Oracle International Corporation

Margaret Susairaj

Sumanta Kumar Chatterjee

Juan R Loaiza

Kumar Rajamani

Richard L Frank

Giridhar Ravipati

Alexander Tsukerman

Sridhar Subramaniam

Akshay Shah

Sue K Lee

Vivekananda C Kolla

Yunrui Li

Dmitry Mikhailovich Potapov

Arun Kaimalettu

Sue-Kyoung Lee

Prashanth Shanthaveerappa

Tirthankar Lahiri

Wei-Ming Hu

Balasubrahmanyam Kuchibhotla

William Havinden Bridge, Jr

Hakan Jakobsson

Vinay H Srihari

Mark Dilman

Jaebock Lee

Sanjay Kaluskar

Sanket Jain

Thomas E Barnes

Ashok M Joshi

Hubert Ken Sun

Dongbo Xiao

Kathiravan Sengodan

Michael James Stewart

Jonghyun Lee

Vsevolod Panteleenko

Rajesh V Patel

Varun Malhotra

Sal Gambino

Waleed Ojeil

Joseph Francis Therrattil Koonen

Peter Ogilvie

Ravi Thammiah

Jose Antonio Lasa Gutierrez

Ranjit Mario Noronha

Akshay D Shah

Consistent External Table Access maintains transactional consistency for queries that access external tables stored in a DBFS. This ability is achieved by bypassing the OS. One or more database processes executing a query that access an external table stored in a DBFS access the database-file table like other database tables in the DBMS that can be accessed to execute a query. Based on metadata stored in the DBMS regarding how an external table is stored in a DBFS, a DBMS is able to marshal database processes that access database-file tables directly to execute a query.

Transactional query processing in external tables

Disclosed is an improved approach to access the contents of database file system. The contents of the database file system can be acquired and stored in a directory buffer. A parallel tree structure is used to retrieve directory contents quickly and in a consistent fashion.

Method and system to implement directory reads for a database file system

Techniques are provided for block-level fail atomicity on byte-level non-volatile media. In one technique, an offset table and application data that stores content of a file are stored for a file. The offset table includes multiple entries, each entry being associated with a different offset value and storing a logical block address (LBA) that references a location in the application data. In response to receiving a request, that includes an input buffer and an offset value, to update the file: (a) an entry, in the offset table, that corresponds to the offset value and comprises a first LBA is identified; (b) a second LBA that is considered free is identified; (c) the second LBA is replaced with the first LBA; (d) the input buffer is written to a location, in the application data, that the second LBA references; and (e) the second LBA is added in the entry.

High-performance, block-level fail atomicity on byte-level non-volatile media

Techniques herein make and use a pluggable database archive file (AF). In an embodiment, a source database server of a source container database (SCD) inserts contents into an AF from a source pluggable database (SPD). The contents include data files from the SPD, a listing of the data files, rollback scripts, and a list of patches applied to the SPD. A target database server (TDS) of a target container database (TCD) creates a target pluggable database (TPD) based on the AF. If a patch on the list of patches does not exist in the TCD, the TDS executes the rollback scripts to adjust the TPD. In an embodiment, the TDS receives a request to access a block of a particular data file. The TDS detects, based on the listing of the data files, a position of the block within the AF. The TDS retrieves the block based on the position.

Pluggable database archive

Techniques are provided for using a sparse file to create a hot archive of a pluggable database of a container database. In an embodiment and while a source pluggable database is in service, a source database server creates a clone of the source pluggable database. Also while the source pluggable database is in service, the source database server creates an archive of the source pluggable database that is based on the clone. Eventually, a need arises to consume the archive. A target database server (which may also be the source database server) creates a target pluggable database based on the archive.

Periodic snapshots of a pluggable database in a container database

Techniques are described herein for cloning a database. According to some embodiments, a database server receives a request to clone a source database. In response to receiving the request, the database server retrieves a set of one or more storage credentials for a set of one or more respective storage systems on which a set of files of the source database are stored. The set of storage credentials grant permission to the database server to create snapshot copies on the set of storage systems. The database server generates, for a target database using the set of storage credentials, a snapshot copy of each respective file in the set of files of the source database. The snapshot copy of the respective file points to the same set of one or more data blocks as the respective file until at least one of the data blocks is modified.

