[2024-08-17T00:13:07.365Z] Running test renaissance-movie-lens_0 ... [2024-08-17T00:13:07.365Z] =============================================== [2024-08-17T00:13:07.365Z] renaissance-movie-lens_0 Start Time: Fri Aug 16 17:13:05 2024 Epoch Time (ms): 1723853585254 [2024-08-17T00:13:07.365Z] variation: NoOptions [2024-08-17T00:13:07.365Z] JVM_OPTIONS: [2024-08-17T00:13:07.365Z] { \ [2024-08-17T00:13:07.365Z] echo ""; echo "TEST SETUP:"; \ [2024-08-17T00:13:07.365Z] echo "Nothing to be done for setup."; \ [2024-08-17T00:13:07.365Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17238495041963/renaissance-movie-lens_0"; \ [2024-08-17T00:13:07.365Z] cd "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17238495041963/renaissance-movie-lens_0"; \ [2024-08-17T00:13:07.365Z] echo ""; echo "TESTING:"; \ [2024-08-17T00:13:07.365Z] "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_1/jdkbinary/j2sdk-image/Contents/Home/bin/..//bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17238495041963/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2024-08-17T00:13:07.365Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/..; rm -f -r "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17238495041963/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-08-17T00:13:07.365Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-08-17T00:13:07.365Z] echo "Nothing to be done for teardown."; \ [2024-08-17T00:13:07.365Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17238495041963/TestTargetResult"; [2024-08-17T00:13:07.365Z] [2024-08-17T00:13:07.365Z] TEST SETUP: [2024-08-17T00:13:07.365Z] Nothing to be done for setup. [2024-08-17T00:13:07.365Z] [2024-08-17T00:13:07.365Z] TESTING: [2024-08-17T00:13:22.976Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-08-17T00:13:30.095Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 3 (out of 3) threads. [2024-08-17T00:13:43.786Z] Got 100004 ratings from 671 users on 9066 movies. [2024-08-17T00:13:50.852Z] Training: 60056, validation: 20285, test: 19854 [2024-08-17T00:13:50.852Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-08-17T00:13:51.571Z] GC before operation: completed in 1580.471 ms, heap usage 169.137 MB -> 36.658 MB. [2024-08-17T00:14:35.672Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T00:14:58.879Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T00:15:31.588Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T00:15:50.713Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T00:16:14.475Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T00:16:24.715Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T00:16:37.959Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T00:16:47.809Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T00:16:48.949Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2024-08-17T00:16:49.386Z] The best model improves the baseline by 14.52%. [2024-08-17T00:16:50.395Z] Movies recommended for you: [2024-08-17T00:16:50.395Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T00:16:50.395Z] There is no way to check that no silent failure occurred. [2024-08-17T00:16:50.395Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (178482.117 ms) ====== [2024-08-17T00:16:50.395Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-08-17T00:16:50.395Z] GC before operation: completed in 254.983 ms, heap usage 148.919 MB -> 50.115 MB. [2024-08-17T00:17:12.834Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T00:17:31.758Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T00:17:58.266Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T00:18:07.496Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T00:18:20.682Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T00:18:27.838Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T00:18:38.647Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T00:18:49.366Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T00:18:49.899Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2024-08-17T00:18:49.899Z] The best model improves the baseline by 14.52%. [2024-08-17T00:18:50.922Z] Movies recommended for you: [2024-08-17T00:18:50.922Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T00:18:50.922Z] There is no way to check that no silent failure occurred. [2024-08-17T00:18:50.922Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (120615.652 ms) ====== [2024-08-17T00:18:50.922Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-08-17T00:18:51.422Z] GC before operation: completed in 303.141 ms, heap usage 74.308 MB -> 51.390 MB. [2024-08-17T00:19:12.951Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T00:19:44.366Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T00:19:53.794Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T00:20:16.757Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T00:20:27.816Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T00:20:37.453Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T00:20:48.532Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T00:21:01.951Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T00:21:02.573Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2024-08-17T00:21:02.573Z] The best model improves the baseline by 14.52%. [2024-08-17T00:21:04.630Z] Movies recommended for you: [2024-08-17T00:21:04.630Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T00:21:04.630Z] There is no way to check that no silent failure occurred. [2024-08-17T00:21:04.630Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (132463.249 ms) ====== [2024-08-17T00:21:04.630Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-08-17T00:21:04.630Z] GC before operation: completed in 300.848 ms, heap usage 63.105 MB -> 52.422 MB. [2024-08-17T00:21:36.491Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T00:21:54.835Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T00:22:13.053Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T00:22:31.666Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T00:22:40.873Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T00:22:50.809Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T00:23:01.816Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T00:23:11.715Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T00:23:12.137Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2024-08-17T00:23:12.137Z] The best model improves the baseline by 14.52%. [2024-08-17T00:23:12.530Z] Movies recommended for you: [2024-08-17T00:23:12.530Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T00:23:12.530Z] There is no way to check that no silent failure occurred. [2024-08-17T00:23:12.530Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (128315.256 ms) ====== [2024-08-17T00:23:12.530Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-08-17T00:23:12.960Z] GC before operation: completed in 241.887 ms, heap usage 71.077 MB -> 51.858 MB. [2024-08-17T00:23:34.990Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T00:23:49.938Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T00:24:16.815Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T00:24:35.999Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T00:24:50.368Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T00:25:03.148Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T00:25:14.723Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T00:25:27.675Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T00:25:34.889Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2024-08-17T00:25:35.404Z] The best model improves the baseline by 14.52%. [2024-08-17T00:25:35.404Z] Movies recommended for you: [2024-08-17T00:25:35.404Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T00:25:35.404Z] There is no way to check that no silent failure occurred. [2024-08-17T00:25:35.404Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (142647.111 ms) ====== [2024-08-17T00:25:35.404Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-08-17T00:25:35.842Z] GC before operation: completed in 459.497 ms, heap usage 312.962 MB -> 49.766 MB. [2024-08-17T00:25:54.119Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T00:26:12.244Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T00:26:30.520Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T00:26:43.312Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T00:26:54.616Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T00:27:10.730Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T00:27:23.068Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T00:27:36.286Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T00:27:36.286Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2024-08-17T00:27:36.286Z] The best model improves the baseline by 14.52%. [2024-08-17T00:27:36.986Z] Movies recommended for you: [2024-08-17T00:27:36.986Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T00:27:36.986Z] There is no way to check that no silent failure occurred. [2024-08-17T00:27:36.986Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (121107.254 ms) ====== [2024-08-17T00:27:36.986Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-08-17T00:27:37.458Z] GC before operation: completed in 363.292 ms, heap usage 466.744 MB -> 52.994 MB. [2024-08-17T00:27:59.546Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T00:28:15.287Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T00:28:30.980Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T00:28:53.093Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T00:29:05.113Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T00:29:12.749Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T00:29:23.809Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T00:29:34.559Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T00:29:34.559Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2024-08-17T00:29:35.058Z] The best model improves the baseline by 14.52%. [2024-08-17T00:29:35.058Z] Movies recommended for you: [2024-08-17T00:29:35.058Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T00:29:35.058Z] There is no way to check that no silent failure occurred. [2024-08-17T00:29:35.058Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (117781.168 ms) ====== [2024-08-17T00:29:35.058Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-08-17T00:29:36.349Z] GC before operation: completed in 1414.393 ms, heap usage 278.250 MB -> 49.815 MB. [2024-08-17T00:29:54.606Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T00:30:13.742Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T00:30:32.528Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T00:30:51.218Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T00:31:04.616Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T00:31:11.982Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T00:31:31.487Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T00:31:37.867Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T00:31:39.304Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2024-08-17T00:31:39.304Z] The best model improves the baseline by 14.52%. [2024-08-17T00:31:41.184Z] Movies recommended for you: [2024-08-17T00:31:41.184Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T00:31:41.184Z] There is no way to check that no silent failure occurred. [2024-08-17T00:31:41.184Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (124245.433 ms) ====== [2024-08-17T00:31:41.184Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-08-17T00:31:41.184Z] GC before operation: completed in 139.832 ms, heap usage 256.972 MB -> 50.094 MB. [2024-08-17T00:31:59.745Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T00:32:22.028Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T00:32:35.046Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T00:32:50.838Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T00:33:00.028Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T00:33:09.644Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T00:33:16.681Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T00:33:24.380Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T00:33:25.255Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2024-08-17T00:33:25.255Z] The best model improves the baseline by 14.52%. [2024-08-17T00:33:25.711Z] Movies recommended for you: [2024-08-17T00:33:25.711Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T00:33:25.711Z] There is no way to check that no silent failure occurred. [2024-08-17T00:33:25.711Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (104709.040 ms) ====== [2024-08-17T00:33:25.711Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-08-17T00:33:26.257Z] GC before operation: completed in 205.259 ms, heap usage 78.068 MB -> 51.921 