EP0963576A2 - Verfahren zur bestimmung der sichtverhältnisse auf mehrfache datenbanktransaktionen für einen ferndatenbank-kunden - Google Patents

Verfahren zur bestimmung der sichtverhältnisse auf mehrfache datenbanktransaktionen für einen ferndatenbank-kunden

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Publication number
EP0963576A2
EP0963576A2 EP98908694A EP98908694A EP0963576A2 EP 0963576 A2 EP0963576 A2 EP 0963576A2 EP 98908694 A EP98908694 A EP 98908694A EP 98908694 A EP98908694 A EP 98908694A EP 0963576 A2 EP0963576 A2 EP 0963576A2
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EP
European Patent Office
Prior art keywords
visibility
node
docking
database
row
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Withdrawn
Application number
EP98908694A
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English (en)
French (fr)
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EP0963576A4 (de
Inventor
Robert S. Brodersen
Peter S. Lim
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Siebel Systems Inc
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Siebel Systems Inc
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Filing date
Publication date
Application filed by Siebel Systems Inc filed Critical Siebel Systems Inc
Publication of EP0963576A2 publication Critical patent/EP0963576A2/de
Publication of EP0963576A4 publication Critical patent/EP0963576A4/de
Withdrawn legal-status Critical Current

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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/27Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor

Definitions

  • This invention relates to a system and method for providing updates to a network of partially replicated relational database systems, and, more particularly, for providing an efficient means for computing the visibility to a client on the network of a transaction processed against the database.
  • Relational databases are a commonly-employed data structure for representing data in a business or other environment.
  • a relational database represents data in the form of a collection of two-dimensional tables. Each table comprises a series of cells arranged in rows and columns. Typically, a row in a table represents a particular observation. A column represents either a data field or a pointer to a row in another table.
  • a database describing an organizational structure may have one table to describe each position in the organization, and another table to describe each employee in the organization.
  • the employee table may include information specific to the employee, such as name, employee number, age, salary, etc.
  • the position table may include information specific to the position, such as the position title ("salesman", "vice president", etc.), a salary range, and the like.
  • the tables may be related by, for example, providing in each row of the employee table a pointer to a particular row in the position table, coordinated so that, for each row in the employee table, there is a pointer to the particular row in the position table that describes that employee's position.
  • RDBMS relational database management system
  • Relational databases may be much more complex than this example, with several tables and a multiplicity of relations among them.
  • One disadvantage is that a full copy of the central database may require more data storage than is desired or economical. For example, a salesman working in the field may need to refer to the database for information regarding sales opportunities in his sales area, but have no need to refer to any information regarding sales opportunities outside of his area.
  • One possible approach to reduce the amount of required data storage is to simply replicate only that portion of the database that is needed by the user.
  • this approach does not recognize that the criteria to determine which portions of the data are required is likely to vary over time. For example, the salesman may have a new city added to his territory. Under conventional approaches, the salesman would need to re-replicate his local copy of the database, this time selecting data including the added city. Such a practice is inconvenient, subject to error, and time-consuming.
  • a further disadvantage to a replicated database is the difficulties encountered in attempting to update data using the replicated copy.
  • a change made to the replicated database is not made to the central database, leading to a discrepancy between the information that is stored in the replicated copy of the database and the information that is stored in the central database.
  • journal modifications made to the replicated copy and apply an identical modification to the central database, one problem that this approach faces is the possibility of colliding updates; that is, where a user of a replicated copy makes a change to data that is also changed by a user of the central copy or by the user of another replicated copy.
  • the present invention is directed to a method of maintaining a partially replicated database in such a way that updates made to a central database, or to another partially replicated database, are selectively propagated to the partially replicated database. Updates are propagated to a partially replicated database if the owner of the partially replicated database is deemed to have visibility to the data being updated. Visibility is determined by use of rules, e.g., dynamic rules or predetermined rules, stored in a rules database. In one aspect of the invention, the stored rules are assessed against data content of various tables that make up a logical entity, known as a docking object, that is being updated.
  • rules e.g., dynamic rules or predetermined rules
  • the stored rules are assessed against data content of one or more docking objects that are not necessarily updated, but that are related to a docking object being updated.
  • the visibility attributes of the related docking objects are recursively determined.
  • changes in visibility are determined to enable the central computer to direct the nodes to insert the docking object into its partially replicated database. Such changes in visibility are determined so as to enable the central computer to direct a node to remove a docking object from its partially replicated database.
  • the predetermined rules are in declarative form and specify visibility of data based upon structure of the data without reference to data content.
  • the transactions made to the database are ordered and processed in such a way as to reduce the computational resources required to calculate the visibility of the transactions.
  • the transactions made to the database are ordered and processed using a cache in such a way as to reduce the computational resources required to calculate the visibility of the transactions.
  • database objects and transactions have an associated visibility strength used to determine the visibility of a transaction to an object.
  • the visibility calculations are performed using a simplified set of rules located in a central dictionary.
  • Figure 1 depicts an overview of the operation of one embodiment of the present invention.
  • Figure 2 depicts a database schema that shows the relationship of the various components that make up a Docking Object.
  • Figure 3 depicts steps performed by an update manager to update a database.
  • Figure 4 depicts steps performed by a Docking Manager to transmit and/or receive one or more transaction logs.
  • Figure 5 depicts the steps performed by a merge processor to merge transaction log records into an existing database.
  • Figure 6 depicts the steps performed by a log manager to prepare a partial transaction log.
  • Figure 7 depicts the steps performed by a visibility calculator for calculating visibility for a docking object as invoked by a log manager.
  • Figure 8 depicts the steps performed to synchronize a partially replicated database in response to a change in data visibility.
  • Figure 9 depicts the structure of the database design of the transaction log table.
  • Figure 10 depicts a database diagram for the central dictionary.
  • Figure 1 depicts an overview of the operation of one embodiment of the present invention.
  • Figure 1 depicts a central computer system 1 and three remote computer systems (or “nodes") 21-a, 21-b, and 21-c.
  • Each of nodes 21-a, 21-b and 21-c are depicted in various states of commumcation with central computer system 1 , as will be more fully explained.
  • Central computer system 1 includes a central database 3, a docking manager 5, a merge processor 7 and a log manager 9.
  • Central computer system 1 additionally optionally includes update manager 11 responsive to user input 13.
  • Node 21-a is a remote computer system, such as a mobile client such as a laptop computer.
  • Node 21-a includes a partially replicated remote database 23-a, update manager 31-a responsive to user input 33-a, docking manager 25-a and merge manager 27-a.
  • update manager is responsive to user input 33-a to make changes to remote database 23-a as directed by the operator of node 21-a. Updates made are recorded, or journaled, in node update log 35-a.
  • node docking manager 35-a is activated, and enters into commumcation with central docking manager 5.
  • Update log 35-a is taken as input by node docking manager 25- a, and provided to central docking manager 5.
  • Central docking manager 5 creates a received node update log 19, which contains all the information that had been recorded in update log 35-a.
  • partial log 17-a is taken as input by central docking manager 5 and provided to node docking manager 25-a, as more fully described herein.
  • merge processor 7 is activated.
  • Merge processor 7 takes as input received node update log 19, and applies the updates described therein to central database 3.
  • merge processor journals the updates applied to central update log 15.
  • update manager 11 responsive to user input 12 makes additional changed to central database 3 as directed by the operator of central computer system 1.
  • the updates made by update manager 11 are additionally journaled in central update log 15.
  • log manager 9 is activated.
  • Log manager 9 takes as input central update log 15 and produces as output a set of partial logs 17-a, 17-b and 17-c according to visibility rules as will be further described herein.
  • Each of partial logs 17-a, 17-b and 17-c corresponds to one of nodes 21-a, 21-b and 21-c.
