Abstract: Provided are systems and methods for creating histograms with distinct value sketches integrated therein and for query processing based on the histograms with distinct value sketches. In one example, the method may include storing a histogram that comprises a representation of a bucket of data from a database and that includes a distinct value sketch with a distinct value attribute that identifies an estimated number of distinct values within the bucket of data, receiving a database query, generating a query execution plan for the database query based on the distinct value attribute of the bucket within the distinct value sketch embedded within the histogram, and executing the database query on the bucket of data from the database based on the generated query execution plan.

Abstract: According to some embodiments, methods and systems may be associated with a cloud computing environment. A workload prediction framework may receive observed workload information associated with a database in the cloud computing environment (e.g., a DataBase as a Service (“DBaaS”)). Based on the observed workload information, a Statement Arrival Rate (“SAR”) prediction may be generated. In addition, a host variable assignment prediction may be generated based on the observed workload information. The workload prediction framework may then use the SAR prediction and the host variable assignment prediction to automatically create a workload prediction for the database. A physical database design advisor (e.g., a table partitioning advisor) may receive the workload prediction and, responsive to the workload prediction, automatically generate a recommended physical layout for the database (e.g., using a cost model, the current physical layout, and an objective function).

Abstract: Provided are systems and methods for creating histograms with distinct value sketches integrated therein and for query processing based on the histograms with distinct value sketches. In one example, the method may include storing a histogram that comprises a representation of a bucket of data from a database and that includes a distinct value sketch with a distinct value attribute that identifies an estimated number of distinct values within the bucket of data, receiving a database query, generating a query execution plan for the database query based on the distinct value attribute of the bucket within the distinct value sketch embedded within the histogram, and executing the database query on the bucket of data from the database based on the generated query execution plan.

Abstract: The present disclosure involves systems, software, and computer implemented methods for improved design and implementation of data access metrics for automated physical database design. An example method includes identifying a database workload for which index advisor access counters are to be tracked. Each SQL statement in the database workload is executed. For each SQL statement, attribute sets are determined for which a selection predicate filters a result for an SQL statement. An output cardinality of each selection predicate is determined. A logarithmic counter for an attribute set corresponding to the selection predicate is determined based on the output cardinality of the selection predicate. The determined logarithmic counter is incremented. Respective values for logarithmic counters of the determined attributes are provided to an index advisor. The index advisor determines attribute sets for which to propose an index based on the logarithmic counters of the respective attribute sets.

Abstract: According to some embodiments, methods and systems may be associated with a cloud computing environment. A workload prediction framework may receive observed workload information associated with a database in the cloud computing environment (e.g., a DataBase as a Service (“DBaaS”)). Based on the observed workload information, a Statement Arrival Rate (“SAR”) prediction may be generated. In addition, a host variable assignment prediction may be generated based on the observed workload information. The workload prediction framework may then use the SAR prediction and the host variable assignment prediction to automatically create a workload prediction for the database. A physical database design advisor (e.g., a table partitioning advisor) may receive the workload prediction and, responsive to the workload prediction, automatically generate a recommended physical layout for the database (e.g., using a cost model, the current physical layout, and an objective function).

Abstract: According to some embodiments, methods and systems may be associated with a cloud computing environment. A workload prediction framework may receive observed workload information associated with a database in the cloud computing environment (e.g., a DataBase as a Service (“DBaaS”)). Based on the observed workload information, a Statement Arrival Rate (“SAR”) prediction may be generated. In addition, a host variable assignment prediction may be generated based on the observed workload information. The workload prediction framework may then use the SAR prediction and the host variable assignment prediction to automatically create a workload prediction for the database. A physical database design advisor (e.g., a table partitioning advisor) may receive the workload prediction and, responsive to the workload prediction, automatically generate a recommended physical layout for the database (e.g., using a cost model, the current physical layout, and an objective function).

Abstract: Provided are systems and methods for creating histograms with distinct value sketches integrated therein and for query processing based on the histograms with distinct value sketches. In one example, the method may include storing a histogram that comprises a representation of a bucket of data from a database and that includes a distinct value sketch with a distinct value attribute that identifies an estimated number of distinct values within the bucket of data, receiving a database query, generating a query execution plan for the database query based on the distinct value attribute of the bucket within the distinct value sketch embedded within the histogram, and executing the database query on the bucket of data from the database based on the generated query execution plan.

Abstract: The present disclosure involves systems, software, and computer implemented methods for improved design and implementation of data access metrics for automated physical database design. An example method includes identifying a database workload for which index advisor access counters are to be tracked. Each SQL statement in the database workload is executed. For each SQL statement, attribute sets are determined for which a selection predicate filters a result for an SQL statement. An output cardinality of each selection predicate is determined. A logarithmic counter for an attribute set corresponding to the selection predicate is determined based on the output cardinality of the selection predicate. The determined logarithmic counter is incremented. Respective values for logarithmic counters of the determined attributes are provided to an index advisor. The index advisor determines attribute sets for which to propose an index based on the logarithmic counters of the respective attribute sets.

