[2025-02-20T05:39:23.843Z] Running test renaissance-movie-lens_0 ... [2025-02-20T05:39:23.843Z] =============================================== [2025-02-20T05:39:23.843Z] renaissance-movie-lens_0 Start Time: Wed Feb 19 21:39:21 2025 Epoch Time (ms): 1740029961784 [2025-02-20T05:39:23.843Z] variation: NoOptions [2025-02-20T05:39:23.843Z] JVM_OPTIONS: [2025-02-20T05:39:23.843Z] { \ [2025-02-20T05:39:23.843Z] echo ""; echo "TEST SETUP:"; \ [2025-02-20T05:39:23.843Z] echo "Nothing to be done for setup."; \ [2025-02-20T05:39:23.843Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17400286687390/renaissance-movie-lens_0"; \ [2025-02-20T05:39:23.843Z] cd "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17400286687390/renaissance-movie-lens_0"; \ [2025-02-20T05:39:23.843Z] echo ""; echo "TESTING:"; \ [2025-02-20T05:39:23.844Z] "/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_17400286687390/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-02-20T05:39:23.844Z] 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_17400286687390/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-02-20T05:39:23.844Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-02-20T05:39:23.844Z] echo "Nothing to be done for teardown."; \ [2025-02-20T05:39:23.844Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17400286687390/TestTargetResult"; [2025-02-20T05:39:23.844Z] [2025-02-20T05:39:23.844Z] TEST SETUP: [2025-02-20T05:39:23.844Z] Nothing to be done for setup. [2025-02-20T05:39:23.844Z] [2025-02-20T05:39:23.844Z] TESTING: [2025-02-20T05:39:26.428Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2025-02-20T05:39:27.711Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 3 (out of 3) threads. [2025-02-20T05:39:30.297Z] Got 100004 ratings from 671 users on 9066 movies. [2025-02-20T05:39:30.297Z] Training: 60056, validation: 20285, test: 19854 [2025-02-20T05:39:30.297Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-02-20T05:39:30.297Z] GC before operation: completed in 47.918 ms, heap usage 108.607 MB -> 36.580 MB. [2025-02-20T05:39:36.846Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-20T05:39:39.405Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-20T05:39:42.754Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-20T05:39:46.077Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-20T05:39:47.434Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-20T05:39:49.357Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-20T05:39:50.710Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-20T05:39:52.644Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-20T05:39:52.644Z] 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. [2025-02-20T05:39:53.039Z] The best model improves the baseline by 14.52%. [2025-02-20T05:39:53.039Z] Movies recommended for you: [2025-02-20T05:39:53.039Z] WARNING: This benchmark provides no result that can be validated. [2025-02-20T05:39:53.039Z] There is no way to check that no silent failure occurred. [2025-02-20T05:39:53.039Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (22510.041 ms) ====== [2025-02-20T05:39:53.040Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-02-20T05:39:53.040Z] GC before operation: completed in 94.505 ms, heap usage 263.354 MB -> 46.848 MB. [2025-02-20T05:39:56.355Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-20T05:39:58.917Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-20T05:40:02.254Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-20T05:40:04.828Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-20T05:40:06.732Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-20T05:40:08.026Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-20T05:40:09.911Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-20T05:40:11.855Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-20T05:40:11.855Z] 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. [2025-02-20T05:40:11.855Z] The best model improves the baseline by 14.52%. [2025-02-20T05:40:11.855Z] Movies recommended for you: [2025-02-20T05:40:11.855Z] WARNING: This benchmark provides no result that can be validated. [2025-02-20T05:40:11.855Z] There is no way to check that no silent failure occurred. [2025-02-20T05:40:11.855Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (18776.924 ms) ====== [2025-02-20T05:40:11.855Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-02-20T05:40:11.855Z] GC before operation: completed in 77.220 ms, heap usage 143.177 MB -> 48.798 MB. [2025-02-20T05:40:15.174Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-20T05:40:17.737Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-20T05:40:21.129Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-20T05:40:24.422Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-20T05:40:25.812Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-20T05:40:27.704Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-20T05:40:29.581Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-20T05:40:30.880Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-20T05:40:31.267Z] 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. [2025-02-20T05:40:31.267Z] The best model improves the baseline by 14.52%. [2025-02-20T05:40:31.267Z] Movies recommended for you: [2025-02-20T05:40:31.267Z] WARNING: This benchmark provides no result that can be