Abstract: In some examples, formatting semi-structured data in a database includes obtaining semi-structured data in a column store database, assigning the semi-structured data to a semi-structured column with a key and value format, and formatting the semi-structured data with an optimal search format.

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 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: In some examples, formatting semi-structured data in a database includes obtaining semi-structured data in a column store database, assigning the semi-structured data to a semi-structured column with a key and value format, and formatting the semi-structured data with an optimal search format.

Abstract: According to an example, a method for executing a query having multiple set operators includes adding an additional column that associates an identifier of the result table with data contained in the input result table in each input result table of an input query. The method also includes performing a Union All operation on the data contained in the input result tables to generate an intermediate result set, performing a Group By operation on the data contained in the intermediate result set to generate a grouped result set, wherein the Group By operation operates on various groups of rows and returns one row per each of the various groups, adding aggregation columns in the grouped result set containing counts of a number of times that each tuple exists in each of the input result tables, and applying a predicate on the grouped result set to execute the query.

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: 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 system, method, and non-transitory computer readable medium are disclosed herein to optimize nested queries. At least one field is associated with each row of data evaluated by at least one nested query. A value is assigned to the at least one field so as to indicate whether each row of data satisfies the at least one nested query. The at least one field associated with each row of data is evaluated to determine satisfaction of the at least one nested query.

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 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: A method of analyzing an expression to infer output data properties, comprises storing, in a storage device, a root node “e” in R, in which “e” is an expression and R is a root node of an abstract syntax tree (AST) of the expression “e”, storing a number of child nodes of R into C1, . . . Cn, with a processor coupled to the storage device, calling analyze(Ci), storing output properties of expression C into Pi I, and determining if any of the child nodes Ci in {C1 . . . Cn} has not been analyzed, in which if the last child node has been analyzed, with the processor, calling compute-output-properties(R, P1, . . . Pn), storing, in the storage device, the result in Poutput, and returning Poutput as the output properties of the expression “e.