  • central docking manager 5 takes as input the appropriate partial log, such as partial log 17-a, and presents it to node docking manager 25-a.
  • Node docking manager 25-a then replicates partial log 17-a as merge log 37-a.
  • merge processor 27-a is activated.
  • Merge processor 27-a takes as input merge log 37-a, and applies the updates described therein to partially replicated database 23-a.
  • Figure 1 also depicts two additional nodes 21-b and
  • Node 21-b is depicted in commumcation with central computer 1.
  • the operator of node 21-b has requested only to send his updates to central computer system 1, and has not requested to be presented with changes made elsewhere to be made to his partially replicated database 23-b. This may be, for example, if the operator has an urgent update that must be made as soon as possible, but does not have the time to receive updates from other nodes.
  • Figure 1 shows only transmission of node update log 35-a from node docking manager 25-b to central docking manager 5, and no transmission from central docking manager 5 to node docking manager 25-b. Accordingly, the merge manager for node 21-b is not activated and is not shown.
  • node 21-c is depicted as not in commumcation with central computer system 1. Accordingly, the docking manager for node 21-c is not activated and is not shown.
  • a Docking Object consists of Member Tables (including one Primary Table), Visibility Rules, Visibility
  • Each docking object has a Visibility Level and Visibility Level attributes as will be described more fully hereinbelow.
  • each member table row can have one or more rows that correspond to the docking object.
  • a Member Table is a table of the relational database that makes up a docking object.
  • the propagation takes the form of an insertion into each of the Member Tables associated with the particular docking object.
  • that removal consists of deleting records from the member tables associated with the docking object.
  • a docking object that represents a sales opportunity may include tables that represent the opportunity itself (e.g., named "S OPTY”), the product whose sale is represented by the opportunity (e.g., named "S OPTY PROD”), the contact for the opportunity (e.g., named "S OPTY CONTACT”), etc.
  • S OPTY the opportunity itself
  • S OPTY PROD the product whose sale is represented by the opportunity
  • S OPTY CONTACT the contact for the opportunity
  • each member table row can have one or more rows that correspond to the docking object.
  • a Primary Table is a Member Table that controls whether a particular instance of a Docking Object is visible to a particular node.
  • the Primary Table has a Primary Row-ID value that is used to identify a row of the Primary Table being updated, deleted or inserted.
  • the "Opportunity Docking Object" may have as a primary table the table S_OPTY.
  • the row-id of that table, i.e., S OPTY.row id, is the Primary Row-ID for the Opportunity Docking Object.
  • Each dock object has a visibility level and a visibility level attribute that are analyzed using visibility rules.
  • the valid values are 'Enterprise', 'Limited' and 'Private'. All member table rows in an enterprise dock object are replicated to any nodes. Member table rows in limited dock objects are replicated to any nodes. Member table rows in limited dock objects are subject to visibility checks and are routed to nodes that have visibility to the rows.
  • a Visibility Rule is a criterion that determines whether a particular instance of a Docking Object is "visible" to a particular node 21. If a Docking Object is visible to a particular node, that node will receive updates for data in the Docking Object.
  • Visibility Rules are of two types, depending on the field RULE TYPE.
  • a Visibility Rule with a RULEJTYPE of "R” is referred to as an SQL Rule.
  • An SQL Rule includes a set of Structured Query Language (SQL) statements that is evaluated to determine if any data meeting the criteria specified in the SQL statements exists in the Docking Object. If so, the Docking Object is visible to the node.
  • a Visibility Rule with a RULE_TYPE of "O” is referred to as a Docking Object Rule.
  • a Docking Object Rule specifies another Docking Object to be queried for visibility. If the specified Docking Object is visible, then the Docking Object pointing to it is also visible.
  • a Related Docking Object is a Docking Object that is propagated or deleted when the Docking Object under consideration is propagated or deleted.
  • an Opportunity Docking Object may have related Docking Objects representing the sales contacts, the organizations, the products to be sold, and the activities needed to pursue the opportunity.
  • an Opportunity Docking Object is propagated from Central Database 3 to one of node databases 23, the related docking objects are also propagated.
  • Figure 2 depicts a database schema that shows the relationship of the various components that make up a Docking Object.
  • the schema is a meta-database, in that it does not describe the data being accessed in the database. Rather, the schema is a separate database that defines the structure of the database being accessed. That is, it is a database comprising tables that describe the relationships and data contexts of another database.
  • Each of the tables shown in Figure 2 is a table in a relational database, and as such is in row-column form. Many columns represent fields that are common to all the illustrated tables. Such fields include for example, a ROW ID to identify a particular row in the table, as well as fields to track the date and time that a row was created and last modified, and the identity of the user who created or modified the row. In addition, each table contains fields specific to that table, and which are described in detail below.
  • Table S DOBJ 61 describes the Docking Objects in an application.
  • Table S_DOBJ 61 includes the fields OBJ_NAME and PRIMARY_TABLE_ID. Field
  • OBJ NAME defines the name of the Docking Object being described.
  • Table S DOBJ INST 63 describes whether a particular instance of a Docking
  • Table S_DOBJ_INST 63 includes the fields NODE D, DOBJ_ID and PR_TBL_ROW_ID.
  • Field NODE ID points to a particular node table 65.
  • Field DOBJ ID points to the Docking Object to which the Docking Object instance applies.
  • Field PR TBL ROW ID is used to select a particular row in the Primary Table of the Docking Object. This value identifies the Docking Object instance.
  • Table S REL DOBJ 67 describes the related Docking Objects of a particular Docking Object, described by table S DOBJ 61.
  • Table S REL DOBJ 67 includes the fields DOBJ ID, REL DOBJ ID, and SQL_STATEMENT.
  • Field DOBJ ID identifies the Docking Object that owns a particular related Docking Object.
  • Field REL DOBJ ID identifies the related Docking Object that is owned by the Docking Object identified by DOBJ ID.
  • Field SQL STATEMENT is an SQL statement that may be executed to obtain the Primary ID value of the related Docking Object.
  • Table S DOBJ TBL 69 describes the member tables of a particular Docking Object, described by table S_DOBJ 61.
  • Table S_DOBJ_TBL 69 includes the fields DOBJ D, TBL ID, and VIS_EVENT_FLG.
  • Field DOBJ ID identifies the Docking Object that contains the member table described by the row.
  • Field TBL ID identifies the particular table in the database that is the member table described by the row.
  • Field VIS EVENT FLG is a flag that indicates whether a change to this Docking Object can result in a visibility event. A value of "Y" indicates that a change can result in a visibility event; a value of "N" indicates that it cannot.
  • Table S DOBJ VIS RULE 71 contains the visibility rules associated with a particular Docking Object.
  • S DOBJ VIS RULE 71 contains the fields DOBJ ID, RULE SEQUENCE, RULEJTYPE, SQL STATEMENT and CHECK_DOBJ_ID.
  • Field DOBJ ID identifies the Docking Object with which a particular visibility rule is associated.
  • Field RULE SEQUENCE is a sequence number that indicates the sequence, relative to other visibility rules in table S DOBJ VIS RULE 71, in which the particular visibility rule should be run.
  • RULE TYPE specifies whether the particular visibility rule is of type "R,” indicating an SQL visibility rule or of type "O,” indicating a Docking Object visibility rule.
  • Field CHECK DOBJJD specifies a docking object whose visibility should be determined. If the specified docking object is deemed to be visible, then the docking object associated with the visibility rule is also visible.
  • Field SQL STATEMENT contains a SQL statement that, when executed, returns the Row-ID of the docking object identified by CHECK DOBJJD that corresponds to the docking object instance associated with the visibility rule.
