[2025-02-26T01:09:41.821Z] Running test renaissance-movie-lens_0 ... [2025-02-26T01:09:42.186Z] =============================================== [2025-02-26T01:09:42.186Z] renaissance-movie-lens_0 Start Time: Wed Feb 26 01:09:41 2025 Epoch Time (ms): 1740532181974 [2025-02-26T01:09:42.186Z] variation: NoOptions [2025-02-26T01:09:42.541Z] JVM_OPTIONS: [2025-02-26T01:09:42.541Z] { \ [2025-02-26T01:09:42.541Z] echo ""; echo "TEST SETUP:"; \ [2025-02-26T01:09:42.541Z] echo "Nothing to be done for setup."; \ [2025-02-26T01:09:42.541Z] mkdir -p "C:/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17405306961450\\renaissance-movie-lens_0"; \ [2025-02-26T01:09:42.541Z] cd "C:/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17405306961450\\renaissance-movie-lens_0"; \ [2025-02-26T01:09:42.541Z] echo ""; echo "TESTING:"; \ [2025-02-26T01:09:42.541Z] "c:/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_windows/jdkbinary/j2sdk-image\\bin\\java" -jar "C:/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_windows/aqa-tests///..//jvmtest\\perf\\renaissance\\renaissance.jar" --json ""C:/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17405306961450\\renaissance-movie-lens_0"\\movie-lens.json" movie-lens; \ [2025-02-26T01:09:42.541Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd C:/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_windows/aqa-tests/; rm -f -r "C:/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17405306961450\\renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-02-26T01:09:42.541Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-02-26T01:09:42.541Z] echo "Nothing to be done for teardown."; \ [2025-02-26T01:09:42.541Z] } 2>&1 | tee -a "C:/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17405306961450\\TestTargetResult"; [2025-02-26T01:09:42.541Z] [2025-02-26T01:09:42.541Z] TEST SETUP: [2025-02-26T01:09:42.541Z] Nothing to be done for setup. [2025-02-26T01:09:42.541Z] [2025-02-26T01:09:42.541Z] TESTING: [2025-02-26T01:09:58.253Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2025-02-26T01:09:59.509Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-02-26T01:10:03.358Z] Got 100004 ratings from 671 users on 9066 movies. [2025-02-26T01:10:03.701Z] Training: 60056, validation: 20285, test: 19854 [2025-02-26T01:10:03.701Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-02-26T01:10:04.064Z] GC before operation: completed in 202.614 ms, heap usage 178.760 MB -> 26.521 MB. [2025-02-26T01:10:17.250Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-26T01:10:30.417Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-26T01:10:43.556Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-26T01:10:56.616Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-26T01:11:00.345Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-26T01:11:06.260Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-26T01:11:12.258Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-26T01:11:18.132Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-26T01:11:18.856Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536. [2025-02-26T01:11:18.856Z] The best model improves the baseline by 14.52%. [2025-02-26T01:11:18.856Z] Movies recommended for you: [2025-02-26T01:11:18.856Z] WARNING: This benchmark provides no result that can be validated. [2025-02-26T01:11:18.856Z] There is no way to check that no silent failure occurred. [2025-02-26T01:11:18.856Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (75076.662 ms) ====== [2025-02-26T01:11:18.856Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-02-26T01:11:19.565Z] GC before operation: completed in 354.180 ms, heap usage 347.878 MB -> 40.530 MB. [2025-02-26T01:11:28.507Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-26T01:11:37.353Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-26T01:11:48.063Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-26T01:11:56.908Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-26T01:12:00.649Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-26T01:12:06.491Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-26T01:12:12.342Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-26T01:12:17.065Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-26T01:12:17.432Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536. [2025-02-26T01:12:17.432Z] The best model improves the baseline by 14.52%. [2025-02-26T01:12:17.765Z] Movies recommended for you: [2025-02-26T01:12:17.765Z] WARNING: This benchmark provides no result that can be validated. [2025-02-26T01:12:17.765Z] There is no way to check that no silent failure occurred. [2025-02-26T01:12:17.765Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (58293.543 ms) ====== [2025-02-26T01:12:17.765Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-02-26T01:12:17.765Z] GC before operation: completed in 207.325 ms, heap usage 539.771 MB -> 45.299 MB. [2025-02-26T01:12:26.564Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-26T01:12:35.382Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-26T01:12:44.174Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-26T01:12:52.959Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-26T01:12:57.663Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-26T01:13:02.378Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-26T01:13:08.222Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-26T01:13:12.914Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-26T01:13:12.914Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536. [2025-02-26T01:13:12.914Z] The