Oracle International Corporation

Nagender Bandi

Chih-Ping Wang

John William Miller

Tirthankar Lahiri

Marie-Anne Neimat

Chi-Kim Hoang

Chi Kim Hoang

Paul Tuck

Dilys Thomas

Susan Cheng

Mark L McAuliffe

Dina Thomas

Derek Taylor

Rohan Aranha

Sourav Ghosh

Ryder B Rishel

Samuel Drake

Susan Sokeng Cheung

Varadarajan Aravamudhan

David Aspinwall

Susan Cheung

John Miller

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

Techniques are described for performing dependency locking to enable parallel execution of database server processes modifying the same object. In an embodiment, a DBMS receives a request to execute an operation on its managed database. The request may include an object identifier and a version identifier for a version of a database object, which is required for the successful execution of the operation on the database. The required version of the database object may not exist and may be generated only after the execution of another, second, operation on the database. The first database server process initiates execution of the earlier received operation on the database. The first database server process queries the first database for the version of the particular database object and determines that the version of the database object does not exist yet, in one embodiment. Based on such a determination, a dependency lock is generated for the version of the object, and the first database server process is suspended, preventing the completion of execution of the earlier received operation on the database. Another, second database server process executes another operation on the database and causes the generation of the version of the object on the database. The dependency lock is thereby released for the version of the object, and the first database server process completes the execution of the first operation on the first database.

Dependency locking

A plurality of mid-tier databases form a single, consistent cache grid for data in one or more backend data sources, such as a database system. The mid-tier databases may be standard relational databases. Cache agents at each mid-tier database swap in data from the backend database as needed. Ownership locks maintain consistency in the cache grid. Cache agents prevent database operations that will modify cached data in a mid-tier database unless and until ownership of the cached data can be acquired for the mid-tier database. Cache groups define what backend data may be cached, as well as a general structure in which the backend data is to be cached. Metadata for cache groups is shared to ensure that data is cached in the same form throughout the entire grid. Ownership of cached data can then be tracked through a mapping of cached instances of data to particular mid-tier databases.

Distributed consistent grid of in-memory database caches

A replication track is a designated group of transactions that are to be replicated at a destination database in a way that, with respect to any other transaction in the replication track, preserves transactional dependency. Further, transactions in a replication track can be replicated at the destination database without regard to transactional dependency of other transactions in another track. This facilitates concurrent parallel replication of transactions of different tracks. Replicating data in this manner is referred to herein as track replication. An application may request execution of transactions and designate different tracks for transactions.

User-defined parallelization in transactional replication of in-memory database

A plurality of mid-tier databases form a single, consistent cache grid for data in a one or more backend data sources, such as a database system. The mid-tier databases may be standard relational databases. Cache agents at each mid-tier database swap in data from the backend database as needed. Consistency in the cache grid is maintained by ownership locks. Cache agents prevent database operations that will modify cached data in a mid-tier database unless and until ownership of the cached data can be acquired for the mid-tier database. Cache groups define what backend data may be cached, as well as a general structure in which the backend data is to be cached. Metadata for cache groups is shared to ensure that data is cached in the same form throughout the entire grid. Ownership of cached data can then be tracked through a mapping of cached instances of data to particular mid-tier databases.

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Foster City, CA, United States of America

Nagender Bandi