Elastic search的应用与入门 - 知乎

   Double[] qv = new Double[]{0.04881, -0.33609, -0.13305, 0.11145, -0.08408, -0.03294, -0.40138, 0.19321, -0.02528, -0.02768, -0.07773, -0.23604, 0.12693, -0.07832, 0.03975, -0.23248, -0.04273, 0.10179, 0.15156, -6.8E-4, 0.07414, 0.02857, 0.19306, -0.06342, -0.15033, 0.0331, 0.01185, 0.08438, -0.04065, -0.10001, 0.09478, 0.07242, 0.07154, -0.11093, -0.0125, -0.10403, -0.07861, -0.16341, -0.17495, 0.10467, -0.08135, -0.18041, 0.23096, 0.16601, 0.00806, 0.06222, -0.11909, -0.0224, -0.00351, 0.00517, -0.10414, 0.07032, 0.17009, 0.13883, -0.12384, -0.13548, -0.01265, -0.01102, -0.02224, -0.10055, 0.11512, 0.04149, -0.0423, -0.01998};
        List<Double> queryVector = Arrays.asList(qv);
        Function<KnnSearchRequest.Builder, ObjectBuilder<KnnSearchRequest>> knnRequest =
                builder -> builder.index(indexName).knn(s -> s.field("vector").queryVector(queryVector).k(10).numCandidates(10L));

        KnnSearchResponse<VectorModel> response = esClient.knnSearch(knnRequest, VectorModel.class);

https://zhuanlan.zhihu.com/p/512758939

kNN search API | Elasticsearch Guide [8.8] | Elastic