Sap Ag

Sap Se

Gerhard L Hill

Thomas Peh

Jane Hartmann

Some embodiments provide a non-transitory machine-readable medium stores a program. The program receives a query for data that includes an intersection operation on a first set of strings and a second set of strings. The program further generates a plurality of candidate query execution plans based on the query. The program also determines a plurality of execution costs associated with the plurality of candidate query execution plans. The program further selects a query execution plan from the plurality of candidate query execution plans based on the plurality of execution costs. The program also executes the query execution plan to generate a set of query results for the query.

Estimating string intersections for database systems

Some embodiments provide a non-transitory machine-readable medium stores a program. The program receives a query for data that includes a join operation. The program further generates a plurality of candidate query execution plans based on the query, each candidate query execution plan comprising a set of reduction operations. The program also determines a plurality of execution costs associated with the plurality of sets of reduction operations in the plurality of candidate query execution plans. The program further selects a query execution plan from the plurality of candidate query execution plans based on the plurality of execution costs. The program also executes the query execution plan to generate a set of query results for the query.

Estimating distinct values for database systems

The present disclosure describes methods, systems, and computer program products for using DeltaIterators in a database. One computer-implemented method includes, for each of multiple delta parts of a database that store values of an attribute of a table: identifying, by operation of a computer system, a set of values of the attribute stored in the delta part of the database, and identifying a current value in the set of values; identifying, a first critical value among the multiple current values, wherein the first critical value is a current value of a first set of values of the attribute stored in a first delta part of the database; outputting the first critical value; identifying a next value in first set of values; identifying a second critical value among the next value and the multiple current values except the first critical value; and outputting the second critical value.

Deltaiterators in database systems

The present disclosure describes methods, systems, and computer program products for performing JOIN value comparisons. One computer-implemented method includes converting, by operation of a computer system, a first value of a first data type into a second value of a second data type, wherein the first value is a value of a first attribute of a first table; converting, by operation of a computer system, the second value of the second data type into a third value of a third data type; converting, by operation of a computer system, a fourth value of the third data type into a fifth value of the second data type, wherein the fourth value is a value of a second attribute of a second table; converting, by operation of a computer system, the fifth value of the second data type into a sixth value of the first data type; and performing JOIN operations of the first table and the second table in response to determining that the first value equals the sixth value, and the fourth value equals the third value.

Comparing join values in database systems

Various embodiments of systems and methods for join tuple assembly by partial specializations are described herein. The join tuple assembly by partial specializations is a phase of the method for join query evaluation by semi-join reduction. By using partial specializations of the non-join part of the WHERE clause of a join query and matching sets, the join tuple assembly is organized in a manner that all computations are necessary, none are repeated, and failure to complete a partial join tuple to a full tuple is detected as early as possible. The method can be applied to inner and outer joins, and to arbitrary join graphs and non-join conditions in the WHERE clause. It can also be used outside the context of semi-join reductions.

Join tuple assembly by partial specializations

Systems and methods consistent with the invention may include selecting a plurality of hosts to store data structures by defining a color incidence process used to model a host assignment process, determining, by the color incidence process, a color allocation, and assigning the data structures to one of the plurality of hosts based on the color allocation determined by the color incidence process.

Systems and methods for assigning hosts in response to a data query

A system and method for executing semijoin reductions on outer join operations are presented. Tuple lists are created based on a query. A sequence of semijoin reduction steps are performed, where each semijoin reduction step either switches one tuple list, or reduces all tuple lists at one relation. Virtual connector pairs are inserted into the tuple lists, and then all tuple lists are centralized at a common host. The join results are assembled at the common host, and negative row IDs are substituted. From the join result, the query result is retrieved by projecting to the requested attributes.

Virtual pair algorithm for outer join resolution

Systems and methods for using optimization techniques to construct a nearly optimal execution plan for an outer join query are disclosed. A query graph of the outer join query is constructed, by computing for each node the set of nodes influencing it, for each target node the set of its needed reducers, and predetermining the effects of all admissible moves in all possible sequences. The directed graph of all admissible move sequences is formed. An optimization process includes dynamically generating good estimations for the target distance of a search state. Some heuristics are disclosed for providing start solutions for the optimization process.

Growing community of inventors

St. Leon-Rot, Germany

Gerhard L Hill