  • Table S APP TBL 73 is an Application Table that describes all the tables used in a particular application. It is pointed to by table S DOBJ TBL 69 for each member table in a docking object, and by table SJDOBJ for the primary table in a docking object. S_APP_TBL 73 points to table S_APP_COL 75, which is an
  • S APP TBL 73 points to table S_APP_COL 75 directly through a primary key and indirectly through such means as a Foreign Key Column Table 81, User Key Column Table 83, and Column Group Table 85.
  • Foreign Key Column Table 81 User Key Column Table 83
  • Column Group Table 85 The relationship of an Application Table, Application Column Table, Foreign Key Column Table, User Key Column Table and Column Group Table are well known in the art and are not further described.
  • Figure 3 depicts steps performed by an update manager 31 such as update manager 31 -a, 31-b or 31-c in updating a database, such as a node database 23-a, 23- b or 23-c, responsive to user input.
  • Execution of update manager 31 begins in step 101.
  • the update manager 31 accepts from the user input 33 in the form of a command requesting that the data in database 23 be altered.
  • the request may be in the form of a request to delete a row of a table, to add a row to a table, or to change the value of a cell at a particular column of a particular row in a table.
  • step 105 using a well-known means, the update manager 31 applies the requested update to database 23.
  • the update manager 31 creates a log record describing the update and writes it to update log 35.
  • Each log record indicates the node identifier of the node making the update, an identification of the table being updated, and an identification of the type of update being made, i.e., an insertion of a new row, a deletion of an existing row, or an update to an existing row.
  • the log record additionally includes an identifier of the row being inserted, including its primary key and the values of the other columns in the row.
  • the log record identifies the primary key of the row being deleted.
  • the log record identifies the primary key of the row being updated, the column within the row being updated, the old value of the cell at the addressed row and column, and the new value of the cell.
  • the update processor After writing a log record in step 107, the update processor exits for this update.
  • the foregoing description of the update processing preferably includes additional steps not material to the present invention, for example, to assure authorization of the user to make the update, to stage and commit the write to the database to allow for rollback in the event of software or hardware failure, and the like. These steps are well-known in the art and are not described further.
  • An update manager 11 executing in central computer system 1 operates in an analogous manner, except that it updates central database 3 and writes its log records to central update log 11.
  • FIG 4 depicts steps performed by a Docking Manager 25 such as Docking Manager 25-a, 25-b or 25-c to transmit and/or receive one or more transaction logs.
  • Docking Manager 25 is invoked by the user of a remote node such as node 21-a, 21-b or 21-c, whereby the user requests that the node dock with central computer 1 to upload an update log such as update log 35-a to central computer 1, to download a partial log such as partial log 17-a, or both.
  • Execution of Docking Manager 25 begins in step 121.
  • Docking Manager 25 connects with central computer 1 under the control of Central Docking Manager 5. This connection can be any connection that enables data exchange.
  • Step 125 checks to see whether the user has requested that node update log 35-a be uploaded to the Central Computer 1. If so, execution proceeds to step 127. If not, step 127 is skipped and control is given to step 129. In step 127, Docking Manager 25 uploads its update log to central computer 1. The upload may be accomplished with any known file transfer means, such as XMODEM, ZMODEM, KERMIT, FTP, ASCII transfer, or any other method of transmitting data.
  • file transfer means such as XMODEM, ZMODEM, KERMIT, FTP, ASCII transfer, or any other method of transmitting data.
  • step 129 Docking Manager 25 checks to see whether the user has requested that a partial log such as partial log 17-a be downloaded from Central Computer 1. If so, execution proceeds to step 131. If not, step 131 is skipped and control is given to step 133. In step 131, Docking Manager 25 downloads its partial log from central computer 1. The download may be accomplished with any known file transfer means, such as XMODEM, ZMODEM, KERMIT, FTP, ASCII transfer, or any other method of transmitting data. In step 133, having completed the requested data transfer, Docking Manager 25 exits.
  • Merge processing is performed by a processor such as node merge processor 27-a, 27-b, or 27-c, or central merge processor 7.
  • the merge process serves to update its associated database with a transaction that has been entered by a user of a computer remote from the computer where merge processing is being performed.
  • Merge processing is analogous to update processing and is similar in form to update processing as previously disclosed with reference to figure 3, with three differences.
  • the input to a merge processor is not an update entered directly by a user, but rather is a log file that is obtained from a computer remote from the computer where the merge is executing.
  • a second difference is that, as shown by in Figure 1 , merge processing does not produce a log when performed at a node.
  • the function of a log on a node is to record a transaction for propagation to Central Computer system 1 and thence to other nodes as required.
  • a transaction that is the subject of a merge in a node has been communicated to Central Computer System 1 , and there is no need to re-communicate it.
  • a third difference is that merge processing must be capable of detecting and resolving multiple conflicting transactions. For example, assume that a field contains the value "Keith Palmer.” Assume further that a user at node 27-a enters a transaction to update that field to "Carl Lake,” and a user at node 27-b enters a transaction to update the same field to "Greg Emerson. " Without collision detection, data among various nodes may become corrupt.
  • merge processing must also have a means of detecting collisions and correcting them.
  • a simple way to detect and correct a collision is to compare the value in the database to the value that the merge log reflects as being the previous value in the node database. If the two values do not match, Merge processor 7 may reject the transaction and generate a corrective transaction to be sent to the node from which the conflicting transaction originated.
  • merge processor 7 would compare "Keith Palmer,” the prior value of the field as recorded by node 27-b to "Carl Lake,” the present value of the field as recorded in central database 3. Detecting the mismatch, merge processor 7 may then generate a transaction to change the value "Greg Emerson" to "Carl Lake,” and write that transaction to update log 15.
  • collisions include, for example, an update to a row that has previously been deleted, inserting a row that has previously been inserted, and the like. Merge processing must detect and correct each of these collisions. This may be performed using any of a number of well-known methods, and is not discussed further.
  • Figure 5 depicts the steps performed by merge processor such as central merge processor 7. Although it depicts merge processor 7 writing to central database 3 and to transaction log 15, it is equally representative of a node merge processor such as node merge processor 27-a, 27-b or 27-c updating a node database 23-a, 23-b or 23- c.
  • Merge processing begins at step 141.
  • merge processor 7 finds the first unprocessed transaction on received log 19.
  • merge processor 7 selects a transaction from received log 19.
  • merge processor 149 attempts to update database 3 according to the transaction selected in step 147.
  • merge processor 7 determines whether the database update of step 149 failed due to a collision.
  • step 153 merge processor proceeds to step 153, which generates a corrective transaction. Following the generation of the corrective transaction, the merge processor returns to step 149 and again attempts to update database 3. If no collision was detected in step 151, execution proceeds to step 157.
  • step 157 merge processing checks to see if it is executing on central computer 1. If so, step 155 is executed to journal the transaction to log 15. In any case, either if step 157 determines that the merge processing is being performed on a node or after step 155, execution proceeds to step 159. Step 159 checks to see if any transactions remain to be processed from log 19. If so, execution repeats from step 147, where the next transaction is selected. If not, merge processing exits in step 161.
  • Figure 6 depicts the steps to be performed by log manager 9 to prepare a partial transaction log such as partial transaction log 17-a, 17-b, or 17-c.
  • the procedure depicted in Figure 6 is executed for each node available to dock with central computer system 1.
  • Log manager 9 begins execution in step 171.
  • Log Manager 9 finds the first unprocessed transaction for the node whose partial transaction log is being prepared.
  • log manager 9 selects a transaction for processing.
  • step 177 log manager 9 checks to see whether the selected transaction originated on the same node for which processing is being performed. If so, there is no need to route the transaction back to the node, and control proceeds to step 179.
  • Step 179 checks to see whether there are any transactions remaining to be processed. If so, control is given again to step 175.
  • step 189 which records the last transaction that was processed for this node, and then exits at step 191. If the transaction originates in other than the same node as the node for which processing is being performed, control is given to step 181.
