[2024-08-02T00:10:55.735Z] Running test renaissance-movie-lens_0 ... [2024-08-02T00:10:56.405Z] =============================================== [2024-08-02T00:10:56.405Z] renaissance-movie-lens_0 Start Time: Fri Aug 2 00:10:56 2024 Epoch Time (ms): 1722557456225 [2024-08-02T00:10:56.713Z] variation: NoOptions [2024-08-02T00:10:56.713Z] JVM_OPTIONS: [2024-08-02T00:10:56.713Z] { \ [2024-08-02T00:10:56.713Z] echo ""; echo "TEST SETUP:"; \ [2024-08-02T00:10:56.713Z] echo "Nothing to be done for setup."; \ [2024-08-02T00:10:56.713Z] mkdir -p "C:/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_windows_testList_0/aqa-tests/\\TKG\\output_17225562359755\\renaissance-movie-lens_0"; \ [2024-08-02T00:10:56.713Z] cd "C:/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_windows_testList_0/aqa-tests/\\TKG\\output_17225562359755\\renaissance-movie-lens_0"; \ [2024-08-02T00:10:56.713Z] echo ""; echo "TESTING:"; \ [2024-08-02T00:10:56.713Z] "c:/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_windows_testList_0/jdkbinary/j2sdk-image\\bin\\java" -jar "C:/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_windows_testList_0/aqa-tests///..//jvmtest\\perf\\renaissance\\renaissance.jar" --json ""C:/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_windows_testList_0/aqa-tests/\\TKG\\output_17225562359755\\renaissance-movie-lens_0"\\movie-lens.json" movie-lens; \ [2024-08-02T00:10:56.714Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd C:/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_windows_testList_0/aqa-tests/; rm -f -r "C:/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_windows_testList_0/aqa-tests/\\TKG\\output_17225562359755\\renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-08-02T00:10:56.714Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-08-02T00:10:56.714Z] echo "Nothing to be done for teardown."; \ [2024-08-02T00:10:56.714Z] } 2>&1 | tee -a "C:/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_windows_testList_0/aqa-tests/\\TKG\\output_17225562359755\\TestTargetResult"; [2024-08-02T00:10:57.033Z] [2024-08-02T00:10:57.033Z] TEST SETUP: [2024-08-02T00:10:57.033Z] Nothing to be done for setup. [2024-08-02T00:10:57.033Z] [2024-08-02T00:10:57.033Z] TESTING: [2024-08-02T00:11:07.615Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-08-02T00:11:09.215Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2024-08-02T00:11:12.919Z] Got 100004 ratings from 671 users on 9066 movies. [2024-08-02T00:11:12.919Z] Training: 60056, validation: 20285, test: 19854 [2024-08-02T00:11:12.919Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-08-02T00:11:12.919Z] GC before operation: completed in 251.982 ms, heap usage 136.731 MB -> 26.305 MB. [2024-08-02T00:11:23.576Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-02T00:11:30.674Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-02T00:11:39.379Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-02T00:11:48.084Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-02T00:11:51.749Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-02T00:11:55.404Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-02T00:12:00.042Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-02T00:12:03.688Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-02T00:12:04.021Z] 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. [2024-08-02T00:12:04.021Z] The best model improves the baseline by 14.52%. [2024-08-02T00:12:04.021Z] Movies recommended for you: [2024-08-02T00:12:04.021Z] WARNING: This benchmark provides no result that can be validated. [2024-08-02T00:12:04.021Z] There is no way to check that no silent failure occurred. [2024-08-02T00:12:04.021Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (51172.917 ms) ====== [2024-08-02T00:12:04.021Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-08-02T00:12:04.702Z] GC before operation: completed in 384.855 ms, heap usage 181.499 MB -> 40.775 MB. [2024-08-02T00:12:11.797Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-02T00:12:17.558Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-02T00:12:24.704Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-02T00:12:30.450Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-02T00:12:35.069Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-02T00:12:38.730Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-02T00:12:42.393Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-02T00:12:46.057Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-02T00:12:46.375Z] 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. [2024-08-02T00:12:46.375Z] The best model improves the baseline by 14.52%. [2024-08-02T00:12:46.711Z] Movies recommended for you: [2024-08-02T00:12:46.712Z] WARNING: This benchmark provides no result that can be validated. [2024-08-02T00:12:46.712Z] There is no way to check that no silent failure occurred. [2024-08-02T00:12:46.712Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (42041.723 ms) ====== [2024-08-02T00:12:46.712Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-08-02T00:12:46.712Z] GC before operation: completed in 240.749 ms, heap usage 170.930 MB -> 41.334 MB. [2024-08-02T00:12:53.845Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-02T00:13:00.943Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-02T00:13:06.761Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-02T00:13:13.856Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-02T00:13:16.704Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-02T00:13:20.377Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-02T00:13:24.041Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-02T00:13:27.709Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-02T00:13:28.053Z] 