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compression

Why Two Identical Teradata Migrations Produce Wildly Different Snowflake Costs

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Migration success stories are everywhere. A quick search reveals case studies of companies that moved from Teradata to Snowflake and achieved faster queries, lower total cost of ownership, and happier analysts. Vendors publish them. Consultants reference them. Conference speakers present them as evidence that the migration path is well-trodden and safe. These stories are not …

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Filter efficiently with Teradata NOS Popular

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Teradata NOS facilitates querying data in an S3 object store with ease. To attain maximum performance, partitioning external data is crucial for efficient reading. This article outlines the key considerations for optimal efficiency when reading data from the object store. To begin, we must establish S3 access by obtaining an AUTHORIZATION object. In this instance, …

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How the Number of Rows per Data Block Affects Teradata NUSI Selectivity: A Case Study

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Teradata NUSI Selectivity and Data-Block Density The goal of this article is to show how the number of rows per base-table data block impacts the selectivity threshold for Non-Unique Secondary Indexes (NUSI) in Teradata. Understanding this correlation is critical when analyzing query plans and tuning indexing strategies.The number of qualifying rows that make a NUSI …

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Teradata Data Type Considerations Most read

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Introduction to Teradata Data Types Further Data Type considerations require occasional attention to additional issues. Happenstance Nullability Strive for nullability settings that adhere to the data model and are consistent throughout all tables. Allowing mandatory columns to be left open for null entries incurs costs for both storage and optimization. An additional presence bit per …

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SQL Tuning Goals: Improving Performance and Reducing Resource Usage Popular

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Learn about the goals of SQL tuning and how to optimize database performance by reducing resource usage. Skew, IOs, and CPU seconds are key metrics. Discover how to ensure completeness and correctness of Teradata statistics, detect missing and stale statistics, and improve query plans.

Understanding Teradata DBQL Tables and Query Logging Widely read

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Learn about Query Logging with Teradata DBQL Tables, a powerful feature for workload analysis and performance tuning. Configure settings and select which key figures to store and their level of detail. The article covers how to implement and activate DBQL tables, determine which information to collect, and analyze tactical queries.

Teradata Table Skew: Understanding Natural and Artificial Skew with DBC.TableSizeV

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Teradata table skew is a common issue encountered while working with the Teradata database. If you’re reading this page, you may have experienced this problem. Common knowledge When searching for Teradata table skew or skew factor online, most or all documentation will refer directly to DBC.TableSizeV for computation. To analyze table skew, the commonly used …

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Teradata Columnar Compression Methods: Run-Length, Dictionary, and Delta Compression

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Learn about the benefits of compression in Teradata Columnar, including a reduction in permanent space and disk IOs. Different compression methods are used, including run-length, dictionary, and delta compression. This article explains how each method works and the advantages of using them.

Designing Small Reference Tables for Teradata: Storing All Rows on One AMP for More Efficient Queries

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When designing tables for Teradata, it is important to distribute the rows across all AMPs in the system evenly. For instance, on a 100-AMP system with 100,000 rows, the objective would be to allocate roughly 1,000 rows per AMP. I agree with the design guideline for many tables in a Teradata system. Nevertheless, a specific …

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