validated. [2025-02-20T05:40:31.267Z] There is no way to check that no silent failure occurred. [2025-02-20T05:40:31.267Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (19503.555 ms) ====== [2025-02-20T05:40:31.267Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-02-20T05:40:31.673Z] GC before operation: completed in 77.532 ms, heap usage 63.818 MB -> 52.501 MB. [2025-02-20T05:40:35.027Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-20T05:40:37.579Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-20T05:40:40.843Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-20T05:40:42.746Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-20T05:40:44.625Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-20T05:40:46.585Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-20T05:40:47.965Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-20T05:40:49.874Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-20T05:40:49.875Z] 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. [2025-02-20T05:40:49.875Z] The best model improves the baseline by 14.52%. [2025-02-20T05:40:49.875Z] Movies recommended for you: [2025-02-20T05:40:49.875Z] WARNING: This benchmark provides no result that can be validated. [2025-02-20T05:40:49.875Z] There is no way to check that no silent failure occurred. [2025-02-20T05:40:49.875Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (18306.745 ms) ====== [2025-02-20T05:40:49.875Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-02-20T05:40:49.875Z] GC before operation: completed in 78.605 ms, heap usage 66.245 MB -> 52.839 MB. [2025-02-20T05:40:53.195Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-20T05:40:55.756Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-20T05:40:58.281Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-20T05:41:00.857Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-20T05:41:02.757Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-20T05:41:04.094Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-20T05:41:05.434Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-20T05:41:07.327Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-20T05:41:07.327Z] 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. [2025-02-20T05:41:07.327Z] The best model improves the baseline by 14.52%. [2025-02-20T05:41:07.327Z] Movies recommended for you: [2025-02-20T05:41:07.327Z] WARNING: This benchmark provides no result that can be validated. [2025-02-20T05:41:07.327Z] There is no way to check that no silent failure occurred. [2025-02-20T05:41:07.327Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (17499.233 ms) ====== [2025-02-20T05:41:07.327Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-02-20T05:41:07.327Z] GC before operation: completed in 85.614 ms, heap usage 356.481 MB -> 53.018 MB. [2025-02-20T05:41:10.751Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-20T05:41:13.300Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-20T05:41:15.854Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-20T05:41:19.143Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-20T05:41:20.463Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-20T05:41:22.312Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-20T05:41:23.615Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-20T05:41:24.922Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-20T05:41:25.314Z] 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. [2025-02-20T05:41:25.314Z] The best model improves the baseline by 14.52%. [2025-02-20T05:41:25.314Z] Movies recommended for you: [2025-02-20T05:41:25.314Z] WARNING: This benchmark provides no result that can be validated. [2025-02-20T05:41:25.314Z] There is no way to check that no silent failure occurred. [2025-02-20T05:41:25.314Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (17933.433 ms) ====== [2025-02-20T05:41:25.314Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-02-20T05:41:25.314Z] GC before operation: completed in 76.756 ms, heap usage 353.997 MB -> 52.941 MB. [2025-02-20T05:41:28.596Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-20T05:41:31.884Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-20T05:41:34.456Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-20T05:41:37.705Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-20T05:41:39.575Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-20T05:41:40.913Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-20T05:41:42.243Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-20T05:41:44.119Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-20T05:41:44.120Z] 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. [2025-02-20T05:41:44.120Z] The best model improves the baseline by 14.52%. [2025-02-20T05:41:44.120Z] Movies recommended for you: [2025-02-20T05:41:44.120Z] WARNING: This benchmark provides no result that can be validated. [2025-02-20T05:41:44.120Z] There is no way to check that no silent failure occurred. [2025-02-20T05:41:44.120Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (18659.950 ms) ====== [2025-02-20T05:41:44.120Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-02-20T05:41:44.120Z] GC before operation: completed in 74.278 ms, heap usage 214.459 MB -> 49.756 