Struct CompositePruningStatistics

pub struct CompositePruningStatistics {
    pub statistics: Vec<Box<dyn PruningStatistics>>,
}

Combine multiple PruningStatistics into a single CompositePruningStatistics. This can be used to combine statistics from different sources, for example partition values and file statistics. This allows pruning with filters that depend on multiple sources of statistics, such as WHERE partition_col = data_col. This is done by iterating over the statistics and returning the first one that has information for the requested column. If multiple statistics have information for the same column, the first one is returned without any regard for completeness or accuracy. That is: if the first statistics has information for a column, even if it is incomplete, that is returned even if a later statistics has more complete information.

Fields

statistics: Vec<Box<dyn PruningStatistics>>

Implementations

impl CompositePruningStatistics

pub fn new( statistics: Vec<Box<dyn PruningStatistics>>, ) -> CompositePruningStatistics

Create a new instance of CompositePruningStatistics from a vector of PruningStatistics.

Trait Implementations

impl PruningStatistics for CompositePruningStatistics

fn min_values(&self, column: &Column) -> Option<Arc<dyn Array>>

Return the minimum values for the named column, if known.

fn max_values(&self, column: &Column) -> Option<Arc<dyn Array>>

Return the maximum values for the named column, if known.

fn num_containers(&self) -> usize

Return the number of containers (e.g. Row Groups) being pruned with these statistics.

fn null_counts(&self, column: &Column) -> Option<Arc<dyn Array>>

Return the number of null values for the named column as an UInt64Array

fn row_counts(&self, column: &Column) -> Option<Arc<dyn Array>>

Return the number of rows for the named column in each container as an UInt64Array.

fn contained( &self, column: &Column, values: &HashSet<ScalarValue>, ) -> Option<BooleanArray>

Returns BooleanArray where each row represents information known about specific literal values in a column.