Abstract: In an example, data from a source location is merged into a target location containing existing data, in which the source location and the target location contain tuples of data. For each tuple in the source location, during a single operation, a determination is made as to whether there is a matched tuple in the target location that satisfies a predetermined condition. For each matched tuple that satisfies the predetermined condition, the matched tuple in the target location is updated with a count value that is equal to a count of the matched tuple in the source location and the target location. In addition, for each tuple that does not have a matched tuple that satisfies the predetermined condition, the unmatched tuple is inserted into the target location.

Abstract: As part of managing the loading of data from a source onto a database, according to an example, an interface through which a user is to define logic related to the loading of the data onto the database is provided. The user-defined logic pertains to at least one of a user-defined location identification of the source, a user-defined filter to be applied on the data, and a user-defined parsing operation to be performed on the data to convert the data into an appropriate format for the database. In addition, the user-defined logic is received and the user-defined logic is implemented to load the data onto the database.

Abstract: A method for query processing includes receiving a query, and determining a query type by determining if the query is a structured query language (SQL) query including multiple distinct aggregates (MDAs), or a SQL query including cube, rollup or grouping sets operations. Based on the determination, the method includes processing the query to generate an output, and performing a predetermined number of maximum group by operations on the output based on the query type to generate a response to the query.

Abstract: In an example, data from a source location is merged into a target location containing existing data, in which the source location and the target location contain tuples of data. For each tuple in the source location, during a single operation, a determination is made as to whether there is a matched tuple in the target location that satisfies a predetermined condition. For each matched tuple that satisfies the predetermined condition, the matched tuple in the target location is updated with a count value that is equal to a count of the matched tuple in the source location and the target location. In addition, for each tuple that does not have a matched tuple that satisfies the predetermined condition, the unmatched tuple is inserted into the target location.

Abstract: A query that is submitted to a database is analyzed so as to determine a join order restriction. The join order restriction is associated with a join between two tables of a plurality of tables of the database that participate in the query. The join order restriction constrains its associated join to be executed prior to another join of the query. At least one join plan is generated, the join plan being constrained by the join order restriction. Different join plans include different join orders. A join plan is selected from among the join plans for execution of the query.

Abstract: In an example, data from a source location is merged into a target location containing existing data, in which both the source location and the target location contain tuples of data. For each tuple in the source location, during a single operation, a determination is made as to whether there is a matched tuple in the target location that satisfies a predetermined condition. For each matched tuple that satisfies the predetermined condition, the matched tuple in the target location is updated with a count value that is equal to a count of the matched tuple in the source location and the target location. In addition, for each tuple that does not have a matched tuple that satisfies the predetermined condition, the unmatched tuple is inserted into the target location.

Abstract: A record-pattern expression of a record pattern of data records is translated to a character-pattern expression of a character pattern. A data-record series of data records is converted to a character string in which each character in the character string corresponds to a respective data record in the data-record series. Pattern instances of the character pattern in the character string are searched to identify ordinal character positions in the character string of characters in the character pattern instances. Data records at ordinal record positions in the record series of data records corresponding to the ordinal character positions are reported.

Abstract: As part of managing the loading of data from a source onto a database, according to an example, an interface through which a user is to define logic related to the loading of the data onto the database is provided. The user-defined logic pertains to at least one of a user-defined location identification of the source, a user-defined filter to be applied on the data, and a user-defined parsing operation to be performed on the data to convert the data into an appropriate format for the database. In addition, the user-defined logic is received and the user-defined logic is implemented to load the data onto the database.

Abstract: In an example, data from a source location is merged into a target location containing existing data, in which both the source location and the target location contain tuples of data. For each tuple in the source location, during a single operation, a determination is made as to whether there is a matched tuple in the target location that satisfies a predetermined condition. For each matched tuple that satisfies the predetermined condition, the matched tuple in the target location is updated with a count value that is equal to a count of the matched tuple in the source location and the target location. In addition, for each tuple that does not have a matched tuple that satisfies the predetermined condition, the unmatched tuple is inserted into the target location.

Abstract: A method for query processing includes receiving a query, and determining a query type by determining if the query is a structured query language (SQL) query including multiple distinct aggregates (MDAs), or a SQL query including cube, rollup or grouping sets operations. Based on the determination, the method includes processing the query to generate an output, and performing a predetermined number of maximum group by operations on the output based on the query type to generate a response to the query.

Abstract: A method for executing a user-defined function on a plurality of input database tuples. The method may include causing a processor to invoke the function once; and to compute results of the function for the plurality of database tuples.

Abstract: A method for executing a user-defined function on a plurality of input database tuples. The method may include causing a processor to invoke the function once; and to compute results of the function for the plurality of database tuples.

Abstract: A record-pattern expression of a record pattern of data records is translated to a character-pattern expression of a character pattern. A data-record series of data records is converted to a character string in which each character in the character string corresponds to a respective data record in the data-record series. Pattern instances of the character pattern in the character string are searched to identify ordinal character positions in the character string of characters in the character pattern instances. Data records at ordinal record positions in the record series of data records corresponding to the ordinal character positions are reported.

Abstract: A system and method for switching algorithms during a run time computation, the method including configuring hardware of a networked cluster of processing elements, each processing element with a memory hierarchy, to perform a first-tier algorithm on input data, the input data having cardinality and stored on one or a plurality of nodes in the networked cluster. Performing at least a portion of a second-tier algorithm and determining whether to complete the second-tier algorithm and perform a third or subsequent tier algorithm, the determination dependent on cardinality. Automatically passing data to an output if the cardinality of the second-tier algorithm is greater than a threshold cardinality, and passing the data back to the second-tier algorithm or to one or a plurality of subsequent algorithms, in response to the cardinality being less than the threshold, and automatically passing the data to an output at the completion of the data processing.

Abstract: A method for constructing a projection for storing data on a storage device may include causing a processor to extract characteristics of expected output of a query on the data, and to construct a projection for the data based on the extracted characteristics.

Abstract: A query that is submitted to a database is analyzed so as to determine a join order restriction. The join order restriction is associated with a join between two tables of a plurality of tables of the database that participate in the query. The join order restriction constrains its associated join to be executed prior to another join of the query. At least one join plan is generated, the join plan being constrained by the join order restriction. Different join plans include different join orders. A join plan is selected from among the join plans for execution of the query.