Oracle International Corporation

Vasudha Krishnaswamy

Tirthankar Lahiri

Juan R Loaiza

Sukhada Pendse

Kartik Kulkarni

Garret Frederick Swart

Ajit Mylavarapu

Vivekanandhan Raja

Solmaz Kolahi

Amit Ganesh

Ankita Kumar

Yunrui Li

Jesse Kamp

Sanket Hase

Meichun Hsu

Shasank Kisan Chavan

Boris Klots

Kothanda Umamageswaran

Bipul Sinha

Allison Holloway

Teck Hua Lee

Hideaki Kimura

Aurosish Mishra

Benoit Dageville

Karl Dias

Mohamed Ziauddin

Dieter Gawlick

Gary C Ngai

Mahesh Baburao Girkar

Niloy Mukherjee

Ananth Raghavan

Mark Charles Ramacher

Dheeraj Pandey

Alex Tsukerman

Shrikanth Shankar

Sujatha Muthulingam

Graham Wood

Gianfranco Putzolu

Ramesh Kumar

Leng Leng Tan

Weiwei Gong

Wanli Yang

Sushil Kumar

Richard Sarwal

Vishwanath Karra

Liang Guo

Francisco Sanchez

Jing Zheng

Amirali Valiani

Maria Colgan

Xiaoming He

Venkatesh Radhakrishnan

Hsiao-te Su

Aditi Gupta

Shruti Gautam

Henry Chau

Akshay Kulkarni

Allison L Holloway

A Lock-Free Reservation mechanism is provided. When a transaction issues an update that affects a value in a 'reservable column' of a row, the database server does not immediately obtain a lock that covers the row. Instead, the database server adds a reservation to a reservation journal. At the time the transaction commits, a lock is obtained and the requested update is made. In one implementation, before adding the reservation to the reservation journal, the database server determines whether making the update would violate any constraints involving the reservable column. In one implementation, the constraint check not only takes into account the current value of the data item that is being updated and the amount of the update, but also pre-existing reservations in the reservation journal that affect the same data item.

System and method for increased transaction throughput and improved response time under high contention

One or more engine instances are executed on each host to form an engine cluster. A plurality of control instances are executed on a first set of hosts to form a control cluster and comprise a control instance leader and one or more control instance followers. In response to a first host indicating a failure of a neighbor host, a pair-wise focused investigation is initiated to check peer-to-peer connections between the first host and the neighbor host. In response to one or more additional hosts indicating failures of neighbor hosts while the pair-wise focused investigation is being performed, a wide investigation is performed to check connections between the control cluster and the plurality of hosts. One or more hosts are added to an eviction list and an eviction protocol is performed to evict the one or more hosts from the engine cluster using the eviction list.

System and method for transaction continuity across failures in a scale-out database

A shared-nothing database system is provided in which parallelism and workload balancing are increased by assigning the rows of each table to 'slices', and storing multiple copies (“duplicas”) of each slice across the persistent storage of multiple nodes of the shared-nothing database system. When the data for a table is distributed among the nodes of a shared-nothing system in this manner, requests to read data from a particular row of the table may be handled by any node that stores a duplica of the slice to which the row is assigned. For each slice, a single duplica of the slice is designated as the “primary duplica”. All DML operations (e.g. inserts, deletes, updates, etc.) that target a particular row of the table are performed by the node that has the primary duplica of the slice to which the particular row is assigned. The changes made by the DML operations are then propagated from the primary duplica to the other duplicas (“secondary duplicas”) of the same slice.

System and method for an ultra highly available, high performance, persistent memory optimized, scale-out database

Techniques related to query execution against an in-memory standby database are disclosed. A first database includes PF data stored on persistent storage in a persistent format. The first database is accessible to a first database server that converts the PF data to a mirror format to produce MF data that is stored within volatile memory. The first database server receives, from a second database server, one or more change records indicating one or more transactions performed against a second database. The one or more change records are applied to the PF data, and a reference timestamp is advanced from a first to a second timestamp. The first database server invalidates any MF data that is changed by a subset of the one or more transactions that committed between the first and second timestamps.