MB. [2025-02-20T05:41:46.631Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-20T05:41:49.110Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-20T05:41:51.572Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-20T05:41:53.469Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-20T05:41:54.294Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-20T05:41:55.593Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-20T05:41:56.435Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-20T05:41:57.770Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-20T05:41:57.770Z] 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. [2025-02-20T05:41:57.770Z] The best model improves the baseline by 14.52%. [2025-02-20T05:41:57.770Z] Movies recommended for you: [2025-02-20T05:41:57.770Z] WARNING: This benchmark provides no result that can be validated. [2025-02-20T05:41:57.770Z] There is no way to check that no silent failure occurred. [2025-02-20T05:41:57.770Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (13588.791 ms) ====== [2025-02-20T05:41:57.770Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-02-20T05:41:57.770Z] GC before operation: completed in 73.538 ms, heap usage 280.599 MB -> 50.178 MB. [2025-02-20T05:42:00.238Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-20T05:42:02.835Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-20T05:42:04.740Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-20T05:42:07.302Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-20T05:42:09.155Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-20T05:42:10.449Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-20T05:42:12.303Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-20T05:42:13.608Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-20T05:42:13.608Z] 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. [2025-02-20T05:42:13.608Z] The best model improves the baseline by 14.52%. [2025-02-20T05:42:14.025Z] Movies recommended for you: [2025-02-20T05:42:14.025Z] WARNING: This benchmark provides no result that can be validated. [2025-02-20T05:42:14.025Z] There is no way to check that no silent failure occurred. [2025-02-20T05:42:14.025Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (15983.222 ms) ====== [2025-02-20T05:42:14.025Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-02-20T05:42:14.025Z] GC before operation: completed in 74.032 ms, heap usage 132.369 MB -> 49.781 MB. [2025-02-20T05:42:16.565Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-20T05:42:19.854Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-20T05:42:22.365Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-20T05:42:24.873Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-20T05:42:26.718Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-20T05:42:28.043Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-20T05:42:29.936Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-20T05:42:31.284Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-20T05:42:31.284Z] 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. [2025-02-20T05:42:31.284Z] The best model improves the baseline by 14.52%. [2025-02-20T05:42:31.284Z] Movies recommended for you: [2025-02-20T05:42:31.284Z] WARNING: This benchmark provides no result that can be validated. [2025-02-20T05:42:31.284Z] There is no way to check that no silent failure occurred. [2025-02-20T05:42:31.284Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (17385.162 ms) ====== [2025-02-20T05:42:31.284Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-02-20T05:42:31.284Z] GC before operation: completed in 64.084 ms, heap usage 142.061 MB -> 49.953 MB. [2025-02-20T05:42:34.613Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-20T05:42:37.858Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-20T05:42:40.323Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-20T05:42:42.244Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-20T05:42:44.082Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-20T05:42:45.409Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-20T05:42:46.763Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-20T05:42:48.234Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-20T05:42:50.677Z] 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. [2025-02-20T05:42:50.677Z] The best model improves the baseline by 14.52%. [2025-02-20T05:42:50.677Z] Movies recommended for you: [2025-02-20T05:42:50.677Z] WARNING: This benchmark provides no result that can be validated. [2025-02-20T05:42:50.677Z] There is no way to check that no silent failure occurred. [2025-02-20T05:42:50.677Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (17287.353 ms) ====== [2025-02-20T05:42:50.677Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-02-20T05:42:50.677Z] GC before operation: completed in 73.480 ms, heap usage 357.126 MB -> 53.090 MB. [2025-02-20T05:42:51.552Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-20T05:42:54.062Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-20T05:42:57.319Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-20T05:42:59.839Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-20T05:43:01.163Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-20T05:43:03.048Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-20T05:43:04.359Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-20T05:43:05.726Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-20T05:43:06.127Z] 