step  840 , the current node is accessed. If it is the start of the “combination process” then the root node is accessed. In step  842 , it is determined whether the node is a simple node. For example, whether the node is one of the following operators: =, &lt;, &lt;=, &gt;, &gt;+, ˜=, =*. If the node is a simple node, then the simple node combine process (described below) is performed in step  844 . If the node is not a simple node, then in step  848  it is determined whether the node is a NOT operator. If the node is a NOT operator, then the NOT type combine process (described below) is performed in step  850 . If the node is not a NOT operator, then in step  858  it is determined whether the node is an AND or Or operator. If the node is an AND operator, then the AND type combine process (described below) is performed in step  862 . If the node is an OR operator, then the OR type combine process (described below) is performed instep  860 . 
       FIG. 12  is a flow chart describing the simple node combine process of step  844 . In step  900 , the attribute mapping class (e.g., A, B, C, etc.—see above) is determined for the attribute(s) in the expression. In step  902 , operand value (for operands other than exists, =*) is converted to a SQL equivalent (in some cases, substitution of ‘*’ with ‘%’ in the operand string and single quote the string data type values). In step  904 , the system gets the filter SQL statement for the binary operator and substitutes the operator equivalent and operand value. In step  906 , the SQL statement is returned. 
       FIG. 13  is a flow chart describing the NOT type combine process of step  850 . In step  940 , the SQL statement for the child node is generated by recursively calling the combination process ( FIG. 11 ). In step  942 , the master_table_name and master_table_primary_key_column_name are accessed. In step  944 , the SQL statement is created: NotSQLStmt=“SELECT”+master_table_name+“.”+master_table_primary_primary_key_column_name+“FROM”+master_table_name+“WHERE”+master_table+“.”+master_table_primary_key_column_name+“NOT IN (“+sql_child_node+”)”. In step  946 , the SQL statement, labeled as NotSQLStmt is returned. 
       FIG. 14  is a flow chart describing the AND type combine process of step  862 . In step  1002 , SQL statements for each child node are generated by recursively calling the combination process ( FIG. 11 ). These SQL statements are stored in sql_child_nodes_list. In step  1004 , master_table_name and master_table_primary_key_column_name are accessed. Steps  1006  and  1008  include creating the SQL statement. If the database is a SQL Server, then in step  1006  the following SQL statement is created: AndSQLStmt=“SELECT”+master_table_name+“.”+master_table_primary_key_colun_name+“FROM”+master_table_name+“WHERE”+master+table+“.”+master_table_primary_key_column_name+“IN (“+sql_child_nodes[0]+”) AND”+. . . +master_table+“.”+master_table_primary_key_column_name+“IN (“+sql_child_nodes[n]+”)”. If the database is a an Oracle, DB2 or Informix database, then in step  1008  the following SQL statement is created: AndSQLStmt=“(“+sql_child_nodes[0]+”) INTERSECT (“+sql_child_nodes[1]+”) INTERSECT (“= . . . +sql_child_nopdes[n]+”)”. In step  1010 , the SQL statement, labeled as ANDSQLStmt is returned. 
       FIG. 15  is a flow chart describing the OR type combine process of step  860 . In step  1040 , SQL statements for each child node are generated by recursively calling combination process ( FIG. 11 ). These SQL statements are stored in sql_child_nodes_list. In step  1042 , the SQL statement is created: OrSQLStmt=“(“+sql_child_nodes[0]+”) UNION (“+sql_child_nodes[1]+”) UNION (“= . . . +sql_child_nopdes[n]+”)”. In step  1044 , the SQL statement, labeled as ORSQLStmt is returned. 
     For the EXIST operator, change the mapped_column &lt;op&gt; value to mapped_column IS NOT NULL in column 2 of table 4. For example, (Name=*) corresponds to SELECT employee.ID from Employee where employee.name IS NOT NULL. 
     Step  712  of  FIG. 9  includes getting the requested attributes for each primary key value returned in step  710 . In one embodiment, the primary key values returned in step  710  are used to construct SELECT statements to access the requested attributes from the data access request received in step  600  of  FIG. 6 . Table 6 provides the templates for constructing SELECT statements that use the primary key values returned in step  710  in order to access the requested attributes from the data access request. The variables in the templates are from the Mapping Catalog. In one embodiment, a separate SELECT statement is constructed for each attribute in the [attributes] of the access request. In another embodiment, a separate SELECT statement is constructed for each primary key value for each attribute in the [attributes] of the access request. In other embodiments, a SELECT statement is constructed for each primary key value and the returned data is parsed to access the one or more attributes in the [attributes] of the access request. In some instances of some embodiments, one SELECT statement can be use to access all attributes. 
     
       
         
           
               
             
               
                 TABLE 6 
               
             
            
               
                   
               
               
                 SQL queries for getting attribute values for a selected data record 
               
            
           
           
               
               
            
               
                 Attribute 
                   
               
               
                 mapping 
               
               
                 kind 
                 SQL statement for getting attribute value(s) 
               
               
                   
               
               
                 A 
                 — 
               
               
                 B 
                 Select mapped-column from master-table 
               
               
                   
                 Where master-table.primary-key-column = ? 
               
