DB000 - common table expression

DB000 common table expression

• When write a query to a table, I have to wrtie very complex query to get the data that I want. In that case, I usually write query like below. This kind of statment using WITH is called as Common Table Expression. Sometime it used to compared with View which is managed in DB and stay alive before deleteing it, but Common Table Express which is known as CTE is just alive for just that query. It mean it can’t be called after the end of that query.

WITH AAAA AS (
  SELECT '1'
  FROM DUAL
)
SELECT *
FROM AAA

Materialization and its Pros and Cons

• In some database systems, CTE can be materialzed, which means that the temporary result set generated by the CTE is stored in temporary storage or memory, and the subsequent references to the CTE in the main query are resolved using this materialized data. This can have some positive and negative points.
• Materializing a CTE can be beneficial in certain situations:
  1. Query Reuse: If a CTE is referenced multiple times within a complex query, materializing it can help avoid recomputing the CTE’s result set each time it’s referenced. This can lead to improved query performance.
  2. Complex Computations: If the CTE involves complex computations or joins, materializing it can help reduce the computational load on the database server, especially when the CTE is referenced multiple times or in a recursive query.
  3. Optimization: In some cases, the database’s query optimizer might decide to materialize a CTE if it determines that materialization would result in a more efficient query execution plan.
• However, materializing CTEs can also have drawbacks:
  1. Memory Usage: Storing the CTE’s result set in memory or temporary storage consumes resources, which can be an issue if the CTE result set is large.
  2. Staleness: Materialized CTEs might not reflect the most up-to-date data if changes are made to the underlying tables after the CTE is materialized.
  3. Recursion: If a CTE is used recursively, materialization might not be as effective, as the recursive logic might not be optimally supported by materialized data.
• It’s important to note that not all database systems support CTE materialization, and the behavior can vary between different database engines. Some databases provide hints or options to control whether a CTE should be materialized or not. When using CTEs, it’s a good practice to analyze query performance and test different approaches (with and without materialization) to determine the most efficient solution for your specific use case and database system.

Materialization and Query Optimizer

• In many cases, the query optimizer will evaluate the complexity of the CTE, the overall query, and available resources before deciding whether to materialize the CTE or not. Some factors that might influence this decision include:

  1. Query Complexity: If the CTE involves simple operations and is referenced only once in the main query, the optimizer might decide that materialization is unnecessary.

  2. CTE Size: The size of the CTE’s result set can impact the decision. If the result set is small, the overhead of materialization might not be justified.

  3. Indexes and Statistics: The presence of indexes and statistics on the underlying tables can affect the optimizer’s choice. It might determine that accessing the base tables directly is more efficient than materializing the CTE.

  4. Available Resources: The available memory and processing power on the database server can influence whether materialization is used, as materializing a CTE consumes resources.

  5. Query Hints: Some database systems allow you to provide hints or directives to the optimizer, which can influence its behavior, including the decision to materialize a CTE or not.

  6. Database System: Different database systems might have different optimization strategies for CTEs. For example, PostgreSQL and SQL Server are known for their advanced CTE optimization capabilities, while other systems might not have as sophisticated optimizations.

• In scenarios where you believe materialization would significantly improve query performance, but the optimizer isn’t choosing to materialize the CTE, you might consider exploring query hints or rewriting the query to encourage materialization. However, it’s important to note that these strategies might have different effects depending on the specific database system you’re using.
• As always, when dealing with query performance optimization, it’s a good practice to analyze execution plans, run performance tests, and consider the specific characteristics of your data and use case to make informed decisions.