322 technical articles on Teradata, Snowflake, Databricks, SQL tuning and data warehouse architecture — written from production experience, not vendor decks.
This article illustrates loading a flat file into an empty Teradata table using TPT. The example was successfully tested on Teradata 16.20. Although TPT does offer a wide range of advanced options for loading files, it can be overwhelming for basic tasks. In this demonstration, I will present a simplified approach to loading flat files …
1. Complete and up-to-date Statistics At the start of Teradata SQL Tuning, statistics are a vital concern. The Teradata Optimizer employs statistics to formulate the optimal execution plan for our query. The adequacy of statistics or dynamic AMP sampling varies according to the data demographics. To initiate optimization, updated statistics must be provided to the …
This article will highlight the contrasting architectural features of Teradata and SQL Server, along with their shared aspects and performance impacts. The piece titled “Teradata versus SQL Server” will be periodically updated. For comparisons against other platforms: how Teradata and Amazon Redshift differ and what makes Teradata an RDBMS rather than an appliance. The same …
What is Teradata Query Rewriting? Teradata query rewriting is an integral component of the optimization process for Teradata. The optimizer replaces your query with a more efficient and faster version. Both queries must produce identical results. Teradata implements various optimization techniques to enhance performance. We will demonstrate the commonly used optimization methods. 1. Removing unreferenced …
Introduction to Teradata Dynamic AMP Sampling Teradata calculates dynamic AMP samples for indexed columns (PI, USI, NUSI) at runtime without requiring statistics. These samples provide key information, including table cardinality and distinct values. They are stored in the FSG cache of each AMP’s table header. This process is referred to as dynamic AMP sampling. A …
Teradata and Redshift share similar architectures and data distribution methods. Teradata’s AMPs store portions of table data, while Redshift utilizes slices. There are notable differences in the way data is stored on file systems. Teradata can function as a Column Store, which can be determined on a per-table basis. However, the primary advantage lies in …
Teradata employs two distinct approaches in Ordered Analytic Functions for preparing the data layout necessary for processing. This article explains both approaches and their respective advantages and disadvantages. Teradata Ordered Analytical Functions Teradata Analytic Functions are versatile tools that allow for a wide range of applications. The ability to retrieve previous and subsequent rows is …
Learn how to use the Teradata OVERLAPS command to detect overlapping time periods with this example query. Caution: minimum overlap required.
1. Outline This showcase demonstrates optimizing statements with multiple JOINs using Teradata Optimizer’s tuning approach. The approach efficiently determines the best JOIN strategy and implements data redistribution instead of duplication when necessary. Identify and break down underperforming segments to optimize complex logic with multiple joins. Employ an execution plan and monitor query performance and resource …
Learn how to optimize LIKE operator queries in Teradata to avoid full table scans and improve performance. Read on for expert tips and tricks.
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