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. [2024-08-02T00:13:28.053Z] The best model improves the baseline by 14.52%. [2024-08-02T00:13:28.053Z] Movies recommended for you: [2024-08-02T00:13:28.053Z] WARNING: This benchmark provides no result that can be validated. [2024-08-02T00:13:28.053Z] There is no way to check that no silent failure occurred. [2024-08-02T00:13:28.053Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (41344.032 ms) ====== [2024-08-02T00:13:28.053Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-08-02T00:13:28.373Z] GC before operation: completed in 178.431 ms, heap usage 558.571 MB -> 45.749 MB. [2024-08-02T00:13:35.507Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-02T00:13:41.279Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-02T00:13:48.371Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-02T00:13:54.133Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-02T00:13:57.810Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-02T00:14:01.471Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-02T00:14:05.141Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-02T00:14:08.813Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-02T00:14:08.813Z] 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. [2024-08-02T00:14:08.813Z] The best model improves the baseline by 14.52%. [2024-08-02T00:14:09.138Z] Movies recommended for you: [2024-08-02T00:14:09.138Z] WARNING: This benchmark provides no result that can be validated. [2024-08-02T00:14:09.138Z] There is no way to check that no silent failure occurred. [2024-08-02T00:14:09.138Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (40734.217 ms) ====== [2024-08-02T00:14:09.138Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-08-02T00:14:09.138Z] GC before operation: completed in 141.689 ms, heap usage 531.688 MB -> 46.125 MB. [2024-08-02T00:14:16.237Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-02T00:14:22.001Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-02T00:14:29.114Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-02T00:14:34.850Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-02T00:14:39.469Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-02T00:14:43.131Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-02T00:14:46.821Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-02T00:14:50.540Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-02T00:14:50.540Z] 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. [2024-08-02T00:14:50.540Z] The best model improves the baseline by 14.52%. [2024-08-02T00:14:50.540Z] Movies recommended for you: [2024-08-02T00:14:50.540Z] WARNING: This benchmark provides no result that can be validated. [2024-08-02T00:14:50.540Z] There is no way to check that no silent failure occurred. [2024-08-02T00:14:50.540Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (41293.182 ms) ====== [2024-08-02T00:14:50.540Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-08-02T00:14:50.861Z] GC before operation: completed in 148.893 ms, heap usage 517.635 MB -> 46.329 MB. [2024-08-02T00:14:57.957Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-02T00:15:03.708Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-02T00:15:09.490Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-02T00:15:16.599Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-02T00:15:20.269Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-02T00:15:23.939Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-02T00:15:27.631Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-02T00:15:31.374Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-02T00:15:31.374Z] 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. [2024-08-02T00:15:31.374Z] The best model improves the baseline by 14.52%. [2024-08-02T00:15:31.374Z] Movies recommended for you: [2024-08-02T00:15:31.374Z] WARNING: This benchmark provides no result that can be validated. [2024-08-02T00:15:31.374Z] There is no way to check that no silent failure occurred. [2024-08-02T00:15:31.374Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (40658.554 ms) ====== [2024-08-02T00:15:31.374Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-08-02T00:15:31.693Z] GC before operation: completed in 135.986 ms, heap usage 492.446 MB -> 46.149 MB. [2024-08-02T00:15:38.796Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-02T00:15:44.572Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-02T00:15:51.685Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-02T00:15:57.425Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-02T00:16:01.093Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-02T00:16:03.986Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-02T00:16:07.640Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-02T00:16:11.312Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-02T00:16:11.685Z] 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. [2024-08-02T00:16:11.685Z] The best model improves the baseline by 14.52%. [2024-08-02T00:16:11.995Z] Movies recommended for you: [2024-08-02T00:16:11.995Z] WARNING: This benchmark provides no result that can be validated. [2024-08-02T00:16:11.995Z] There is no way to check that