               
                 C 
                 Select child.mapped-column 
               
               
                   
                 From master-table master, mapped-column-table child 
               
               
                   
                 Where (master.master-link-column = child.master-linked- 
               
               
                   
                 column) and (master.primary-key-column = ?) 
               
               
                 D 
                 Select mapped-column From mapped-column-table 
               
               
                   
                 Where master-linked-column = ? 
               
               
                 E 
                 Select mapped-column From mapped-column-table 
               
               
                   
                 Where master-linked-column = ? 
               
               
                 F 
                 Select mapped-column From master-linked-column-table, 
               
               
                   
                 mapped-column-table Where (table-link-column = table- 
               
               
                   
                 linked-column) and (master-linked-column = ?) 
               
               
                 G 
                 Select mapped-column From master-table Where master- 
               
               
                   
                 link-column = ? 
               
               
                 H 
                 Select mapped-column From master-table Where master- 
               
               
                   
                 link-column = ? 
               
               
                   
               
            
           
         
       
     
     Table 7 provides examples of SELECT statements created according to Table 6. Note that example SQL statements of Table 7 are based on the example above. 
     
       
         
           
               
             
               
                 TABLE 7 
               
             
            
               
                   
               
               
                 Example SQL Queries Getting Attributes 
               
            
           
           
               
               
            
               
                 Attribute 
                   
               
               
                 Name 
                 SQL statement for getting attribute value 
               
               
                   
               
               
                 ID 
                 — 
               
               
                 Name 
                 Select Employee.name from Employee where 
               
               
                   
                 Employee.id = ? 
               
               
                 Login 
                 Select Employee.login from Employee where 
               
               
                   
                 Employee.id = ? 
               
               
                 Department 
                 Select child.Name From employee master, 
               
               
                 Name 
                 department child Where (master.DeptID = child.ID) 
               
               
                   
                 and (master.id = ?) 
               
               
                 Manager Name 
                 Select child.Name From employee master, employee 
               
               
                   
                 child Where (master.mgrId = child.id) and 
               
               
                   
                 (master.id = ?) 
               
               
                 Team Member 
                 Select employee.Name From employee Where 
               
               
                 Names 
                 employee.MgrId = ? 
               
               
                 Project Names 
                 Select projects.name From projects, emp_projects 
               
               
                   
                 Where (projects.id = emp_projects.projid) and 
               
               
                   
                 (emp_projects.empid = ?) 
               
               
                   
               
            
           
         
       
     
     Below is an example of a translation. The LDAP filter being translated is: ldap:///?name??(&amp;(manager=Minoo)(project_names=performance). The result of the translation is: 
     
       
         
           
               
               
             
               
                   
                   
               
             
            
               
                   
                 select employee.name from employee 
               
               
                   
                 where employee.id in 
               
               
                   
                 (select employee.id from employee where employee.id in 
               
            
           
           
               
               
            
               
                   
                 (select master.id 
               
               
                   
                 from employee master, employee child 
               
               
                   
                 where (master.mgrid = child.id) and 
               
               
                   
                 (child.name = ‘Minoo’)) 
               
            
           
           
               
               
            
               
                   
                 and employee.id in 
               
            
           
           
               
               
            
               
                   
                 (select emp_projects.empid 
               
               
                   
                 from emp_projects, projects 
               
               
                   
                 where (emp_projects.projid = projects.id) 
               
               
                   
                 and (projects.name = ‘performance’)) 
               
               
                   
                   
               
            
           
         
       
     
     If a filter expression involves only single valued attributes mapped to a column from the master table of mapping kinds A and B only, then one embodiment provides an optimization to the translation that will generate the following SELECT statement. Note that Sql(filter) is a SQL equivalent of the LDAP filter obtained by replacing attribute names with table column names in infix representation of the filter.
         Select master-table.primary-key-column where sql(filter)       

     If a filter expression involves only single valued attributes of mapping kinds A, B, C, and D, then a Join query can be generated to get the correct result. The Join query involves participant tables defining a dynamic view of the data. The sql(filter) selects rows from the dynamic view. The following statement will be generated for the filter. The alias set {ctab1, . . . , ctabm} is generated for each attribute of mapping class C in the filter. The set is based on unique master-link-column for the attribute. The alias set {dtab1, . . . , dtabn} is generated for each attribute of mapping class D in the filter. The set is based on the unique master-linked-column for the attribute. 
     
       
         
           
               
               
             
               
                   
                   
               
             
            
               
                   
                 Select master-table.primary-key-column 
               
               
                   
                 From master-table atab, mapped-table-c1 ctab1,..., 
               
               
                   
                 mapped-table-cm ctabm, 
               
            
           
           
               
               
            
               
                   
                 Mapped-table-d1 dtab1, ..., mapped-table-dn dtabn 
               
            
           
           
               
               
            
               
                   
                 Where (atab.master-link-column-for-c1 = 
               
               
                   
                 ctab1.master-linked-column-for-c1) 
               
            
           
           
               
               
            
               
                   
                 and 
               
            
           
           
               
               
            
               
                   
                 ... 
               
