Oracle International Corporation

Other

Edwina Lu

Lik Wong

James William Stamos

Nimar Singh Arora

Neerja Bhatt

Sanjay Kaluskar

Thuvan Hoang

Byron Wang

Lakshminarayanan Luxi Chidambaran

Haobo Xu

Ravi Murthy

Zhen Hua Liu

Aleksey M Urmanov

Muralidhar Krishnaprasad

Dustin R Garvey

Sampanna Shahaji Salunke

James W Warner

Geeta Arora

Anand Lakshminath

Rajendra Pingte

Sundeep Abraham

Mahesh Subramaniam

Lakshminaray Chidambaran

Neeraj Shadhan

Techniques are described for performing cluster analysis on a set of data points using tri-point arbitration. In one embodiment, a first cluster that includes a set of data points is generated within volatile and/or non-volatile storage of a computing device. A set of tri-point arbitration similarity values are computed where each similarity value in the set of similarity values corresponds to a respective data point pair and is computed based, at least in part, on a distance between the respective data point pair and a set of one or more arbiter data points. The first cluster is partitioned within volatile and/or non-volatile storage of the computing device into a set of two or more clusters. A determination is made, based at least in part on the set of similarity values in the tri-arbitration similarity matrix, whether to continue partitioning the set of data points.

Scalable tri-point arbitration and clustering

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

Described herein are various approaches that allow rules to be used to specify actions, that alleviate the complexity and burden of developing and maintaining rules in a rules-based messaging system, and that provide more efficient ways of evaluating rules. The approaches allow rules to specify user-defined transformation functions for transforming messages, to specify when and how to perform row migration, and to specify other types of actions. Rules are grouped into rule sets. Several types of rule sets, referred to as positive and negative rule sets, allow users to use rules that are less complex to develop and maintain. Rule sets are evaluated more efficiently by attempting to evaluate the rule set with less information than is needed to evaluate all the rules in the rule set. Also, the results of rules evaluations that are based on a set of values are cached for later retrieval.

Partial evaluation of rule sets

Instances of complex types are logically replicated. In general, the logical replication of complex types involves converting a complex type instance from its storage format into a logical representation written in a markup language, like XML. The logical representation is then propagated to a destination (or destinations), which converts the logical representation to a storage format used at the destination for that complex type.

Using XML for flexible replication of complex types

An approach is provided to automatically resolve conflict between instantiation and ongoing data replication operations. In an embodiment, incremental change records that describe one or more database operations are received at a sink entity. Here, all of the one or more database operations have occurred in a second database after a particular time. A first database operation in the one or more database operations to a particular row in the first database is applied. When a conflict with a second database operation that operates on the particular row is detected, one or more compensating actions, which may, but are not limited to, be a different database operation and/or an operation that creates a conflict log entry, may be performed. Here, the second database operation has occurred in the second database prior to the particular time. When the second database operation is to be performed, an appropriate operation may be performed.

Automatic error correction for replication and instantaneous instantiation

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

Utilizing rules in a distributed information sharing system

In some messaging system architectures, messages can cycle back to the originator of a message, who may then propagate the message, causing the cycle to be repeated. Described herein are techniques that use rules and fields in a redo log, to manage message flows such that undesired cycles are prevented. The techniques may be used in messaging systems that have various topologies.

Preventing change cycling using rules and redo tags in a redo log

A source database system sends information to a destination database system, and each database system generates a separate set of sequence information. A mapping is maintained between the two sets of sequence information. Using the mapping, the destination database system may be used to restore changes lost at the source database system without reinstating the source database. Additionally, queries associated with a particular point in a sequence associated with the sequence information of the source database may be redirected to the destination database, and the destination database system may serve as a logical standby for the source database system. A variety of methods of maintaining and/or extracting the mapping information are disclosed.

Mapping source logical clock into destination logical clock in a distributed system

An approach efficiently and dynamically allocates and de-allocates database instances and nodes between databases. The approach performs this function in a way that accounts for the users of and services hosted by multiple databases.

On demand node and server instance allocation and de-allocation

Growing community of inventors

Palo Alto, CA, United States of America

Edwina Lu