rally-custom/custom_tracks/opensearch/dense_vector/track.py [241:279]:
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                                "vector": query_vector,
                                "k": num_candidates
                            }
                        }
                    },
                    "_source": False,
                    "profile": True
                },
                index=index,
                request_cache=request_cache,
                size=k,
            )
            knn_hits = [hit["_id"] for hit in knn_result["hits"]["hits"]]
            script_hits = await knn_vector_store.get_neighbors_for_query(index, query_id, target_k, request_cache, es)
            script_hits = script_hits[:k]
            current_recall = len(set(knn_hits).intersection(set(script_hits)))
            recall_total += current_recall
            exact_total += len(script_hits)
            min_recall = min(min_recall, current_recall)

        return (
            {
                "avg_recall": recall_total / exact_total,
                "min_recall": min_recall,
                "k": k,
                "num_candidates": num_candidates
            }
            if exact_total > 0
            else None
        )

    def __repr__(self, *args, **kwargs):
        return "knn-recall"


def register(registry):
    registry.register_param_source("knn-param-source", KnnParamSource)
    registry.register_param_source("knn-recall-param-source", KnnRecallParamSource)
    registry.register_runner("knn-recall", KnnRecallRunner(), async_runner=True)
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rally-custom/custom_tracks/opensearch/so_vector/track.py [233:271]:
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                                "vector": query_vector,
                                "k": num_candidates
                            }
                        }
                    },
                    "_source": False,
                    "profile": True
                },
                index=index,
                request_cache=request_cache,
                size=k,
            )
            knn_hits = [hit["_id"] for hit in knn_result["hits"]["hits"]]
            script_hits = await knn_vector_store.get_neighbors_for_query(index, query_id, target_k, request_cache, es)
            script_hits = script_hits[:k]
            current_recall = len(set(knn_hits).intersection(set(script_hits)))
            recall_total += current_recall
            exact_total += len(script_hits)
            min_recall = min(min_recall, current_recall)

        return (
            {
                "avg_recall": recall_total / exact_total,
                "min_recall": min_recall,
                "k": k,
                "num_candidates": num_candidates
            }
            if exact_total > 0
            else None
        )

    def __repr__(self, *args, **kwargs):
        return "knn-recall"


def register(registry):
    registry.register_param_source("knn-param-source", KnnParamSource)
    registry.register_param_source("knn-recall-param-source", KnnRecallParamSource)
    registry.register_runner("knn-recall", KnnRecallRunner(), async_runner=True)
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