Oracle International Corporation

Gary Hallmark

Daniel Leary

Ravi Prem Mirchandaney

William H Waddington

Jonathan D Klein

Roger J Bamford

James William Stamos

Alok Singh

Leng Leng Tan

Brian M Oki

Robert J Jenkins, Jr

Allen Brumm

Sunita Datti

Sarita Sridharan

Sumeet Rijhsinghani

Raveesh Yadav

Venkatesh Malapati

Balaji Iyengar

Nikhilkumar Parikh

Sasi Kala Erla

Krishna Raju Addala

Nagaveena Raju

Lalitha Kavuri

Maitrayee Bhoumik

Pascal Felber

Jyotin Gautam

A distributed order orchestration system publishes one or more newly generated artifacts that are generated as a result of generating one or more extensible flex fields to a rule dictionary. The distributed order orchestration system then imports the one or more newly generated artifacts within the rule dictionary as one or more facts. The distributed order orchestration system then creates one or more rules for the rule dictionary that references the one or more facts.

Distributed order orchestration system with extensible flex field support

The present invention implements parallel processing in a Database Management System. The present invention provides the ability to locate transaction and recovery information at one location and eliminates the need for read locks and two-phased commits. The present invention provides the ability to dynamically partition row sources for parallel processing. Parallelism is based on the ability to parallelize a row source, the partitioning requirements of consecutive row sources and the entire row source tree, and any specification in the SQL statement. A Query Coordinator assumes control of the processing of a entire query and can execute serial row sources. Additional threads of control, Query Server, execute a parallel operators. Parallel operators are called data flow operators (DFOs). A DFO is represented as structured query language (SQL) statements and can be executed concurrently by multiple processes, or query slaves. A central scheduling mechanism, a data flow scheduler, controls a parallelized portion of an execution plan, and can become invisible for serial execution. Table queues are used to partition and transport rows between sets of processes. Node linkages provide the ability to divide the plan into independent lists that can each be executed by a set of query slaves. The present invention maintains a bit vector that is used by a subsequent producer to determine whether any rows need to be produced to its consumers. The present uses states and a count of the slaves that have reached these states to perform its scheduling tasks.

Method and apparatus for implementing parallel operations in a database management system

Techniques are provided for executing an operation in which a client invokes a replicated object. According to one technique, a primary replica of a replicated object receives a first request from a client, wherein the first request includes a request identifier. Rather than immediately attempting to process the request, the primary replica determines whether a record exists that corresponds to the request identifier. If a record exists that corresponds to the request identifier, then the primary replica responds to the first request with a reply associated with the record. If no record exists that corresponds to the request identifier, then the primary replica performs the steps of: starting a transaction; as part of the transaction, processing the request; as part of the transaction, storing a record associated with the request identifier and a reply to the request; committing the transaction; and delivering the reply to the client. The client may itself be a replicated object. If the client is nondeterministic, then the transaction initiated by the primary replica may be a nested transaction relative to a transaction executed by the client, or be executed as part of the same transaction as the client. If the transaction executed by the primary replica is executed as part of the same transaction as the client, then a savepoint may be established before the primary replica processes the request, so that a failure will not necessarily require all processing performed by the client to be rolled back.

Preserving consistency of passively-replicated non-deterministic objects

A method and apparatus for distributing work granules of a parent task among processes running on various nodes in a multi-processing computer system is provided. The parent task is divided into work granules of varying sizes based on the location of the data that must be accessed to perform the work granules. At least one process on each of the nodes that will be assisting in the execution of the parent task is initially assigned a work granule based on efficiency considerations. Such efficiency considerations may include, for example, the location of the data to be accessed relative to the process, the current I/O load of the devices on which data to be accessed is stored, and the relative sizes of the various work granules. When a process completes the work granule assigned to it, the process is assigned one of the remaining unassigned work granules. Again the work granule assignment is made based on efficiency considerations. This process continues until all of the work granules have been completed.

Method and apparatus for distributing work granules among processes based on the location of data accessed in the work granules

A method and apparatus for executing queries on a set of data that has been partitioned into a plurality of partitions based on a partitioning key is provided. A query is received that includes a reference to a second key. The second key is not part of the partitioning key but has a predetermined correlation with the partitioning key. This second key is referred to as an overlapping partition key. A subset of the plurality of partitions is selected to be scanned based on the reference to the second key and the predetermined correlation with the partitioning key. The query is then executed by scanning only those partitions of the plurality of partitions that belong to the subset of partitions. The overlapping partition key provides for reduced query execution time even when the partitioning key is not directly involved in the query. Specifically, the overlapping partition key permits a partial table scan in situations that would require a fill table scan with partitioning alone.

Using overlapping partitions of data for query optimization

A method and apparatus for parallelizing operations that change a database is provided. A coordinator process receives a statement that requires data to be written into the database. In response to the statement, the coordinator process assigns granules of work to multiple processes. Each of the multiple processes executes the granule of work by writing to the database a distinct portion of the set of data that is to be added to the database. The various portions of data are then merged to update the set of data to be added to the database.

Method and apparatus for parallelizing operations that insert data into

Method and apparatus for distributing work granules among processes

Method and apparatus for implementing parallel operations in a database

A method and apparatus for comparing a first set of data and a second set of data are disclosed. A subset of base data is compared to a subset of replicated data to determine discrepancies. These discrepancies are then used to modify the replicated set of data, and the replicated set of data thus becomes identical to the base set of data. Alternately, the base data is compared directly to the replicated data and differences between the base data and the replicated data are obtained. These differences are then used to modify the replicated data to become identical to the base data.

Method and apparatus for data comparisons

The present invention describes a method and apparatus that forces all parts of an update transaction to commit automatically using a two-phase commit. The present invention uses the two-phase commit messages to negotiate a system commit number (SCN) that is then recorded on each of the nodes as the logical point in time that the distributed transaction committed. The two-phase commit scheme of the present invention consists of a 'prepare' phase and a 'commit' phase. The transaction in the distributed database environment involves multiple participants (databases). In the prepare phase, one of the N database participants is selected as the 'commit point.' The commit point includes the log into which the information is written that states the transaction has committed. The remaining N-1 participants enter a 'prepare phase.' In the prepare phase, the prepare participants lock their databases and enter a state in which they are ready to roll back or commit to the transaction. The mid-point of the two-phase commit is the point at which the commit point database (nth participant) writes the commit transaction to its log. In the second phase, the remaining participants are informed to commit the transaction and release locks that have been set.

Two-pass multi-version read consistency

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San Carlos, CA, United States of America

Gary Hallmark