Abstract: Techniques are described herein for grouping of operations in local memory of a processing unit. The techniques involve adding a first operation for a first leaf operator of a query execution plan to a first pipelined group. The query execution plan includes a set of leaf operators and a set of non-leaf operators. Each leaf operator of the set of one or more leaf operators has a respective parent non-leaf operator and each non-leaf operator has one or more child operators from among the set of leaf operators or others of the set of non-leaf operators. The techniques further involve determining a memory requirement of executing the first operation for the first leaf operator and executing a second operation for the respective parent non-leaf operator of the first leaf operator. The output of the first operation is input to the second operation. The techniques further involve determining whether the memory requirement is satisfied by an amount of local memory.

Abstract: Techniques related to distributed relational dictionaries are disclosed. In some embodiments, one or more non-transitory storage media store a sequence of instructions which, when executed by one or more computing devices, cause performance of a method. The method involves generating, by a query optimizer at a distributed database system (DDS), a query execution plan (QEP) for generating a code dictionary and a column of encoded database data. The QEP specifies a sequence of operations for generating the code dictionary. The code dictionary is a database table. The method further involves receiving, at the DDS, a column of unencoded database data from a data source that is external to the DDS. The DDS generates the code dictionary according to the QEP. Furthermore, based on joining the column of unencoded database data with the code dictionary, the DDS generates the column of encoded database data according to the QEP.

Abstract: Techniques related to relational dictionaries are disclosed. In some embodiments, one or more non-transitory storage media store a sequence of instructions which, when executed by one or more computing devices, cause performance of a method. The method involves storing a code dictionary comprising a set of tuples. The code dictionary is a database table defined by a database dictionary and comprises columns that are each defined by the database dictionary. The set of tuples maps a set of codes to a set of tokens. The set of tokens are stored in a column of unencoded database data. The method further involves generating encoded database data based on joining the unencoded database data with the set of tuples. Furthermore, the method involves generating decoding database data based on joining the encoded database data with the set of tuples.

Abstract: Techniques related to a sparse dictionary tree are disclosed. In some embodiments, computing device(s) execute instructions, which are stored on non-transitory storage media, for performing a method. The method comprises storing an encoding dictionary as a token-ordered tree comprising a first node and a second node, which are adjacent nodes. The token-ordered tree maps ordered tokens to ordered codes. The ordered tokens include a first token and a second token. The ordered codes include a first code and a second code, which are non-consecutive codes. The first node maps the first token to the first code. The second node maps the second token to the second code. The encoding dictionary is updated based on inserting a third node between the first node and the second node. The third node maps a third token to a third code that is greater than the first code and less than the second code.

Abstract: Techniques are described herein for grouping of operations in local memory of a processing unit. The techniques involve adding a first operation for a first leaf operator of a query execution plan to a first pipelined group. The query execution plan includes a set of leaf operators and a set of non-leaf operators. Each leaf operator of the set of one or more leaf operators has a respective parent non-leaf operator and each non-leaf operator has one or more child operators from among the set of leaf operators or others of the set of non-leaf operators. The techniques further involve determining a memory requirement of executing the first operation for the first leaf operator and executing a second operation for the respective parent non-leaf operator of the first leaf operator. The output of the first operation is input to the second operation. The techniques further involve determining whether the memory requirement is satisfied by an amount of local memory.

Abstract: A method, system, and computer program product for normalized ranking of semantic query search results. The method commences by forming a SPARQL query, the SPARQL query specifying a collection of named RDF graphs, then executing the SPARQL query to retrieve matched documents selected from the collection of named RDF graphs. Having retrieved the matches, the method calculates an absolute normalized score for the matched document. The calculation of an absolute normalized score for a second matched document allows for relevance ranking. To enhance the relationship of the computer-calculated score to the relevance (and not solely to occurrence counts) embodiments consider the number of distinct variables selected in the SPARQL query, and also consider the total number of bindings to the aforementioned variables. For comparing from among possibly different sized documents, a further normalization component is implemented by considering the total number of triples found in the document's underlying subgraph.

Abstract: A method, system, and computer program product for normalized ranking of semantic query search results. The method commences by forming a SPARQL query, the SPARQL query specifying a collection of named RDF graphs, then executing the SPARQL query to retrieve matched documents selected from the collection of named RDF graphs. Having retrieved the matches, the method calculates an absolute normalized score for the matched document. The calculation of an absolute normalized score for a second matched document allows for relevance ranking. To enhance the relationship of the computer-calculated score to the relevance (and not solely to occurrence counts) embodiments consider the number of distinct variables selected in the SPARQL query, and also consider the total number of bindings to the aforementioned variables. For comparing from among possibly different sized documents, a further normalization component is implemented by considering the total number of triples found in the document's underlying subgraph.

Abstract: Systems, methods, and other embodiments associated with query pruning via query rewrite are described. One example method includes receiving a query on a partitioned table that will result in a first query plan that includes accessing a local domain index on each partition in the database. The query is rewritten to generate a second query that will result in a second query plan that includes accessing a global domain index instead of the local domain index on each partition in the database.

