Oracle International Corporation

Byron Wang

Lik Wong

Nimar Singh Arora

Anand Lakshminath

Thuvan Hoang

Edwina Lu

Jun Yuan

James William Stamos

Alan Robert Downing

Ramkumar Venkatesan

Haobo Xu

Lei Gao

Patricia H McElroy

Lakshminarayanan Luxi Chidambaran

Jingwei Wu

Lakshminaray Chidambaran

Neeraj Shadhan

Techniques for replicating data in database systems are described. In an example embodiment, a set of changes is received at a destination database, where the set of changes has been applied at a source database and is being replicated from the source database to the destination database. The set of changes is analyzed and it is determined that the set of changes includes two or more of: a subset of row-level changes, a subset of statement-level changes, and a subset of procedure-level changes. A set of dependencies is determined at least between the changes that are included in the subsets of changes. The changes, in the subsets of changes, are assigned to two or more processing elements. The set of changes is applied to the destination database by executing the two or more processing elements in parallel to each other and based on the set of dependencies.

Statement-level and procedural-level replication

Techniques for combining statement level, procedural, and row level replication

Systems, methodologies, media, and other embodiments associated with managing of a distributed database are described. One exemplary system embodiment includes an input logic configured to obtain information associated with a distributed database where the distributed database comprises a plurality of databases. An analysis logic analyzes the information obtained from the distributed database to determine performance information associated with the distributed database and, an output logic can provide information regarding the performance information associated with the distributed database.

Management of a distributed database

Splitting and merging database object information sharing streams. Streams are also referred to herein as 'propagations'. Splitting and merging information sharing streams can be used to improve performance in a information sharing environment when a failed or slow DBS impacts the performance. In one embodiment, an auto split process monitors the progress of applying changes at each node and detects the presence of a failed or a slow node. Once the failed or slow node is identified, the auto split process splits the propagation such that the offending node is sent through a separate propagation. Furthermore, an auto merge process can be started to monitor the newly created separate propagation. At a later point, the new propagation can be merged back into the original stream. For example, if the offending node catches up with other nodes, the auto merge process merges the newly created propagation back to the original propagation.

Reconfiguring propagation streams in distributed information sharing

Configuring an n-way multi-master information sharing topology. Adding a new node (e.g., database server) to the information sharing topology can be implemented as follows. Initially, the new node is added as a slave of a particular co-master in the information sharing topology. The objects to replicate are instantiated on the new node by propagating data from the particular co-master to the new node. Furthermore, a capture process is created on the particular co-master to send changes to the objects to the slave. Meanwhile, the co-masters continue to propagate changes to each other. To promote the slave to a master, changes to objects stored at the slave are propagated to each of the co-masters. Furthermore, changes at each of the masters are propagated to the promoted node.

Configuring or reconfiguring a multi-master information sharing environment

A method and apparatus for replicating data between heterogeneous databases is provided. Data is replicated between two heterogeneous databases with the use of a volatile storage queue, enabling the rapid replication of data across databases provided by different vendors or operating on different platforms. According to one embodiment, an in-memory queue is used to queue change operations to be performed on a target data repository. The change operations may be operations that were applied to a source data repository. An apply process retrieves the change operations from in-memory queue and commits the change operations to persistent storage. When the change operations have been committed, the apply process notifies the source platform that the particular change operation has been stored.

Replicating data between heterogeneous data systems

Growing community of inventors

Mountain View, CA, United States of America

Byron Wang