[2024-08-22T02:21:00.745Z] Running test renaissance-movie-lens_0 ... [2024-08-22T02:21:00.745Z] =============================================== [2024-08-22T02:21:00.745Z] renaissance-movie-lens_0 Start Time: Wed Aug 21 19:20:59 2024 Epoch Time (ms): 1724293259362 [2024-08-22T02:21:00.745Z] variation: NoOptions [2024-08-22T02:21:00.745Z] JVM_OPTIONS: [2024-08-22T02:21:00.745Z] { \ [2024-08-22T02:21:00.745Z] echo ""; echo "TEST SETUP:"; \ [2024-08-22T02:21:00.745Z] echo "Nothing to be done for setup."; \ [2024-08-22T02:21:00.745Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17242911701126/renaissance-movie-lens_0"; \ [2024-08-22T02:21:00.745Z] cd "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17242911701126/renaissance-movie-lens_0"; \ [2024-08-22T02:21:00.745Z] echo ""; echo "TESTING:"; \ [2024-08-22T02:21:00.745Z] "/Users/admin/workspace/workspace/Test_openjdk17_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_openjdk17_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17242911701126/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2024-08-22T02:21:00.745Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/..; rm -f -r "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17242911701126/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-08-22T02:21:00.745Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-08-22T02:21:00.745Z] echo "Nothing to be done for teardown."; \ [2024-08-22T02:21:00.745Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17242911701126/TestTargetResult"; [2024-08-22T02:21:00.745Z] [2024-08-22T02:21:00.745Z] TEST SETUP: [2024-08-22T02:21:00.745Z] Nothing to be done for setup. [2024-08-22T02:21:00.745Z] [2024-08-22T02:21:00.745Z] TESTING: [2024-08-22T02:21:16.350Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-08-22T02:21:23.547Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 3 (out of 3) threads. [2024-08-22T02:21:34.955Z] Got 100004 ratings from 671 users on 9066 movies. [2024-08-22T02:21:36.895Z] Training: 60056, validation: 20285, test: 19854 [2024-08-22T02:21:36.895Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-08-22T02:21:37.313Z] GC before operation: completed in 251.633 ms, heap usage 55.581 MB -> 37.384 MB. [2024-08-22T02:22:16.506Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T02:22:38.972Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T02:23:01.651Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T02:23:24.568Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T02:23:34.602Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T02:23:46.002Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T02:23:58.935Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T02:24:07.227Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T02:24:08.440Z] 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. [2024-08-22T02:24:08.440Z] The best model improves the baseline by 14.52%. [2024-08-22T02:24:08.901Z] Movies recommended for you: [2024-08-22T02:24:08.901Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T02:24:08.901Z] There is no way to check that no silent failure occurred. [2024-08-22T02:24:08.901Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (151616.591 ms) ====== [2024-08-22T02:24:08.901Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-08-22T02:24:08.901Z] GC before operation: completed in 327.248 ms, heap usage 517.503 MB -> 55.090 MB. [2024-08-22T02:24:32.220Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T02:24:48.961Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T02:25:12.062Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T02:25:28.008Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T02:25:40.192Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T02:25:46.664Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T02:25:54.734Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T02:26:06.732Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T02:26:06.732Z] 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. [2024-08-22T02:26:06.732Z] The best model improves the baseline by 14.52%. [2024-08-22T02:26:06.732Z] Movies recommended for you: [2024-08-22T02:26:06.732Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T02:26:06.732Z] There is no way to check that no silent failure occurred. [2024-08-22T02:26:06.732Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (117501.944 ms) ====== [2024-08-22T02:26:06.732Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-08-22T02:26:07.376Z] GC before operation: completed in 716.266 ms, heap usage 77.381 MB -> 52.195 MB. [2024-08-22T02:26:23.813Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T02:26:36.634Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T02:26:52.144Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T02:27:06.821Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T02:27:14.667Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T02:27:24.223Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T02:27:30.836Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T02:27:39.064Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T02:27:39.064Z] 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. [2024-08-22T02:27:39.064Z] The best model improves the baseline by 14.52%. [2024-08-22T02:27:39.648Z] Movies recommended for you: [2024-08-22T02:27:39.648Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T02:27:39.648Z] There is no way to check that no silent failure occurred. [2024-08-22T02:27:39.648Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (92329.385 ms) ====== [2024-08-22T02:27:39.648Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-08-22T02:27:39.648Z] GC before operation: completed in 159.954 ms, heap usage 105.964 MB -> 53.163 MB. [2024-08-22T02:27:52.939Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T02:28:09.431Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T02:28:28.496Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T02:28:52.357Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T02:28:58.715Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T02:29:08.848Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T02:29:18.592Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T02:29:27.961Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T02:29:27.961Z] 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. [2024-08-22T02:29:27.961Z] The best model improves the baseline by 14.52%. [2024-08-22T02:29:28.693Z] Movies recommended for you: [2024-08-22T02:29:28.694Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T02:29:28.694Z] There is no way to check that no silent failure occurred. [2024-08-22T02:29:28.694Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (109029.684 ms) ====== [2024-08-22T02:29:29.139Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-08-22T02:29:29.139Z] GC before operation: completed in 227.266 ms, heap usage 284.987 MB -> 50.432 MB. [2024-08-22T02:29:45.185Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T02:30:04.764Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T02:30:24.454Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T02:30:38.059Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T02:30:44.393Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T02:30:53.964Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T02:31:03.275Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T02:31:11.705Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T02:31:11.705Z] 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. [2024-08-22T02:31:11.705Z] The best model improves the baseline by 14.52%. [2024-08-22T02:31:12.178Z] Movies recommended for you: [2024-08-22T02:31:12.178Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T02:31:12.178Z] There is no way to check that no silent failure occurred. [2024-08-22T02:31:12.178Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (103102.659 ms) ====== [2024-08-22T02:31:12.178Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-08-22T02:31:12.178Z] GC before operation: completed in 207.324 ms, heap usage 272.078 MB -> 50.633 MB. [2024-08-22T02:31:30.832Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T02:31:50.770Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T02:32:09.441Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T02:32:23.178Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T02:32:34.402Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T02:32:44.235Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T02:32:50.868Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T02:33:02.050Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T02:33:04.383Z] 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. [2024-08-22T02:33:04.383Z] The best model improves the baseline by 14.52%. [2024-08-22T02:33:04.383Z] Movies recommended for you: [2024-08-22T02:33:04.383Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T02:33:04.383Z] There is no way to check that no silent failure occurred. [2024-08-22T02:33:04.383Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (112089.145 ms) ====== [2024-08-22T02:33:04.383Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-08-22T02:33:05.002Z] GC before operation: completed in 190.139 ms, heap usage 271.490 MB -> 50.575 MB. [2024-08-22T02:33:21.148Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T02:33:40.561Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T02:33:54.659Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T02:34:11.638Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T02:34:21.429Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T02:34:30.544Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T02:34:44.238Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T02:34:54.093Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T02:34:55.927Z] 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. [2024-08-22T02:34:55.927Z] The best model improves the baseline by 14.52%. [2024-08-22T02:34:55.927Z] Movies recommended for you: [2024-08-22T02:34:55.927Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T02:34:55.927Z] There is no way to check that no silent failure occurred. [2024-08-22T02:34:55.927Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (111201.868 ms) ====== [2024-08-22T02:34:55.927Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-08-22T02:34:56.616Z] GC before operation: completed in 291.620 ms, heap usage 401.875 MB -> 54.066 MB. [2024-08-22T02:35:15.911Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T02:35:39.268Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T02:35:57.794Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T02:36:13.441Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T02:36:23.891Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T02:36:34.736Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T02:36:45.959Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T02:36:56.155Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T02:36:58.082Z] 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. [2024-08-22T02:36:58.082Z] The best model improves the baseline by 14.52%. [2024-08-22T02:36:58.082Z] Movies recommended for you: [2024-08-22T02:36:58.082Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T02:36:58.082Z] There is no way to check that no silent failure occurred. [2024-08-22T02:36:58.082Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (121845.520 ms) ====== [2024-08-22T02:36:58.082Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-08-22T02:36:58.082Z] GC before operation: completed in 195.239 ms, heap usage 401.194 MB -> 54.333 MB. [2024-08-22T02:37:25.518Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T02:37:41.722Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T02:37:57.774Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T02:38:16.635Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T02:38:25.881Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T02:38:33.851Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T02:38:43.723Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T02:38:54.446Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T02:38:57.825Z] 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. [2024-08-22T02:38:57.825Z] The best model improves the baseline by 14.52%. [2024-08-22T02:38:57.825Z] Movies recommended for you: [2024-08-22T02:38:57.825Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T02:38:57.825Z] There is no way to check that no silent failure occurred. [2024-08-22T02:38:57.825Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (119503.879 ms) ====== [2024-08-22T02:38:57.825Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-08-22T02:38:58.991Z] GC before operation: completed in 259.155 ms, heap usage 283.150 MB -> 50.902 