               
                   
                 (atab.master-link-column-for-cm = 
               
               
                   
                 ctabm.master-linked-column-for-cm) 
               
            
           
           
               
               
            
               
                   
                 and 
               
            
           
           
               
               
            
               
                   
                 (atab.master-link-column-for-d1 = 
               
               
                   
                 dtab1.master-linked-column-for-d1) 
               
            
           
           
               
               
            
               
                   
                 and 
               
            
           
           
               
               
            
               
                   
                 ... 
               
               
                   
                 (atab.master-link-column-for-dn = 
               
               
                   
                 dtab1.master-linked-column-for-dn) 
               
            
           
           
               
               
            
               
                   
                 and 
               
            
           
           
               
               
            
               
                   
                 (sql(filter)) 
               
               
                   
                   
               
            
           
         
       
     
     The above discussion explains how to translate LDAP SEARCH operations to SQL SELECT operations. The translation process is also used to translate LDAP ADD operations to SQL INSERT operations. 
     B. Add 
       FIG. 16  is a flow chart describing a process for performing steps  606  and  610  of  FIG. 6  for an ADD operation. When creating a new entry in a database, some RDBMS servers will automatically generate a new primary key for the new entry in the database. If the database server does not generate unique identifier for the primary key, then system will provide a function to generate the new primary key. A numeric sequencing function configurable at table level can be provided if the database server does not generate the primary key values. A non-numeric primary key is not efficient for database access, and the user will have to register a function to generate a non-numeric primary key value. For each record entry to be inserted in a database that does not automatically generate the primary key, a primary key value (pkvalue) will be generated and saved as a tuple (primary-key, pkvalue) in a single-value-attribute-list (SVAL) for the master table. Each table to receive data for the new entry will have a SVAL, which contains a set of key—value pairs. 
     For class B attributes, a (mapped-column, value) tuple is added to the SVAL for the master table. For class C attributes, existence of the attribute value (cvalue) is checked in the linked table and the corresponding primary key value from the linked table is obtained (pkvalue-for-cvalue). If pkvalue-for-cvalue does not exist, then the add record entry operation is aborted. In other embodiments, the data can be added. In some embodiments, the data must be added previously as part of a configuration step or maintenance. The tuple (master-link-column, pkvalue-for-cvalue) is added to the SVAL for the master table. For inserting values for class D attributes, the existence of pkvalue is checked in the mapped table. If the pkvalue exists in the mapped table then dvalue is updated in the mapped-table corresponding to the pkvalue. Otherwise the add record entry operation is aborted. For each attribute value for a class E attribute, the tuple (attrib-value, pkvalue) is added to the SVAL for the linking table. For each attribute value for class F attributes, the primary key value is obtained from the linking table. The tuple (primary-key-value-from-linking-table, pkvalue-from-master) is added to the SVAL for the intermediate table. For each attribute value of class G attributes, the attribute master-link-column needs to be updated to pkvalue in the master table identified by the attribute value of G. For each attribute value of class H attributes, the primary key values for the attribute values h from the master table are obtained. The master-link-column needs to be updated to the pkvalue in the master table identified by the primary key values. 
     There are at least two possibilities for adding an entry with class C and D attributes. The first possibility is to create a new row for the attribute value dependent on keyvalue from master table in the mapped-column-table. The second possibility is to assume existence of the row (dependent on keyvalue from master table in the mapped-column-table) and update the mapped-column value to new attribute value. The above steps for adding an entry record have described the second option. Support for the first option can also be configured during mapping of the logical object class. 
     The translation module will generate INSERT statements for the tuples in the SVALs. For example: INSERT into PTOC(colname, . . . , colname) values (pkvalue, . . . , valn). 
     More details for adding the new entry is provided with respect to  FIG. 16 . In step  1102 , a primary key for the master table is generated. If the database automatically generates a primary key, then step  1102  is not performed. In step  1104 , the SVAL is created for class B attributes. In step  1106 , the key values for the class C attributes are obtained. For example a SELECT statement can be used: Select master-linked-column from mapped-column-table where mapped-column=cvalue. In step  1108 , attribute values for class A, B and C attributes are added to the master table. For example, the following INSERT statement adds a pkvalue for a class A attribute, a bvalue for a class B attribute or cvalue for a class attributre: INSERT into PTOC (Master-table primary-key, Mapped-column, Master-link-column) values (pkvalue, bvalue, cvalue). 
     In step  1110 , for the cases where the database automatically assigns a primary key for the master table, that primary key is obtained using a SELECT operation. In step  1112 , SELECT statements are executed to obtain the primary key values from the mapped-table for class D attributes. For example: SELECT master-linked-column FROM mapped-column-table WHERE master-linked-column=?. In step  1114 , the mapped-column value for class D attributes are updated, for example: UPDATE mapped-column-table SET mapped-column=dvalue Where master-linked-column=pkvalue. If the mapped-column value for the class E attributes doesn&#39;t exist, then insert it: INSERT into mapped-column-table(master-linked-column, mapped-column) values(pkvalue, dvalue). In step  1116 , the attribute values are inserted for class c attributes. For example: INSERT into mapped-column-table (mapped-column, master-linked-column) values (Evalue, pkvalue). 
     In step  1118 , the key values (fkeyvalues) for each class F attribute are obtained using, for example, a SELECT statement: SELECT mapped-table-link-column from mapped-column-table where mapped-column in (Fvalues). The key values (fkeyvalues) obtained are inserted into the table for master-linked-column using, for example, the following INSERT statement: INSERT into master-linked-column-table (mapped-table-linked-column, master-linked-column) values (FKeyValues, pkvalue). 
     In step  1120 , the master table is updated for class G attributes. For example: UPDATE master-table set master-link-column=pkvalue where master-table.primary-key in (Gvalues). In step  1122 , the key values (HkeyValues) are obtained for each class H attribute, for example, using a SELECT statement: SELECT master-table.primary-key from master-table where mapped-column in (Hvalues). The master table is then updated, for example, as follows: UPDATE master-table set master-link-column=pkvalue where master-table.primary-key in (HkeyValues). 12. If any of the above steps fail, then rollback the transaction; otherwise, commit the transaction in step  1124 . 
     To help explain the above, the following example is provided. Consider a request to add the following new entry: 
     
