Oracle International Corporation

Hewlett-packard Company

Dataxel Corporation

Marie-Anne Neimat

Chih-Ping Wang

Tirthankar Lahiri

John William Miller

Nagender Bandi

Mark L McAuliffe

Chi-Kim Hoang

Dina Thomas

Rohan Aranha

Paul Tuck

Dilys Thomas

Susan Cheng

Oded Shmueli

Chi Kim Hoang

John Raitto

Kirk Meredith Edson

Witold Litwin

Subhradyuti Sarkar

Sourav Ghosh

Susan Sokeng Cheung

W Kevin Wilkinson

Kurt Shoens

Donovan Schnelder

In column domain dictionary compression, column values in one or more columns are tokenized by a single dictionary. The domain of the dictionary is the entire set of columns. A dictionary may not only map a token to a tokenized value, but also to a count ('token count') of the number of occurrences of the token and corresponding tokenized value in the dictionary's domain. Such information may be used to compute queries on the base table.

Column domain dictionary compression

A method, apparatus, and system for automatically determining an optimal database subsection is provided. A database subsection is selected to optimize certain benefits when the database subsection is translated, transferred, and cached on an alternative database system, which may utilize a different technology or database engine that provides certain performance benefits compared to the original database system. Algorithms such as multi-path greedy selection and/or dynamic programming may provide optimal or near-optimal results. A host for the alternative database server may be shared with or otherwise located in close physical proximity to improve latency for a database application or client layer. Once the database subsection analysis is completed, a report may be generated and presented to the user, and an implementation script may also be created to automatically configure a client host to function as a cache or replacement system according various cache size configurations described in the report.

Automatically determining an optimal database subsection

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 system includes an active node and a standby node and zero or more replica nodes. Each of the nodes includes a database system, such as an in-memory database system. Client updates applied to the active node are written through to the standby node, and the standby node writes the updates through to a primary database and updates the replica nodes. Commit ticket numbers tag entries in transaction logs and are used to facilitate recovery if either of the active node or the standby node fails. Updates applied to the primary database are autorefreshed to the active node and written through by the active node to the standby node which propagates the updates to the replica nodes. Bookmarks are used to track updated records of the primary database and are used to facilitate recovery if either of the active node or the standby node fails.

Database system with active standby and nodes

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.

Local transactions are run at replication sites while receiving and tracking replication packages from primary sites. If a package coming in from a primary site updates data that a local transaction used, the data is considered stale and the local transaction is restarted. When the replication site wishes to commit (e.g., update data at the primary sites), a special dummy marker is submitted and committed. The marker comprises a dummy transaction that updates a piece of data at the primary site private to the replication site. The local site waits for the dummy transaction in the stream of replication packages sent from the primary site. Once the dummy transaction is received, the replication site is assured that any subsequent replication packages from the primary site will not affect the local transaction. If the replication packages received before the marker do not affect data items referenced during the local transaction, the local transaction commits.

Method and apparatus for replicated transaction consistency

A data processing method and apparatus, which generate a correct memory address from a character or digit string such as a record key value, and which is adapted for use in distributed or parallel processing architectures such as computer networks, multiprocessing systems, and the like. The invention provides a plurality of client data processors and a plurality of file servers, each server including at least a respective one memory location or 'bucket'. The method of the invention includes the following steps: generating the key value by means of any one of the client data processors; generating a first memory address from the key value, the first address identifying a first memory location; selecting from the plurality of servers a server that includes the first memory location; transmitting the key value from the one client to the server that includes the first memory location; and determining whether the first address is the correct address by means of the server. The method of the invention further provides that if the first address is not the correct address then the following steps are performed: generating a second memory address from the key value by means of the server, the second address identifying a second memory location; selecting from the plurality of servers another server, which includes the second memory location; transmitting the key value from the server that includes the first memory location to the other server, which includes the second memory location; determining whether the second address is the correct address by means of the other server; and generating a third memory address, which is the correct address, if neither the first or second addresses is the correct address. The present invention provides fast storage and subsequent searching and retrieval of data records in data processing applications such as database applications.

Linear hashing for distributed records

A method of maintaining the consistency of cached data in a client-server database system. Three new locks--a cache lock, a pending lock and an out-of-date lock--are added to a two-lock concurrency control system. A new long-running envelope transaction holds a cache lock on each object cached by a given client. A working transaction of the client works only with the cached object until commit time. If a second client's working transaction acquires an 'X' lock on the object the cache lock is changed to a pending lock; if the transaction thereafter commits the pending lock is changed to an out-of-date lock. If the first client's working transaction thereafter attempts to commit, it waits for a pending lock to change; it aborts if it encounters an out-of-date lock; and otherwise it commits.

Growing community of inventors

Atherton, CA, United States of America

Marie-Anne Neimat