Cardinallevel

Cardinallevel is a term used in data modeling and database design to describe the level of cardinality of an attribute or column. It provides an ordinal, qualitative assessment of how many distinct values exist in relation to the size of the dataset, helping practitioners select storage layouts, indexing strategies, and query plans.

Definition and scale: Cardinallevel is typically expressed on a small ordinal scale such as 0 to 4 or as labeled categories (very low, low, moderate, high, very high). The assignment is dataset-dependent and commonly based on the proportion of distinct values or the raw count of distinct values relative to the total number of rows. For example, a column with a single value across all rows has cardinallevel 0; a column with a handful of values across many rows might be level 1 or 2; a column with nearly every row having a unique value is level 4.

Calculation and estimation: In practice, cardinallevel is estimated using statistics collected by the database or profiling tool, such as the number of distinct values (NDV) and the row count. A simple rule uses NDV divided by row_count to classify the column into a level, with higher ratios indicating higher cardinallevels.

Applications: Cardinallevel informs indexing decisions, storage planning, and query optimization. Low-cardinality columns often benefit from bitmap indexes or dictionary encoding, while high-cardinality columns typically use B-tree or hash-based indexes. It can also influence join strategies and compression schemes, as different levels imply different performance trade-offs.

Limitations: The cardinallevel scale is heuristic and can change with data updates or varying workloads. It may not capture value distribution, skew, or cross-column correlations, and thresholds for each level vary across systems and implementations.

See also: Cardinality, Distinct values, Bitmap index, B-tree index, Data profiling, Histogram.