Storage integrated snapshot cloning for database

A system and method can provide a scalable data storage in a middleware environment. The system can include a cluster of replicated store daemon processes in a plurality of processing nodes, wherein each machine node can host a replicated store daemon process of the cluster of replicated store daemon processes. Additionally, the system can include one or more replicated stores associated with an application server the processing node. The replicated store daemon cluster can persist data from a replicated store to another node, the other node also being associated with the replicated store daemon cluster. The system and method can additionally support a messaging service in a middleware environment. The messaging service can use the replicated store to store a copy of a message in the local processing node and on another processing node associated with the same replicated store daemon cluster.

Highly performant reliable message storage using in-memory replication technology

In accordance with an embodiment, described herein is a system and method for enabling persistence of application data, using replication over a remote direct memory access (RDMA) network. In an enterprise application server or other environment having a plurality of processing nodes, a replicated store enables application data to be written using remote direct memory access to the random access memory (RAM) of a set of nodes, which avoids single points of failure. Replicated store daemons allocate and expose memory to client applications via network endpoints, at which data operations such as reads and writes can be performed, in a manner similar to a block storage device. Resilvering can be used to copy data from one node to another, if it is determined that the number of data replicas within a particular set of nodes is not sufficient to meet the persistence requirements of a particular client application.

System and method for persistence of application data using replication over remote direct memory access

Automated management of shared I/O resources involves use of a policy engine for implementing I/O scheduling group I/O policies. The I/O policies are used for determining whether corresponding I/O requests should be issued to a shared storage system immediately or should be delayed via corresponding policy-based queues. In the context of database systems, a database administrator can specify policies regarding how I/O resources should be used and the database system itself enforces the policies, rather than requiring the database administrator enforce the I/O usage of the database and of the individual users.

Management of shared storage I/O resources

Techniques for moving data files without interrupting access are described. A first process moves a database file from a first location to a second location while the database file is accessible to one or more other processes for read or write operations. According to one technique, the first process communicates a move status and a copy range into the database file to one or more database server instances executing the one or more other processes. The one or more other processes then perform input/output (IO) operations on the database file based at least in part on the move status and the copy range communicated by the first process.

Techniques for moving data files without interrupting access

Techniques are provided for managing, within a storage system, the sequence in which I/O requests are processed by the storage system based, at least in part, on one or more logical characteristics of the I/O requests. The logical characteristics may include, for example, the identity of the user for whom the I/O request was submitted, the service that submitted the I/O request, the database targeted by the I/O request, an indication of a consumer group to which the I/O request maps, the reason why the I/O request was issued, a priority category of the I/O request, etc. Techniques are also provided for automatically establishing a scheduling policy within a storage system, and for dynamically changing the scheduling policy in response to changes in workload.

Storage-side storage request management

A database management system (DBMS) maintains a clone database in a clone space without storing an entire copy of the database and without requiring a snapshot function from an underlying storage device. This DBMS may receive a database command to access a data block of the clone database, and may determine whether the data block is stored in the clone space. If the data block is not stored in the local clone space, the DBMS may receive the data block from a backup copy of the database. If the database command comprises a write operation, the DBMS may perform the write operation to update the data block, and may store the updated data block in the clone space. Also, if the database command comprises a read operation, the DBMS may perform the read operation on the data block received from the backup copy of the database.

Database cloning

A computer is programmed to execute a diagnostic procedure either on a pre-set schedule or asynchronously in response to an event, such as an error message, or a user command. When executed, the diagnostic procedure automatically checks for integrity of one or more portions of data in the computer, to identify any failure(s). In some embodiments, the failure(s) may be displayed to a human, after revalidation to exclude any failure that no longer exists.

Data corruption diagnostic engine

Growing community of inventors

Sunnyvale, CA, United States of America

Margaret Susairaj