[2024-11-16T10:15:02.937Z] Running test renaissance-movie-lens_0 ... [2024-11-16T10:15:02.937Z] =============================================== [2024-11-16T10:15:02.937Z] renaissance-movie-lens_0 Start Time: Sat Nov 16 10:15:02 2024 Epoch Time (ms): 1731752102353 [2024-11-16T10:15:02.937Z] variation: NoOptions [2024-11-16T10:15:02.937Z] JVM_OPTIONS: [2024-11-16T10:15:02.937Z] { \ [2024-11-16T10:15:02.937Z] echo ""; echo "TEST SETUP:"; \ [2024-11-16T10:15:02.937Z] echo "Nothing to be done for setup."; \ [2024-11-16T10:15:02.937Z] mkdir -p "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17317486617463/renaissance-movie-lens_0"; \ [2024-11-16T10:15:02.937Z] cd "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17317486617463/renaissance-movie-lens_0"; \ [2024-11-16T10:15:02.937Z] echo ""; echo "TESTING:"; \ [2024-11-16T10:15:02.937Z] "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_alpine-linux/jdkbinary/j2sdk-image/bin/java" -jar "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17317486617463/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2024-11-16T10:15:02.937Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17317486617463/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-11-16T10:15:02.937Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-11-16T10:15:02.937Z] echo "Nothing to be done for teardown."; \ [2024-11-16T10:15:02.937Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17317486617463/TestTargetResult"; [2024-11-16T10:15:02.937Z] [2024-11-16T10:15:02.937Z] TEST SETUP: [2024-11-16T10:15:02.937Z] Nothing to be done for setup. [2024-11-16T10:15:02.937Z] [2024-11-16T10:15:02.937Z] TESTING: [2024-11-16T10:15:16.747Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-11-16T10:15:31.088Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2024-11-16T10:15:56.896Z] Got 100004 ratings from 671 users on 9066 movies. [2024-11-16T10:15:59.420Z] Training: 60056, validation: 20285, test: 19854 [2024-11-16T10:15:59.421Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-11-16T10:16:00.205Z] GC before operation: completed in 1291.832 ms, heap usage 118.834 MB -> 27.099 MB. [2024-11-16T10:16:48.848Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-16T10:17:08.265Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-16T10:17:33.915Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-16T10:17:59.923Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-16T10:18:11.695Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-16T10:18:21.547Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-16T10:18:33.281Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-16T10:18:41.649Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-16T10:18:44.238Z] 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. [2024-11-16T10:18:44.238Z] The best model improves the baseline by 14.52%. [2024-11-16T10:18:45.902Z] Movies recommended for you: [2024-11-16T10:18:45.902Z] WARNING: This benchmark provides no result that can be validated. [2024-11-16T10:18:45.902Z] There is no way to check that no silent failure occurred. [2024-11-16T10:18:45.902Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (165225.292 ms) ====== [2024-11-16T10:18:45.902Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-11-16T10:18:48.410Z] GC before operation: completed in 2617.165 ms, heap usage 259.602 MB -> 41.298 MB. [2024-11-16T10:19:07.506Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-16T10:19:29.716Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-16T10:19:45.726Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-16T10:20:05.048Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-16T10:20:14.913Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-16T10:20:26.581Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-16T10:20:40.387Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-16T10:20:52.119Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-16T10:20:53.795Z] 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. [2024-11-16T10:20:53.795Z] The best model improves the baseline by 14.52%. [2024-11-16T10:20:53.795Z] Movies recommended for you: [2024-11-16T10:20:53.795Z] WARNING: This benchmark provides no result that can be validated. [2024-11-16T10:20:53.795Z] There is no way to check that no silent failure occurred. [2024-11-16T10:20:53.795Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (125810.338 ms) ====== [2024-11-16T10:20:53.795Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-11-16T10:20:55.425Z] GC before operation: completed in 1422.451 ms, heap usage 338.840 MB -> 43.943 MB. [2024-11-16T10:21:18.152Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-16T10:21:31.939Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-16T10:21:48.038Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-16T10:22:04.156Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-16T10:22:12.505Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-16T10:22:22.474Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-16T10:22:32.862Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-16T10:22:42.843Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-16T10:22:45.430Z] 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. [2024-11-16T10:22:45.430Z] The best model improves the baseline by 14.52%. [2024-11-16T10:22:46.278Z] Movies recommended for you: [2024-11-16T10:22:46.278Z] WARNING: This benchmark provides no result that can be validated. [2024-11-16T10:22:46.278Z] There is no way to check that no silent failure occurred. [2024-11-16T10:22:46.278Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (110549.449 ms) ====== [2024-11-16T10:22:46.278Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-11-16T10:22:47.080Z] GC before operation: completed in 1242.737 ms, heap usage 510.858 MB -> 46.598 MB. [2024-11-16T10:23:06.212Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-16T10:23:28.369Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-16T10:23:47.826Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-16T10:24:06.871Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-16T10:24:15.263Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-16T10:24:25.176Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-16T10:24:36.954Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-16T10:24:45.158Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-16T10:24:45.915Z] 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. [2024-11-16T10:24:45.915Z] The best model improves the baseline by 14.52%. [2024-11-16T10:24:46.675Z] Movies recommended for you: [2024-11-16T10:24:46.675Z] WARNING: This benchmark provides no result that can be validated. [2024-11-16T10:24:46.675Z] There is no way to check that no silent failure occurred. [2024-11-16T10:24:46.675Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (119550.156 ms) ====== [2024-11-16T10:24:46.675Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-11-16T10:24:47.443Z] GC before operation: completed in 825.863 ms, heap usage 454.130 MB -> 46.738 MB. [2024-11-16T10:25:04.105Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-16T10:25:26.279Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-16T10:25:48.290Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-16T10:26:04.352Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-16T10:26:16.098Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-16T10:26:25.037Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-16T10:26:35.206Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-16T10:26:47.209Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-16T10:26:48.024Z] 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. [2024-11-16T10:26:48.024Z] The best model improves the baseline by 14.52%. [2024-11-16T10:26:48.024Z] Movies recommended for you: [2024-11-16T10:26:48.024Z] WARNING: This benchmark provides no result that can be validated. [2024-11-16T10:26:48.024Z] There is no way to check that no silent failure occurred. [2024-11-16T10:26:48.024Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (120811.454 ms) ====== [2024-11-16T10:26:48.024Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-11-16T10:26:48.792Z] GC before operation: completed in 816.260 ms, heap usage 470.515 MB -> 47.030 MB. [2024-11-16T10:27:07.917Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-16T10:27:24.238Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-16T10:27:43.475Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-16T10:27:59.926Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-16T10:28:08.328Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-16T10:28:16.722Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-16T10:28:28.627Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-16T10:28:38.718Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-16T10:28:39.498Z] 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. [2024-11-16T10:28:39.498Z] The best model improves the baseline by 14.52%. [2024-11-16T10:28:40.282Z] Movies recommended for you: [2024-11-16T10:28:40.282Z] WARNING: This benchmark provides no result that can be validated. [2024-11-16T10:28:40.282Z] There is no way to check that no silent failure occurred. [2024-11-16T10:28:40.282Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (110873.292 ms) ====== [2024-11-16T10:28:40.282Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-11-16T10:28:41.075Z] GC before operation: completed in 833.289 ms, heap usage 467.832 MB -> 46.942 MB. [2024-11-16T10:28:57.842Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-16T10:29:11.749Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-16T10:29:30.832Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-16T10:29:49.890Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-16T10:29:58.284Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-16T10:30:08.186Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-16T10:30:18.793Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-16T10:30:30.721Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-16T10:30:30.721Z] 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. [2024-11-16T10:30:30.721Z] The best model improves the baseline by 14.52%. [2024-11-16T10:30:30.721Z] Movies recommended for you: [2024-11-16T10:30:30.721Z] WARNING: This benchmark provides no result that can be validated. [2024-11-16T10:30:30.721Z] There is no way to check that no silent failure occurred. [2024-11-16T10:30:30.721Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (109887.763 ms) ====== [2024-11-16T10:30:30.721Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-11-16T10:30:31.529Z] GC before operation: completed in 832.880 ms, heap usage 486.595 MB -> 47.130 