Teradata Us, Inc.

Ncr Corporation

Teradota Us, Inc.

Michael Warren Watzke

Bhashyam Ramesh

Curt J Ellmann

Gang Luo

Jeffrey F Naughton

Ambuj Shatdal

Donald Raymond Pederson

Steven Bart Cohen

Manjula Koppuravuri

Jaiprakash G Chimanchode

Chandrasekhar Tekur

Rangavajjula K N Sai Krishna

Muthukumaran Raveendiran

Jaya Saxena

Curt L Ellmann

Peter Gerritson

Venkata Ramana Jyothula

Xidong Wang

In some examples, in response to a join query to join a plurality of tables, a first processing engine retrieves tuples of a first table from a subset of objects of a data store, and adds content of the retrieved tuples to an in-memory table, where the objects are range partitioned across a plurality of processing engines based on respective ranges of values of at least one join attribute in the join query. The first processing engine retrieves, from the data store, tuples of a second table of the plurality of tables based on a range of values of the at least one join attribute in the retrieved tuples of the first table. The first processing engine performs an in-memory join of the plurality of tables based on the retrieved tuples of the second table and the in-memory table.

Range partitioned in-memory joins

A query that is frequently processed to access an object storage is identified. Results from the query returned from the object storage is transformed into a relational database format as a materialized view. When the query is submitted a subsequent time, updated results are managed from the materialized view, other materialized views, and/or the object storage when needed.

Point in time consistent materialization for object storage environments

In some examples, a database system includes a plurality of processing engines to process data for database operations, and instructions executable on at least one processor to insert first data into first objects stored in a remote data store coupled to the database system over a network, and select, based on a size of the first data, a first partition level from a plurality of different partition levels to associate with the first objects. Different partition levels define different quantities of hash buckets that correspond to different distributions of objects across the plurality of processing engines. The first partition level is associated with the first objects.

Multilevel partitioning of objects

In some examples, a database system includes a storage medium to store a materialized view (MV) that includes data satisfying an MV condition. At least one processor is to receive a query including a query condition, determine that the query condition partially matches the MV condition, and access a part of the data in the MV partially satisfy the query.

Using materialized views to respond to queries

In some examples, a system stores data in a logically disconnected data store. In response to a query for data in the data store, the system accesses metadata of objects stored in the data store, the metadata including information of a respective range of values of at least one clustering attribute in data contained in each respective object of the objects. The system partitions the objects across the plurality of processing engines based on the information of the respective ranges of values of the at least one clustering attribute in the data contained in the objects. The system assigns, based on the partitioning, the objects to respective processing engines of the plurality of processing engines.

Assignment of objects to processing engines for efficient database operations

A method for spooling data for use in joining a small table with a large table in a relational database system. The method analyzes a join condition for combining records from the small and large tables, selects qualified rows from the large table, and writes the qualified rows to a spool file. The spool file includes a first partition containing hash values of all bind terms for the join condition; a second partition including a join column with a best selective bind term; and at least one additional partition including additional join columns used in bind terms. The partitions are grouped together within a container row in the spool file, and multiple container rows are written together within a super-container row in the spool file.

Spool file for optimizing hash join operations in a relational database system

A database system may process multiple column-oriented tasks in parallel for a database being stored according to a row-partitioning protocol. The database system may determine when the query should process the column-oriented task serially or in parallel. For parallel processing, the database system may generate processing tasks for each unique column-oriented task contained in the query used to retrieve column data and to process the column data according to the column-oriented tasks requested. A method of operating the database system may determine that multiple column-oriented tasks included in a query are to be processed in parallel. The method may further include generating a processing task for each unique column-oriented task included in the query. The method may further include performing the column-oriented tasks in parallel based on the processing threads. The method may implement various considerations in determining to process to the column-oriented tasks in parallel.