MB. [2024-08-17T00:33:44.391Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T00:34:02.752Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T00:34:18.332Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T00:34:40.744Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T00:34:44.392Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T00:34:53.978Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T00:35:03.782Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T00:35:13.275Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T00:35:13.275Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2024-08-17T00:35:13.275Z] The best model improves the baseline by 14.52%. [2024-08-17T00:35:13.275Z] Movies recommended for you: [2024-08-17T00:35:13.275Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T00:35:13.275Z] There is no way to check that no silent failure occurred. [2024-08-17T00:35:13.275Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (107148.074 ms) ====== [2024-08-17T00:35:13.275Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-08-17T00:35:14.552Z] GC before operation: completed in 959.710 ms, heap usage 71.156 MB -> 51.858 MB. [2024-08-17T00:35:33.332Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T00:35:49.347Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T00:36:05.449Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T00:36:20.669Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T00:36:31.749Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T00:36:43.109Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T00:36:49.108Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T00:37:09.287Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T00:37:09.287Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2024-08-17T00:37:09.287Z] The best model improves the baseline by 14.52%. [2024-08-17T00:37:09.287Z] Movies recommended for you: [2024-08-17T00:37:09.287Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T00:37:09.287Z] There is no way to check that no silent failure occurred. [2024-08-17T00:37:09.287Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (114803.259 ms) ====== [2024-08-17T00:37:09.287Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-08-17T00:37:09.287Z] GC before operation: completed in 403.201 ms, heap usage 250.525 MB -> 49.775 MB. [2024-08-17T00:37:32.141Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T00:37:54.876Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T00:38:16.986Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T00:38:30.751Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T00:38:40.369Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T00:38:49.176Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T00:39:00.514Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T00:39:08.745Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T00:39:08.745Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2024-08-17T00:39:08.745Z] The best model improves the baseline by 14.52%. [2024-08-17T00:39:10.725Z] Movies recommended for you: [2024-08-17T00:39:10.725Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T00:39:10.725Z] There is no way to check that no silent failure occurred. [2024-08-17T00:39:10.725Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (121392.217 ms) ====== [2024-08-17T00:39:10.725Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-08-17T00:39:10.725Z] GC before operation: completed in 312.229 ms, heap usage 128.754 MB -> 49.805 MB. [2024-08-17T00:39:26.862Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T00:39:53.783Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T00:40:09.863Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T00:40:36.282Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T00:40:43.618Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T00:40:54.133Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T00:41:03.299Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T00:41:10.785Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T00:41:11.787Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2024-08-17T00:41:11.787Z] The best model improves the baseline by 14.52%. [2024-08-17T00:41:12.231Z] Movies recommended for you: [2024-08-17T00:41:12.231Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T00:41:12.231Z] There is no way to check that no silent failure occurred. [2024-08-17T00:41:12.231Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (121282.584 ms) ====== [2024-08-17T00:41:12.231Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-08-17T00:41:12.638Z] GC before operation: completed in 333.468 ms, heap usage 166.609 MB -> 50.107 MB. [2024-08-17T00:41:44.377Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T00:41:55.652Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T00:42:23.057Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T00:42:37.138Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T00:42:46.271Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T00:42:55.839Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T00:43:03.420Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T00:43:12.550Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T00:43:13.600Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2024-08-17T00:43:14.175Z] The best model improves the baseline by 14.52%. [2024-08-17T00:43:14.175Z] Movies recommended for you: [2024-08-17T00:43:14.175Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T00:43:14.175Z] There is no way to check that no silent failure occurred. [2024-08-17T00:43:14.175Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (121558.964 ms) ====== [2024-08-17T00:43:14.175Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-08-17T00:43:15.221Z] GC before operation: completed in 1063.087 ms, heap usage 205.635 MB -> 49.788 MB. [2024-08-17T00:43:42.359Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T00:43:59.716Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T00:44:19.913Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T00:44:38.862Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T00:44:55.413Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T00:45:03.266Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T00:45:12.205Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T00:45:24.317Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T00:45:24.832Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2024-08-17T00:45:24.832Z] The best model improves the baseline by 14.52%. [2024-08-17T00:45:24.832Z] Movies recommended for you: [2024-08-17T00:45:24.832Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T00:45:24.832Z] There