I have three data nodes, configured as 16 core 64g, with an index of about 19million documents, including 768 dimensional vector fields. The number of fragments is 24, the number of copies is 1, and the total size includes about 600g copies. Currently, it is retrieved by KNN, k=10, num_ Candidates=50, the retrieval time is about 20~30 seconds, and the retrieval time after caching is about 10~20 seconds. How to optimize the retrieval speed to within 10 seconds? What is the bottleneck of current retrieval? I think the current CPU utilization rate is usually less than 25%. How can we make full use of CPU resources? Or how can I analyze the memory usage and CPU usage in a query process?
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