Column-oriented task execution in a row-partitioned database system

A query is received. It is determined that the query includes an inner join between a parent table and a child table. It is determined that the following relationships exist between the parent table and the child table: referential integrity ('RI') between a primary key attribute (pk) in the parent table and a foreign key attribute (fk) in the child table, where 'attribute' is defined to mean one or more columns; and a temporal relationship constraint (&#x201c;TRC&#x201d;) between a period attribute in the parent table and a TRC-attribute in the child table, the TRC-attribute being a date or time attribute. It is determined that the query does not access any attribute in the parent table other than the pk. It is determined that the query specifies an equality predicate of the form pk=fk. It is determined that the query specifies a condition that requires the TRC-attribute value to be contained in the parent table's period attribute duration. It is determined that the query contains no other qualification conditions on the parent table's period attribute. The inner join is eliminated when planning execution of the query. The query is executed to produce a result. The result is saved.

Eliminating inner joins based on a contained predicate and a temporal relationship constraint

Trip data that includes points traversed during corresponding trips is received. Transportation network data that describes geographic locations and links between the geographic locations is received. The trip data and transportation network data are partitioned across a plurality of processing units executing on one or more processors. At each of the plurality of processing units, a subset of the trip data at the corresponding processing unit is locally matched to a subset of the transportation network data at the corresponding processing unit to identify a subset of paths of the transportation network data traversed by one or more of the trips.

Matching trip data to transportation network data

There is provided a method, system and computer program for updating at least one component in a multi-component software application. The method includes receiving application data describing characteristics of the software application, receiving update data describing at least one update applicable to the software application and reviewing the application data and update data to determine whether the at least one update is applied to the software application.

Software update system and method

A database system is capable of processing a query and providing a progress indicator of the processing of the query based on at least a first cost factor. Initially, an estimate is set for the first cost factor. During processing of the query, the estimate of the first cost factor is updated to enable refinement of the progress indicator.

Providing a progress indicator in a database system

A method, computer program, database system and data structure for indexing spatial objects are disclosed. Each spatial object has a location in an n-dimensional space. The indexing is for use in a partitioned parallel environment including P partitions. Each partition resides on one or more parallel processing systems. The n-dimensional space is divided into quad-tree cells (QTCs) in a quad-tree structure. Each spatial object is assigned to one or more QTCs based on the location of the spatial object in the n-dimensional space. A spatial object index entry is created which includes a designator for the QTC to which the spatial object is assigned and a pointer to the spatial object. The entries are sorted by their QTC numbers into a list. The list of entries is divided into P substantially equal parts. The entries associated with each part are stored in a different one of the P partitions.

Spatial indexing

A method or apparatus for use with a database system that stores a join view associated with plural base relations includes receiving modification operations to modify at least two of the base relations of the join view, and re-ordering the received modification operations to avoid concurrent execution of modification operations of more than one of at least two base relations.

Rescheduling of modification operations for loading data into a database system

A method and system for performing logical partial declustering in a shared-nothing database environment. The solution defines a partial declustering technique that can be used to dynamically adapt the declustering of base tables or intermediate result sets. The partial declustering technique is defined to limit the number of partitions (P) involved in an operation. The technique is defined to limit the operation to a subset of the system partitioning map (SPM). There are two components: the association between the data values and partitions is altered by restricting the data values to P' partition values where P&#x2032; is less than P; and the actual partitions of the SPM selected are then derived based on a seed derived from a dynamic parameter, such as a session number, or a static parameter, such as a table identifier. In the case of intermediate result sets the number of P&#x2032; partitions selected is a cost based decision based on the estimated number of rows in the input intermediate result sets. In the case of a base table the number of P&#x2032; partitions is selected based on the table DDL. There is no physical partitioning definitions, rather logical partitions are defined based on subsetting the SPM.

Method and system for performing logical partial declustering

A method and apparatus identifies SQL statements in a first transaction that specify modification operations that are commutative and associative. The SQL statements are combined into one SQL statement, and the one SQL statement is submitted to a database system. Optionally, or alternatively, multiple transactions can be grouped together into one transaction.

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Fitchburg, WI, United States of America

Michael Warren Watzke