MB. [2024-08-22T02:39:17.722Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T02:39:33.673Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T02:39:49.298Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T02:40:05.652Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T02:40:14.642Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T02:40:27.916Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T02:40:36.917Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T02:40:46.408Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T02:40:46.408Z] 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. [2024-08-22T02:40:46.408Z] The best model improves the baseline by 14.52%. [2024-08-22T02:40:48.771Z] Movies recommended for you: [2024-08-22T02:40:48.771Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T02:40:48.771Z] There is no way to check that no silent failure occurred. [2024-08-22T02:40:48.771Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (109905.398 ms) ====== [2024-08-22T02:40:48.771Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-08-22T02:40:48.771Z] GC before operation: completed in 307.216 ms, heap usage 64.359 MB -> 54.388 MB. [2024-08-22T02:41:07.902Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T02:41:23.684Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T02:41:42.985Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T02:41:59.370Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T02:42:08.755Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T02:42:25.589Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T02:42:36.659Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T02:42:47.861Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T02:42:48.419Z] 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. [2024-08-22T02:42:48.419Z] The best model improves the baseline by 14.52%. [2024-08-22T02:42:49.201Z] Movies recommended for you: [2024-08-22T02:42:49.201Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T02:42:49.201Z] There is no way to check that no silent failure occurred. [2024-08-22T02:42:49.201Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (120916.458 ms) ====== [2024-08-22T02:42:49.201Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-08-22T02:42:50.235Z] GC before operation: completed in 963.938 ms, heap usage 446.739 MB -> 54.169 MB. [2024-08-22T02:43:09.082Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T02:43:27.595Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T02:43:46.255Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T02:43:59.836Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T02:44:07.708Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T02:44:19.541Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T02:44:27.526Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T02:44:37.074Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T02:44:39.052Z] 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. [2024-08-22T02:44:39.052Z] The best model improves the baseline by 14.52%. [2024-08-22T02:44:39.052Z] Movies recommended for you: [2024-08-22T02:44:39.052Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T02:44:39.052Z] There is no way to check that no silent failure occurred. [2024-08-22T02:44:39.052Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (109144.092 ms) ====== [2024-08-22T02:44:39.052Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-08-22T02:44:39.522Z] GC before operation: completed in 114.259 ms, heap usage 357.855 MB -> 51.080 MB. [2024-08-22T02:44:58.844Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T02:45:22.196Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T02:45:38.868Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T02:45:54.956Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T02:46:03.726Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T02:46:11.537Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T02:46:23.198Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T02:46:34.544Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T02:46:35.697Z] 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. [2024-08-22T02:46:35.697Z] The best model improves the baseline by 14.52%. [2024-08-22T02:46:35.697Z] Movies recommended for you: [2024-08-22T02:46:35.697Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T02:46:35.697Z] There is no way to check that no silent failure occurred. [2024-08-22T02:46:35.697Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (116409.603 ms) ====== [2024-08-22T02:46:35.697Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-08-22T02:46:36.264Z] GC before operation: completed in 380.688 ms, heap usage 356.980 MB -> 51.253 MB. [2024-08-22T02:46:52.442Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T02:47:11.214Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T02:47:30.797Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T02:47:49.658Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T02:47:58.265Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T02:48:09.609Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T02:48:19.024Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T02:48:28.780Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T02:48:28.780Z] 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. [2024-08-22T02:48:28.780Z] The best model improves the baseline by 14.52%. [2024-08-22T02:48:29.237Z] Movies recommended for you: [2024-08-22T02:48:29.237Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T02:48:29.237Z] There is no way to check that no silent failure occurred. [2024-08-22T02:48:29.237Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (112960.870 ms) ====== [2024-08-22T02:48:29.237Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-08-22T02:48:29.670Z] GC before operation: completed in 277.341 ms, heap usage 68.068 MB -> 54.230 MB. [2024-08-22T02:48:48.681Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T02:49:10.402Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T02:49:23.770Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T02:49:48.401Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T02:49:58.106Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T02:50:09.918Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T02:50:19.226Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T02:50:28.253Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T02:50:29.309Z] 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. [2024-08-22T02:50:29.309Z] The best model improves the baseline by 14.52%. [2024-08-22T02:50:29.851Z] Movies recommended for you: [2024-08-22T02:50:29.851Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T02:50:29.851Z] There