International Business Machines Corporation

Balakrishna Raghavendra Iyer

Piyush Goel

Vahit Hakan Hacigumus

Gautam Bhargava

Hong Min

Atul Chadha

Sharad Mehrotra

Bhaskar Sinha

Steven Wayne White

Sameh W Asaad

Inderpal Singh Narang

Bharat Sukhwani

Mathew S Thoennes

Jerry Mukai

Hong Sang Tie

Wolfram Sauer

Piotr M Plachta

Parijat Dube

Chandrasekaran Mohan

Robert William Lyle

Daniel Manuel Dias

Min Wang

Kenneth E Plambeck

Steven John Watts

Peter Hoa

Dante Aligheri Aubert

Hubertus Franke

Gary Ross Ricard

Terence Patrick Purcell

Thomas Abel Beavin

Guogen Zhang

Fen-Ling Lin

Donald J Haderle

Lu Nguyen

Akira Shibamiya

Craig Alan Friske

Bernard V Brezzo

Donna N Eng Dillenberger

Paramesh Sampatrai Desai

Jeonghee Yi

Hammou Messatfa

Teresa A Meriwether

Elton B Sherwin, Jr

Thuan Quang Bui

Sanjoy Das

John P Lazarus

John T Flynn

Chung-Chia Chang

Gregory L Davoll

Mohamed H El-Ruby

David Wilhite

William Samuel Perlman

Gururaj Seshagiri Rao

Hatem Mohamed Ghafir

Yun Yu Wang

Karthick Rajamani

Philip Shilung Yu

Curt Lee Cotner

Jaishankar Moothedath Menon

Satya Prakash Sharma

James T Brady

Daniel Alexander Ford

Prasad Manikarao Deshpande

You-Chin Gene Fuh

Ahmad Zandi

James Zu-Chia Teng

Casper A Scalzi

Ashish Gupta

Lin Qiao

Josephine Miu Cheng

Apostol Ivanov Natsev

Richard I Baum

Aamer U Sachedina

Hansjorg Zeller

Noshir Cavas Wadia

Jeffrey Allen Berger

Glen G Langdon, Jr

Bryan Frederick Smith

Enzo Cialini

Glen A Brent

Arun N Swami

Jayashree Subrahmonia

Lee Hardy Wilson

Sauraj Goswami

John Thomas Flynn, Jr

Ullas Balan Nambiar

Laura Myers Haas

Scott Dennis Helt

Michael R Shadduck

Venkatachary Srinivasan

Gary Howard Sockut

Stephen Walter Turnbaugh

Charles William Lickel

Yitzhak Dishon

Clodoaldo Barrera

Saugata Guha

Allen William Luniewski

Ramanujam Seshadri Halasipuram

Richard W Hedges

Peter Joseph Varman

Embodiments provide an approach for efficiently searching a temporal key index as well as enforcing key distinctiveness property in a database table corresponding to the index. For example, by addressing time range overlaps in an index having a sort order for temporal keys, a database management tool of a server system may efficiently process client requests while enforcing a temporal key property in the database table.

Managing a temporal key property in a database management system

Methods and arrangements for mapping a query operation to an accelerator are provided. The method includes receiving, by a processor, a query operation and determining the design logic of the query operation, receiving a configuration of one or more available accelerators and a design logic of each of the one or more available accelerators, and determining if the query operation can be offloaded to one or more of the one or more available accelerators. Based on a determination that the query operation can be offloaded to one or more of the one or more available accelerators, the method also includes creating software structures to interface with a selected accelerator and executing the query operation on the selected accelerator. Based on a determination that the query operation cannot be offloaded to one or more of the one or more available accelerators, the method further includes executing the query operation in software.

Mapping query operations in database systems to hardware based query accelerators

A computer-implemented method, computer program product, and computing system for implementing multi-temporal tables in a database is described. One or more databases are utilized, wherein the one or more databases implement a first temporal table that includes a first and a second time domain. The one or more databases are enabled to implement a second temporal table that includes at least a third time domain, wherein the second temporal table is associated with the first temporal table.

System and method for implementing multi-temporal database functionality

Methods and arrangements for facilitating accelerations of database functions. A field programmable gate array is incorporated. At least one query control block is incorporated in the field programmable gate array, and database management system operations are accelerated via the field programmable gate array. The accelerating includes employing the at least one query control block to execute a query without reconfiguring the field programmable gate array.

Facilitating field programmable gate array accelerations of database functions

An apparatus comprises a hardware accelerator coupled to a memory. The hardware accelerator comprises one or more decompression units. The one or more decompression units are reconfigurable. The hardware accelerator may be a field-programmable gate array. The hardware accelerator may also comprise one or more reconfigurable scanner units. The one or more decompression units, in the aggregate, are operative to decompress one or more rows of a database at a bus speed of the coupling between the hardware accelerator and the memory. Two or more decompression units are operative to decompress two or more rows of a database in parallel. The apparatus allows for hardware accelerated row decompression.