no silent failure occurred. [2024-08-02T00:16:11.995Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (40361.100 ms) ====== [2024-08-02T00:16:11.995Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-08-02T00:16:11.995Z] GC before operation: completed in 155.648 ms, heap usage 475.324 MB -> 46.330 MB. [2024-08-02T00:16:19.086Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-02T00:16:24.852Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-02T00:16:31.943Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-02T00:16:37.675Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-02T00:16:41.349Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-02T00:16:44.202Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-02T00:16:47.869Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-02T00:16:51.525Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-02T00:16:51.853Z] 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. [2024-08-02T00:16:51.854Z] The best model improves the baseline by 14.52%. [2024-08-02T00:16:52.210Z] Movies recommended for you: [2024-08-02T00:16:52.210Z] WARNING: This benchmark provides no result that can be validated. [2024-08-02T00:16:52.210Z] There is no way to check that no silent failure occurred. [2024-08-02T00:16:52.210Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (40135.555 ms) ====== [2024-08-02T00:16:52.210Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-08-02T00:16:52.210Z] GC before operation: completed in 136.778 ms, heap usage 508.036 MB -> 52.750 MB. [2024-08-02T00:16:59.282Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-02T00:17:05.076Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-02T00:17:12.168Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-02T00:17:17.937Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-02T00:17:21.603Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-02T00:17:25.263Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-02T00:17:28.943Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-02T00:17:31.797Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-02T00:17:32.116Z] 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. [2024-08-02T00:17:32.471Z] The best model improves the baseline by 14.52%. [2024-08-02T00:17:32.471Z] Movies recommended for you: [2024-08-02T00:17:32.471Z] WARNING: This benchmark provides no result that can be validated. [2024-08-02T00:17:32.471Z] There is no way to check that no silent failure occurred. [2024-08-02T00:17:32.471Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (40152.489 ms) ====== [2024-08-02T00:17:32.471Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-08-02T00:17:32.471Z] GC before operation: completed in 135.367 ms, heap usage 613.734 MB -> 46.933 MB. [2024-08-02T00:17:39.549Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-02T00:17:45.292Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-02T00:17:52.418Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-02T00:17:58.166Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-02T00:18:01.818Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-02T00:18:04.676Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-02T00:18:09.307Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-02T00:18:12.173Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-02T00:18:12.499Z] 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. [2024-08-02T00:18:12.499Z] The best model improves the baseline by 14.52%. [2024-08-02T00:18:12.852Z] Movies recommended for you: [2024-08-02T00:18:12.852Z] WARNING: This benchmark provides no result that can be validated. [2024-08-02T00:18:12.852Z] There is no way to check that no silent failure occurred. [2024-08-02T00:18:12.852Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (40184.838 ms) ====== [2024-08-02T00:18:12.852Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-08-02T00:18:12.852Z] GC before operation: completed in 190.416 ms, heap usage 541.482 MB -> 46.643 MB. [2024-08-02T00:18:19.947Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-02T00:18:25.691Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-02T00:18:32.791Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-02T00:18:38.600Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-02T00:18:42.267Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-02T00:18:45.917Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-02T00:18:49.583Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-02T00:18:52.441Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-02T00:18:53.146Z] 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. [2024-08-02T00:18:53.146Z] The best model improves the baseline by 14.52%. [2024-08-02T00:18:53.146Z] Movies recommended for you: [2024-08-02T00:18:53.146Z] WARNING: This benchmark provides no result that can be validated. [2024-08-02T00:18:53.146Z] There is no way to check that no silent failure occurred. [2024-08-02T00:18:53.146Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (40216.826 ms) ====== [2024-08-02T00:18:53.146Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-08-02T00:18:53.146Z] GC before operation: completed in 129.823 ms, heap usage 560.438 MB -> 46.364 