  • Step 181 calls a visibility calculator to determine whether the selected transaction is visible to the node being processed. The Visibility calculator routine is described in detail further herein.
  • step 183 log manager 9 checks to see whether the visibility calculator determined that the transaction is visible. If it is not visible, control is passed to step 179, which performs as disclosed above. If the transaction is visible, control is passed to step 185. Step 185 writes a record for this transaction to the partial transaction log for the node being processed, for example, partial transaction log 17-a for node 21-a.
  • step 187 the log manager 9 records the last transaction that was processed for this node, and then passes control to step 179, which determines whether to select additional transactions or exit, as disclosed above.
  • Figure 7 depicts a flowchart describing the process a visibility calculator for calculating visibility for a docking object as invoked by step 181 of log manager 9.
  • the visibility calculator is called with the node-id of the node for which visibility is being calculated, the docking object for which the visibility is being calculated, and the row-id of the docking object whose visibility id being calculated.
  • the visibility calculator uses this information, in conjunction with information obtained from metadata stored in the schema depicted in Figure 2, to determine whether a particular transaction that updates a particular row of a particular docking object is visible to a particular node.
  • the Visibility calculator begins execution at step 201.
  • the visibility calculator makes a default finding that the transaction is not visible. Therefore, unless the visibility calculator determines that a transaction is visible, it will exit with a finding of no visibility.
  • the visibility calculator selects the first visibility rule associated with the docking object. This is done by finding the table S DOBJ VIS RULE 71 associated with the current Docking Object as pointed to by table S_DOBJ 61.
  • the visibility calculator selects the row of table S_DOBJ VIS RULE 71 with the lowest value for field RULE SEQUENCE.
  • step 207 the Visibility Calculator checks the field RULE TYPE for a value of "R."
  • the value of "R" indicates that the rule is a SQL visibility rule. If so, the Visibility Calculator proceeds to step 209.
  • step 209 the Visibility Calculator obtains a SQL statement from field SQL STATEMENT and executes it.
  • An example of such an SQL statement might be:
  • This SQL statement causes a query to be made of application table S OPTY EMP.
  • the query selects any records meeting two criteria.
  • the records selected must have a field OPTY ID, which is a row id or key, equal to the Primary Row-ID of the Docking Object whose visibility is being determined.
  • the records selected must have a field EMP ID, which may be for example, an identifier of a particular employee, equal to the Nodeld of the node for whom visibility is being determined.
  • this SQL statement will return records only if a row is found in a table that matches employees to opportunities, where the opportunity is equal to the one being updated, and the employee to whom the opportunity is assigned is the operator of the node.
  • This rule queries the tables S ACCT POSTN (which relates a particular account with a particular position in the organization that is responsible for the account) and S EMP POSTN (which relates what employee corresponds to a particular position).
  • S ACCT POSTN which relates a particular account with a particular position in the organization that is responsible for the account
  • S EMP POSTN which relates what employee corresponds to a particular position.
  • Step 211 evaluates whether the execution of SQL STATEMENT in step 209 returned any records. If records were returned, this indicates that the Node for which visibility is being checked has visibility to the docking object being processed.
  • Step 213 the transaction is marked visible. Because no further rules need to be evaluated to determine visibility, the visibility calculator proceeds to step 228.
  • Step 228 synchronizes the databases by determining whether the calculated visibility requires the insertion or deletion of a docking object into a particular node's partially replicated database. This may occur, for example, if a node is determined to have visibility to a docking object due to a change to a related docking object. For example, an owner of a node may be assigned to a particular activity that is related to a particular sales opportunity. As a result, the node should be provided with a copy of the object representing the sales opportunity.
  • Figure 8 depicts the steps performed to synchronize a partially replicated database in response to a change in data visibility. Execution begins in step 241. In step 243, the Visibility Calculator references the visibility just calculated for a docking object. If the Docking Object is visible, execution proceeds to step 245. Step 245 references the S DOBJ INST table, to verify that a row exists for the Docking Object for the current node. If a row exists, this indicates that the node in question already has a copy of the referenced Docking Object, and the routine proceeds to step 255, where it exits.
  • step 247 a transaction is generated to direct the node to insert the Docking Object into its partially replicated database.
  • step 243 determines that the Docking Object is not visible, execution proceeds to step 249.
  • Step 249 references the S DOBJ INST table, to verify that no row exists for the Docking Object for the current node. If step 243 determines that no row exists in the S DOBJ INST table for the current docking object for the current row, this indicates that the node in question does not have a copy of the referenced Docking Object, and the routine proceeds to step 255, where it exits. If, however, a row exists for the Docking Object at the node being processed, this indicates that the node in question does have a copy of the Docking Object on its partially replicated database. The routine then proceeds to step 251, where a transaction is generated to direct the node to delete the Docking Object from its partially replicated database.
  • step 2208 the Visibility Calculator proceeds to step 229, where it exits.
  • the resulting finding of visibility is available to be checked by the log manager in step 183 to determine to write the transaction.
  • step 211 determines that no records were returned by the execution of the SQL statement in step 209
  • execution proceeds with step 215.
  • Step 215 checks to see whether there are any remaining visibility rules to be assessed. If not, the visibility calculator proceeds to step 228 to synchronize the database, and then to step 229, where it exits. In this case, the default mark of no visibility that was set in step 203 remains set. This value will also be used by the log manager as shown in Figure 6, step 183, to determine not to write the transaction.
  • control proceeds to step 217, which selects the next rule to be processed. Control is then given again to step 207 to begin processing the new rule.
  • step 207 determines that the visibility rule is not of type "R," the visibility rule is of type "O.”
  • Type "O" indicates a docking- object visibility rule. In such a case, the docking object being processed will be considered to be visible if it is related to a particular related docking object that is visible. If field RULE TYPE is not equal to "R,” then, execution proceeds to step 221.
  • Step 221 determines the related Docking Object whose visibility must be determined to determine whether the current docking object is visible.
  • the related Docking Object identifier is obtained from field CHECK JDOBJ JLD in table S DOB J VIS RULE 71.
  • the Visibility Calculator determines which row in the related Docking Object must be queried for visibility. In order to determine this, the Visibility Calculator obtains a predetermined SQL statement from the field SQL STATEMENT and executes it.
  • the SQL statement is a query that select one or more rows of the Docking Object that, for example, correspond to the docking object for which the Visibility Calculator was invoked.
  • This SQL statement accesses a table S DOC QUOTE that contains all sales quotes.
  • the WHERE clause specifies retrieval of all rows where the Opportunity ID of the row is equal to the Row-ID of the opportunity for which visibility is being calculated.
  • the Visibility manager retrieves the specified Row-Ids, thereby identifying the rows of the S DOC QUOTE table whose visibility must checked.
  • the Visibility Calculator proceeds to step 225.
  • the Visibility Calculator recursively invokes itself to determine visibility of the related docking object.
  • the recursively invoked Visibility Calculator operates in the same manner as the Visibility Calculator as called from the Log Manager 9, including the capability to further recursively invoke itself.
  • the recursive call concludes, it returns a visibility indicator for the related Docking Object, and control proceeds to step 227.
  • the Visibility calculator determines whether the related Docking Object was determined to have been visible.
  • step 213 the Visibility Calculator proceeds to step 213 to mark the originally current Docking Object as visible, and then to step 228 to synchronize the database and then to step 229 to exit. If the related Docking Object was not determined to be visible, control proceeds to step 215 to determine whether additional visibility rales remain to be assessed.
  • the Visibility Calculator in conjunction with the Log Manager is therefore able to determine what subset of update transaction data is required to be routed to any particular node. This operation serves to reduce the transmission of unneeded data from the Central Computer 1 to the various nodes such as nodes 21-a, 21-b and 21-c that utilize partially replicated databases, and to reduce the system resources such as disk space needed to store, and the CPU time needed to process, what would otherwise be required to maintain a fully replicated database on each remote node.