       
         
           
               
             
               
                 TABLE 8 
               
             
            
               
                   
               
               
                 Example 
               
            
           
           
               
               
               
               
            
               
                   
                   
                 Attribute 
                   
               
               
                   
                 Attribute 
                 Mapping Kind 
                 Value 
               
               
                   
                   
               
               
                   
                 ID 
                 A 
                 (generated by DB) 
               
               
                   
                 Name 
                 B 
                 Vikas 
               
               
                   
                 Dept. 
                 C 
                 Engineering 
               
               
                   
                 Manager 
                 C 
                 Joan 
               
               
                   
                 Projects 
                 F 
                 (id-XML SDK, performance) 
               
               
                   
                   
               
            
           
         
       
     
     In step  1104 , an SVAL is created that includes the following tuple (name, Vikas). In  1106 , the following SELECT statements are used to get the key values for the class C attributes: SELECT department.ID from department where name=‘engineering’ AND SELECT employee.ID from employee where employee.name=‘Joan’. In step  1108 , the following INSERT command is used: INSET into employee(Name,deptID, MgrID) values (‘vikas’, 2, 6), assuming that “2” was returned for the “SELECT department.ID” operation and “6” was returned for the “SELECT employee.ID” operation. In step  1110 , the primary key (assume it is 24) is obtained with the following SELECT statement: SELECT employee.ID from employee where employee.Name=‘vikas’ In step  1118 , the key values for the projects attribute is obtained with the following SQL statement: SELECT projects.ID from projects where projects.name in (‘id-XML SDK’, ‘performance’). Assuming that the result set is {2, 4}, the following INSERT statement are executed: INSERT into emp_projects(PID, EID) values (2, 24), INSERT into emp_projects(PID, EID) values (4, 24). 
     C. Delete 
       FIG. 17  is a flow chart describing a process for performing steps  606  and  610  of  FIG. 6  for a DELETE operation. In step  1202 , the primary key value in the master table for the entry being deleted is obtained. In some cases, the primary key value in the master table for the entry being deleted is provided in the LDAP DELETE request and step  1202  need not be performed. In other cases, the LDAP delete request will not include that primary key, but will uniquely identify the entry using a unique attribute (or attributes). When a unique attribute is provided, the primary key value in the master table for the entry being deleted is obtained using, for example, the following SQL statement:=SELECT masetr-table.primary-key from master-table where master-table.&lt;unique-column&gt;=?. 
     In steps  1204  and  1206  of  FIG. 17 , the master-link-column of H and G attributes are set to null using, for example, the following SQL statement: Update master-table set master-link-column=null where master-link-column=primary-key-value (for record being deleted). In step  1208 , values for class F attributes no longer needed are removed from the master-linked-column-table using, for example, the following SQL statement: DELETE from master-linked-column-table where master-linked-column=? Note that in some cases it may be desirable to not delete the class F attribute values. In step  1210 , values for class E attributes are removed from linking tables for values deleted from the master table using, for example, the following SQL statement: DELETE from mapped-table where master-linked-column=? Note that in some cases it may be desirable to not delete the class E (or other classes) attribute values. In step  1212 , the rows in the mapped table for the class D attributes are deleted using, for example, the following SQL statement: DELETE from mapped-column-table where master-linked-column=? In step  1214 , the row in the master table is deleted using, for example, the following SQL statement: DELETE Delete from master-table where master-table.primary-key=pkvalue—(pkvalue is from step  1202 ). If any of the above steps fail, then rollback the transaction; otherwise, commit the transaction in step  1216 . Note that class B attributes will be removed when the row for the primary key in the master table is deleted. Attribute values of class C will be unlinked from the entry being deleted upon such deletion. 
     D. Modify 
       FIG. 18  is a flow chart describing a process for performing steps  606  and  610  of  FIG. 6  for a MODIFY operation. In general, a LDAP MODIFY operation is translated to a SQL UPDATE operation. A primary key value or a unique attribute value(s) should be provided for update of an entry record. If the primary key value (pkvalue) is not provided, then it is obtained using the unique attribute. Updates of primary key values (attribute class A) are not allowed. Updates of class B attributes will include the addition of a tuple (mapped-column, value) into a SVAL for update of master-table. If update results in change of the unique attribute of the object class, then get the pkvalue for the object based on the old value of the unique attribute. Updates of class C attributes will result in updating the master-link-column with the master-linked-column value corresponding to the new mapped-column value. Updates of class D attributes will result in updating the mapped-column value corresponding to the pkvalue in the master-linked-column. 
     Updates of multi-valued attribute can result in change of membership. The old values will be removed and the new member will be added to the attribute value set. The operation context will have an old value set and a new value set. The deleted set and added set can be constructed from the old and new value set. Updates of class E attributes will result in deleting entries (pkvalue, deleted-e-value) for deleted values from the mapped-column-table and inserting entries (pkvalue, added-e-value) for added values. Updates of class F attributes will result in getting key values corresponding to deleted values and added F attribute values, deleting entries (pkvalue, deleted-f-key-value) for deleted values from the mapped-table-linked-column table, and adding entries (pkvalue, added-f-key-value) to the table. Updates of class G attributes will result in updating the master-link-column to null for all deleted G values (G values being removed) and updating the master-link-column to the pkvalue for added entries (G values being added). Updates of class H attributes will result in getting key values for deleted and added H values. Master-link-column values for old key values will be set to null and master-link-column values for new key values will be set to pkvalue. More details are provided below with respect to  FIG. 18 . 
