Teradata 16 introduces a new option for handling sets of rows combined with “UNION ALL” in views and derived tables, reducing resource usage. The optimizer can apply aggregation steps and join operations to each branch of the “UNION ALL” separately, resulting in smaller spool sizes and improved performance.
Learn about heuristics in Teradata optimizer and how they estimate the number of selected data rows for nonindexed columns in WHERE condition predicates. This post analyzes several queries and their estimates based on heuristics and provides insights on how to replace heuristic estimations with more accurate ones.
Learn about referential integrity and how it ensures data consistency in databases. Discover soft referential integrity and its use in inner join elimination.
Learn how to optimize joins in Teradata with this case study. Discover how simple changes in query text can improve query performance.
Learn how biased value histograms store exact cardinalities and provide up-to-date statistics for queries, and witness how the Optimizer estimates the number of rows for a given query.
Learn how query rewriting can improve performance in row partition elimination. Follow the test setup to optimize the retrieval of rows from a table.
Natural skew may hinder join performance, but the PDPR capability in Teradata 14 can alleviate this problem. However, PDPR may not detect all potential applications if skewed values are not evident in the statistics. If your Teradata version is below 14, PDPR is unavailable. To address this, you can use a technique based on the …
Learn how to analyze workload in Teradata using the DBC.ResUsageSAWT table. This guide explores the essential columns and measures to consider.
Learn how express requests work in Teradata, bypassing stages like syntax checking and permission checking, and how Teradata 14.10 offers a new feature to expedite them.
Learn how to optimize Teradata performance with these general tuning ideas. From changing one parameter at a time to testing on the target system.
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