1. A computer-implemented method of statistical view refinement based on constraints in order to reduce a processing cost incurred in maintaining statistical views in a database management system, the computer-implemented method comprising: responsive to receiving a request to execute a database workload including a plurality of sub-expressions, evaluating the database workload in order to generate a join graph; determining a respective arity for each of a plurality of joins in the database workload, including a one-to-one arity for a first join, a one-to-many arity of a second join, and a many-to-many arity for a third join, wherein any join having one-to-one arity is disregarded in statistical view generation; determining a respective skew for each of the plurality of joins in the database workload, at least one skew of which is determined based on at least one of: (i) a measure of an extent to which a value frequency distribution of a column the respective join deviates from a uniform value-frequency distribution of the column of the respective join; and (ii) a ratio between: (A) a count of rows of a respective value having a highest frequency in a respective foreign key and (B) an average count of rows per value of the respective foreign key; generating a plurality of statistical view candidates, based on the respective arity of each of the plurality of joins, the respective skew for each of the plurality of joins, and the join graph; identifying one or more predefined constraints pertaining to executing the database workload; programmatically refining the statistical view candidates by operation of one or more computer processors and based on the identified one or more predefined constraints in order to generate a set of refined statistical view candidates that excludes at least one of the plurality of statistical view candidates, wherein statistical view generation from the plurality of statistical view candidates is restricted to the set of refined statistical view candidates; generating one or more statistical views based on the refined statistical view candidates, wherein no statistical view is generated based on the excluded at least one statistical view candidate, wherein the processing cost incurred in maintaining statistical views in the database management system is reduced by at least a measure associated with the excluded at least one statistical view candidate; generating a plurality of distinct plans for executing the database workload, including determining an estimated cost for each of the plurality of distinct plans based on the one or more statistical views and with a higher degree of accuracy than in an absence of the one or more statistical views, wherein the first plan is selected for executing the database workload, based on the estimated cost; and executing the database workload according to the selected plan in order to generate a set of results, wherein the set of results is output.
1. A computer-implemented method of statistical view refinement based on constraints in order to reduce a processing cost incurred in maintaining statistical views in a database management system, the computer-implemented method comprising: responsive to receiving a request to execute a database workload including a plurality of sub-expressions, evaluating the database workload in order to generate a join graph; determining a respective arity for each of a plurality of joins in the database workload, including a one-to-one arity for a first join, a one-to-many arity of a second join, and a many-to-many arity for a third join, wherein any join having one-to-one arity is disregarded in statistical view generation; determining a respective skew for each of the plurality of joins in the database workload, at least one skew of which is determined based on at least one of: (i) a measure of an extent to which a value frequency distribution of a column the respective join deviates from a uniform value-frequency distribution of the column of the respective join; and (ii) a ratio between: (A) a count of rows of a respective value having a highest frequency in a respective foreign key and (B) an average count of rows per value of the respective foreign key; generating a plurality of statistical view candidates, based on the respective arity of each of the plurality of joins, the respective skew for each of the plurality of joins, and the join graph; identifying one or more predefined constraints pertaining to executing the database workload; programmatically refining the statistical view candidates by operation of one or more computer processors and based on the identified one or more predefined constraints in order to generate a set of refined statistical view candidates that excludes at least one of the plurality of statistical view candidates, wherein statistical view generation from the plurality of statistical view candidates is restricted to the set of refined statistical view candidates; generating one or more statistical views based on the refined statistical view candidates, wherein no statistical view is generated based on the excluded at least one statistical view candidate, wherein the processing cost incurred in maintaining statistical views in the database management system is reduced by at least a measure associated with the excluded at least one statistical view candidate; generating a plurality of distinct plans for executing the database workload, including determining an estimated cost for each of the plurality of distinct plans based on the one or more statistical views and with a higher degree of accuracy than in an absence of the one or more statistical views, wherein the first plan is selected for executing the database workload, based on the estimated cost; and executing the database workload according to the selected plan in order to generate a set of results, wherein the set of results is output. 6. The computer-implemented method of claim 1 , wherein identifying one or more predefined constraints pertaining to executing the database workload comprises identifying a plurality of distinct constraints including at least two of a first constraint, a second constraint, a third constraint, a fourth constraint, and a fifth constraint, wherein programmatically refining the statistical view candidates based on the identified one or more predefined constraints comprises programmatically refining the statistical view candidates based on the plurality of distinct constraints, wherein at least one generated statistical view includes a column sub-expression or specifies to generate statistics pertaining to a column group having a plurality of columns.