To optimize Teradata SQL performance, it is crucial to identify the root cause of any issues. The SQL statement itself is typically not the culprit but rather one or more stages of the execution plan. This article does not cover genuine optimization techniques. Instead, it presents a pragmatic method for query optimization. I have noticed …
The Teradata NUSI is an alternative access path to table rows, similar to other relational database indexes. Indexes are used to minimize resource consumption, especially IOs. Unlike Oracle, Teradata employs a hashing method for indexing, which is a common method for shared-nothing database systems. Amazon Redshift and Postgres-based database systems also utilize hashing. Teradata has …
Learn about the benefits of partitioned primary index (PPI) in Teradata, a method for reducing I/Os and improving performance in database systems.
Learn how the CHAR2HEXINT function helped solve a real-world problem of extracting number parts from a string in Teradata SQL. Read on for the solution.
Learn about Teradata’s temporal data management functionality based on TSQL2 specification in this article. Discover how it simplifies historization.
Learn about the latest improvements in Teradata 14.00 that allow you to customize the collection of statistics to better suit your needs. These improvements include the option to set different sample sizes, consider more bytes for histogram creation, and choose the number of intervals for building statistics histograms. Read on to discover how these changes can benefit your optimization efforts.
Block Level Compression (BLC) is a feature that allows compression of entire data blocks, leading to disk space reduction. Read on to know more.
Learn how variable declarations work in a Teradata Stored Procedure. Declarations are always local to the surrounding compound statement. See examples.
Learn about the Teradata Hash Index, designed to minimize disk IOs and improve access to rows. Discover how it differs from Single Table Join Indexes.
Learn how to optimize SQL tuning on Teradata by minimizing I/Os and maximizing parallelism, which can be achieved by evenly distributing rows across all AMPs.
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