Oracle International Corporation

Oracel International Corporation

Alex Tsukerman

Juan R Loaiza

J William Lee

Gianfranco Putzolu

Kothanda Umamageswaran

Mark Charles Ramacher

Jonathan D Klein

Gary C Ngai

William Havinden Bridge, Jr

Benoit Dageville

Jia Shi

Vikram Joshi

Graham Wood

Leng Leng Tan

Shari Yamaguchi

Karl Dias

Richard Sarwal

Mohamed Ziauddin

Sujatha Muthulingam

Zuoyu Tao

Hasan Rizvi

Boris Erlikhman

David Friedman

Umesh Panchaksharaiah

Sushil Kumar

Jane Xin Chen

Vishwanath Karra

Tirthankar Lahiri

Carol L Colrain

Wei-Ming Hu

Krishnan Meiyyappan

Vasudha Krishnaswamy

Selcuk Aya

Bharat Chandra Baddepudi

Kiran Badrinarain Goyal

Roger J Hansen

Stephen John Vivian

Vijay Sridharan

Eric P Voss

Wanli Yang

Nicholas A Whyte

Adrian Ng

Semen Ustimenko

Gregory Scott Smith

Francisco Sanchez

Sreenath Bodagala

Michael Feng

Luxi Chidambaran

Hsiao-te Su

Tsz Him (Adrian) Ng

Jacco Draaller

Mineharu Takahara

Devang Mundhra

Yinian Qi

Huy Nguyen

Juan R Loiza

Kiran B Goyal

A storage device uses non-volatile memory devices for caching. The storage device operates in a mode referred to herein as write-back mode. In write-back mode, a storage device responds to a request to write data by persistently writing the data to a cache in a non-volatile memory device and acknowledges to the requestor that the data is written persistently in the storage device. The acknowledgement is sent without necessarily having written the data that was requested to be written to primary storage. Instead, the data is written to primary storage later.

Write-back storage cache based on fast persistent memory

No-loss rapid recovery performs resynchronization efficiently while concurrently allowing availability to mirrored data on the storage device. No-loss rapid recovery has two stages and involves storage devices that have both a non-volatile cache and primary storage and that operate as mirror buddies. The first stage is referred to herein as the buddy-retention stage. During the buddy-retention stage, writes to mirrored data are not performed on the offline mirror buddy but are performed on the online mirror buddy. The mirrored data changed in the online mirrored buddy is retained in the non-volatile cache of the retention buddy. The next stage is referred to herein as the rapid resynchronization stage. In this stage, the changed mirrored data retained by the retention buddy for no-loss rapid recovery is used to resynchronize the offline buddy. The storage device is resynchronized using the changed mirrored data retained in the cache of the mirror buddy.

Rapid recovery from downtime of mirrored storage device

Techniques are described herein for supporting multiple versions of a database server within a database machine comprising a separate database layer and storage layer. In an embodiment, the database layer includes compute nodes each hosting one or more instances of a database server. The storage layer includes storage nodes each hosting one or more instances of a storage server, also referred to herein as a 'cell server.' In general, the database servers may receive data requests, such as SQL queries, from client applications and service the requests in coordination with the cell servers of the storage layer.

Systems and methods for supporting multiple database server versions on a database machine

Systems, methods, and other embodiments associated with detecting a node death in a clustered distributed system are described. In one embodiment, a method includes transmitting a ping message to a peer node in the network. If a reply to the ping message is not received from the peer node, a query is sent to table of port identifiers that lists ports in the cluster. In one embodiment, the query includes a port identifier associated with the peer node. The peer node is declared as inactive/dead when the query fails to locate a match in the table for the port identifier. When the query locates a match in the table for the port identifier, another ping message is periodically transmitted to the peer node.

Node death detection by querying

Dirty data in a storage device is made current through rapid re-silvering, which uses a mirrored and up-to-date version of the dirty data from another storage device to recover the data. Because under rapid re-silvering cache metadata in volatile memory survives the failure of the cache, the cache metadata is used to determine which subset of data from the other storage device needs to be copied to the storage device being re-silvered. During re-silvering, cache metadata is used to determine which I/O requests from clients are requests for data that is not stale.

Rapid recovery from loss of storage device cache

A computer readable medium storing a database query language statement tuning base in a tuning base memory location is disclosed. The tuning base includes tuning information for one or more query language statements. The tuning information for each statement includes one or more tuning actions for the statement, and a signature to allow an optimizer to identify the one or more tuning actions for the statement.

SQL tuning base

Techniques are provided for isolating faults in a software program by providing at least two code paths that are capable of performing the same operation. When a fault occurs while the one of the code paths is being used to perform an operation, data that indicates the circumstances under which the fault occurred is stored. For example, a fault-recording mechanism may store data that indicates the entities that were involved in the failed operation. Because they were involved in an operation that experienced a fault, one or more of those entities may be 'quarantined'. When subsequent requests arrive to perform the operation, a check may be performed to determine whether the requested operation involves any of the quarantined entities. If the requested operation involves a quarantined entity, a different code path is used to perform the operation, rather than the code path from which the entity is quarantined.

