Sap Se

Florian Wolf

Norman May

Paul Willems

Kai-Uwe Sattler

Wolfgang Lehner

Lars Fricke

Guido Moerkotte

Michael Brendle

Axel Hertzschuch

Alexander Boehm

Lukas Landgraf

A system includes reception of a query execution plan associated with a plurality of query execution pipelines, estimated execution costs and estimated intermediate result cardinalities, determination of one or more precedence relationships of the plurality of query execution pipelines, determination of an execution order of the plurality of query execution pipelines based on the estimated execution costs, the estimated intermediate result cardinalities, and the one or more precedence relationships, and providing of the execution order of the plurality of query execution pipelines and the query execution plan to a query execution engine.

Scheduling of query pipeline execution

A method may include responding to a query to retrieve data from a database by identifying a plurality of query execution plans. An overall robustness value may be determined for each query execution plan. The overall robustness value of a query execution plan may correspond to a sum of individual robustness values for each operator included in the query execution plan. Each operator may have an individual robustness value that corresponds to a first change in a total cost of a query execution plan including the operator relative to a second change in an output cardinality of the operator. One of the plurality of query execution plans may be selected based on the overall robustness value of each of the plurality of query execution plans. The query may be executed by performing a sequence of operators included in the selected one of the plurality of query execution plan.

Robustness metrics for optimization of query execution plans

A system includes determination of a plurality of queries of a workload, determination of a data source comprising a plurality of data rows, and determination of a sample data source based on a cardinality of each of the plurality of queries with respect to the data source and an estimated cardinality of each of the plurality of queries with respect to the data source, wherein the estimated cardinality of a query with respect to the data source is determined based on the sample data source.

Workload-based sampling

A system includes determination of a query on a table, the query including a first predicate and a second predicate, determination of a sample of the table, the sample comprising a plurality of tuples of the table, determination of a first conditional probability of selecting a tuple of the sample satisfying the first predicate and the second predicate, determination of a second conditional probability of selecting a tuple of the sample satisfying the first predicate and not satisfying the second predicate, adjustment of the first conditional probability based on the second conditional probability, a number of tuples of the sample satisfying the second predicate, a number of tuples of the sample not satisfying the second predicate, and a number of tuples of the sample satisfying the first predicate and not satisfying the second predicate, and determination of a selectivity of the query on the table based on the first adjusted conditional probability.

Selectivity estimation using non-qualifying tuples

In some implementations, there is provided an apparatus having at least one data processor and at least one memory storing instructions which, when executed by the at least one data processor, cause executing at least a portion of a query execution plan; determining, at an edge including an intermediate result, a cardinality; proceeding with the execution of the query execution plan, when the determined cardinality is within an optimality range associated with the edge; and selecting an alternative query execution plan for execution, when the determined cardinality is outside the optimality range associated with the edge. Related systems and articles of manufacture are also provided.

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Heidelberg, Germany

Florian Wolf