best model improves the baseline by 14.52%. [2025-02-26T01:13:13.249Z] Movies recommended for you: [2025-02-26T01:13:13.249Z] WARNING: This benchmark provides no result that can be validated. [2025-02-26T01:13:13.249Z] There is no way to check that no silent failure occurred. [2025-02-26T01:13:13.249Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (55376.913 ms) ====== [2025-02-26T01:13:13.249Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-02-26T01:13:13.581Z] GC before operation: completed in 207.962 ms, heap usage 607.928 MB -> 46.078 MB. [2025-02-26T01:13:22.368Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-26T01:13:31.317Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-26T01:13:40.472Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-26T01:13:49.324Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-26T01:13:54.002Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-26T01:13:58.679Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-26T01:14:04.533Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-26T01:14:09.235Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-26T01:14:09.235Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536. [2025-02-26T01:14:09.235Z] The best model improves the baseline by 14.52%. [2025-02-26T01:14:09.235Z] Movies recommended for you: [2025-02-26T01:14:09.235Z] WARNING: This benchmark provides no result that can be validated. [2025-02-26T01:14:09.235Z] There is no way to check that no silent failure occurred. [2025-02-26T01:14:09.235Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (55926.027 ms) ====== [2025-02-26T01:14:09.235Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-02-26T01:14:09.567Z] GC before operation: completed in 167.657 ms, heap usage 563.071 MB -> 46.110 MB. [2025-02-26T01:14:18.365Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-26T01:14:25.544Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-26T01:14:36.271Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-26T01:14:42.092Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-26T01:14:47.990Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-26T01:14:52.882Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-26T01:14:58.824Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-26T01:15:03.566Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-26T01:15:03.566Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536. [2025-02-26T01:15:03.566Z] The best model improves the baseline by 14.52%. [2025-02-26T01:15:03.903Z] Movies recommended for you: [2025-02-26T01:15:03.903Z] WARNING: This benchmark provides no result that can be validated. [2025-02-26T01:15:03.903Z] There is no way to check that no silent failure occurred. [2025-02-26T01:15:03.903Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (54286.142 ms) ====== [2025-02-26T01:15:03.903Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-02-26T01:15:03.903Z] GC before operation: completed in 158.817 ms, heap usage 586.458 MB -> 46.573 MB. [2025-02-26T01:15:12.731Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-26T01:15:21.498Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-26T01:15:30.282Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-26T01:15:37.547Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-26T01:15:42.228Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-26T01:15:46.932Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-26T01:15:52.744Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-26T01:15:57.516Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-26T01:15:57.516Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536. [2025-02-26T01:15:57.516Z] The best model improves the baseline by 14.52%. [2025-02-26T01:15:57.516Z] Movies recommended for you: [2025-02-26T01:15:57.516Z] WARNING: This benchmark provides no result that can be validated. [2025-02-26T01:15:57.516Z] There is no way to check that no silent failure occurred. [2025-02-26T01:15:57.516Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (53561.723 ms) ====== [2025-02-26T01:15:57.516Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-02-26T01:15:57.846Z] GC before operation: completed in 159.197 ms, heap usage 565.457 MB -> 46.212 MB. [2025-02-26T01:16:06.626Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-26T01:16:13.810Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-26T01:16:24.573Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-26T01:16:31.757Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-26T01:16:36.484Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-26T01:16:41.175Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-26T01:16:47.004Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-26T01:16:51.698Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-26T01:16:51.698Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536. [2025-02-26T01:16:51.698Z] The best model improves the baseline by 14.52%. [2025-02-26T01:16:52.032Z] Movies recommended for you: [2025-02-26T01:16:52.032Z] WARNING: This benchmark provides no result that can be validated. [2025-02-26T01:16:52.032Z] There is no way to check that no silent failure occurred. [2025-02-26T01:16:52.032Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (54316.998 