MB. [2024-08-02T00:19:00.247Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-02T00:19:06.017Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-02T00:19:13.106Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-02T00:19:18.860Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-02T00:19:22.531Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-02T00:19:26.171Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-02T00:19:29.849Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-02T00:19:33.537Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-02T00:19:33.537Z] 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. [2024-08-02T00:19:33.537Z] The best model improves the baseline by 14.52%. [2024-08-02T00:19:33.537Z] Movies recommended for you: [2024-08-02T00:19:33.537Z] WARNING: This benchmark provides no result that can be validated. [2024-08-02T00:19:33.537Z] There is no way to check that no silent failure occurred. [2024-08-02T00:19:33.537Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (40380.975 ms) ====== [2024-08-02T00:19:33.537Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-08-02T00:19:33.862Z] GC before operation: completed in 130.869 ms, heap usage 559.069 MB -> 46.553 MB. [2024-08-02T00:19:40.969Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-02T00:19:46.749Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-02T00:19:53.827Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-02T00:19:59.581Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-02T00:20:03.242Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-02T00:20:06.899Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-02T00:20:10.568Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-02T00:20:14.278Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-02T00:20:14.278Z] 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. [2024-08-02T00:20:14.278Z] The best model improves the baseline by 14.52%. [2024-08-02T00:20:14.278Z] Movies recommended for you: [2024-08-02T00:20:14.278Z] WARNING: This benchmark provides no result that can be validated. [2024-08-02T00:20:14.278Z] There is no way to check that no silent failure occurred. [2024-08-02T00:20:14.278Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (40444.628 ms) ====== [2024-08-02T00:20:14.278Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-08-02T00:20:14.278Z] GC before operation: completed in 127.752 ms, heap usage 531.012 MB -> 52.775 MB. [2024-08-02T00:20:21.373Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-02T00:20:27.127Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-02T00:20:34.217Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-02T00:20:39.986Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-02T00:20:43.666Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-02T00:20:47.317Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-02T00:20:50.990Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-02T00:20:54.663Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-02T00:20:55.028Z] 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. [2024-08-02T00:20:55.028Z] The best model improves the baseline by 14.52%. [2024-08-02T00:20:55.028Z] Movies recommended for you: [2024-08-02T00:20:55.028Z] WARNING: This benchmark provides no result that can be validated. [2024-08-02T00:20:55.028Z] There is no way to check that no silent failure occurred. [2024-08-02T00:20:55.028Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (40661.238 ms) ====== [2024-08-02T00:20:55.028Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-08-02T00:20:55.346Z] GC before operation: completed in 121.226 ms, heap usage 611.898 MB -> 46.869 MB. [2024-08-02T00:21:02.457Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-02T00:21:08.219Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-02T00:21:13.957Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-02T00:21:21.060Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-02T00:21:24.727Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-02T00:21:27.608Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-02T00:21:31.277Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-02T00:21:34.939Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-02T00:21:35.267Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536. [2024-08-02T00:21:35.267Z] The best model improves the baseline by 14.52%. [2024-08-02T00:21:35.267Z] Movies recommended for you: [2024-08-02T00:21:35.267Z] WARNING: This benchmark provides no result that can be validated. [2024-08-02T00:21:35.267Z] There is no way to check that no silent failure occurred. [2024-08-02T00:21:35.267Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (40240.980 ms) ====== [2024-08-02T00:21:35.267Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-08-02T00:21:35.593Z] GC before operation: completed in 117.674 ms, heap usage 553.608 MB -> 46.646 MB. [2024-08-02T00:21:42.695Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-02T00:21:48.455Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-02T00:21:55.548Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-02T00:22:01.293Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-02T00:22:04.158Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-02T00:22:07.816Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-02T00:22:11.481Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-02T00:22:15.143Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-02T00:22:15.833Z] 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. [2024-08-02T00:22:15.833Z] The best model improves the baseline by 14.52%. [2024-08-02T00:22:15.833Z] Movies recommended for you: [2024-08-02T00:22:15.833Z] WARNING: This benchmark provides no result that can be validated. [2024-08-02T00:22:15.833Z] There