Join Index Storage | Database Design | VantageCloud Lake - Join Index Storage - Teradata VantageCloud Lake

Lake - Database Reference

Deployment
VantageCloud
Edition
Lake
Product
Teradata VantageCloud Lake
Release Number
Published
February 2025
ft:locale
en-US
ft:lastEdition
2025-11-21
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ohi1683672393549

The storage organization for join indexes supports a row compressed format to reduce storage space.

If you know that a join index contains groups of rows with repeating information, then its definition DDL can specify repeating groups, indicating the repeating columns in parentheses. The column list is specified as two groups of columns, with each group stipulated within parentheses. The first group contains the non-repeating columns and the second group contains the repeating columns.

You can store join indexes in value order, ordered by the values of a 4-byte column. Value-ordered storage provides better performance for queries that specify selection constraints on the value ordering column. For example, suppose a common task is to look up sales information by sales date. You can create a join index on the sales table and order it by sales date. The benefit is that queries that request sales by sales date only need to access those data blocks that contain the value or range of values that the queries specify.