Abstract: Systems, methods, and other embodiments associated with sequence matching with no more than a number E errors are disclosed. A test fragment to be located within a target sequence with at most a number E errors is received. The test fragment is broken into E+1 test sub-fragments. If one test sub-fragment is located within the target sequence with no errors; a determination is made as to whether the other test sub-fragments are located within the target sequence adjacent to the one test sub-fragment with a total of at most E errors. If the other test sub-fragments are located within the target sequence adjacent the one test sub-fragment with at most E errors, a location of the test fragment within the target sequence is returned.

Abstract: Systems, methods, and other embodiments associated with visualizing data using summary graphs are described. One example method includes constructing a summary graph for display. The summary graph represents the data as a summary node having a plurality of property edges connected to the summary node. The summary node represents the set of values for the node in the data.

Abstract: Systems, methodologies, media, and other embodiments associated with supporting queries with hard time constraints are described. One exemplary system embodiment includes logic for accepting a query having a hard time constraint. The example system may also include logic for selectively rewriting the query having the hard time constraint into a query having a row limitation or a sample percentage limitation. In one example, the row limitation or sample percentage limitation are computed by repetitively comparing an estimated query execution time to the hard time constraint. The example system may also include logic for establishing a timer(s) associated with the rewritten query.

Abstract: In one embodiment, a database server registers one or more functions included in a user-defined index that includes one or more auxiliary properties. The one or more functions are operable to generate index entries of the user-defined index for the one or more auxiliary properties. The one or more auxiliary properties are different than, and in addition to, a primary property of the user-defined index that provides for evaluating a query operator. The database server receives a first statement that defines the user-defined index, where the first statement includes one or more parameters that define the one or more auxiliary properties. The database server invokes the one or more functions in response to the first statement, where the one or more functions when invoked generate and store the index entries of the user-defined index according to the one or more parameters that define the one or more auxiliary properties.

Abstract: A method, system, and computer program product provides improved performance for rebuild of user-defined indexes during partition maintenance operations (partition split, merge, and move). A method of maintaining a index of a partitioned database table comprises performing a partition maintenance operation on the partitioned database table wherein a plurality of rows of the partitioned database table are moved from one partition to another, storing mapping information for at least some of the plurality of moved rows, including an old mapping for each of the moved rows and a corresponding new mapping for each of the moved rows, and when rebuilding the index, replacing an old mapping in the index for each of the plurality of moved rows with the corresponding stored new mapping for each of the plurality of moved rows.

Abstract: Systems, methods, and other embodiments associated with sequence matching with no more than a number E errors are disclosed. A test fragment to be located within a target sequence with at most a number E errors is received. The test fragment is broken into E+1 test sub-fragments. If one test sub-fragment is located within the target sequence with no errors; a determination is made as to whether the other test sub-fragments are located within the target sequence adjacent to the one test sub-fragment with a total of at most E errors. If the other test sub-fragments are located within the target sequence adjacent the one test sub-fragment with at most E errors, a location of the test fragment within the target sequence is returned.

Abstract: Systems, methodologies, media, and other embodiments associated with supporting queries with soft time constraints are described. One exemplary system embodiment includes logic for accepting a query having a soft time constraint. The example system may also include logic for rewriting the query having the soft time constraint into a query having a row limitation or a sample percentage limitation. In one example, the row limitation or sample percentage limitation are computed by repetitively comparing an estimated query execution time to the soft time constraint.

Abstract: In one embodiment, a database server registers one or more functions included in a user-defined index that includes one or more auxiliary properties. The database server receives a query that specifies one or more parameters. A query optimizer generates a plurality of execution plans for evaluating the query. The query optimizer estimates a plurality of total costs respectively associated with the plurality of execution plans, where estimating a particular total cost associated with a particular execution plan comprises: invoking the one or more functions with one or more function arguments based on the one or more parameters; receiving one or more index costs that are associated with using the one or more auxiliary properties of the user-defined index to evaluate the query; and determining the particular total cost based on the one or more index costs.

Abstract: Systems, methodologies, media, and other embodiments associated with supporting materialized views with user-defined aggregates are described. One example system includes logic for exposing a set of interface actions to support a user-defined aggregate in a materialized view associated with a base table. The materialized view may store both the user-defined aggregate and a user-defined aggregate context that facilitates logically connecting the user-defined aggregate to the base table. The example system may also include logic for supporting the user-defined aggregate. The support may be based on the set of interface actions. Example systems and methods may, therefore, facilitate incremental updating of the materialized view and/or rewriting a query to access the materialized view.

Abstract: Systems, methods, and other embodiments associated with query pruning via query rewrite are described. One example method includes receiving a query on a partitioned table that will result in a first query plan that includes accessing a local domain index on each partition in the database. The query is rewritten to generate a second query that will result in a second query plan that includes accessing a global domain index instead of the local domain index on each partition in the database.

Abstract: A database management system that has bitmap values in which set bits in a representation of a bitstring specify a set of objects whose definitions are built into the database management system. The database management system further includes user-accessible operations on the bitmap values. The bitmap values are represented by means of a mapping specifier that specifies a range of the set of objects and a representation of a string of bits that has been mapped onto the set of object specified by the range specifier. Objects containing bitmap values may be indexed by means of an index tree that includes summary bitmap values.

Abstract: Systems, methods, and other embodiments associated with visualizing data using summary graphs are described. One example method includes constructing a summary graph for display. The summary graph represents the data as a summary node having a plurality of property edges connected to the summary node. The summary node represents the set of values for the node in the data.