ms) ====== [2025-02-26T01:16:52.032Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-02-26T01:16:52.365Z] GC before operation: completed in 174.070 ms, heap usage 567.699 MB -> 46.430 MB. [2025-02-26T01:17:01.190Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-26T01:17:08.452Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-26T01:17:19.143Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-26T01:17:26.339Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-26T01:17:31.042Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-26T01:17:35.717Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-26T01:17:41.492Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-26T01:17:46.206Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-26T01:17:46.539Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536. [2025-02-26T01:17:46.539Z] The best model improves the baseline by 14.52%. [2025-02-26T01:17:46.539Z] Movies recommended for you: [2025-02-26T01:17:46.539Z] WARNING: This benchmark provides no result that can be validated. [2025-02-26T01:17:46.539Z] There is no way to check that no silent failure occurred. [2025-02-26T01:17:46.539Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (54357.521 ms) ====== [2025-02-26T01:17:46.539Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-02-26T01:17:46.869Z] GC before operation: completed in 169.982 ms, heap usage 562.499 MB -> 46.752 MB. [2025-02-26T01:17:55.648Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-26T01:18:02.831Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-26T01:18:13.524Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-26T01:18:20.756Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-26T01:18:25.246Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-26T01:18:29.948Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-26T01:18:35.805Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-26T01:18:40.502Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-26T01:18:40.502Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536. [2025-02-26T01:18:40.502Z] The best model improves the baseline by 14.52%. [2025-02-26T01:18:40.837Z] Movies recommended for you: [2025-02-26T01:18:40.837Z] WARNING: This benchmark provides no result that can be validated. [2025-02-26T01:18:40.837Z] There is no way to check that no silent failure occurred. [2025-02-26T01:18:40.837Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (54028.163 ms) ====== [2025-02-26T01:18:40.837Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-02-26T01:18:40.837Z] GC before operation: completed in 154.620 ms, heap usage 569.211 MB -> 46.505 MB. [2025-02-26T01:18:49.616Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-26T01:18:58.425Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-26T01:19:07.298Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-26T01:19:14.522Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-26T01:19:19.226Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-26T01:19:23.907Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-26T01:19:29.752Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-26T01:19:34.440Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-26T01:19:34.440Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536. [2025-02-26T01:19:34.440Z] The best model improves the baseline by 14.52%. [2025-02-26T01:19:34.784Z] Movies recommended for you: [2025-02-26T01:19:34.784Z] WARNING: This benchmark provides no result that can be validated. [2025-02-26T01:19:34.784Z] There is no way to check that no silent failure occurred. [2025-02-26T01:19:34.784Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (53856.123 ms) ====== [2025-02-26T01:19:34.784Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-02-26T01:19:35.114Z] GC before operation: completed in 205.625 ms, heap usage 575.723 MB -> 46.660 MB. [2025-02-26T01:19:43.984Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-26T01:19:52.763Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-26T01:20:01.606Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-26T01:20:10.410Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-26T01:20:14.129Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-26T01:20:18.813Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-26T01:20:24.694Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-26T01:20:29.382Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-26T01:20:29.383Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536. [2025-02-26T01:20:29.383Z] The best model improves the baseline by 14.52%. [2025-02-26T01:20:29.717Z] Movies recommended for you: [2025-02-26T01:20:29.717Z] WARNING: This benchmark provides no result that can be validated. [2025-02-26T01:20:29.717Z] There is no way to check that no silent failure occurred. [2025-02-26T01:20:29.717Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (54687.337 ms) ====== [2025-02-26T01:20:29.717Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-02-26T01:20:29.717Z] GC before operation: completed in 153.065 ms, heap usage 575.088 MB -> 46.309 MB. [2025-02-26T01:20:38.489Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-26T01:20:47.317Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-26T01:20:56.167Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-26T01:21:03.351Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-26T01:21:09.197Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-26T01:21:12.900Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-26T01:21:18.738Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-26T01:21:23.418Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-26T01:21:23.418Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536. [2025-02-26T01:21:23.418Z] The