What are Deadlocks in Teradata? Deadlocks arise when two transactions hold locks on database objects required by the other transaction. Here is an example of a deadlock: Transaction 1 locks some rows in Table 1, and transaction 2 locks some rows in Table 2. The next step of transaction 1 is to lock rows in table 2, and …
Introduction This blog post discusses tactical workloads on a Teradata system. Despite Teradata’s implementation of features that support tactical workloads, this workload category remains challenging to manage. Selecting an optimal physical design is essential to meet user expectations for query speed. Designing the Teradata tactical workload on a test environment can be frustrating, especially when …
It’s time to share a new Teradata SQL tuning case study that showcases the impressive impact of query rewriting on performance. We are studying the query below that originally took 40 minutes to run. As a SQL tuning specialist, I always prioritize adding missing statistics and refreshing stale ones. I analyzed the SQL statement that …
Isolation Levels and their Impact on Performance & Concurrency Isolation is a crucial factor in determining the visibility of transaction integrity to database users. This property guarantees that concurrently executed transactions produce identical results to those executed sequentially. Nonetheless, relinquishing this requirement can enhance transaction concurrency, improving performance. However, this also implies accepting inconsistent outcomes. …
The optimizer has various access paths to consider when creating the execution plan, each with unique advantages and disadvantages. This article will introduce the 8 most essential access paths. The lack of a hash index may surprise you; however, Teradata has entirely substituted it with the single-table join index and discourages its utilization in the …
What is Partial Group By? Joins are costly. Before the introduction of PARTIAL GROUP BY, the join would be performed first, and then the aggregated result would follow. PARTIAL GROUP BY reduces the amount of data that must be redistributed or duplicated to all AMPs during join preparation by performing aggregations before the join, without …
Executive summaryGUEST POST BY ARTEMIY KOZYR Today I shed some light on how Data Warehousing lies at the core of Retail Banking operations. We will see the actual case of vital marketing process malfunction and dive deep under the surface level to comprehend data alchemy technical issues. You will learn how to approach such issues, …
The Optimizer typically excels in utilizing statistics, yet examining the execution plan and cardinality estimations can sometimes be beneficial. Since Teradata 14.10, I have habitually included the SHOW STATISTICS statement in my considerations. The resulting metrics can aid in identifying statistical issues. Teradata Statistics – Avoid the Heuristics This case study demonstrates how the Optimizer …
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.
Expert network for enterprise data platforms. Senior consultants, project teams built for your challenge — across Teradata, Snowflake, Databricks, and more.
📍Vienna, Austria & Jacksonville, Florida
Join 4,000+ data professionals.
Weekly insights on Teradata, Snowflake & data architecture.