qua_analyze_table#

Procedure orders the underlying system to update its object-level, or column-level statistics, or both. It uses the configuration to derive information about which statistics to calculate.

Depending on the underlying system, procedure issues a system-specific command requiring it to physically process the data to gather information useful for query optimization.

For example, if a Querona view View1(col1, col2) resides in a virtual database backed by Apache Spark, its physical name in Spark is view1, then the procedure issues a Spark-specific command ANALYZE TABLE view1 FOR COLUMNS col1, col2 upon execution.

Note

If a view is materialized using multiple physical objects, like in “rotated tables” caching strategy, only the active physical object is analyzed.

Syntax#

qua_analyze_table @virtualName = 'virtualName'
             [ , [@forceAllColumns] = forceAllColumns ]
[;]

Arguments#

@virtualName = ‘virtualName’

Name of the virtual object to analyze. virtualName is of type Sysname.

[@forceAllColumns] = forceAllColumns

Binary flag that instructs the procedure to override the statistics-oriented settings derived from metadata, and forces it to analyze data for all physical columns. forceAllColumns is of type Boolean with a default of NULL.

Example#

  1. Updates objects statistics for DimDate view cached on Apache Spark. Configuration derives from object-level metadata stored in Querona.

EXEC qua_analyze_table @virtualName = 'DimDate';

  1. Updates objects statistics for DimDate view cached on Apache Spark. Configuration derived from object-level metadata is ignored and analysis target all physical columns.

EXEC qua_analyze_table @virtualName = 'DimDate', 1

See Also#