MB. [2024-11-16T10:30:50.469Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-16T10:31:09.567Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-16T10:31:28.529Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-16T10:31:42.476Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-16T10:31:50.895Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-16T10:31:59.372Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-16T10:32:11.243Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-16T10:32:21.283Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-16T10:32:22.083Z] 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. [2024-11-16T10:32:22.083Z] The best model improves the baseline by 14.52%. [2024-11-16T10:32:22.868Z] Movies recommended for you: [2024-11-16T10:32:22.868Z] WARNING: This benchmark provides no result that can be validated. [2024-11-16T10:32:22.868Z] There is no way to check that no silent failure occurred. [2024-11-16T10:32:22.868Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (111253.700 ms) ====== [2024-11-16T10:32:22.868Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-11-16T10:32:23.655Z] GC before operation: completed in 959.630 ms, heap usage 492.708 MB -> 52.605 MB. [2024-11-16T10:32:43.060Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-16T10:33:02.409Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-16T10:33:21.378Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-16T10:33:40.421Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-16T10:33:48.934Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-16T10:33:59.015Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-16T10:34:07.743Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-16T10:34:16.250Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-16T10:34:17.884Z] 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. [2024-11-16T10:34:17.884Z] The best model improves the baseline by 14.52%. [2024-11-16T10:34:17.884Z] Movies recommended for you: [2024-11-16T10:34:17.884Z] WARNING: This benchmark provides no result that can be validated. [2024-11-16T10:34:17.884Z] There is no way to check that no silent failure occurred. [2024-11-16T10:34:17.884Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (114425.946 ms) ====== [2024-11-16T10:34:17.884Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-11-16T10:34:19.486Z] GC before operation: completed in 870.061 ms, heap usage 542.063 MB -> 47.302 MB. [2024-11-16T10:34:41.673Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-16T10:34:55.650Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-16T10:35:14.720Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-16T10:35:31.682Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-16T10:35:40.173Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-16T10:35:50.249Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-16T10:36:02.249Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-16T10:36:12.502Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-16T10:36:13.313Z] 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. [2024-11-16T10:36:13.313Z] The best model improves the baseline by 14.52%. [2024-11-16T10:36:14.114Z] Movies recommended for you: [2024-11-16T10:36:14.114Z] WARNING: This benchmark provides no result that can be validated. [2024-11-16T10:36:14.114Z] There is no way to check that no silent failure occurred. [2024-11-16T10:36:14.114Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (114679.226 ms) ====== [2024-11-16T10:36:14.114Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-11-16T10:36:14.911Z] GC before operation: completed in 1137.828 ms, heap usage 497.258 MB -> 49.656 MB. [2024-11-16T10:36:34.737Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-16T10:36:51.404Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-16T10:37:14.037Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-16T10:37:30.626Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-16T10:37:42.686Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-16T10:37:51.830Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-16T10:38:02.166Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-16T10:38:14.318Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-16T10:38:14.318Z] 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. [2024-11-16T10:38:15.149Z] The best model improves the baseline by 14.52%. [2024-11-16T10:38:15.149Z] Movies recommended for you: [2024-11-16T10:38:15.149Z] WARNING: This benchmark provides no result that can be validated. [2024-11-16T10:38:15.149Z] There is no way to check that no silent failure occurred. [2024-11-16T10:38:15.149Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (120466.334 ms) ====== [2024-11-16T10:38:15.149Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-11-16T10:38:16.799Z] GC before operation: completed in 1302.763 ms, heap usage 132.444 MB -> 42.822 MB. [2024-11-16T10:38:36.215Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-16T10:38:52.745Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-16T10:39:09.915Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-16T10:39:29.149Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-16T10:39:41.173Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-16T10:39:52.100Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-16T10:40:04.238Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-16T10:40:14.504Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-16T10:40:15.339Z] 