From 7a7c7d9224e9941867cd430b9dbb0e5d78b0f51b Mon Sep 17 00:00:00 2001 From: wt Date: Thu, 16 Sep 2021 18:47:49 +0800 Subject: [PATCH] [skip ci] Add comments to search file in the benchmark (#8100) Signed-off-by: wangting0128 --- tests/benchmark/milvus_benchmark/runners/search.py | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/tests/benchmark/milvus_benchmark/runners/search.py b/tests/benchmark/milvus_benchmark/runners/search.py index 29b7d0eb22..6c6417424e 100644 --- a/tests/benchmark/milvus_benchmark/runners/search.py +++ b/tests/benchmark/milvus_benchmark/runners/search.py @@ -158,6 +158,7 @@ class InsertSearchRunner(BaseRunner): } vector_type = utils.get_vector_type(data_type) index_field_name = utils.get_default_field_name(vector_type) + # Get the path of the query.npy file stored on the NAS and get its data base_query_vectors = utils.get_vectors_from_binary(utils.MAX_NQ, dimension, data_type) cases = list() case_metrics = list() @@ -177,6 +178,7 @@ class InsertSearchRunner(BaseRunner): # filter_param.append(filter["term"]) # logger.info("filter param: %s" % json.dumps(filter_param)) for nq in nqs: + # Take nq groups of data for query query_vectors = base_query_vectors[0:nq] for top_k in top_ks: search_info = { @@ -257,6 +259,7 @@ class InsertSearchRunner(BaseRunner): start_time = time.time() self.milvus.create_index(index_field_name, case_param["index_type"], case_param["metric_type"], index_param=case_param["index_param"]) build_time = round(time.time()-start_time, 2) + # build_time includes flush and index time logger.debug({"flush_time": flush_time, "build_time": build_time}) self.build_time = build_time logger.info(self.milvus.count()) @@ -271,6 +274,7 @@ class InsertSearchRunner(BaseRunner): min_query_time = 0.0 total_query_time = 0.0 for i in range(run_count): + # Number of successive queries logger.debug("Start run query, run %d of %s" % (i+1, run_count)) logger.info(case_metric.search) start_time = time.time() @@ -281,6 +285,7 @@ class InsertSearchRunner(BaseRunner): min_query_time = round(interval_time, 2) avg_query_time = round(total_query_time/run_count, 2) logger.info("Min query time: %.2f, avg query time: %.2f" % (min_query_time, avg_query_time)) + # insert_result: "total_time", "rps", "ni_time" tmp_result = {"insert": self.insert_result, "build_time": self.build_time, "search_time": min_query_time, "avc_search_time": avg_query_time} # # logger.info("Start load collection")