Netezza Corporation

Ibm International Group Bv

Paraccel LLC

Other

Netezza Corporaton

Huawei Technologies Co., Limited

Barry M Zane

Foster D Hinshaw

John K Metzger

Sanjay G Dixit

Venkannababu Tammisetti

David L Meyers

Premanand Yerabothu

David E Steinhoff

James P Ballard

David A Utter

Steven T Almy

Michael Sporer

William K Stewart

Craig S Harris

Sharon Miller

Philip J MacDonald

Dana A Kirkpatrick

Vincent F Femia

Raymond J Andraka

Claus Hofmann

Mario A Guthrie

A usage model and the underlying technology used to provide sequence analysis as part of a relational database system. Included components include the semantic and syntactic integration of the sequence analysis with an existing query language, the storage methods for the sequence data, and the design of a multipart execution scheme that runs the sequence analysis as part of a potentially larger database join, especially using parallel execution techniques.

Performing sequence analysis as a relational join

A database appliance in which two or more internetworked data storage units are used to coordinate the storage and retrieval of database records. One or more central database processing units are also associated with the data storage units. A network infrastructure provides the ability for the central database processors and storage processors to communicate as network nodes, with the network infrastructure using a communication protocol. A software application for executing database operations executes in a distributed fashion with portions of the database application executing on at least one central database processor and other portions executing on the data storage processors. At least a portion of the database application is implemented within and/or coordinated by a communication process that is executing the communication protocol. This coordination takes place such that data blocks are passed between the communication process and at least one portion of the database application process by passing data block reference information. In accordance with other aspects of the present invention, the communication process may have at least portions of the database application process executing within it. These database application operations executing within the same context as the communication process may include database operations such as join, sort, aggregate, restrict, reject, expression evaluation, statistical analysis or other operations.

Network interface for distributed intelligence database system

A system and method for enhancing data throughput in data warehousing environments by connecting multiple servers having local storages with designated external storage systems, such as, for example, those provided by SANS. The system and method may preserve a full reference copy of the data in a protected environment (e.g., on the external storage system) that is fully available. The system and method may enhance overall I/O potential performance and reliability for efficient and reliable system resource utilization.

Storage performance optimization

A usage model and the underlying technology used to provide sequence analysis as part of a relational database system. Included components include the semantic and syntactic integration of the sequence analysis with an existing query language, the storage methods for the sequence data, and the design of a multipart execution scheme that runs the sequence analysis as part of a potentially larger database query, especially using parallel execution techniques.

Performing sequence analysis as a multipart plan storing intermediate results as a relation

The same data is stored in at least two different database management systems (DBMS's), including a columnar DBMS () and a non-columnar (e.g. row-oriented) DBMS (). The columnar DBMS may provide fast responses to queries involving aggregation, and such queries can be routed to the columnar DBMS. A query may be routed to the non-columnar DBMS if for example the query execution involves only small DBMS tables on the non-columnar DBMS. In some situations, an execution time estimate can be obtained from each DBMS, and the query is routed to the DBMS providing the shortest estimate.

Query handling in databases with replicated data

A system and method for enhancing data throughput in data warehousing environments by connecting multiple servers having local storages with designated external storage systems, such as, for example, those provided by SANs. The system and method may preserve a full reference copy of the data in a protected environment (e.g., on the external storage system) that is fully available. The system and method may enhance overall I/O potential performance and reliability for efficient and reliable system resource utilization.

System and method for enhancing storage performance in analytical database applications

This invention relates generally to a system for processing database queries, and more particularly to a method for generating high level language or machine code to implement query execution plans. In one preferred embodiment, the method begins by receiving a subject query, and then forming an execution plan corresponding to the subject query. The execution plan will typically have a sequence of component snippets or pieces and corresponding processes for implementing the pieces. For at least one piece in the plan, the process then (a) generates source code using different code generation techniques as a function of expected runtime processing machine types; and then (b) compiles the generated source code to form machine executable code for implementing the subject query. As a result, the query executed directly as machine executable code thereby avoiding runtime interpretation of the pieces in the execution plan.

SQL code generation for heterogeneous environment

A system and method from processing database queries allows for cost and locale based distribution for execution of database queries. The database queries are executed on execution engines that provide flexible configuration and overlapping functionality. The system reduces various costs, including elapsed time, required to perform database queries. The method provides processing of a database query using a database catalog comprising database table locality information, record locality information and execution engine information. A query optimizer receives the query and accesses the catalog to create a query execution plan comprising locality-based database operations. A central database operation processor providing a first execution engine executes the query execution plan by performing at least a portion of the locality-based database operations and distributing at least a portion of the locality-based database operations as a subplan. A second database operation processor providing a second execution engine executes the subplan received from the central processor.

Optimized database appliance

A programmable streaming data processor that can be programmed to recognize record and field structures of data received from a streaming data source such as a mass storage device. Being programmed with, for example, field information, the unit can locate record and field boundaries and employ logical arithmetic methods to compare fields with one another or with values otherwise supplied by general purpose processors to precisely determine which records are worth transferring to memory of the more general purpose distributed processors. The remaining records arrive and are discarded by the streaming data processor or are tagged with status bits to indicate to the more general purpose processor that they are to be ignored. In a preferred embodiment, the streaming data processor may analyze and discard records for several reasons. The first reason may be an analysis of contents of the field. Other reasons for record blocking may have to do with tagging records that are to be visible to particular users depending upon a series of concurrent transactions.

Intelligent storage device controller

A data processing system having two or more groups of data processors that have attributes that are optimized for their assigned functions. A first group consists of one or more host computers responsible for interfacing with applications and/or end users to obtain queries and for planning query execution. A second processor group consists of many streaming record-oriented processors called Job Processing Units (JPUs), preferably arranged as an MPP structure. The JPUs typically carry out the bulk of the data processing required to implement the logic of a query. Each of the JPUs typically include a general purpose microcomputer, local memory, one or more mass storage devices, and one or more network connections. Each JPU also has a special purpose programmable processor, referred to herein as a Programmable Streaming Data Processor (PSDP). The PSDP serves as an interface between the CPU of a JPU and the mass storage device, to offload functions from the CPU of the JPU.

Programmable streaming data processor for database appliance having multiple processing unit groups

An asymmetric data record processor and method includes host computers and Job processing units (JPU's) coupled together on a network. Each host computer and JPU forms a node on the network. A plurality of software operators allow each node to process streams of records. For each operator in a given sequence within nodes and across nodes, output of the operator is input to a respective succeeding operator. Data processing follows a logical data flow based on readiness of a record. As soon as a record is ready it is passed for processing from one part to a next part in the logical data flow. The flow of records during data processing is substantially continuous and of a streaming fashion.

Asymmetric streaming record data processor method and apparatus

A system from processing database queries allows for cost and locale based distribution for execution of database queries. The database queries are executed on execution engines that provide flexible configuration and overlapping functionality. The system reduces various costs, including elapsed time, required to perform database queries. The system provides processing of a database query using a database catalog comprising database table locality information, record locality information and execution engine information. A query optimizer receives the query and accesses the database catalog to create a query execution plan comprising locality-based database operations. A central database operation processor providing a first execution engine executes the query execution plan by performing at least a portion of the locality-based database operations and distributing at least a portion of the locality-based database operations as a subplan. A second database operation processor providing a second execution engine executes the subplan received from the central database operation processor. At least one of the database operations can be executed on either the first execution engine or the second execution engine. A storage unit stores at least a portion of database tables and records. A data communications network connects the central database processor to the second database processor.

Growing community of inventors

Wayland, MA, United States of America

Barry M Zane