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. [2024-11-16T10:40:15.339Z] The best model improves the baseline by 14.52%. [2024-11-16T10:40:16.123Z] Movies recommended for you: [2024-11-16T10:40:16.123Z] WARNING: This benchmark provides no result that can be validated. [2024-11-16T10:40:16.123Z] There is no way to check that no silent failure occurred. [2024-11-16T10:40:16.123Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (119076.484 ms) ====== [2024-11-16T10:40:16.123Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-11-16T10:40:17.795Z] GC before operation: completed in 1534.572 ms, heap usage 517.072 MB -> 47.482 MB. [2024-11-16T10:40:34.373Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-16T10:40:48.377Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-16T10:41:07.647Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-16T10:41:19.662Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-16T10:41:26.919Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-16T10:41:34.187Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-16T10:41:44.445Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-16T10:41:52.961Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-16T10:41:53.752Z] 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. [2024-11-16T10:41:53.752Z] The best model improves the baseline by 14.52%. [2024-11-16T10:41:53.752Z] Movies recommended for you: [2024-11-16T10:41:53.752Z] WARNING: This benchmark provides no result that can be validated. [2024-11-16T10:41:53.752Z] There is no way to check that no silent failure occurred. [2024-11-16T10:41:53.752Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (96385.190 ms) ====== [2024-11-16T10:41:53.752Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-11-16T10:41:55.420Z] GC before operation: completed in 1383.019 ms, heap usage 460.274 MB -> 43.600 MB. [2024-11-16T10:42:09.488Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-16T10:42:23.627Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-16T10:42:38.113Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-16T10:42:48.301Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-16T10:42:57.009Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-16T10:43:04.113Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-16T10:43:12.679Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-16T10:43:21.258Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-16T10:43:22.086Z] 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. [2024-11-16T10:43:22.086Z] The best model improves the baseline by 14.52%. [2024-11-16T10:43:22.883Z] Movies recommended for you: [2024-11-16T10:43:22.883Z] WARNING: This benchmark provides no result that can be validated. [2024-11-16T10:43:22.883Z] There is no way to check that no silent failure occurred. [2024-11-16T10:43:22.883Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (87644.411 ms) ====== [2024-11-16T10:43:22.883Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-11-16T10:43:23.710Z] GC before operation: completed in 1015.101 ms, heap usage 527.827 MB -> 43.605 MB. [2024-11-16T10:43:38.319Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-16T10:43:52.365Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-16T10:44:06.526Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-16T10:44:20.628Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-16T10:44:27.661Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-16T10:44:36.271Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-16T10:44:44.786Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-16T10:44:53.673Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-16T10:44:53.673Z] 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. [2024-11-16T10:44:53.673Z] The best model improves the baseline by 14.52%. [2024-11-16T10:44:54.479Z] Movies recommended for you: [2024-11-16T10:44:54.479Z] WARNING: This benchmark provides no result that can be validated. [2024-11-16T10:44:54.479Z] There is no way to check that no silent failure occurred. [2024-11-16T10:44:54.479Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (90464.472 ms) ====== [2024-11-16T10:44:54.479Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-11-16T10:44:55.316Z] GC before operation: completed in 1039.623 ms, heap usage 471.035 MB -> 42.695 MB. [2024-11-16T10:45:09.471Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-16T10:45:25.940Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-16T10:45:40.255Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-16T10:45:56.810Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-16T10:46:05.938Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-16T10:46:14.541Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-16T10:46:24.775Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-16T10:46:33.478Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-16T10:46:34.290Z] 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. [2024-11-16T10:46:34.290Z] The best model improves the baseline by 14.52%. [2024-11-16T10:46:34.290Z] Movies recommended for you: [2024-11-16T10:46:34.290Z] WARNING: This benchmark provides no result that can be validated. [2024-11-16T10:46:34.290Z] There is no way to check that no silent failure occurred. [2024-11-16T10:46:34.290Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (99112.777 