  • the calculation of visibility events and the routing of visible transactions may be optimized by batching related SQL statements, rather than performing successive row-by-row operations. This optimization is achieved by eliminating redundant operations, using set processing and reducing network traffic. Redundant work is eliminated by denormalizing key data used to calculate visibility into the transaction log. For example, the Log Manager the docking object, primary table id, visibility event flags, and related data are stored in the transaction log table. Instead of calculating this data once for every mobile client, Log Manager calculates this data once for all mobile clients to use. Log Manager uses set processing by submitting SQL statements to check the visibility of many thousands of transactions simultaneously instead of submitting a SQL statement for each transaction. Network traffic is reduced by retrieving only the visible transactions from the database server to the docking server. Consequently, significantly less data travels over the network from the database server to the docking server.
  • Figure 9 depicts the structure of the database design of the Transaction Log Table 300 used to support batch visibility checking.
  • Node table 301 is the central table of the database, and contains one-to-many pointers to Dock Object Instance table 302, Dock Status table 304, and Transaction table 306.
  • Docking Object Instance table 302 stores whether a docking object instance is visible to a mobile client and has been downloaded to the mobile client. A row exists in Docking Object Instance table 302 if the docking object instance is rally visible or partially visible to the mobile client. If the docking object is not visible, then a row for the docking object instance does not appear in Docking Object Instance table 302. Docking Object Instance table 302 (S DOBJ INST) comprises the following fields to support batch visibility checking:
  • NODE ID a non-null user key of the node to which this docking object instance relates.
  • DOBJ ID a non-null user key of the docking object to which this docking object instance relates.
  • PRJTBL ROW ID a non-null user key containing the Row ID of the primary table in the docking object. This value identifies the Docking Object Instance.
  • STAT Flag a one-byte flag containing the value 'F' or 'P'.
  • the value 'F' indicates that the docking object instance is fully visible.
  • 'P' indicates that the docking object instance is partially visible.
  • Dock Status table 304 stores status information relating to each mobile client. This includes the identity of the last file merged, the last file extracted, and the last transaction extracted. Dock Status Table 304 (S DCK STAT) comprises the following fields to support batch visibility checking: ROWJLD: primary key.
  • NODE_ID Identity of the mobile client that owns this status information.
  • TYPE This field is used to interpret the VAL field, and contains one of the strings “ EXTRACT JtECORD” , "LOG_EXTRACT” , “MERGE RECORD”, “LASTJvIERGE”, or "SESSION”.
  • VAL This field contains the value corresponding to the data type in the TYPE field.
  • this table records the last transaction processed by an executable program called the Log Preprocessor. This is indicated in the VAL field for a row with a ROW D of zero and a TYPE of "EXTRACT IECORD" .
  • Transaction table 306 stores transaction that may need to be routed to all mobile clients.
  • Transaction table 306 (S DCK TXN LOG) comprises the following fields to support batch visibility checking:
  • TXN ID A non-null primary key that identifies the transaction.
  • DOBJJLD a non-null user key of the docking object to which this docking object instance relates.
  • PR TBL ROW ID a non-null user key containing the Row ID of the primary table in the docking object. This value identifies the Docking Object
  • VIS_EVT_FLG This field contains either the value 'Y' or 'N', and indicates whether the transaction causes a visibility event.
  • VIS_LEVEL_FLG This field indicates the visibility level of the dock object.
  • a value 'L' indicates that the dock object has limited visibility.
  • a value of 'P' indicates that the dock object is private.
  • a value of 'E' indicates that this object has enterprise visibility.
  • Batch visibility checking executes in four phases. Briefly, Phase 1 is ran one for each transaction in Transaction Log Table 300 and denormalizes the transaction log data into the constituent tables. Phase 2 is ran once per mobile client per iteration, and checks for visibility events for a mobile client. Phase 3 is run once per mobile client per iteration, and extracts visible transactions for the mobile client. Phase 4 is ran once per iteration and deletes transactions from Transaction Log Table 300. Details of all four phases are described below.
  • phases 1 and 4 may be combined into a single executable program called the Log Preprocessor. Only one Log Preprocessor is run against an installation at any one time. Phases 2 and 3 may be combined into a single executable program called the Log Router. One or more Log Routers may be ran against a single installation concurrently. The Log Router program may use semaphores to prevent more than one Log Router from routing transactions to the same mobile client simultaneously.
  • Phase 1 is ran one for each transaction in Transaction Log Table 300 and denormalizes the transaction log data into the constituent tables. This phase denormalizes values in S DCK TXN LOG based on transaction log data.
  • the following pseudocode describes the operation of Phase 1 in detail:
  • Phase 2 is ran once per mobile client per iteration, and checks for visibility events for a mobile client. This phase looks for all visibility event transactions and recomputes visibility. The phase downloads and removes Docking Object instances in response to visibility changes and stores the visibility of Docking Object instances, in table S DOBJ INST 63.
  • the following pseudocode describes the operation of Phase 2 in detail:
  • TXN PROCESSEDJD VIS_CHECK_RECORD THEN return; END IF;
  • Phase 3 is a separate program
  • Phase 3 is ran once per mobile client per iteration, and extracts visible transactions for the mobile client.
  • the following pseudocode describes the operation of Phase 3 in detail.
  • Phase 4 is ran once per iteration and deletes obsolete transactions from Transaction Log Table 300, including its substituent Transaction table 306 and Set Transaction ID table 308.
  • the following pseudocode describes the operation of Phase 4 in detail.
  • the S DOBJ INST table 63 is particularly suitable to provide such a "visibility cache.”
  • the existence of a particular docking object instance in S DOBJ INST table 63 may be used to assert that the docking object instance is visible to the mobile client.
  • the visibility cache improves performance in two ways. First, it reduces the number of times visibility must be calculated.
  • Log Manager 9 can use the cache in memory to determine visibility of a docking object instance when the transaction is on a table that does not cause implicit visibility events (i.e. the VISIBILITY EVT FLG is not checked for the table).
  • Log Manager does not need to ran any visibility SQL statements to determine the visibility of the transaction. Note that, if a transaction affects a table that can cause a visibility event, Log Manager must re-ran the visibility SQL statements to determine that transaction's visibility.
  • the visibility cache reduces the number of SQL statements executed per visibility calculation.
  • Log Manager uses the cache to determine visibility of check docking objects.
  • Log Manager does not need to recursively ran visibility rale SQL statements on each check docking object instance to determine the visibility of the transaction. Instead, Log Manager 9 joins to the S DOBJ INST table 63 to determine the visibility of check docking objects.
  • An SQL rale is an SQL fragment that expresses whether the docking object instance is visible.
  • An example of a visibility condition specified by an SQL rale for the opportunity docking object is "An Opportunity is visible if the sales rep is on the sales team. "
  • a check- docking-object rale indicates that a docking object instance is visible if another docking object is visible.
  • the definition of a check-docking-object rale contains a SQL fragment that tells the Log Manager how to get all the check docking objects for the docking object instance.
  • An example of a visibility condition specified by a check- docking-object rale for the opportunity docking object is "An Opportunity is visible if the Opportunity is used by a Quote that is visible to the sales rep. "
  • SQL rales are relatively inexpensive in execution resources. In contrast,
  • Log Manager In order to execute a check-docking-object rale, Log Manager recursively runs visibility SQL statements for the docking object it is checking. Determining visibility of a transaction can require rarining hundreds, or even thousands of SQL statements. Some objects may have eight to ten check-docking-object rales. Running all the visibility rale SQL statements for these objects could take between 0.25 seconds and several seconds for each mobile client. As the number of mobile clients increases, this can lead to undesirably low levels of service.
