Module statistics 

Statistics for cost-based query optimization.

The query optimizer uses these statistics to pick the best execution plan. Without stats, it has to guess - with stats, it knows that filtering by “status = ‘active’” returns 90% of rows while “label = ‘Admin’” returns 0.1%.

Statistic	What it tells the optimizer
Label cardinality	How many nodes have this label
Property histograms	Distribution of values for range predicates
Degree stats	How many edges per node (affects traversal cost)
Distinct counts	Selectivity of equality predicates

Structs

ColumnStatistics

Detailed statistics about a property’s values - min, max, histogram, null ratio.

EdgeTypeStatistics

Statistics for edges of a particular type (like “KNOWS” or “WORKS_AT”).

Histogram

Divides a column’s value range into buckets of roughly equal row counts.

HistogramBucket

One slice of the value distribution - a range with its row count.

IndexStatistics

Cost estimates for different index access patterns.

LabelStatistics

Statistics for nodes with a particular label (like “Person” or “Company”).

PredicateStatistics

Statistics for a single predicate (like :knows or :name).

RdfStatistics

Everything the SPARQL optimizer knows about your RDF data.

RdfStatisticsCollector

Streams triples through to build RDF statistics automatically.

Statistics

Everything the optimizer knows about the data - cardinalities, distributions, degrees.

Enums

TriplePosition

Which position in a triple pattern - subject, predicate, or object.

Type Aliases

PropertyKey

A property key identifier.

TableStatistics

Alias for table statistics (used in relational contexts).