Why it always returns only 10 rows of result even if collection.num_entities>1000 and limit=10
The script is as belowed:
collection = Collection(name="test_collection")collection.load()print(collection.num_entities)search_params = {"metric_type": "IP","params": {"nprobe": 10}}np_query_embeddings = np.array(query_embeddings, dtype=np.float32)norms = np.linalg.norm([np_query_embeddings], axis=1, keepdims=True)normalized_query_embeddings = np_query_embeddings / normsquery_vectors = normalized_query_embeddings.tolist()limit = 1000results = collection.search(data=query_vectors,anns_field="embedding",param=search_params,limit=limit,consistency_level="Strong",)print(results)Display:
8503 ["['id: 449617239426872838, distance: 0.7159370183944702, entity: {}', 'id: 449617239426877164, distance: 0.7090992331504822, entity: {}', 'id: 449617239426880450, distance: 0.699631929397583, entity: {}', 'id: 449617239426876554, distance: 0.6782248020172119, entity: {}', 'id: 449617239426876178, distance: 0.6769057512283325, entity: {}', 'id: 449617239426880350, distance: 0.6754627823829651, entity: {}', 'id: 449617239426875291, distance: 0.6698116064071655, entity: {}', 'id: 449617239426877126, distance: 0.6647711396217346, entity: {}', 'id: 449617239426876516, distance: 0.6610612869262695, entity: {}', 'id: 449617239426880437, distance: 0.6571118831634521, entity: {}']"]