Oracle International Corporation

Ryder B Rishel

Derek Taylor

Tirthankar Lahiri

Chi-Kim Hoang

Chih-Ping Wang

Stephen Schleimer

John William Miller

Nagender Bandi

Paul Tuck

Susan Sokeng Cheung

Varadarajan Aravamudhan

Samuel Drake

William S Rishel

David Aspinwall

A database is stored as a plurality of database shards in a distributed database grid comprising a plurality of grid elements, each including a mid-tier database system. A first grid element receives, from an application executing in the same memory as a mid-tier database system of the first grid element, a first database transaction including at least one database operation on specific data stored in a first database shard that belongs to the first grid element. The first grid element performs and commits the first database transaction without participation of another grid element of the plurality of grid elements. The first grid element receives a second database transaction that requires access to another database shard that does not belong to the first grid element. Multiple grid elements of the plurality of grid elements perform the second database transaction and commit the second database transaction using a two-phase commit protocol.

Direct-connect functionality in a distributed database grid

Methods and systems are described for applying the use of shards within a single memory address space. A database request is processed by providing the request from a client to a processor, the processor then distributing the request to multiple threads within a single process but executing in a shared memory address environment, wherein each thread performs the request on a distinct shard, and aggregating the results of the multiple threads being aggregated and returning a final result to the client. By parallelizing operations in this way, the request response time can be reduced and the total amount of communication overhead can be reduced.

Method and system for parallelizing database requests

Load balancing in a parallel database system is performed using multi-reordering, in which a sequence of multiple processors (two, three, or more) that have small average load (for example, the smallest of any such sequence) is selected to participate in load balancing. In the case of three adjacent low-load processors, the load of all three is evenly distributed over two of them, and the remaining processor becomes a free processor. The free processor is moved adjacent to a high-load processor, the load of which is then shared with the free processor. Data is moved in a 'transaction' so that the view of data is always consistent. The database continues to service requests from a former location while data undergoes a transfer.

Load balancing in parallel database systems using multi-reordering

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Mountain View, CA, United States of America

Ryder B Rishel