Oracle International Corporation

Vipin Gokhale

Juan R Loaiza

Wei-Ming Hu

J William Lee

Kiran Badrinarain Goyal

Adam Y Lee

Neil MacNaughton

Bharat Chandra Baddepudi

Neil J S MacNaughton

Eugene Reddy Ho

Tirthankar Lahiri

Kothanda Umamageswaran

Alexander Tsukerman

Selcuk Aya

Roger J Hansen

Boris Erlikhman

Bharat C V Baddepudi

Adrian Ng

Yunrui Li

Kumar Rajamani

William Havinden Bridge, Jr

Vivekanandhan Raja

Niloy Mukherjee

Dheeraj Pandey

Jia Shi

Vinay H Srihari

David Vengerov

Mark Dilman

Jaebock Lee

Michael P Stewart

Dmitry Mikhailovich Potapov

Sanket Hase

Sujatha Muthulingam

Muthu Olagappan

Krishna Kunchithapadam

Michael John Skarpelos

Hochak Hung

Ankur Kemkar

Kaan Baloglu

Sivaram Prasad Soma

Vishvesh Mohanarangam Selvakumaar

Nirman Kumar

Jr William H Bridge

Neil JS Macnaughton

Aya Selcuk

Bharat CV Baddepudi

Roger Hansen

Techniques herein store database blocks (DBBs) in byte-addressable persistent memory (PMEM) and prevent tearing without deadlocking or waiting. In an embodiment, a computer hosts a DBMS. A reader process of the DBMS obtains, without locking and from metadata in PMEM, a first memory address for directly accessing a current version, which is a particular version, of a DBB in PMEM. Concurrently and without locking: a) the reader process reads the particular version of the DBB in PMEM, and b) a writer process of the DBMS replaces, in the metadata in PMEM, the first memory address with a second memory address for directly accessing a new version of the DBB in PMEM. In an embodiment, a computer performs without locking: a) storing, in PMEM, a DBB, b) copying into volatile memory, or reading, an image of the DBB, and c) detecting whether the image of the DBB is torn.

Persistent memory file store for directly mapped persistent memory database

Techniques are provided for managing cached data objects in a mixed workload environment. In an embodiment, a database system receives request to access a target data object. The database system determines whether the request to access the target data object is associated with a first type of workload or a second type of workload. In response to determining that the request is associated with the first type of workload, the target data object replaces a least recently used data object in a cache. In response to determining that the request is associated with the second type of workload, the target data object is cached based on an associated access-level value.

Caching large objects in a computer system with mixed data warehousing and online transaction processing workload

Techniques are provided for using an intermediate cache between the shared cache of an application and the non-volatile storage of a storage system. The application may be any type of application that uses a storage system to persistently store data. The intermediate cache may be local to the machine upon which the application is executing, or may be implemented within the storage system. In one embodiment where the application is a database server, the database system includes both a DB server-side intermediate cache, and a storage-side intermediate cache. The caching policies used to populate the intermediate cache are intelligent, taking into account factors that may include which object an item belongs to, the item type of the item, a characteristic of the item, or the type of operation in which the item is involved.

Caching data between a database server and a storage system

In an approach, a database server maintains a container database which comprises: one or more pluggable databases, a root database that stores an undo log for rolling back transactions on the consolidated database, and a redo log for replaying modifications to the container database. The database server restores a particular pluggable with a backup version that corresponds to a first point in time. The database server generates a clone database loaded with a backup version of the root database that corresponds to the first point in time. The database server applies the redo log to recover the particular pluggable database and the clone database to a second point in time that is later than the first point in time. The database server identifies, based on the clone database, one or more active transactions on the particular pluggable database. The database server rolls back the one or more active transactions.

In place point-in-time recovery of pluggable databases

Techniques are provided for using an intermediate cache between the shared cache of a database server and the non-volatile storage of a storage system. The intermediate cache may be local to the machine upon which the database server is executing, or may be implemented within the storage system. In one embodiment, the database system includes both a DB server-side intermediate cache, and a storage-side intermediate cache. The caching policies used to populate the intermediate cache are intelligent, taking into account factors that may include which database object an item belongs to, the item type of the item, a characteristic of the item; or the database operation in which the item is involved.

A method, system and computer program product are described for state maintenance of a large object. In one approach, the method, system and computer program product perform by associating one or more buffers with a transaction involving a large object, the large object data may be accessed using the one or more buffers during the transaction, and storing data for the large object from the one or more buffers in one or more sets of contiguous blocks. In one approach, a system performs state maintenance of a large object with a cache that associates one or more buffers with a transaction involving a large object, the large object data may be accessed using the one or more buffers during the transaction, and the cache stores large object data from the one or more buffers in one or more sets of contiguous blocks in storage.

Method and system for state maintenance of a large object

A standby database system or another replica data system replicates changes, made to data blocks at a source database system or another primary data copy, to replicas of the data blocks at the standby database system or other replica. While replicating the changes to the data blocks thereof, the standby database system (or other replica) receives queries (or reads) issued thereto and computes the queries based on data read from the data blocks thereof.

Readable physical storage replica and standby database system

Techniques are provided for performing changes to a resource governed by a locking mechanism. An entity (such as a server instance in a database system cluster) requests permission to modify the resource. In response to the request, the entity receives a first lock on the resource, which grants permission to perform the change to the resource without making the change permanent. After receiving the first lock, the entity performs the change to a copy of the resource that resides in shared memory without making another copy of the resource. After performing the change and until receiving permission to make the change permanent, the entity prevents the change to the resource from becoming permanent. After performing the change, the entity receives a second lock on the resource, which grants the entity permission to make the change permanent. After receiving the second lock, the entity ceases to prevent the change to the resource from becoming permanent.

Techniques for improved read-write concurrency

Growing community of inventors

Fremont, CA, United States of America

Vipin Gokhale