is no way to check that no silent failure occurred. [2024-08-17T00:45:24.832Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (129839.742 ms) ====== [2024-08-17T00:45:24.832Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-08-17T00:45:26.503Z] GC before operation: completed in 1105.872 ms, heap usage 250.245 MB -> 50.019 MB. [2024-08-17T00:45:48.765Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T00:46:05.595Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T00:46:23.921Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T00:46:39.538Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T00:46:47.319Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T00:47:00.826Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T00:47:20.637Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T00:47:25.540Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T00:47:26.784Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2024-08-17T00:47:27.776Z] The best model improves the baseline by 14.52%. [2024-08-17T00:47:27.776Z] Movies recommended for you: [2024-08-17T00:47:27.776Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T00:47:27.776Z] There is no way to check that no silent failure occurred. [2024-08-17T00:47:27.776Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (121850.935 ms) ====== [2024-08-17T00:47:27.776Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-08-17T00:47:28.200Z] GC before operation: completed in 253.311 ms, heap usage 175.235 MB -> 50.044 MB. [2024-08-17T00:47:47.114Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T00:48:10.690Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T00:48:26.193Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T00:48:44.642Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T00:48:53.625Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T00:48:59.752Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T00:49:09.764Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T00:49:21.296Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T00:49:25.855Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2024-08-17T00:49:25.855Z] The best model improves the baseline by 14.52%. [2024-08-17T00:49:28.417Z] Movies recommended for you: [2024-08-17T00:49:28.417Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T00:49:28.417Z] There is no way to check that no silent failure occurred. [2024-08-17T00:49:28.417Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (119219.174 ms) ====== [2024-08-17T00:49:28.417Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-08-17T00:49:28.893Z] GC before operation: completed in 1465.028 ms, heap usage 129.950 MB -> 49.816 MB. [2024-08-17T00:49:47.522Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T00:50:05.820Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T00:50:30.021Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T00:50:45.166Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T00:50:53.821Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T00:51:02.967Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T00:51:14.118Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T00:51:23.453Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T00:51:24.692Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2024-08-17T00:51:24.692Z] The best model improves the baseline by 14.52%. [2024-08-17T00:51:25.758Z] Movies recommended for you: [2024-08-17T00:51:25.758Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T00:51:25.758Z] There is no way to check that no silent failure occurred. [2024-08-17T00:51:25.758Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (115931.610 ms) ====== [2024-08-17T00:51:25.758Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-08-17T00:51:25.758Z] GC before operation: completed in 345.597 ms, heap usage 274.240 MB -> 50.004 MB. [2024-08-17T00:51:49.493Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T00:52:08.220Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T00:52:27.474Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T00:52:43.503Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T00:52:53.563Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T00:53:01.059Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T00:53:19.844Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T00:53:25.814Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T00:53:25.814Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2024-08-17T00:53:25.814Z] The best model improves the baseline by 14.52%. [2024-08-17T00:53:26.225Z] Movies recommended for you: [2024-08-17T00:53:26.225Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T00:53:26.225Z] There is no way to check that no silent failure occurred. [2024-08-17T00:53:26.225Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (120982.781 ms) ====== [2024-08-17T00:53:26.225Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-08-17T00:53:26.225Z] GC before operation: completed in 256.271 ms, heap usage 211.814 MB -> 50.209 MB. [2024-08-17T00:53:42.229Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T00:54:09.414Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T00:54:20.643Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T00:54:43.333Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T00:54:50.712Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T00:54:58.622Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T00:55:08.624Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T00:55:15.652Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T00:55:17.946Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2024-08-17T00:55:17.946Z] The best model improves the baseline by 14.52%. [2024-08-17T00:55:18.370Z] Movies recommended for you: [2024-08-17T00:55:18.370Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T00:55:18.370Z] There is no way to check that no silent failure occurred. [2024-08-17T00:55:18.370Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (111740.503 ms) ====== [2024-08-17T00:55:23.033Z] ----------------------------------- [2024-08-17T00:55:23.033Z] renaissance-movie-lens_0_PASSED [2024-08-17T00:55:23.033Z] ----------------------------------- [2024-08-17T00:55:23.033Z] [2024-08-17T00:55:23.033Z] TEST TEARDOWN: [2024-08-17T00:55:23.033Z] Nothing to be done for teardown. [2024-08-17T00:55:23.442Z] renaissance-movie-lens_0 Finish Time: Fri Aug 16 17:55:22 2024 Epoch Time (ms): 1723856122397