is no way to check that no silent failure occurred. [2024-08-02T00:22:15.833Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (40334.716 ms) ====== [2024-08-02T00:22:15.833Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-08-02T00:22:15.833Z] GC before operation: completed in 131.862 ms, heap usage 542.824 MB -> 46.743 MB. [2024-08-02T00:22:22.941Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-02T00:22:28.692Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-02T00:22:35.796Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-02T00:22:41.583Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-02T00:22:45.262Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-02T00:22:48.115Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-02T00:22:52.770Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-02T00:22:55.630Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-02T00:22:55.630Z] 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. [2024-08-02T00:22:55.982Z] The best model improves the baseline by 14.52%. [2024-08-02T00:22:55.982Z] Movies recommended for you: [2024-08-02T00:22:55.982Z] WARNING: This benchmark provides no result that can be validated. [2024-08-02T00:22:55.982Z] There is no way to check that no silent failure occurred. [2024-08-02T00:22:55.982Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (39973.054 ms) ====== [2024-08-02T00:22:55.982Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-08-02T00:22:55.982Z] GC before operation: completed in 128.024 ms, heap usage 517.897 MB -> 46.568 MB. [2024-08-02T00:23:03.063Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-02T00:23:08.799Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-02T00:23:15.909Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-02T00:23:21.642Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-02T00:23:25.320Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-02T00:23:28.984Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-02T00:23:32.653Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-02T00:23:36.354Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-02T00:23:36.354Z] 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. [2024-08-02T00:23:36.354Z] The best model improves the baseline by 14.52%. [2024-08-02T00:23:36.354Z] Movies recommended for you: [2024-08-02T00:23:36.354Z] WARNING: This benchmark provides no result that can be validated. [2024-08-02T00:23:36.354Z] There is no way to check that no silent failure occurred. [2024-08-02T00:23:36.354Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (40281.099 ms) ====== [2024-08-02T00:23:36.354Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-08-02T00:23:36.354Z] GC before operation: completed in 121.948 ms, heap usage 542.472 MB -> 48.536 MB. [2024-08-02T00:23:43.433Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-02T00:23:49.215Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-02T00:23:54.975Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-02T00:24:02.051Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-02T00:24:04.937Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-02T00:24:08.588Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-02T00:24:13.197Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-02T00:24:16.063Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-02T00:24:16.392Z] 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. [2024-08-02T00:24:16.392Z] The best model improves the baseline by 14.52%. [2024-08-02T00:24:16.392Z] Movies recommended for you: [2024-08-02T00:24:16.392Z] WARNING: This benchmark provides no result that can be validated. [2024-08-02T00:24:16.392Z] There is no way to check that no silent failure occurred. [2024-08-02T00:24:16.392Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (40050.469 ms) ====== [2024-08-02T00:24:16.392Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-08-02T00:24:16.713Z] GC before operation: completed in 125.700 ms, heap usage 533.871 MB -> 46.847 MB. [2024-08-02T00:24:23.792Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-02T00:24:29.532Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-02T00:24:35.271Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-02T00:24:42.379Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-02T00:24:46.023Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-02T00:24:48.884Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-02T00:24:52.592Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-02T00:24:56.257Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-02T00:24:56.579Z] 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. [2024-08-02T00:24:56.579Z] The best model improves the baseline by 14.52%. [2024-08-02T00:24:56.942Z] Movies recommended for you: [2024-08-02T00:24:56.942Z] WARNING: This benchmark provides no result that can be validated. [2024-08-02T00:24:56.942Z] There is no way to check that no silent failure occurred. [2024-08-02T00:24:56.942Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (40097.130 ms) ====== [2024-08-02T00:24:57.262Z] ----------------------------------- [2024-08-02T00:24:57.262Z] renaissance-movie-lens_0_PASSED [2024-08-02T00:24:57.262Z] ----------------------------------- [2024-08-02T00:24:57.930Z] [2024-08-02T00:24:57.930Z] TEST TEARDOWN: [2024-08-02T00:24:57.930Z] Nothing to be done for teardown. [2024-08-02T00:24:57.930Z] renaissance-movie-lens_0 Finish Time: Fri Aug 2 00:24:57 2024 Epoch Time (ms): 1722558297665