  • Log Manager also uses the S DOBJ INST table to track whether a docking object instance (e.g., a particular Opportunity instance) has been downloaded to a mobile client.
  • the S_DOBJJNST table prevents Log Manager from downloading a docking object instance that was already previously downloaded, or removing a docking object instance that was already previously removed.
  • the benefit is that the Log Manager does not need to ran any visibility SQL rales or check-docking-object rales to determine the visibility.
  • the SJDOBJJNST table is used to determine visibility of check- docking-objects.
  • Most of the check-docking-object rales may be converted to SQL rales that join the check-docking object to the S DOBJ INST table. If any check- docking object exists in the S DOBJ INST table, then the check-docking object must be visible to the mobile client.
  • the benefit is that the Log Manager runs at most one SQL statement to determine visibility of a check-docking object.
  • the following example shows the benefits of the visibility cache. Without the visibility cache, the set of rales used to check visibility of a docking object representing an account might be expressed as the following four rales.
  • Rule 3 Check-Docking-Object: Account is visible if it is an account for an
  • Log Manager To check the visibility of an Account docking object without a visibility cache, Log Manager performs the following steps to generate and execute SQL statements based on the above visibility rales.
  • Step 1 OR together the SQL rales and execute the result:
  • SQL rales and check docking object rales to determine whether the opportunity is visible. This can be many SQL statements.
  • the visibility rale SQL statements SQL rales and check docking object rales are executed to determine whether the quote is visible. This can be many SQL statements.
  • the total number of SQL statements executed by this process may be computed as 1 + (Opty Check Objs * Opty vis rales) + (Quote Check Objs * Quote vis rales). This may be anywhere from one statement to several hundred statements, depending on the number of Opportunity and Quotes objects retrieved.
  • the set of rales used to check visibility of a docking object representing an account might be expressed as the following four rales.
  • the two SQL rales 1 and 2 are unchanged; the two check-dock-object rules have been replaced with SQL rales that interrogate the S DOBJ INST table.
  • Log Manager To check the visibility of an Account docking object using a visibility cache, Log Manager generates and executes a single SQL statement derived from the four
  • This single SQL statement accomplishes the same result as the potentially hundreds of SQL statements that would be required without the visibility cache.
  • the following SQL fragments each provide a mechanism for joining to the S DOBJ INST table.
  • the fragment that is best for a particular implementation may vary depending on the performance characteristics for that implementation.
  • — txn is for a table that does not cause visibility
  • RuleType ! SQLRule
  • j RuleLocalFlag ! eVisType THEN continue;
  • RuleType ! CheckDockObjectRule j
  • RuleLocalFlag ! eVisType THEN continue;
  • the docking process may be further enhanced by treating object visibility as a non-binary condition; that is, providing for an object to have a degree of visibility so that it may be visible in certain contexts and not visible in others. This may be provided for by associating a visibility strength with each dock object visibility rale. Visibility strength is a positive integer that states how visible a given dock object instance is.
  • Visibility strength provides an alternative to concepts of fiilly and partially visible dock object instances. Rather than specifying visibility as either full or partial, visibility strengths allow for an unlimited range of visibility for an object.
  • the dock object instance receives the visibility strength associated with the visibility rale. This visibility strength controls two aspects.
  • the first aspect controlled by visibility strength is the downloading or removal of member table rows.
  • Each member table also has a visibility strength. Docking downloads (or removes) member table rows only if the dock object instance visibility strength is greater or equal to the member table visibility strength.
  • This aspect may be used to limit the number of member table rows replicated to docking clients. For example, when an Account is visible due to a Quote, docking should download the Account header, but does not need to download rows in the Account Notes, Account Positions, and other member tables. Log Manager download and removal processing is improved because Log Manager can skip downloading and removing certain member tables. In addition, docking replicates fewer rows to the docking clients, and the docking clients occupy less disk space.
  • a second aspect controlled by visibility strength is the downloading or removal of related dock object instances.
  • Each related dock object rule also has a visibility strength.
  • When a dock object instance is visible docking downloads (or removes) related dock object instances only if the dock object instance visibility strength is greater or equal to the related dock object rale visibility strength.
  • This aspect may be used to follow a subsets of related dock objects depending on the reason why the dock object instance is visible. This allows docking to follow a subset of related dock objects even if a dock object instance is partially visible.
  • Visibility strength is implemented by adding new attributes to the repository dock object table, dock object visibility rales and dock object related dock object rales. These new attributes specify the visibility strengths of member tables, visibility rales and related dock object rales.
  • Each dock object visibility rale has a visibility strength.
  • the dock object instance's visibility strength is equal to the highest visibility strength value of all visibility rales that pass.
  • the dock object instance visibility strength specifies which member table rows to replicate to a docking client and which related dock object rales to ran.
  • Check dock object visibility rules also have a check-dock-object visibility strength.
  • the check-dock-object visibility strength value specifies that the current dock object instance is visible only if the other dock object instance has a visibility strength greater than or equal to the check-dock-object visibility strength value.
  • Visibility strength is indicated by an attribute VIS STRENGTH that specifies the strength of the dock object instance.
  • the semantics of this attribute may vary depending on the context of the table in which it appears, as more fully discussed herein.
  • VIS STRENGTH may have the following values:
  • the S_DOCK_TABLE table stores the member tables for a docking object. Each docking object can have one or more member tables.
  • the table contains an additional field, VIS JSTRENGTH.
  • VIS STRENGTH is a numeric field containing the minimum visibility strength of the dock object instance for rows in this table to be downloaded. The field has a default value of 5, indicating that member table rows are downloaded if the dock object instance is partially visible.
  • the S DOCK VIS RULE table stores the visibility rales for a docking object. Each docking object can have one or more visibility rales.
  • the table contains an additional field, VIS_STRENGTH.
  • the S DOCK REL OBJ table stores the related dock object rales for a docking object. Each docking object can have one or more related dock object rales.
  • the table contains an additional field, VIS STRENGTH.
  • VIS STRENGTH is a numeric field containing the minimum visibility strength of the dock object instance for Log Manager to ran this rale. It has a default value of 10, requiring full visibility.
  • the S DOCK REL OBJ table also includes a field
  • REL VIS STRENGTH This field contains a value that is used to provide a visibility strength value to related dock instances. It has a default value of 5.
  • the S DOCK INST table is a new table replacing S DOBJ JNST, and stores the current visibility strength of a dock object instance for each docking client. It has the following fields. NODEJD is a non-null unique key that indicates the docking client corresponding to this row. DOCK ID is a non-null unique key that indicates the dock object corresponding to this dock object instance. PR TBL ROWJD contains a key that is the primary table row id of the dock object instance. VISJSTRENGTH is a numeric field containing the current visibility strength of the dock object instance for the docking client.
  • the following SQL code may be used to define the S DOCK INST table: create table S DOCK JNST (
  • the S DCK TXN LOG table stores the transactions to route to docking clients.
  • the table contains an additional field, VISJSTRENGTH.
  • VIS STRENGTH is a numeric field containing the visibility strength of the table referenced by the transaction. This value is denormalized by the Log Preprocessor and is used by the Log Router.
  • the following SQL code may be used to define the S JDCK TXN LOG table: alter table S_DCK_TXN_LOG add (TBL _VIS_STRENGTH NUMBER);
  • Log Manager processing Log Manager routes a transaction to a docking client only if the dock object instance visibility strength is greater or equal to the member table visibility strength.
  • the Log Preprocessor stores the member table visibility strength as a denormalized value in the transaction log table.
  • visibility rales are executed in decreasing order of visibility strength until a visibility rale passes.
