Abstract: A SEQUENCED request a) to apply a temporal Source table to a temporal Target table under a predicate is received. The Source table includes a plurality of rows that qualify to apply to a single Target table row under the predicate. The predicate specifies a Source table join column. Each of the plurality of Source table rows and the single Target table row include a ValidTime dimension. The plurality of Source table rows is b) ordered by the Source table join column and a period-to-be-modified. The next of the ordered plurality of Source table rows is c) applied by determining that the Target table row has a TransactionTime and, in response, closing out the TransactionTime of the Target table row. Applying the next of the ordered plurality of Source table rows includes identifying an RDIFF range as the period-to-be-modified of the Source table row being applied that is later than the ValidTime range of the single Target table row.

Abstract: A method, computer program and database system are disclosed for guiding the development of workload group definition (WD) classifications for a database system having resources. WD classification information is provided where a workload group is a set of system requests having characteristics defined by a WD and a WD classification identifies one or more WDs with similar performance requirements. If WD classification is not acceptable, one or more of the following functions is performed until WD classification is acceptable: (a) splitting one or more WDs; and (b) merging two or more WDs.

Abstract: 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.

Abstract: A method, computer program, and database system are disclosed. A plurality of instances of a request to a database system are received. All instances of the request have a same set of variables to use in executing the request. The values of the variables are supplied by data in a data source. A specific plan for executing one instance of the request is generated. Generating the specific plan includes taking into account data in the data source. The specific plan is executed on the database system. A system run-time metric and a parsing time for executing the specific plan are captured and saved. A generic plan is generated and cached based on a comparison of the system run-time metric and the parsing time for executing the specific plan.

Abstract: A request is received at a computer programmed as a database system. The request is a request selected from the group consisting of a query and a utility. A business concept is associated with the request. The business concept is a business concept selected from the group consisting of “who” information defining the source of the request, “what” information defining the processing to be performed by the request, “where” information defining a database object that the request will affect. The computer maps the received request to a database feature setting by mapping the business concept associated with the request to a workload. The workload is defined by a workload definition including a workload classification attribute that maps to the business concept of the request, a workload throttling attribute that defines conditions under which requests assigned to the workload are throttled. Submission of the request to the database system for processing is delayed based on the workload definition.

Abstract: 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 (“TRC”) 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 selects a snapshot from the parent using a predicate of the form parent.[period attribute] contains a point in time (t1).

Abstract: A computer receives a query for optimization. The query includes a SEQUENCED join between a temporal parent table and a temporal child table. The parent table has one or more rows. The child table has one or more rows. The parent table has a Primary Key (“PK”) column having a value for each row. The parent table has a temporal dimension having a value for each row. The child table has a Foreign Key (“FK”) column having a value for each row. The child table has a temporal dimension. The child table's temporal dimension has a value for each row. The computer determines that the query, the parent table, the child table, and the join satisfy a set of CURRENT temporal join elimination criteria. The computer determines that the query, the parent table, the child table, and the join satisfy a set of SEQUENCED temporal join elimination criteria. In response, the computer eliminates the join from the query to produce an optimized form of the query.

Abstract: A temporal table is present in an active data warehouse (“ADW”) on a massively parallel processing system (“MPP system”). The MPP system includes a plurality of units of parallelism. Each of the plurality of units of parallelism maintains its own moving system time separate from that of the other units of parallelism. A load-job for the ADW is accepted. The load-job includes a requested modification to an identified row. The identified row is stored in the temporal table on a first of the MPP system's units of parallelism. The requested modification is implemented on the identified row. The identified row is timestamped with the moving system time maintained by the first of the MPP system's units of parallelism at the time of the implementation of the modification.

Abstract: A method, system, and computer program for optimizing execution of a DML statement on a temporal database are disclosed. A first execution package is provided to an execution engine. The first execution package includes a plurality of operations to be executed if the contents of a row in a table in the temporal database indicate the row has a first temporal condition. A second execution package is provided to the execution engine. The second execution package includes a plurality of operations to be executed if the contents of the row in the table in the temporal database indicate the row has a second temporal condition. The execution engine is run to produce a result. The result is saved.

Abstract: A base table temporal row affected by a transaction is timestamped. The temporal row has a row ID. The temporal row in the base table is modified according to the transaction. The row ID for the modified temporal row is associated with an identifier for the transaction in a temporal work table. Upon committing the transaction: the temporal work table is searched to determine the row ID of the temporal row modified by the transaction, and a commit-time is saved into the temporal row identified by the row ID.

Abstract: A method, computer program, and database system are disclosed for identifying a second source of a request sent to a database management system by a first source. A database message is received from the first source. The database message includes a second value for a second source-identifying parameter. The second value identifies a second source. The second value for the second source-identifying parameter is stored in a log.

Abstract: A computer system programmed as a database receives a query Q1. Q1 includes a predicate. The predicate includes a reference to a current timestamp of time TT1. The database has R data structures. The computer system creates a plan, Plan 1, to execute Q1. Plan 1 includes the identification of a first set of data structures, P1, to be accessed in executing Plan 1, at the current timestamp of time TT1. The number of data structures in P1 is less than R. The computer system determines that Plan 1 is valid for a period of time. The computer system stores in a cache Plan 1 and an indication that Plan 1 is valid for the period of time.

Abstract: A method, database system and computer program are disclosed for performing a temporal join between two temporal database tables. The method includes determining a selected table intersection between a period of interest and a time period value for a selected table row, scanning an inner table for a row that matches the selected table on the join conditions and overlaps the selected table intersection, and determining the remainder time period values from the selected table intersection.

Abstract: 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.

Abstract: 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? 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? partitions selected is a cost based decision based on the estimated number of rows in the input intermediate result sets.

Abstract: A SQL query that includes an IN-List is optimized by utilizing an array insert to insert the IN-List into a spool and piggybacking IN-List rows into a join step.

Abstract: A SQL query that includes an IN-List is optimized by (1) performing an evaluation to determine whether access to a table can be performed as a join operation, (2) converting the IN-List to an IN-LIST relation, and (3) joining the IN-List relation with the table to access the data in the table.

Abstract: Methods, computer programs, and database systems for performing a database query to join a column A and a column B on an inequality condition are disclosed. A database includes value-count indexes for columns A and B. Minimum and a maximum values for A and B are determined, using the value-count indexes for A and B, respectively. The method includes defining three or more sets of values in A and B, relative to the minimum and maximum values for B and A, respectively. The method includes generating one or more Cartesian products between values in A and B. The database query is performed on a set of values in A and a set of values in B to generate a partial query result. The method includes merging one or more Cartesian products and the partial query result.

Abstract: Processing of a request is optimized. The request has one or more predicates. A list of the one or more predicates in the request is created and predicates for which an actual cost has not been stored or for which a cost cannot be estimated are pruned from the list. An access path for the each of the predicates is selected. The request is processed using the selected access paths producing one or more actual predicate costs. The one or more actual predicate costs are stored.

Abstract: A database query is optimized for a star database schema that includes at least one fact table and at least one dimension table, where the database query includes an IN-List condition. During optimization, the IN-List is transformed into a relation and the relation is joined with the dimension table to produce a join result. The join result is then joined to the fact table.