best model improves the baseline by 14.52%. [2025-02-26T01:21:23.752Z] Movies recommended for you: [2025-02-26T01:21:23.752Z] WARNING: This benchmark provides no result that can be validated. [2025-02-26T01:21:23.752Z] There is no way to check that no silent failure occurred. [2025-02-26T01:21:23.752Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (53828.558 ms) ====== [2025-02-26T01:21:23.752Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-02-26T01:21:23.752Z] GC before operation: completed in 147.318 ms, heap usage 572.785 MB -> 46.529 MB. [2025-02-26T01:21:32.565Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-26T01:21:41.442Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-26T01:21:50.229Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-26T01:21:59.015Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-26T01:22:03.692Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-26T01:22:08.387Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-26T01:22:14.233Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-26T01:22:18.932Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-26T01:22:19.266Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536. [2025-02-26T01:22:19.266Z] The best model improves the baseline by 14.52%. [2025-02-26T01:22:19.266Z] Movies recommended for you: [2025-02-26T01:22:19.266Z] WARNING: This benchmark provides no result that can be validated. [2025-02-26T01:22:19.266Z] There is no way to check that no silent failure occurred. [2025-02-26T01:22:19.266Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (55552.498 ms) ====== [2025-02-26T01:22:19.266Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-02-26T01:22:19.643Z] GC before operation: completed in 153.854 ms, heap usage 572.365 MB -> 46.746 MB. [2025-02-26T01:22:28.463Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-26T01:22:37.245Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-26T01:22:46.037Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-26T01:22:54.314Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-26T01:22:59.009Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-26T01:23:03.695Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-26T01:23:08.385Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-26T01:23:13.074Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-26T01:23:13.782Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536. [2025-02-26T01:23:13.782Z] The best model improves the baseline by 14.52%. [2025-02-26T01:23:13.782Z] Movies recommended for you: [2025-02-26T01:23:13.782Z] WARNING: This benchmark provides no result that can be validated. [2025-02-26T01:23:13.782Z] There is no way to check that no silent failure occurred. [2025-02-26T01:23:13.782Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (54297.840 ms) ====== [2025-02-26T01:23:13.782Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-02-26T01:23:14.102Z] GC before operation: completed in 139.263 ms, heap usage 565.375 MB -> 46.435 MB. [2025-02-26T01:23:22.931Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-26T01:23:31.713Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-26T01:23:40.505Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-26T01:23:47.673Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-26T01:23:53.528Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-26T01:23:58.206Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-26T01:24:02.906Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-26T01:24:07.588Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-26T01:24:08.288Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536. [2025-02-26T01:24:08.288Z] The best model improves the baseline by 14.52%. [2025-02-26T01:24:08.288Z] Movies recommended for you: [2025-02-26T01:24:08.288Z] WARNING: This benchmark provides no result that can be validated. [2025-02-26T01:24:08.288Z] There is no way to check that no silent failure occurred. [2025-02-26T01:24:08.288Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (54360.830 ms) ====== [2025-02-26T01:24:08.288Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-02-26T01:24:08.618Z] GC before operation: completed in 154.822 ms, heap usage 564.418 MB -> 46.658 MB. [2025-02-26T01:24:17.451Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-26T01:24:24.633Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-26T01:24:35.372Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-26T01:24:42.618Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-26T01:24:47.337Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-26T01:24:52.023Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-26T01:24:57.903Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-26T01:25:02.611Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-26T01:25:02.952Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536. [2025-02-26T01:25:02.952Z] The best model improves the baseline by 14.52%. [2025-02-26T01:25:03.286Z] Movies recommended for you: [2025-02-26T01:25:03.287Z] WARNING: This benchmark provides no result that can be validated. [2025-02-26T01:25:03.287Z] There is no way to check that no silent failure