  • Log Manager uses the member table's visibility strength attribute to identify member table rows to download or remove: When the visibility strength of a dock object instance changes, Log Manager downloads or removes member table rows for the dock object instance. If the new visibility strength is greater than the old visibility strength, the referenced member table rows have not previously been downloaded and now should be downloaded. If the new visibility strength is less than the old visibility strength, then Log Manager removes member table rows that have previously been downloaded and should not now be downloaded.
  • Log Manager When processing related dock object rales, Log Manager uses the visibility strength attribute of each rale to identify which related dock object rales to execute. When the visibility strength of a dock object does not change and the visibility strength is not None, Log Manager checks related dock object instances and verifies that their visibility strength have not changed. When the visibility strength of a dock object instance changes, Log Manager checks all related dock object instances and downloads or removes related dock object instances as needed. If the new visibility strength is greater than the old visibility strength, Log Manager executes the related dock object rales that have not previously been ran and now should be ran. If the new visibility strength is less than the old visibility strength, Log Manager executes the related dock object rales that have been previously ran and now should not be ran.
  • Log Manager uses the relVisStrength attribute of each rale to reduce visibility checking. If the new visibility strength is greater than or equal to the old visibility strength, and Log Manager finds a related dock object instance and the related dock object's relVisStrength is greater than or equal to the other dock object's maximum visibility rale visStrength, then Log Manager does not need to re-check visibility of other dock object instance.
  • the related dock object instance visStrength is set to the related dock object's relVisStrength.
  • the utility of the present invention may be made more useful by simplifying the docking visibility rales.
  • the docking visibility rales may be stored in a single location, the central dictionary, so that Log Manager can rely on the same definitions to extract and route transactions to mobile clients.
  • Predefined docking visibility rales may also be provided to support commonly required visibility tasks such as position dependencies, employee dependencies, and check-dock-object rales. This approach provides several benefits.
  • Second, storing all docking visibility rales in the central dictionary lets Log Manager use the same definitions to route transactions to mobile clients, reducing the cost of maintaining docking visibility rales. This also eliminates the need to maintain SQL scripts for each different database vendor (e.g. SybaseTM, OracleTM, or InformixTM) . Second, it permits the definition of pre-defined visibility rales commonly used by vendor-supplied applications. These rales make it unnecessary to enter SQL fragments or define related docking object rales. 90% of all docking visibility rales for typical applications may use pre-defined visibility rales. Third, the central dictionary lets customers use the Docking Object List view to easily customize docking visibility rales to satisfy site-specific requirements.
  • clients such as end users, can change visibility rales using an easy-to-use graphical user interface. This improves performance for majority of customers by letting us define specialized visibility rales for a small set of customers as inactive rales and letting the customers activate the specialized rales. Customers that do not use the specialized rales do not incur the performance cost of the specialized rales.
  • Simplified docking rales are implemented as follows. Five new types of visibility rales are defined and stored in the central dictionary. 1) Check-dock-object rales relate two docking object instance to each other without the use of a SQL fragment. Check dock object rales are similar to SQL rales except that a check dock object definition between two docking objects is stored instead of a SQL fragment. For example, an opportunity is visible if an activity that is fully visible uses the opportunity.
  • Position rales specify that a docking object instance is visible if an employee on the docking client occupies a position for the docking object. For example, an opportunity is visible if an employee on the docking client is an opportunity sales team member.
  • Position manager rales specify that the docking object instance is visible if an employee on the docking client is the manager of an employee that occupies a position for the docking object. For example, an opportunity is visible if an employee on the docking client is the manager of an opportunity sales team member.
  • Employee rales specify that a docking object instance is visible if an employee on the docking client is assigned to the docking object. For example, an activity is visible if an employee on the docking client is assigned to the activity. Employee rules are typically used for owner, creator, etc. 5) Employee manager rales specify that the docking object instance is visible if an employee on the docking client is the manager of an employee assigned to the docking object. For example, an activity is visible if an employee on the docking client is the manager of an employee assigned to the activity. Employee manager rales are typically used for manager of owner, manager of creator, etc.
  • Log Manager visibility SQL statements are generated from the central dictionary at runtime. Code is added to the visibility checker common API to generate and ran SQL statements for the new visibility rale types. Log Manager's visibility event code is modified to use the new types of visibility rales to find related docking object instances.
  • Fig. 10 depicts a database diagram for the central dictionary. This diagram is akin to the schema of Fig. 2 with additional support added to the SJDOCKJVTS JUTLE table, as follows.
  • the S JDOCKJVIS JRULE table contains the visibility rales associated with a particular Docking Object.
  • SJDOCKJVTS RULE 71 contains the additional fields DOCKJD, SEQUENCE, TYPE, ACTIVE and PARTIAL.
  • Field DOCK ID identifies the Docking Object with which a particular visibility rale is associated, referred to as the "current docking object.
  • Field SEQUENCE is a sequence number that indicates the sequence, relative to other visibility rales in the table, in which the particular visibility rale should be ran.
  • the ACTIVE field indicates whether a particular rale is active or not.
  • a value of 'Y' or null indicates that the rale is active, and a value of 'N' indicates that it is inactive.
  • the field TYPE specifies the type of the particular visibility rale.
  • a value of 'S' indicates an SQL rale; a value 'O' indicates a parameter dock object rale; a value 'C indicates a check-dock-object rale; a value 'P' indicates a position rale; a value 'Q' indicates a position manager rale; a value 'E' indicates an employee rale; a value 'F' indicates an employee manager rale.
  • the field PARTIAL if set to 'Y', indicates that if the visibility rale is satisfied, the current docking object is partially visible. If set to 'N' or null, it indicates that if the visibility rule is satisfied, the current docking object instance is fully visible.
  • S DOCK VIS RULE table contains a number of fields whose meaning and meaningfulness depends upon the rale type.
  • SQL rales use the fields SQL STATEMENT and VIS_EVT_COLS.
  • SQL STATEMENT field is an SQL fragment that, if it returns any rows, indicates that the dock object instance is visible.
  • Parameter Dock Object Rules use the fields CHECK JDOCKJD and SQL STATEMENT.
  • CHECK JDOCKJD contains a pointer to another docking object and SQL STATEMENT contains an SQL statement to obtain the PrimarylD values for the other dock object.
  • Logical Description For each PrimaryJD retrieved, Log
  • Manager runs the visibility rule of the other dock object.
  • SRC_COLUMNJD and TAR_COLUMN_ID identifies the column in the current dock object that joins to the check dock object and TAR COLUMN JD identifies the column in the check dock object that joins to the dock object join column.
  • SRC_COLUMN_ID identifies the column in the current dock object that joins to the check dock object
  • TAR COLUMN JD identifies the column in the check dock object that joins to the dock object join column.
  • the visibility event columns is implicit: all columns needed to join from the primary table of the current dock object to the dock object join column.
  • Position rales use the field POSTN COLUMN ID, which is a column in a member of table of the current dock object that points to the S POSTN table.
  • POSTN COLUMN ID is a column in a member of table of the current dock object that points to the S POSTN table.
  • the visibility event columns is implicit: all columns needed to join from the primary table of the current dock object to the position column.
  • Position Manager rales use the field POSTN_COLUMNJD, which is a column in a member of table of the current dock object that points to the S POSTN table.
  • POSTN_COLUMNJD is a column in a member of table of the current dock object that points to the S POSTN table.
  • the visibiMty event columns is implicit: all columns needed to join from the primary table of the current dock object to the position column.
  • SQL statements are stored in the central dictionary memory stractures for access by Log Manager.
  • SQL statements are generated and stored in the memory stractures. Because the number of SQL statements are small, the generation code is expected to take less than one second.
  • the dictionary API may be modified to generate the SQL statements for a given dock object whenever the dock object is first referenced.
  • Appendix B describes the format SQL statements that Log Manager generates at rantime and provides an example of these SQL statements using the Accounts dock object.