is no way to check that no silent failure occurred. [2024-08-22T02:50:29.851Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (120146.566 ms) ====== [2024-08-22T02:50:29.851Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-08-22T02:50:30.686Z] GC before operation: completed in 1262.886 ms, heap usage 133.953 MB -> 52.161 MB. [2024-08-22T02:50:52.584Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T02:51:12.217Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T02:51:31.786Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T02:51:48.058Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T02:51:57.064Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T02:52:03.970Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T02:52:15.552Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T02:52:22.300Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T02:52:24.228Z] 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. [2024-08-22T02:52:24.228Z] The best model improves the baseline by 14.52%. [2024-08-22T02:52:24.808Z] Movies recommended for you: [2024-08-22T02:52:24.808Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T02:52:24.808Z] There is no way to check that no silent failure occurred. [2024-08-22T02:52:24.808Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (113864.180 ms) ====== [2024-08-22T02:52:24.808Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-08-22T02:52:24.808Z] GC before operation: completed in 283.764 ms, heap usage 423.502 MB -> 56.947 MB. [2024-08-22T02:52:47.322Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T02:53:03.065Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T02:53:18.627Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T02:53:37.914Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T02:53:44.896Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T02:53:55.902Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T02:54:03.842Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T02:54:14.764Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T02:54:14.764Z] 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. [2024-08-22T02:54:14.764Z] The best model improves the baseline by 14.52%. [2024-08-22T02:54:15.402Z] Movies recommended for you: [2024-08-22T02:54:15.402Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T02:54:15.402Z] There is no way to check that no silent failure occurred. [2024-08-22T02:54:15.402Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (110555.802 ms) ====== [2024-08-22T02:54:15.402Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-08-22T02:54:16.015Z] GC before operation: completed in 265.538 ms, heap usage 294.885 MB -> 51.025 MB. [2024-08-22T02:54:31.339Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T02:54:50.019Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T02:55:03.439Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T02:55:19.937Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T02:55:28.987Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T02:55:40.741Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T02:55:50.187Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T02:55:57.639Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T02:55:59.574Z] 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. [2024-08-22T02:55:59.574Z] The best model improves the baseline by 14.52%. [2024-08-22T02:56:00.061Z] Movies recommended for you: [2024-08-22T02:56:00.061Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T02:56:00.061Z] There is no way to check that no silent failure occurred. [2024-08-22T02:56:00.061Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (104269.123 ms) ====== [2024-08-22T02:56:00.061Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-08-22T02:56:00.061Z] GC before operation: completed in 206.985 ms, heap usage 165.051 MB -> 50.980 MB. [2024-08-22T02:56:18.660Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T02:56:29.269Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T02:56:45.736Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T02:57:07.908Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T02:57:15.586Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T02:57:25.188Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T02:57:36.533Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T02:57:44.605Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T02:57:45.044Z] 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. [2024-08-22T02:57:45.044Z] The best model improves the baseline by 14.52%. [2024-08-22T02:57:45.044Z] Movies recommended for you: [2024-08-22T02:57:45.044Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T02:57:45.044Z] There is no way to check that no silent failure occurred. [2024-08-22T02:57:45.044Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (104927.522 ms) ====== [2024-08-22T02:57:45.044Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-08-22T02:57:46.344Z] GC before operation: completed in 224.997 ms, heap usage 182.927 MB -> 51.297 MB. [2024-08-22T02:58:04.502Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T02:58:24.543Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T02:58:40.929Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T02:59:00.181Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T02:59:08.077Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T02:59:25.470Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T02:59:34.380Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T02:59:43.744Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T02:59:44.731Z] 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. [2024-08-22T02:59:45.337Z] The best model improves the baseline by 14.52%. [2024-08-22T02:59:45.845Z] Movies recommended for you: [2024-08-22T02:59:45.845Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T02:59:45.845Z] There is no way to check that no silent failure occurred. [2024-08-22T02:59:45.845Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (120401.236 ms) ====== [2024-08-22T02:59:48.069Z] ----------------------------------- [2024-08-22T02:59:48.069Z] renaissance-movie-lens_0_PASSED [2024-08-22T02:59:48.069Z] ----------------------------------- [2024-08-22T02:59:48.962Z] [2024-08-22T02:59:48.962Z] TEST TEARDOWN: [2024-08-22T02:59:48.962Z] Nothing to be done for teardown. [2024-08-22T02:59:48.962Z] renaissance-movie-lens_0 Finish Time: Wed Aug 21 19:59:48 2024 Epoch Time (ms): 1724295588042