Fault isolation using code paths

Various embodiments of the invention provide solutions that can offer a consistent framework for tools that assist in the configuration, tuning, and/or troubleshooting of a database and/or an RDBMS. Merely by way of example, one set of embodiments provides a software framework for an advisor component of a database and/or RDBMS. In accordance with some embodiments, the framework might specify a common data model for such advisor components. The data model can include, merely by way of example, a set of one or more findings (which might, in some cases, describe the result of an analysis of a circumstance in the database, RDBMS, and/or a mid-tier application used with the database) and/or a set of one or more recommendations (which might provide suggestions for addressing the circumstance). In particular embodiments. In particular embodiments, the data model might include a set of on or more rationales, which can explain the recommendations. In some cases, the software framework might include a task associated with the advisor component and/or one or more interfaces, which can include, inter alia, user interfaces and/or APIs. Other sets of embodiments can provide methods, systems and/or software programs for implementing an advisor framework.

Advisor framework, systems, methods and software for implementing the same

Various embodiments of the invention provide solutions to allow more sophisticated management of the relationship between a database and its clients (which can be, inter alia, end users, business applications, etc.). Merely by way of example, some embodiments can facilitate the management of work requests in a database, as well as the management of the quality-of-service in a database system. In some embodiments, an identification handle may be assigned to a database work request. A database management application can use the identification handle to identify the work request, as well, perhaps, as any related work requests. The identification handle may also identify the database (and/or an instance thereof) and/or a clustered database node, and the identification handle may be transmitted to a mid-tier application, e.g., to notify the mid-tier about the processing of the work request, changes in quality-of service, server availability, etc.

Methods, systems and software for identifying and managing database work

A self-managing workload repository (AWR) infrastructure useful for a database server to collect and manage selected sets of important system performance statistics. Based on a schedule, the AWR runs automatically to collect data about the operation of the database system, and stores the data that it captures into the database. The AWR is advantageously designed to be lightweight and to self manage its use of storage space so as to avoid ending up with a repository of performance data that is larger than the database that it is capturing data about. The AWR is configured to automatically capture snapshots of statistics data on a periodic basis as well as purge stale data on a periodic basis. Both the frequency of the statistics data capture and length of time for which data is kept is adjustable. Manual snapshots and purging may also be performed. The AWR captured data allows for both system level and user level analysis to be automatically performed without unduly impacting system performance, e.g., by eliminating or reducing the requirement to repeat the workload in order to diagnose problems.

Self-managing performance statistics repository for databases

Systems and methods to define and store performance baselines. A baseline may be defined as a pair of snapshots, each snapshot containing the same set of statistics and having a timestamp value associated therewith. The present invention allows for the designation, automatically or manually, of statistics collected over a certain period of time to be stored and used for comparison. Baselines may be used, for example, to manually or automatically compare with current system performance, compare difference-difference values and set thresholds to monitor current system performance.

Database performance baselines

A method and system of reclaiming storage space in data storage systems is disclosed. In one embodiment, a high water mark of a data container is adjusted after data in the data container is compacted. As a result, unused space in the data container can be reclaimed.

Method and system of reclaiming storage space in data storage systems

An intelligent database infrastructure wherein the management of all database components is performed by and within the database itself by integrating management of various components with a central management control. Each individual database component, as well as the central management control, is self-managing. A central management control module integrates and interacts with the various database components. The database is configured to automatically tune to varying workloads and configurations, correct or alert about bad conditions, and advise on ways to improve overall system performance.

Self-managing database architecture

Various embodiments of the invention provide solutions to facilitate the management and/or automation of various database tasks, in particular system tasks. Merely by way of example, some embodiments provide methods systems and/or software products that can facilitate automation of such tasks. In accordance with certain embodiments, a maintenance window may be defined. The maintenance window can provide an opportunity for system tasks (and/or other tasks, especially those that consume significant database resources) to execute without significantly impacting the usability of the database. In particular embodiments, a maintenance window may be defined to coincide with a period of relatively low user activity. In some cases, a maintenance window may be implemented in conjunction with a job scheduler and/or a resource manager. Merely by way of example, a resource manager might allocate relatively more system and/or database resources to system tasks during the maintenance window, and/or a job scheduler may schedule system tasks to execute during the maintenance window.

Systems, methods and software for automating database tasks

A method and apparatus for debugging a software program is provided that is non-intrusive and allows multiple persons to debug concurrently in view private sessions. In one example, a method includes preserving a memory state of a portion of a software program, such as a database system. A second software program is compiled and dynamically linked, and which when executed, would normally cause modification to targeted data in the preserved portion of the software program. The second software program is executed by making a copy of the targeted data in the preserved portion of the software program. The copy is modified to generate a modified copy of the targeted data without modifying the data that is in the preserved portion of the software program. In subsequent accesses, the user that issued that executed the second software program accesses the modified copy whenever the user would have otherwise accessed the corresponding preserved portion. The second software program is made accessible to other users of the database system by publishing in the preserved portion a corresponding symbolic name associated with the second software program. If another user accesses the second software program and executes it, then another copy of the targeted data is made for that user. As before the copy is modified to generate a modified copy of the targeted data without modifying the data that is in the preserved portion of the software program.

Method and apparatus for debugging a software program using dynamic debug patches and copy on write views

Growing community of inventors

Foster City, CA, United States of America

Alex Tsukerman