occurred. [2025-02-26T01:25:03.287Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (54728.419 ms) ====== [2025-02-26T01:25:03.287Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-02-26T01:25:03.287Z] GC before operation: completed in 156.829 ms, heap usage 565.182 MB -> 46.741 MB. [2025-02-26T01:25:12.069Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-26T01:25:20.864Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-26T01:25:29.652Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-26T01:25:38.467Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-26T01:25:43.188Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-26T01:25:47.895Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-26T01:25:52.584Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-26T01:25:58.408Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-26T01:25:58.408Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536. [2025-02-26T01:25:58.408Z] The best model improves the baseline by 14.52%. [2025-02-26T01:25:58.408Z] Movies recommended for you: [2025-02-26T01:25:58.408Z] WARNING: This benchmark provides no result that can be validated. [2025-02-26T01:25:58.408Z] There is no way to check that no silent failure occurred. [2025-02-26T01:25:58.408Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (54908.932 ms) ====== [2025-02-26T01:25:58.408Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-02-26T01:25:58.408Z] GC before operation: completed in 164.596 ms, heap usage 571.733 MB -> 46.609 MB. [2025-02-26T01:26:07.189Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-26T01:26:15.990Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-26T01:26:24.787Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-26T01:26:32.756Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-26T01:26:37.453Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-26T01:26:44.111Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-26T01:26:47.822Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-26T01:26:51.979Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-26T01:26:52.714Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536. [2025-02-26T01:26:52.714Z] The best model improves the baseline by 14.52%. [2025-02-26T01:26:52.714Z] Movies recommended for you: [2025-02-26T01:26:52.714Z] WARNING: This benchmark provides no result that can be validated. [2025-02-26T01:26:52.714Z] There is no way to check that no silent failure occurred. [2025-02-26T01:26:52.714Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (54365.984 ms) ====== [2025-02-26T01:26:52.714Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-02-26T01:26:55.019Z] GC before operation: completed in 169.649 ms, heap usage 561.705 MB -> 46.622 MB. [2025-02-26T01:27:03.616Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-26T01:27:10.803Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-26T01:27:19.616Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-26T01:27:28.403Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-26T01:27:33.140Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-26T01:27:37.824Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-26T01:27:43.746Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-26T01:27:48.452Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-26T01:27:48.452Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536. [2025-02-26T01:27:48.452Z] The best model improves the baseline by 14.52%. [2025-02-26T01:27:48.791Z] Movies recommended for you: [2025-02-26T01:27:48.791Z] WARNING: This benchmark provides no result that can be validated. [2025-02-26T01:27:48.791Z] There is no way to check that no silent failure occurred. [2025-02-26T01:27:48.791Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (55761.763 ms) ====== [2025-02-26T01:27:48.791Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-02-26T01:27:48.791Z] GC before operation: completed in 143.848 ms, heap usage 563.254 MB -> 46.832 MB. [2025-02-26T01:27:57.584Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-26T01:28:06.416Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-26T01:28:15.313Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-26T01:28:24.185Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-26T01:28:28.874Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-26T01:28:34.723Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-26T01:28:39.404Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-26T01:28:45.235Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-26T01:28:45.235Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536. [2025-02-26T01:28:45.235Z] The best model improves the baseline by 14.52%. [2025-02-26T01:28:45.235Z] Movies recommended for you: [2025-02-26T01:28:45.235Z] WARNING: This benchmark provides no result that can be validated. [2025-02-26T01:28:45.235Z] There is no way to check that no silent failure occurred. [2025-02-26T01:28:45.235Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (56266.650 ms) ====== [2025-02-26T01:28:45.946Z] ----------------------------------- [2025-02-26T01:28:45.946Z] renaissance-movie-lens_0_PASSED [2025-02-26T01:28:45.946Z] ----------------------------------- [2025-02-26T01:28:46.275Z] [2025-02-26T01:28:46.275Z] TEST TEARDOWN: [2025-02-26T01:28:46.275Z] Nothing to be done for teardown. [2025-02-26T01:28:46.593Z] renaissance-movie-lens_0 Finish Time: Wed Feb 26 01:28:46 2025 Epoch Time (ms): 1740533326329