Query execution against an in-memory standby database

A shared-nothing database system is provided in which parallelism and workload balancing are increased by assigning the rows of each table to 'slices', and storing multiple copies ('duplicas') of each slice across the persistent storage of multiple nodes of the shared-nothing database system. When the data for a table is distributed among the nodes of a shared-nothing system in this manner, requests to read data from a particular row of the table may be handled by any node that stores a duplica of the slice to which the row is assigned. For each slice, a single duplica of the slice is designated as the &#x201c;primary duplica&#x201d;. All DML operations (e.g. inserts, deletes, updates, etc.) that target a particular row of the table are performed by the node that has the primary duplica of the slice to which the particular row is assigned. The changes made by the DML operations are then propagated from the primary duplica to the other duplicas (&#x201c;secondary duplicas&#x201d;) of the same slice.

System and method for high performance multi-statement interactive transactions with snapshot isolation in a scale-out database

Embodiments store transaction metadata in dedicated pools of allocated memory chunks. Portions of the pools of allocated memory chunks are dedicated to the respective apply slave processes that mine and process change records. Also, the pools of allocated memory chunks are anchored within the structure of a transaction log such that buffering and application of metadata for one transaction does not block required buffering and application of metadata for other transactions. The standby database system pre-processes transaction metadata in preparation for application of the metadata to invalidate appropriate portions of MF data. Further, embodiments divide the work of pre-processing invalidation records among the many apply slave processes that record the invalidation records. A garbage collection selects memory chunks for garbage collection in reverse order of how the chunks were allocated. Also, a deduplication algorithm ensures that typically only a single invalidation message per block is applied to invalidate MF data.

Space management for transactional consistency of in-memory objects on a standby database

Techniques are described herein for distributing distinct portions of a database object across volatile memories of selected nodes of a plurality of nodes in a clustered database system. The techniques involve storing a unit-to-service mapping that associates a unit (a database object or portion thereof) to one or more database services. The one or more database services are mapped to one or more nodes. The nodes to which a service is mapped may include nodes in disjoint database systems, so long as those database systems have access to a replica of the unit. The database object is treated as in-memory enabled by nodes that are associated with the service, and are treated as not in-memory enabled by nodes that are not associated with the service.

Flexible in-memory column store placement

Techniques are described for maintaining coherency of a portion of a database object populated in the volatile memories of multiple nodes in a database cluster. The techniques involve maintaining a local invalidation bitmap for which identifies block-level invalidity data and item-level invalidity data. In response to detecting a patch-up triggering event, a particular node identifies, in the block-level invalidity data, blocks that have been marked as invalid. For each block that has been marked as invalid, the node identifies specific items that have changed and marks the items as invalid in the item-level invalidity data. The node then updates the block-level invalidity data to indicate that the blocks are no longer invalid.

Patch-up operations on invalidity data

A minimum value (MV) is computed for start timestamps that each correspond to an uncommitted transaction. In an embodiment, the MV is computed for a pluggable database that is open on at least first and second instances of a database. The MV is computed for the first instance as of a first current timestamp (CT). The MV and the first CT are communicated to a second instance that has a second CT. If the first and second CTs are equal, the second instance store the MV. If the first CT is bigger, the second CT also becomes equal to the first CT. If the first CT is smaller, the MV is discarded, and the first CT becomes equal to the second CT. In an embodiment, if the MV remains unchanged for a predetermined time period, a start timestamp corresponding to the MV is advanced to a current or future timestamp.

Efficient determination of committed changes

A method and apparatus for updating databases are disclosed. In response to a flashback request, a database object is restored to a state as of a specified flashback time. The changes introduced into the database object are reversed in a sequence starting with a change introduced into the database object immediately before issuance of the flashback request and ending with a change introduced into the database object immediately after the specified flashback time.

Online recovery of user tables using flashback table

A technique for making versions of rows of a user-defined tracked table temporally queryable. The database management system of the technique permits temporal queries of user-defined tables. The queries return versions of rows in the user-defined table that are currently in an undo log maintained by the database system. Associated with the tracked table are a system history table which contains versions of the rows and temporal metadata indicating when the versions were in the tracked table and a system form history table which contains versions of the form of the tracked table and metadata indicating when the tracked table had the form. These tables are created and maintained by a background process in the database management system. A temporal query on the tracked table combines results from the undo log with results from the system history table. The results' form is determined by the system form history table.

Techniques for automatically tracking and archiving transactional data changes

Growing community of inventors

Fremont, CA, United States of America

Vasudha Krishnaswamy