     In step  1302  of  FIG. 18 , the primary key value in the master table for the entry being deleted is obtained. In some cases, the primary key value in the master table for the entry being deleted is provided in the LDAP delete request and step  1302  need not be performed. In other cases, the LDAP modify request will not include that primary key, but will uniquely identify the entry using a unique attribute (or attributes). When a unique attribute is provided, the primary key value in the master table for the entry being deleted is obtained using, for example, the following SQL statement:=SELECT master-table.primary-key from master-table where master-table.&lt;unique-column&gt;=? In step  1304 , new values for class B attributes are placed in a SVAL, and one or more UPDATE statements are executed. An example of a suitable UPDATE statement is: UPDATE master-table set mapped-column=newBvalue where master-table.primary-key=pkvalue. In step  1306 , at least two operations are performed. First, the key value for the new attribute value is obtained (e.g. obtain the key value for the employee&#39;s new Manager) using, for example, the SQL statement: SELECT master-linked-column from mapped-column-table where mapped-column=&lt;cvalue&gt;. Second, the master table is then updated using the key value obtained from the SELECT operation. For example, the following SQL statement can be used: UPDATE master-table set master-link-column=KeyValue_for_newCvalue where master-table.primary-key=pkvalue. In step  1308 , the mapped-table is updated for class D attributes using, for example, the following SQL statements: UPDATE mapped-table set mapped-column=Dvalue where master-linked-column=pkvalue. 
     In step  1310 , for each class E attribute, delete the-old evalues and pkvalue from the mapped column table and insert new evalues and pkvalue in the mapped column table using, for example, the following SQL statements: (1) DELETE from mapped-column-table where mapped-column=deleted-evalue and master-linked-column=pkvalue ; and (2) INSERT into mapped-column-table(mapped-column, master-linked-column) values (new-evalue, pkvalue). In step  1312 , for each class F attribute, get the key values (old and new) for the updated attribute, delete the old key values and pkvalue from the master-linked-column table, and insert new key values and pkvalue to the master-linked-column table. In one embodiment, step  1312  is performed using the following SQL statements: (1) SELECT mapped-table-link-column from mapped-table where mapped-column in (deleted-f-values); (2) SELECT mapped-table-link-column from mapped-table where mapped-column in (added-f-values); (3) INSERT into master-linked-column-table (mapped-table-linked-column, master-table-linked-column) values (added-f-keyvalue, pkvalue); and (4) DELETE from master-linked-column-table where mapped-table-linked-column=deleted-f-keyvalue and master-linked-column=pkvalue. 
     In step  1314 , for each class G attribute, update the master-link-column of master table to null for deleted gvalues and set the master-link-column to pkvalue for the added gvalues. In one embodiment, step  1314  is performed using the following SQL statements: (1) UPDATE master-table set master-link-column=null where master-table.primary-key in (deleted-g-values); and (2) UPDATE master-table set master-link-column=pkvalue where master-table.primary-key in (added-g-values). In step  1316 , for each class H attribute, get key values for deleted values and added (e.g., new) values, update the master table to set the master-link-column to null for deleted values and set the master-link-column to pkvalue for the added values. In one embodiment, step  1316  is performed using the following SQL statements: (1) SELECT master-table.primary-key from master-table where mapped-column in (deleted-h-values); (2) SELECT master-table.primary-key from master-table where mapped-column in (added-h-values); (3) UPDATE master-table set master-link-column=null where master-table.primary-key in (deleted-h-keyvalues); and (4) UPDATE master-table set master-link-column=pkvalue where master-table.primary-key in (added-h-keyvalues). If any of the above steps fail, then rollback the transaction; otherwise, commit the transaction in step  1318 . 
     IV. Partitioning 
     Step  602  of  FIG. 6  includes determining which data stores can service a particular data access request and step  604  includes sending that data access request to the appropriate translation modules corresponding to the appropriate data stores.  FIG. 19  provides a flowchart for performing steps  602  and  604  of  FIG. 6 . That is, the process described in  FIG. 19  includes determining which data store a particular access request is for and providing the request (or a portion of that request) to the translation module for that data store. The process of  FIG. 19  will first be described with respect to a search operation. Other operations will be described below. In one embodiment, any one profile will be stored within a single data store. That is, profiles are not split. In other embodiments, profiles can be split. 
     In step  1402  of  FIG. 19 , the access request is received. This corresponds to step  600  of  FIG. 6 . In step  1404 , one of the system&#39;s partition expressions is accessed. A partitioning expression is defined, generally, as criteria for defining what data is in a particular data store. In one embodiment, the partitioning expression is in LDAP filter format, with the attribute names being in the logical object class namespace. The partition expression can be a simple filter expression or a composite expression, where the composite expression is made up of multiple simple expressions combined by one or more logical operators. For example, consider a system that has two data stores, where one data store is used to store information about employees in the United States and the other data store is used to store information about employees in Europe. The partition expression for the first data store may be (region=United States) and the partition expression for the second data store may be (region=Europe). In one embodiment, a partition expression is created for each data store. For example, an administrator can manually create the partition expression, software can be used to automatically create the partition expression statically in advance or dynamically during use of the data store, or other means can be used to create the partition expression. 
