待验证50% 置信事实时间未知
Prior to Milvus 3.0, vector search could only sort results by similarity, requiring users to pull all results to the client and write custom sorting code for secondary sorting.
1
来源数
50%
置信度
中期 (~90 天)
时效性
2026/7/2
首次发现
有效期至：2026/9/30
来源
相关事实
待验证Milvus 3.0 introduces an Order By feature that supports specifying multi-level sorting rules directly in the search statement, processed in a single pass by the database kernel.74% 相似待验证Python 内置排序算法 Tim Sort 由 Tim Peters 于2002年设计，结合了归并排序与插入排序的优点，最坏情况下保持 O(n log n)55% 相似待验证Vector search uses ANN (Approximate Nearest Neighbor) algorithms to quickly find similar vectors54% 相似待验证Vector similarity search uses cosine similarity or Euclidean distance to find chunks whose vectors are closest to the user's query vector.54% 相似待验证Milvus 3.0 supports aggregation queries (such as group by, count, average, maximum) written directly in queries and processed at the database layer, eliminating the need to fetch all records to the application layer.53% 相似
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