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. [2025-02-20T05:43:06.127Z] The best model improves the baseline by 14.52%. [2025-02-20T05:43:06.127Z] Movies recommended for you: [2025-02-20T05:43:06.128Z] WARNING: This benchmark provides no result that can be validated. [2025-02-20T05:43:06.128Z] There is no way to check that no silent failure occurred. [2025-02-20T05:43:06.128Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (17469.584 ms) ====== [2025-02-20T05:43:06.128Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-02-20T05:43:06.128Z] GC before operation: completed in 82.253 ms, heap usage 359.098 MB -> 53.241 MB. [2025-02-20T05:43:09.445Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-20T05:43:11.964Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-20T05:43:14.473Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-20T05:43:17.749Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-20T05:43:19.086Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-20T05:43:20.428Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-20T05:43:22.331Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-20T05:43:23.652Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-20T05:43:24.035Z] 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. [2025-02-20T05:43:24.035Z] The best model improves the baseline by 14.52%. [2025-02-20T05:43:24.035Z] Movies recommended for you: [2025-02-20T05:43:24.035Z] WARNING: This benchmark provides no result that can be validated. [2025-02-20T05:43:24.035Z] There is no way to check that no silent failure occurred. [2025-02-20T05:43:24.035Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (17805.113 ms) ====== [2025-02-20T05:43:24.035Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-02-20T05:43:24.035Z] GC before operation: completed in 76.055 ms, heap usage 188.399 MB -> 50.032 MB. [2025-02-20T05:43:27.401Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-20T05:43:29.948Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-20T05:43:32.462Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-20T05:43:35.020Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-20T05:43:36.363Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-20T05:43:37.682Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-20T05:43:38.985Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-20T05:43:40.859Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-20T05:43:40.859Z] 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. [2025-02-20T05:43:40.859Z] The best model improves the baseline by 14.52%. [2025-02-20T05:43:40.859Z] Movies recommended for you: [2025-02-20T05:43:40.859Z] WARNING: This benchmark provides no result that can be validated. [2025-02-20T05:43:40.859Z] There is no way to check that no silent failure occurred. [2025-02-20T05:43:40.859Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (16713.566 ms) ====== [2025-02-20T05:43:40.859Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-02-20T05:43:40.859Z] GC before operation: completed in 68.550 ms, heap usage 144.288 MB -> 49.788 MB. [2025-02-20T05:43:44.179Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-20T05:43:46.075Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-20T05:43:48.610Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-20T05:43:51.106Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-20T05:43:53.072Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-20T05:43:54.380Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-20T05:43:56.247Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-20T05:43:57.524Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-20T05:43:57.896Z] 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. [2025-02-20T05:43:57.896Z] The best model improves the baseline by 14.52%. [2025-02-20T05:43:57.896Z] Movies recommended for you: [2025-02-20T05:43:57.896Z] WARNING: This benchmark provides no result that can be validated. [2025-02-20T05:43:57.896Z] There is no way to check that no silent failure occurred. [2025-02-20T05:43:57.896Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (16959.411 ms) ====== [2025-02-20T05:43:57.896Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-02-20T05:43:57.896Z] GC before operation: completed in 84.432 ms, heap usage 119.174 MB -> 49.904 MB. [2025-02-20T05:44:01.353Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-20T05:44:03.925Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-20T05:44:06.432Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-20T05:44:08.917Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-20T05:44:10.796Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-20T05:44:12.085Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-20T05:44:14.036Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-20T05:44:15.332Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-20T05:44:15.716Z] 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. [2025-02-20T05:44:15.716Z] The best model improves the baseline by 14.52%. [2025-02-20T05:44:15.716Z] Movies recommended for you: [2025-02-20T05:44:15.716Z] WARNING: This benchmark provides no result that can be validated. [2025-02-20T05:44:15.716Z] There is no way to check that no silent failure occurred. [2025-02-20T05:44:15.717Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (17692.054 