     In step  1406 , that partition expression will be evaluated against the data access request. The partition expression is in LDAP filter format. The access request also includes an LDAP filter. The filters are compared. If the filters overlap (completely or partially), then the partition expression is satisfied (step  1408 ), and a partitioning module  422  will create a filter for the data store associated with the partition expression in step  1410 . That created filter will be provided to the appropriate translation module in step  1412 . In step  1414 , it is determined whether there are any more partition expressions to evaluate. If so, the process loops back to step  1404 , accesses the next partition expression and repeats steps  1406 - 1412 . If there are no more partition expressions to evaluate, the process of  FIG. 19  is finished. Note that in step  1408 , if the partition expression is not satisfied (e.g., because there is no overlap between the partition and the filter expression in the data access request), the process skips from step  1408  directly to step  1414 . 
     Note that if the partition expression is satisfied in step  1408 , a filter is created for the particular data store and that filter is provided to the appropriate translation module. That filter will then be translated as described above. The reason that a new filter is created in step  1410  is that, in some cases, a portion of the filter in the access request may not be appropriate for the particular data store. For example, if one or more terms of the data access request are not mapped to the particular data store, then those terms need to be removed from the filter expression. Thus, the new filter created in step  1410  will include most of the original filter but will remove the attributes that are not mapped. In some embodiments, when all attributes are mapped to the data store, step  1410  will just pass on the original filter from the data access request. 
     For example, consider two data stores: data store  1  and data store  2 . Data store  1  stores identity profiles that include the following three attributes: name, userID and password. Data store  2  stores identity profiles that include the following three attributes: name, salary and manager. The partition expression for data store  1  may be, for example, (name=s*), indicating that data store  1  always stores identity profiles of people whose name starts with a “s.” The partitioning expression for data store  2  may be, for example, NOT (name=s*), indicating that identity profiles for those people whose names do not start with an “s” are stored in data store  2 . The system may also include other data stores. Assume that an access request is received that includes a filter that indicates, for example, AND [OR (name=Sam) (name=Albert)][OR (userid=s*) or (salary&gt;1000)]. In the above case, the filter overlaps with both partition expressions; therefore, steps  1410  and  1412  will be performed for both data store  1  and data store  2 . However, when creating the filter for step  1410 , the original filter will be truncated to only include those attributes mapped to the appropriate data store. For example, the output filter in step  1410  for data store  1  will be (AND(name=Sam)(userid=s*)). The filter from step  1410  for data store  2  will be (AND(name=Al)(salary&gt;1000)). 
       FIG. 20  is a flowchart describing one embodiment of a process for evaluating a partition expression against a data access request (see step  1406  of  FIG. 19 ). In step  1440 , a filter expression tree is created from the filter expression of the data access request. For example,  FIG. 10A  provides an example of a filter expression tree. In step  1442 , a partition expression tree is created from the partition expression. Step  1442  is carried out in a similar manner to step  1440 . Thai is, a partition expression is similar to a filter expression in that both are in LDAP filter formats. Thus, both are used to create an expression trees in the same manner.  FIG. 21  provides an example of a partition expression tree for the following partition expression: NOT (AND(country=US)(department=sales)). In step  1444 , the mapped attributes of the filter and partition expressions are accessed. If these attributes have already been mapped in the Mapping Catalog, then the data from the Mapping Catalog can be accessed. In step  1446 , a partition function is called. This partition function includes three parameters: the filter expression tree (FT), the partition expression tree (PT), and the mapped attributes (MA). Note that  FIG. 20  is performed for one filter expression tree and one partition expression tree. For each partition expression, the process of  FIG. 20  will be performed. 
       FIG. 22  is a flowchart describing one embodiment of a process for performing a partition function (see step  1446  of  FIG. 20 ). In step  1480 , it is determined what type of expressions the filter expression and partition expression are. If both the filter expression and the partitioning expression are simple expressions, then the process continues at step  1482 . A simple expression is in the form (attribute&lt;operator&gt;value). In step  1482 , it is determined whether the attribute of the filter expression is mapped to the data store corresponding to the partition expression. That is, the system determines whether the particular attribute in the filter expression resides in the mapping catalogue for the data store. If it is not mapped, then the filter expression is marked as being invalid in step  1484 . If the attribute is mapped, then in step  1486  it is determined whether the attributes in the filter expression and the partition expression are the same. If they are different, the filter expression is marked as true because it is possible that the expressions overlap. If the attribute in the filter expression is the same as the attribute in the partition expression, then table 9 is used to determine whether there is an overlap condition. If there is an overlap condition, then the filter expression is marked as true. If there is no overlap, then the filter expression is marked as false. For example, if the partition expression says (SALARY&gt;1000) and the filter expression says (SALARY=5000), then there is overlap and the filter expression is marked as true in step  1490 . 
     