Abstract: Techniques and solutions are described for partitioning data among different types of computer-readable storage media, such as between RAM and disk-based storage. A measured workload can be used to estimate data access for one or more possible partition arrangements. The partitions arrangements can be automatically enumerated. Scores for the partition arrangements can be calculated, where a score can indicate how efficiently a partition arrangement places frequently accessed data into storage specified for frequently-accessed data and placed infrequently accessed data into storage specified for infrequently accessed data.

Abstract: 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.

Abstract: The present disclosure involves systems, software, and computer implemented methods for improved design and implementation of data access metrics for automated physical database design. An example method includes identifying a database workload for which index advisor access counters are to be tracked. Each SQL statement in the database workload is executed. For each SQL statement, attribute sets are determined for which a selection predicate filters a result for an SQL statement. An output cardinality of each selection predicate is determined. A logarithmic counter for an attribute set corresponding to the selection predicate is determined based on the output cardinality of the selection predicate. The determined logarithmic counter is incremented. Respective values for logarithmic counters of the determined attributes are provided to an index advisor. The index advisor determines attribute sets for which to propose an index based on the logarithmic counters of the respective attribute sets.

Abstract: The present disclosure involves systems, software, and computer implemented methods for improved design and implementation of data access metrics for automated physical database design. An example method includes identifying a database workload for which index advisor access counters are to be tracked. Each SQL statement in the database workload is executed. For each SQL statement, attribute sets are determined for which a selection predicate filters a result for an SQL statement. An output cardinality of each selection predicate is determined. A logarithmic counter for an attribute set corresponding to the selection predicate is determined based on the output cardinality of the selection predicate. The determined logarithmic counter is incremented. Respective values for logarithmic counters of the determined attributes are provided to an index advisor. The index advisor determines attribute sets for which to propose an index based on the logarithmic counters of the respective attribute sets.

Abstract: The present disclosure involves systems, software, and computer implemented methods for improved design and implementation of data access metrics for automated physical database design. An example method includes identifying a database workload for which index advisor access counters are to be tracked. Each SQL statement in the database workload is executed. For each SQL statement, attribute sets are determined for which a selection predicate filters a result for an SQL statement. An output cardinality of each selection predicate is determined. A logarithmic counter for an attribute set corresponding to the selection predicate is determined based on the output cardinality of the selection predicate. The determined logarithmic counter is incremented. Respective values for logarithmic counters of the determined attributes are provided to an index advisor. The index advisor determines attribute sets for which to propose an index based on the logarithmic counters of the respective attribute sets.

Abstract: The present disclosure involves systems, software, and computer implemented methods for improved design and implementation of data access metrics for automated physical database design. An example method includes identifying a database workload for which index advisor access counters are to be tracked. Each SQL statement in the database workload is executed. For each SQL statement, attribute sets are determined for which a selection predicate filters a result for an SQL statement. An output cardinality of each selection predicate is determined. A logarithmic counter for an attribute set corresponding to the selection predicate is determined based on the output cardinality of the selection predicate. The determined logarithmic counter is incremented. Respective values for logarithmic counters of the determined attributes are provided to an index advisor. The index advisor determines attribute sets for which to propose an index based on the logarithmic counters of the respective attribute sets.

Abstract: 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.

Abstract: Techniques and solutions are described for partitioning data among different types of computer-readable storage media, such as between RAM and disk-based storage. A measured workload can be used to estimate data access for one or more possible partition arrangements. The partitions arrangements can be automatically enumerated. Scores for the partition arrangements can be calculated, where a score can indicate how efficiently a partition arrangement places frequently accessed data into storage specified for frequently-accessed data and placed infrequently accessed data into storage specified for infrequently accessed data.

Abstract: A system includes determination of a query comprising z predicates, determination of known selectivities of each of a set of conjuncts of the z predicates, and estimation of selectivities of all conjuncts of the z predicates based on the known selectivities and a recursive determination of Cx, where x represents selectivities of all complete conjuncts of the z predicates and C is a complete design matrix complete design matrix (ci,j)=1 if i?j, else 0, having indices [0, 2z?1].

Abstract: 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.

Abstract: 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.

Abstract: A system for cardinality estimation for database query planning is provided. In some implementations, the system performs operations comprising determining, based on a first bounds and a second bounds for a combination of query predicates, whether a solution for the combination of the query predicates exists which includes both the first and second bounds. When the solution is determined to exist, the operations can further comprise determining at least one selectivity estimate for the combination of the query predicates. A query plan for execution of a database query comprising the query predicates can be generated based on the at least one selectivity estimate, and the database query can be executed through execution of the query plan. Related systems, methods, and articles of manufacture are also described.