ms) ====== [2025-02-20T05:44:15.717Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-02-20T05:44:15.717Z] GC before operation: completed in 72.088 ms, heap usage 123.644 MB -> 49.980 MB. [2025-02-20T05:44:18.998Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-20T05:44:20.916Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-20T05:44:24.163Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-20T05:44:26.689Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-20T05:44:27.713Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-20T05:44:29.570Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-20T05:44:31.456Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-20T05:44:32.785Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-20T05:44:32.785Z] 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. [2025-02-20T05:44:32.785Z] The best model improves the baseline by 14.52%. [2025-02-20T05:44:33.173Z] Movies recommended for you: [2025-02-20T05:44:33.173Z] WARNING: This benchmark provides no result that can be validated. [2025-02-20T05:44:33.173Z] There is no way to check that no silent failure occurred. [2025-02-20T05:44:33.173Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (17262.092 ms) ====== [2025-02-20T05:44:33.173Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-02-20T05:44:33.173Z] GC before operation: completed in 79.034 ms, heap usage 350.033 MB -> 53.264 MB. [2025-02-20T05:44:35.747Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-20T05:44:39.003Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-20T05:44:41.465Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-20T05:44:43.996Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-20T05:44:45.872Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-20T05:44:47.232Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-20T05:44:49.098Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-20T05:44:50.402Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-20T05:44:50.402Z] 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. [2025-02-20T05:44:50.402Z] The best model improves the baseline by 14.52%. [2025-02-20T05:44:50.402Z] Movies recommended for you: [2025-02-20T05:44:50.402Z] WARNING: This benchmark provides no result that can be validated. [2025-02-20T05:44:50.402Z] There is no way to check that no silent failure occurred. [2025-02-20T05:44:50.402Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (17448.375 ms) ====== [2025-02-20T05:44:50.402Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-02-20T05:44:50.790Z] GC before operation: completed in 67.279 ms, heap usage 124.907 MB -> 49.923 MB. [2025-02-20T05:44:53.317Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-20T05:44:56.606Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-20T05:44:59.137Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-20T05:45:01.690Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-20T05:45:03.052Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-20T05:45:04.428Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-20T05:45:06.351Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-20T05:45:07.190Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-20T05:45:07.569Z] 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. [2025-02-20T05:45:07.569Z] The best model improves the baseline by 14.52%. [2025-02-20T05:45:07.569Z] Movies recommended for you: [2025-02-20T05:45:07.569Z] WARNING: This benchmark provides no result that can be validated. [2025-02-20T05:45:07.569Z] There is no way to check that no silent failure occurred. [2025-02-20T05:45:07.569Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (16971.741 ms) ====== [2025-02-20T05:45:07.569Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-02-20T05:45:07.569Z] GC before operation: completed in 73.695 ms, heap usage 72.247 MB -> 51.624 MB. [2025-02-20T05:45:10.090Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-20T05:45:12.688Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-20T05:45:15.980Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-20T05:45:17.936Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-20T05:45:19.267Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-20T05:45:21.138Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-20T05:45:22.431Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-20T05:45:23.724Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-20T05:45:24.115Z] 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. [2025-02-20T05:45:24.115Z] The best model improves the baseline by 14.52%. [2025-02-20T05:45:24.115Z] Movies recommended for you: [2025-02-20T05:45:24.115Z] WARNING: This benchmark provides no result that can be validated. [2025-02-20T05:45:24.115Z] There is no way to check that no silent failure occurred. [2025-02-20T05:45:24.115Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (16477.516 ms) ====== [2025-02-20T05:45:24.920Z] ----------------------------------- [2025-02-20T05:45:24.920Z] renaissance-movie-lens_0_PASSED [2025-02-20T05:45:24.920Z] ----------------------------------- [2025-02-20T05:45:24.920Z] [2025-02-20T05:45:24.920Z] TEST TEARDOWN: [2025-02-20T05:45:24.920Z] Nothing to be done for teardown. [2025-02-20T05:45:24.921Z] renaissance-movie-lens_0 Finish Time: Wed Feb 19 21:45:23 2025 Epoch Time (ms): 1740030323431