Other Factors Affecting SMP Performance
Besides resource factors, there are other factors that impact the SMP parallelism performance, such as unevenly data distributed in a partitioned table and system parallelism degree.
- Impact of data skew on SMP performance
Serious data skew deteriorates parallel execution performance. For example, if the data volume of a value in the join column is much more than that of other values, the data volume of a parallel thread will be much more than that of others after Hash-based data redistribution, resulting in the long-tail issue and poor parallelism performance.
- Impact on the SMP performance due to system parallelism degree
The SMP feature uses more resources, and unused resources are decreasing in a high concurrency scenario. Therefore, enabling the SMP parallelism will result in serious resource compete among queries. Once resource competes occur, no matter the CPU, I/O, memory, or network resources, all of them will result in entire performance deterioration. In the high concurrency scenario, enabling the SMP will not improve the performance effect and even may cause performance deterioration.
Feedback
Was this page helpful?
Provide feedbackThank you very much for your feedback. We will continue working to improve the documentation.See the reply and handling status in My Cloud VOC.
For any further questions, feel free to contact us through the chatbot.
Chatbot