ms) ====== [2024-11-16T10:46:34.290Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-11-16T10:46:35.088Z] GC before operation: completed in 939.752 ms, heap usage 449.466 MB -> 45.229 MB. [2024-11-16T10:46:51.617Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-16T10:47:05.676Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-16T10:47:25.646Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-16T10:47:42.203Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-16T10:47:49.305Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-16T10:47:59.584Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-16T10:48:08.138Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-16T10:48:18.373Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-16T10:48:18.373Z] 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. [2024-11-16T10:48:18.373Z] The best model improves the baseline by 14.52%. [2024-11-16T10:48:19.160Z] Movies recommended for you: [2024-11-16T10:48:19.160Z] WARNING: This benchmark provides no result that can be validated. [2024-11-16T10:48:19.160Z] There is no way to check that no silent failure occurred. [2024-11-16T10:48:19.160Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (103626.151 ms) ====== [2024-11-16T10:48:19.160Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-11-16T10:48:19.965Z] GC before operation: completed in 919.038 ms, heap usage 489.583 MB -> 43.427 MB. [2024-11-16T10:48:36.536Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-16T10:48:52.975Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-16T10:49:07.185Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-16T10:49:23.788Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-16T10:49:34.021Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-16T10:49:42.672Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-16T10:49:53.501Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-16T10:50:03.725Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-16T10:50:04.526Z] 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. [2024-11-16T10:50:04.526Z] The best model improves the baseline by 14.52%. [2024-11-16T10:50:05.331Z] Movies recommended for you: [2024-11-16T10:50:05.331Z] WARNING: This benchmark provides no result that can be validated. [2024-11-16T10:50:05.331Z] There is no way to check that no silent failure occurred. [2024-11-16T10:50:05.331Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (105184.960 ms) ====== [2024-11-16T10:50:05.331Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-11-16T10:50:06.142Z] GC before operation: completed in 1103.374 ms, heap usage 437.581 MB -> 43.288 MB. [2024-11-16T10:50:22.679Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-16T10:50:39.351Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-16T10:50:58.530Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-16T10:51:15.589Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-16T10:51:25.703Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-16T10:51:35.910Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-16T10:51:46.044Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-16T10:51:54.630Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-16T10:51:56.259Z] 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. [2024-11-16T10:51:56.259Z] The best model improves the baseline by 14.52%. [2024-11-16T10:51:56.259Z] Movies recommended for you: [2024-11-16T10:51:56.259Z] WARNING: This benchmark provides no result that can be validated. [2024-11-16T10:51:56.259Z] There is no way to check that no silent failure occurred. [2024-11-16T10:51:56.259Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (110412.283 ms) ====== [2024-11-16T10:51:56.259Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-11-16T10:51:57.901Z] GC before operation: completed in 1184.396 ms, heap usage 431.395 MB -> 43.435 MB. [2024-11-16T10:52:14.444Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-16T10:52:31.457Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-16T10:52:50.696Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-16T10:53:04.979Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-16T10:53:15.318Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-16T10:53:25.442Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-16T10:53:34.363Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-16T10:53:44.653Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-16T10:53:45.480Z] 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. [2024-11-16T10:53:45.480Z] The best model improves the baseline by 14.52%. [2024-11-16T10:53:46.269Z] Movies recommended for you: [2024-11-16T10:53:46.269Z] WARNING: This benchmark provides no result that can be validated. [2024-11-16T10:53:46.269Z] There is no way to check that no silent failure occurred. [2024-11-16T10:53:46.269Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (108526.397 ms) ====== [2024-11-16T10:53:49.855Z] ----------------------------------- [2024-11-16T10:53:49.855Z] renaissance-movie-lens_0_PASSED [2024-11-16T10:53:49.855Z] ----------------------------------- [2024-11-16T10:53:49.855Z] [2024-11-16T10:53:49.855Z] TEST TEARDOWN: [2024-11-16T10:53:49.855Z] Nothing to be done for teardown. [2024-11-16T10:53:49.855Z] renaissance-movie-lens_0 Finish Time: Sat Nov 16 10:53:49 2024 Epoch Time (ms): 1731754429063