       
         
           
               
             
               
                 TABLE 9 
               
             
            
               
                   
               
               
                 Do Simple expressions overlap? 
               
            
           
           
               
               
               
               
            
               
                   
                 Partition expression 
                 Filter expression 
                 Overlap condition 
               
               
                   
                   
               
               
                   
                 a = k1 
                 a = k2 
                 (k1 = k2) 
               
               
                   
                 a = k1 
                 A &gt;= k2 
                 (k1 &gt;= k2) 
               
               
                   
                 a = k1 
                 A &lt;= k2 
                 (k1 &lt;= k2) 
               
               
                   
                 a &gt;= k1 
                 a = k2 
                 (k1 &lt;= k2) 
               
               
                   
                 a &gt;= k1 
                 A &gt;= k2 
                 True 
               
               
                   
                 a &gt;= k1 
                 A &lt;= k2 
                 (k1 &lt;= k2) 
               
               
                   
                 a &lt;= k1 
                 a = k2 
                 (k1 &gt;= k2) 
               
               
                   
                 a &lt;= k1 
                 A &gt;= k2 
                 (k1 &gt;= k2) 
               
               
                   
                 a &lt;= k1 
                 A &lt;= k2 
                 True 
               
               
                   
                   
               
            
           
         
       
     
     If, in step  1480 , it is determined that the filter expression is simple and the partition expression is a composite expression (made up of multiple simple expressions joined together by one or more operators), then the partition function (the process in  FIG. 22 ) is called with reverse parameters in step  1492 . That is, the partition function is called as P(PF, FT, MA) rather than P(FT, PT, MA). When this is done, the partition function knows to transfer any markings of invalid, true and false, from the partition expression tree to the filter expression tree. 
     If, in step  1480 , it is determined that the filter expression is a composite expression, then in step  1496 , the system recursively recalls the partition function (the process of  FIG. 22 ) for each child sub-filter of the current level of the filter. For example, if a filter is made up of the following sub-filters: (name=Sam) OR (name=Al), the first child sub-filter is (name=Sam) and the second child sub-filter is (name=Al). Step  1496  will include calling the partition function first for the child sub-filter (name=Sam) and then for the child sub-filter (name=Al). In step  1498 , the results from recursively calling the partition function for the child sub-filters will be combined, as explained below. 
       FIG. 23  is a flowchart describing one embodiment of a process for combining the results when calling the partition function for multiple child sub-filters (see step  1498  of  FIG. 22 ). The input to the process of  FIG. 23  will be the filter expression tree with each of the child nodes being marked true, false or invalid. In step  1530 , it is determined whether the operator for the relationship among the child filters is “AND,” “OR,” or “NOT.” If the operator is “AND,” then the process continues at step  1532 . In step  1532 , if any of the child sub-filters are marked as false, then the node under consideration (the node that operates on the sub-filters) is marked as false. In step  1534 , if none of the child sub-filters were marked as false, then it is determined whether any of the sub-filters were marked as invalid in step  1536 . If any of the sub-filters were marked as invalid, the node under consideration is marked as invalid in step  1538 . If none of the sub-filters were marked as invalid, then the node under consideration is marked as true in step  1540 . 
     If, in step  1530 , it is determined that the logical operator for the current node is “NOT,” then the process continues at step  1550 . In the case where the logical operator is “NOT,” there is likely to be one child sub-filter. If that child sub-filter is marked as true (step  1550 ), then the node under consideration is also marked true in step  1552 . Otherwise, it is determined whether the sub-filter is marked as false in step  1554 . If the sub-filter is marked as false, then the node under consideration is marked true in step  1556 . If the sub-filter is not marked as false, then the node is marked as invalid in step  1558 . 
     If, in step  1530 , it is determined that the operator for the current node is “OR,” then the process continues as step  1570 . If any of the sub-filters are marked true, then the node under consideration is also marked true in step  1572 . Otherwise, if all of the sub-filters are invalid (step  1574 ), then the node is marked as invalid in step  1576 . If all of the sub-filters are not marked invalid in step  1574 , then the node is marked as false in step  1578 . Note that when generating the filter expressions in step  1410 , in one embodiment, only the “true” nodes will need to be translated to datasource specific namespace. Except in the case of filter nodes under a “NOT” node, all of the invalid nodes are not translated to datasource specific name spaces. Note that OR/AND nodes will not generate corresponding OR/AND operator datasource specific filters if it only has one child marked true, only the child node will generate the datasource specific filter. 
     The above process is primarily used for search operations. If the data access request is a DELETE or MODIFY operation, then it is likely to be commenced by first performing a SELECT statement (e.g., a search) followed by the various DELETES and/or UPDATES. In that case, the search operation (the SELECT) is subjected to the process of  FIG. 19 . When the UPDATES and/or DELETES are performed, they already know which data stores to use. In the event that the delete or modify operation does not require a search, the system can perform a select statement, thereby forcing the performance of the process of  FIG. 19 . 
     For an ADD operation, the partitioning module can be provided all of the attributes. The partitioning module can then compare the attributes of the ADD operation to the attributes of the various partition expressions, as explained above, and determine which data store the profile should be added to. That is, the attributes can be used to create a filter expression tree which can be created as part of step  1440  of  FIG. 12  and compared to partition functions in order to determine which data store the data should be stored into. 
     Consider the following example with three data stores. The following table indicates the attributes mapped into each data store and the partition expression for each data store. 
     
