remove unecessary prints

uwdb · Nov 10, 2023 · 830caed · 830caed
1 parent ba8c7c3
commit 830caed
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Showing 2 changed files with 4 additions and 10 deletions.
diff --git a/Experiments/graph_results.jl b/Experiments/graph_results.jl
@@ -70,7 +70,6 @@ end
 
 function get_query_id(dataset, query_path)
     return if dataset == "lubm80"
-        println(query_path)
         match(r".*/queryset/(.*/.*)", query_path).captures[1]
     elseif dataset in ["aids", "human", "yago"]
         match(r".*/queryset/.*/(.*/.*)", query_path).captures[1]

diff --git a/Experiments/run_estimators.jl b/Experiments/run_estimators.jl
@@ -11,18 +11,13 @@ function run_estimation_experiments(experiment_params_list::Vector{ExperimentPar
             query::QueryGraph = all_queries[dataset][i].query
             query_path = all_queries[dataset][i].query_path
             exact_size = all_queries[dataset][i].exact_size
-            estimate_times = [(@timed get_cardinality_bounds(query, summary;
+            estimate_results = [(@timed get_cardinality_bounds(query, summary;
                                     max_partial_paths = experiment_params.inference_max_paths,
                                     use_partial_sums=experiment_params.use_partial_sums, usingStoredStats=true,
                                     sampling_strategy=experiment_params.sampling_strategy,
-                                    only_shortest_path_cycle= experiment_params.only_shortest_path_cycle)).time for _ in 1:3]
-            estimate_time = median(estimate_times) # Convert back to seconds from nano seconds
-
-            bounds = get_cardinality_bounds(query, summary;
-                                max_partial_paths = experiment_params.inference_max_paths,
-                                use_partial_sums=experiment_params.use_partial_sums, usingStoredStats=true,
-                                sampling_strategy=experiment_params.sampling_strategy,
-                                only_shortest_path_cycle= experiment_params.only_shortest_path_cycle)
+                                    only_shortest_path_cycle= experiment_params.only_shortest_path_cycle)) for _ in 1:3]
+            estimate_time = median([x.time for x in  estimate_results]) # Convert back to seconds from nano seconds
+            bounds = estimate_results[1].value
             upper_bound = bounds[3]
             estimate = max(1, bounds[2])
             lower_bound = bounds[1]