Accelerated row decompression

Techniques are provided for encoded data processing which allows for continuous data processing as encoded data changes. Data is decomposed into one or more blocks with each block containing at least one data record. At least one data record within a given block is encoded with a first encoding process selected from one or more encoding processes. The first encoding process is associated with the given data block. Techniques evaluate whether or not to implement an encoding change for a given block when updating a given data record in the given block. Responsive to the evaluation, the given block is re-encoded with a second encoding process. Responsive to the re-encoding, the association of the given block is updated. A map is formed to convert the given data record encoded with the first encoding process to the second encoding process so as to preserve comparative relationships of the given data record.

Encoded data processing

Techniques are provided for accessing sector data. An embedded storage function is received. One or more data management functions are generated in response to receiving the embedded storage function. The one or more data management functions are invoked to retrieve the sector data from a sector table.

Implementing storage management functions using a data store system

Techniques for encoded data processing which allow for continuous data processing as encoded data changes. Data is decomposed into one or more blocks with each block containing at least one data record. At least one data record within a given block is encoded with a first encoding process selected from one or more encoding processes. The first encoding process is associated with the given data block. Techniques evaluate whether or not to implement an encoding change for a given block when updating a given data record in the given block. Responsive to the evaluation, the given block is re-encoded with a second encoding process. Responsive to the re-encoding, the association of the given block is updated. A map is formed to convert the given data record encoded with the first encoding process to the second encoding process so as to preserve comparative relationships of the given data record.

A row property provides a mechanism for implementing advanced functional behavior in a relational database management system (RDBMS) without introducing new data types. A row property is part of a table definition, such that, when a table is defined in the RDBMS, at least one row property is specified for one or more associated columns of rows of the table, wherein the row property has an associated functional behavior that is predefined within the RDBMS. The columns associated with the row property are generally of existing data types supported by an RDBMS. A row property may be invoked when the RDBMS processes a language statement that references the row property. When the row property is invoked, the RDBMS executes programming logic associated with the row property, in order to perform the advanced functional behavior using data stored in the associated columns.

Technique to introduce advanced functional behaviors in a database management system without introducing new data types

Some aspects of the invention provide methods, systems, and computer program products for creating a static dictionary in which longer byte-strings are preferred. To that end, in accordance with aspects of the present invention, a new heuristic is defined to replace the aforementioned frequency count metric used to record the number of times a particular node in a data tree is visited. The new heuristic is based on counting the number of times an end-node of a particular byte-string is visited, while not incrementing a count for nodes storing characters in the middle of the byte-string as often as each time such nodes are visited. The result is an occurrence count metric that favors longer byte-strings, by being biased towards not incrementing the respective occurrence count values for nodes storing characters in the middle of a byte-string.

Methods of creating a dictionary for data compression

The present invention provides a computer-readable medium and system for selecting a set of n-grams for indexing string data in a DBMS system. Aspects of the invention include providing a set of candidate n-grams, each n-gram comprising a sequence of characters; identifying sample queries having character strings containing the candidate n-grams; and based on the set of candidate n-grams, the sample queries, database records, and an n-gram space constraint, automatically selecting, given the space constraint, a minimal set of an n-grams from the set of candidate n-grams that minimizes the number of false hits for the set of sample queries had the sample queries been executed against the database records.

Selection of a set of optimal n-grams for indexing string data in a DBMS system under space constraints introduced by the system

An apparatus, system, and method are disclosed for supporting storage functions using an embedded database management system. The apparatus includes a disk controller configured to receive input/output (I/O) requests from a host, an embedded database management system module, and a conversion module configured to translate the input/output requests into database requests and communicate the database requests with the embedded database management system module. The system may include the apparatus, a network, and a plurality of storage devices coupled to the network and configured to store data. The method includes receiving input/output (I/O) requests from a host, translating the input/output requests into database requests, communicating the database requests with an embedded database management system module, and executing the database requests.

Apparatus, system, and method for supporting storage functions using an embedded database management system

A system and computer readable storage medium for creating an in-memory physical dictionary for data compression are provided. A new heuristic is defined for converting each of a plurality of logical nodes into a corresponding physical node forming a plurality of physical nodes. Each of the physical nodes are placed into the physical dictionary while traversing the dictionary tree in descending visit count order. Each physical node is placed in its nearest ascendant's cache-line with sufficient space. If there is no space in any of the ascendant's cache-line, then the physical node is placed into a new cache-line, unless a pre-defined packing threshold has been reached, in which case the physical node is placed in the first available cache-line.

Method and system for creating an in-memory physical dictionary for data compression

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San Jose, CA, United States of America

Balakrishna Raghavendra Iyer