       
         
           
               
             
               
                 TABLE 10 
               
             
            
               
                   
               
               
                 Example 
               
            
           
           
               
               
               
               
            
               
                   
                 Data Store 
                 Mapped Attributes 
                 Partition Expression 
               
               
                   
                   
               
               
                   
                 P1 
                 x1, x2, x3 
                 (x1 &lt;= 2) 
               
               
                   
                 P2 
                 x1, x2, x4 
                 AND (x1 &gt;= 3)(x1 &lt;= 20) 
               
               
                   
                 P3 
                 x1, x2, x3, x4 
                 (x1 &gt;= 21) 
               
               
                   
                   
               
            
           
         
       
     
     The following is the filter expression for a data access request: Ft=(and(x1&lt;=6)(x2=5)). For data store P1, the partition function is called as follows: partition (Ft, (x1&lt;=2), MA=[x1, x2, x3]). The filter is a composite filter. Thus, step  1496  includes recursively recalling the partition function for sub-filter (x1&lt;=6) and sub-filter (x2=5). For the first sub-filter (x1&lt;=6), the attributes in the sub-filter expression and the partition expression are the same, so step  1490  is performed. The sub-filter is marked true based on Table 9 because there is partial overlap. For the second sub-filter, the attributes are different and, thus, the sub-filter is marked as true in step  1488 . After recursively recalling the partition function twice, the results are combined in step  1498 , which includes marking the entire filter as true in step  1540 . 
     For data store P2, the partition function is called as follows: partition (Ft, PT, MA), where MA=[x1, x2, x4) and PT=AND(x1&gt;=3) (x1&lt;=20). Because Ft is a composite, step  1496  is performed. The partition function is recalled recursively for both child sub-filters in step  1496 . When the partition function is called for the first child filter, step  1480  determines that the partition function was called for a simple filter expression (the child filter) and a composite partition expression. Thus, step  1492  is performed which includes calling a partitioning function again but switching the filter expression and the partition expression. For example, P([AND(x1&gt;=3)(x1&lt;=20)], (x1&lt;=6), MA). 
     For the third data store P3, the partition expression is (x1&gt;=21). The composite expression for the filter causes the process to perform step  1496  and recursively call the partition function for each of the child sub-filters. The first child sub-filter is compared against the partition expression to determine if there is overlap. It is determined that (x1&lt;=6) and (x1&gt;=21) do not overlap in step  1490 ; therefore, the node is marked as false. When the partition function is called for the second child sub-filter in step  1486 , it is determined that the attributes of the second child sub-filter are different than the partition expression; therefore, the second sub-filter (x2=5) is marked as true in step  1488 . When the composite is determined by combining the results for child sub-filters in step  1498 , step  1534  marks the composite as false because one of the sub-filters is false. Therefore, the filter FT does not qualify for the partition expression and the filter will not be sent to the translation module for data store P3. 
     The foregoing detailed description of the invention has been presented for purposes of illustration and description. It is not intended to be exhaustive or to limit the invention to the precise form disclosed. Many modifications and variations are possible in light of the above teaching. The described embodiments were chosen in order to best explain the principles of the invention and its practical application to thereby enable others skilled in the art to best utilize the invention in various embodiments and with various modifications as are suited to the particular use contemplated. It is intended that the scope of the invention be defined by the claims appended hereto.