  • This program will be called by a server-side process that processes transaction log entries for all Laptop Nodes. For each Laptop Node, the calling process building the UserTrxnLogFileName and calling Program 1.
  • Data Merge can call this function to check whether a txn is -- still visible when merging txns into a laptop or server database .
  • LogRecordTypes are routed to all nodes -- No visibility events with these LogRecordTypes. ELSIF LogRecordType in (' ShadowOperation' , 'MultiRecordDelete' ,
  • RemoveObjectlnstance (LaptopNodeld, PrimaryTableName, PrimaryRowId) ; return FALSE; ⁇
  • CHAR* selectList CHAR* fromClause; CHAR* whereClause; UINT numTables ; /* also the number of joint to reach the Primary Table */ ⁇ GenStmt ;
  • each element in the array is a path from the Table to the Primary Table*/ DynArrld GenStmtArr; GenStmt newGenStmt;
  • newGenStmt mallocO
  • newGenStmt .numTables 1
  • newGenStmt. selectList "SELECT row_id”
  • newGenStmt. fromClause "FROM ⁇ Table> tl”
  • DynArrAppend (GenStmtArr, &newGenStmt) ;
  • GenStmtArr [j] .fromClause I GenStmtArr [j ] . hereClause; sqlStmt sqlStmt j
  • PKTable is a Member Table of the Docking Object THEN -- If there's more than one FK, then there is more than one path
  • StmtNum InputStmtNum; END IF;
  • BOOL DownloadObjectlnstance (LaptopNodeld, ObjectName, PrimaryRowId)
  • DownloadObjectlnstance (LaptopNodeld, RelatedDockingObject, newPrimaryRowId) ; END IF; END LOOP; END LOOP; return TRUE; ⁇
  • Appendix B SQL Statements and Examples
  • Log Manager generates visibility sql statements when checking the visibility of a dock object instance.
  • Log Manager Related Dock Object SQL Statements
  • Log Manager generates related dock object sql statements after the visibility of a dock object instance has changed.
  • Log Manager generates one or more ⁇ sub sql statements > for each visibility rule, the structure of which depends on the visibility rule type (see Sub SQL Statements below). ⁇ sub sql statement>
  • the path will not include the target primary table if the path traverses any other member table.
  • Example 1 Opportunity visible due to Activity
  • Source Object Opportunity (src ptable: S_OPTY)
  • Target Object Activity (tar ptable: S_EVT_ACT)
  • Source join column S_OPTY.ROW_ID
  • Target join column S_EVT_ACT. OPTY_ID 1.
  • PR_TBL_RO _ID tl.R0 _ID pTarJoinCol : tl .0PTY_ID
  • Source Path S_OPTY.
  • ROW_ID STables add nothing
  • Source Object Activity (src ptable: S_EVT_ACT)
  • Target Object Opportunity (tar ptable: S_OPTY)
  • Source join column S_EVT_ACT. OPTY_ID
  • Target join column S_OPTY.
  • Source Object Account (src ptable: S_ORG_EXT)
  • Target Object Account (tar ptable: S_ORG_EXT)
  • Src join column S_ORG_EXT.ROW_ID
  • Target Path S_ORG_REL .
  • OU_ID &Tables S_ORG_REL tl &Joins: and di .
  • PR_TBL_ROW_ID tl.0U_ID pTarJoinCol : tl - PRTNR_OU_ID
  • Source Object Account (src ptable: S_ORG_EXT)
  • Target Object Account (tar ptable: S_ORG_EXT)
  • Target Path S_ORG_EXT.ROW_ID &Tables: S_ORG_EXT tl
  • PR_TBL_ROW_ID tl.ROW_ID pTarJoinCol: tl.PARENT___OU_ID
  • target join column target primary table R0W_ID THEN -- can optimize: join source object directly to :primary_row_id
  • Source Object Opportunity (src ptable: S_OPTY)
  • Target Object Activity (tar ptable: S_EVT_ACT)
  • Source join column S_OPTY.ROW_ID
  • Target join column S_EVT_ACT. OPTY_ID
  • Source Path S_OPTY.
  • ROW_ID &Tables S_OPTY pt &Joins : add nothing pSrcJoinCol: pt.OPTY_ID
  • tl.0PTY_ID pt.R0W_ID select pt.ROW_ID from &Table_Owner.S_EVT_ACT tl,
  • Source Object Activity (src ptable: S_EVT_ACT)
  • Target Object Opportunity (tar ptable: S_OPTY)
  • Source join column S_EVT_ACT.
  • OPTY_ID Target join column S_OPTY.ROW_ID
  • Source Path S_EVT_ACT.
  • ROW_ID &Tables S_EVT_ACT pt &Joins : add nothing pSrcJoinCol : pt .OPTY_ID
  • Source Object Account (src ptable: S_ORG_EXT)
  • Target Object Account (tar ptable: S_ORG_EXT)
  • Example 4 Account visible due to Parent Account (Get all Accounts for a Parent Account)
  • Source Object Account (src ptable: S_ORG_EXT)
  • Target Object Account (tar ptable: S_0RG_EXT)
  • &Join_Column "j 1. ⁇ position column>" END IF Replace STables, &Join_Column and &Joins in the SQL statement template.
  • Object Opportunity (ptable: S DPTY) Position Column: S_OPTY_POSTN.
  • POSTN_ID Path: S_OPTY_POSTN.OPTY_ID &Tables: S_OPTY_POSTN jl, S_0PTY pt ScJoins : and jl.0PTY_ID pt.ROW_ID &Join_Column: : j 1.
  • POSTN_ID select pt.R0W_ID from &Table_Owner.S_NODE_REL join_table, &Table_Owner.S_NODE_EMP ne, &Table_Owner. S_EMP_POSTN ep, &Table_Owner.S_OPTY_POSTN jl,
  • SUB POSTN ID &Join Column
  • S_NODE_EMP ne &Table_Owner .
  • POSITIONED prr . POSITIONED and prr .

Landscapes

  • Engineering & Computer Science (AREA)
  • Databases & Information Systems (AREA)
  • Theoretical Computer Science (AREA)
  • Computing Systems (AREA)
  • Data Mining & Analysis (AREA)
  • Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
EP98908694A 1997-02-26 1998-02-24 Verfahren zur bestimmung der sichtverhältnisse auf mehrfache datenbanktransaktionen für einen ferndatenbank-kunden Withdrawn EP0963576A4 (de)

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US3947797P 1997-02-26 1997-02-26
US39477P 1997-02-26
PCT/US1998/003574 WO1998040806A2 (en) 1997-02-26 1998-02-24 Method of determining the visibility to a remote database client of a plurality of database transactions

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SE515459C2 (sv) * 1999-02-10 2001-08-06 Ericsson Telefon Ab L M Metod för att synkronisera en värddatabas och en fjärrdatabas
JP2002175209A (ja) * 2000-12-06 2002-06-21 Plus Alpha:Kk 情報サーバー内データ自動更新方法及びそのシステム
JP3926778B2 (ja) * 2003-08-28 2007-06-06 株式会社亀田医療情報研究所 医療情報システム及びコンピュータプログラム
WO2005122034A1 (ja) 2004-06-14 2005-12-22 Olympus Corporation データマネージメントシステム

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WO1997035265A1 (en) * 1996-03-19 1997-09-25 Siebel Systems, Inc. Method of maintaining a network of partially replicated database system

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WO1997035265A1 (en) * 1996-03-19 1997-09-25 Siebel Systems, Inc. Method of maintaining a network of partially replicated database system

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WO1998040806A3 (en) 1998-12-10
AU6665998A (en) 1998-09-29
WO1998040806A2 (en) 1998-09-17
JP2001514775A (ja) 2001-09-11
EP0963576A4 (de) 2005-05-11

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