Oracle International Corporation

Adrian Ng

Juan R Loaiza

Kothanda Umamageswaran

Alexander Tsukerman

Wei-Ming Hu

Krishnan Meiyyappan

Selcuk Aya

Neil J S MacNaughton

Kiran Badrinarain Goyal

Roger J Hansen

Adam Y Lee

Eugene Reddy Ho

Vipin Gokhale

Boris Erlikhman

Bharat C V Baddepudi

Amit Ganesh

Vineet Marwah

Jesse Kamp

Alex Tsukerman

Allison Holloway

Dmitry Mikhailovich Potapov

Roger MacNicol

Umesh Panchaksharaiah

Semen Ustimenko

Devang Mundhra

Yinian Qi

Aya Selcuk

Bharat CV Baddepudi

Roger Hansen

Techniques for optimizing a query with an extrema function are provided. In main memory, a data summary is maintained for a plurality of extents stored by at least one storage server. The data summary includes an extent minimum value and an extent maximum value for one or more columns. A storage server request is received, from a database server, based on a query with an extrema function applied to a particular column of a particular table. The data summaries for a set of relevant extents are processed by maintaining at least one global extrema value corresponding to the extrema function and, for each relevant extent of the set of relevant extents, determining whether to scan records of the relevant extent based on at least one of the global extrema value and an extent summary value of the data summary of the relevant extent.

Optimizing a query with extrema function using in-memory data summaries on the storage server

A method for accelerating queries using dynamically generated columnar data in a flash cache is provided. In an embodiment, a method comprises a storage device receiving a first request for data that is stored in the storage device in a base major format in one or more primary storage devices. The storage device comprises a cache. The base major format is any one of: a row-major format, a column-major format and a hybrid-columnar format. Based on first one or more criteria, it is determined whether to rewrite the data into rewritten data in a rewritten major format. In response to determining to rewrite the data into rewritten data in a rewritten major format, the storage device rewrites at least a portion of the data into particular rewritten data in the rewritten major format. The rewritten data is stored in the cache.

Method to accelerate queries using dynamically generated alternate data formats in flash cache

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

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

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.

Growing community of inventors

Redwood City, CA, United States of America

Adrian Ng