SMP for Parallel Execution
Availability
This feature is available since openGauss 1.1.0.
Introduction
The Symmetric Multi-Processing (SMP) technology of openGauss uses the multi-core CPU architecture of a computer to implement multi-thread parallel computing, fully using CPU resources to improve query performance.
Benefits
Fully utilizes the system multi-core capability to improve requery performance.
Description
In complex query scenarios, a single query takes long time and the system concurrency is low. Therefore, the SMP technology is used to implement operator-level parallel execution, which effectively reduces the query time and improves the query performance and resource utilization. The overall implementation of the SMP technology is as follows: For query operators that can be executed in parallel, data is sliced, multiple working threads are started for computation, and then the results are summarized and returned to the frontend. A data interaction operator named Stream is added to the SMP architecture to implement data interaction between multiple working threads, ensuring the correctness and integrity of the query.
Enhancements
None.
Constraints
- Index scanning cannot be executed in parallel.
- MergeJoin cannot be executed in parallel.
- WindowAgg order by cannot be executed in parallel.
- The cursor cannot be executed in parallel.
- Queries in stored procedures and functions cannot be executed in parallel.
- Subplans and initplans cannot be queried in parallel, and operators that contain subqueries cannot be executed in parallel, either.
- Query statements that contain the median operation cannot be executed in parallel.
- Updating materialized views cannot be executed in parallel.
- Queries that trigger triggers cannot be executed concurrently. Especially, INSERT, UPDATE, and DELETE operations on tables that contain foreign keys will trigger triggers.
- The Ustore engine does not support parallel execution.
- Query statements containing rownum do not support parallel execution.
- Statements involving LOBs greater than 1 GB cannot be executed concurrently.
Dependencies
None.