[2024-10-29T22:03:36.443Z] Running test renaissance-movie-lens_0 ... [2024-10-29T22:03:36.443Z] =============================================== [2024-10-29T22:03:36.443Z] renaissance-movie-lens_0 Start Time: Tue Oct 29 22:03:35 2024 Epoch Time (ms): 1730239415614 [2024-10-29T22:03:36.443Z] variation: NoOptions [2024-10-29T22:03:36.443Z] JVM_OPTIONS: [2024-10-29T22:03:36.443Z] { \ [2024-10-29T22:03:36.443Z] echo ""; echo "TEST SETUP:"; \ [2024-10-29T22:03:36.443Z] echo "Nothing to be done for setup."; \ [2024-10-29T22:03:36.443Z] mkdir -p "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17302381859372/renaissance-movie-lens_0"; \ [2024-10-29T22:03:36.443Z] cd "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17302381859372/renaissance-movie-lens_0"; \ [2024-10-29T22:03:36.443Z] echo ""; echo "TESTING:"; \ [2024-10-29T22:03:36.443Z] "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/jdkbinary/j2sdk-image/bin/java" -jar "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17302381859372/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2024-10-29T22:03:36.443Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17302381859372/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-10-29T22:03:36.443Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-10-29T22:03:36.443Z] echo "Nothing to be done for teardown."; \ [2024-10-29T22:03:36.443Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17302381859372/TestTargetResult"; [2024-10-29T22:03:36.443Z] [2024-10-29T22:03:36.443Z] TEST SETUP: [2024-10-29T22:03:36.443Z] Nothing to be done for setup. [2024-10-29T22:03:36.443Z] [2024-10-29T22:03:36.443Z] TESTING: [2024-10-29T22:03:39.737Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-10-29T22:03:43.014Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2024-10-29T22:03:48.246Z] Got 100004 ratings from 671 users on 9066 movies. [2024-10-29T22:03:48.246Z] Training: 60056, validation: 20285, test: 19854 [2024-10-29T22:03:48.246Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-10-29T22:03:48.246Z] GC before operation: completed in 229.890 ms, heap usage 125.239 MB -> 25.958 MB. [2024-10-29T22:03:56.110Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-10-29T22:04:00.280Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-10-29T22:04:05.428Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-10-29T22:04:08.735Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-10-29T22:04:11.239Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-10-29T22:04:13.167Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-10-29T22:04:15.010Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-10-29T22:04:17.550Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-10-29T22:04:17.946Z] 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. [2024-10-29T22:04:17.946Z] The best model improves the baseline by 14.52%. [2024-10-29T22:04:18.318Z] Movies recommended for you: [2024-10-29T22:04:18.318Z] WARNING: This benchmark provides no result that can be validated. [2024-10-29T22:04:18.318Z] There is no way to check that no silent failure occurred. [2024-10-29T22:04:18.318Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (29899.895 ms) ====== [2024-10-29T22:04:18.318Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-10-29T22:04:18.698Z] GC before operation: completed in 369.607 ms, heap usage 95.704 MB -> 41.592 MB. [2024-10-29T22:04:22.271Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-10-29T22:04:26.484Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-10-29T22:04:29.827Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-10-29T22:04:32.316Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-10-29T22:04:34.196Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-10-29T22:04:36.040Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-10-29T22:04:37.881Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-10-29T22:04:40.470Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-10-29T22:04:40.470Z] 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. [2024-10-29T22:04:40.470Z] The best model improves the baseline by 14.52%. [2024-10-29T22:04:40.470Z] Movies recommended for you: [2024-10-29T22:04:40.470Z] WARNING: This benchmark provides no result that can be validated. [2024-10-29T22:04:40.470Z] There is no way to check that no silent failure occurred. [2024-10-29T22:04:40.470Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (21937.944 ms) ====== [2024-10-29T22:04:40.470Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-10-29T22:04:40.841Z] GC before operation: completed in 242.245 ms, heap usage 184.316 MB -> 41.007 MB. [2024-10-29T22:04:44.250Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-10-29T22:04:47.522Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-10-29T22:04:50.032Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-10-29T22:04:53.301Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-10-29T22:04:54.598Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-10-29T22:04:56.461Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-10-29T22:04:58.287Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-10-29T22:05:00.211Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-10-29T22:05:00.211Z] 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. [2024-10-29T22:05:00.211Z] The best model improves the baseline by 14.52%. [2024-10-29T22:05:00.594Z] Movies recommended for you: [2024-10-29T22:05:00.594Z] WARNING: This benchmark provides no result that can be validated. [2024-10-29T22:05:00.594Z] There is no way to check that no silent failure occurred. [2024-10-29T22:05:00.594Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (19617.025 ms) ====== [2024-10-29T22:05:00.594Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-10-29T22:05:00.594Z] GC before operation: completed in 203.467 ms, heap usage 473.958 MB -> 45.249 MB. [2024-10-29T22:05:03.833Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-10-29T22:05:06.390Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-10-29T22:05:09.660Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-10-29T22:05:12.933Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-10-29T22:05:15.437Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-10-29T22:05:17.038Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-10-29T22:05:18.416Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-10-29T22:05:20.309Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-10-29T22:05:20.309Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536. [2024-10-29T22:05:20.680Z] The best model improves the baseline by 14.52%. [2024-10-29T22:05:20.680Z] Movies recommended for you: [2024-10-29T22:05:20.680Z] WARNING: This benchmark provides no result that can be validated. [2024-10-29T22:05:20.680Z] There is no way to check that no silent failure occurred. [2024-10-29T22:05:20.680Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (20015.250 ms) ====== [2024-10-29T22:05:20.680Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-10-29T22:05:20.680Z] GC before operation: completed in 192.527 ms, heap usage 401.345 MB -> 45.551 MB. [2024-10-29T22:05:23.947Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-10-29T22:05:27.233Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-10-29T22:05:29.759Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-10-29T22:05:33.042Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-10-29T22:05:34.923Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-10-29T22:05:36.787Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-10-29T22:05:38.636Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-10-29T22:05:40.520Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-10-29T22:05:40.910Z] 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. [2024-10-29T22:05:40.910Z] The best model improves the baseline by 14.52%. [2024-10-29T22:05:41.281Z] Movies recommended for you: [2024-10-29T22:05:41.281Z] WARNING: This benchmark provides no result that can be validated. [2024-10-29T22:05:41.281Z] There is no way to check that no silent failure occurred. [2024-10-29T22:05:41.281Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (20260.872 ms) ====== [2024-10-29T22:05:41.281Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-10-29T22:05:41.281Z] GC before operation: completed in 183.491 ms, heap usage 411.191 MB -> 45.774 MB. [2024-10-29T22:05:44.593Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-10-29T22:05:46.680Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-10-29T22:05:49.929Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-10-29T22:05:52.460Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-10-29T22:05:54.323Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-10-29T22:05:55.630Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-10-29T22:05:57.471Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-10-29T22:05:59.340Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-10-29T22:05:59.340Z] 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. [2024-10-29T22:05:59.340Z] The best model improves the baseline by 14.52%. [2024-10-29T22:05:59.340Z] Movies recommended for you: [2024-10-29T22:05:59.340Z] WARNING: This benchmark provides no result that can be validated. [2024-10-29T22:05:59.340Z] There is no way to check that no silent failure occurred. [2024-10-29T22:05:59.340Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (18183.257 ms) ====== [2024-10-29T22:05:59.340Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-10-29T22:05:59.712Z] GC before operation: completed in 190.956 ms, heap usage 515.148 MB -> 48.143 MB. [2024-10-29T22:06:02.188Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-10-29T22:06:05.447Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-10-29T22:06:07.941Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-10-29T22:06:10.427Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-10-29T22:06:12.269Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-10-29T22:06:14.294Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-10-29T22:06:15.633Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-10-29T22:06:17.514Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-10-29T22:06:17.514Z] 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. [2024-10-29T22:06:17.514Z] The best model improves the baseline by 14.52%. [2024-10-29T22:06:17.514Z] Movies recommended for you: [2024-10-29T22:06:17.514Z] WARNING: This benchmark provides no result that can be validated. [2024-10-29T22:06:17.514Z] There is no way to check that no silent failure occurred. [2024-10-29T22:06:17.514Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (17921.508 ms) ====== [2024-10-29T22:06:17.514Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-10-29T22:06:17.899Z] GC before operation: completed in 179.004 ms, heap usage 531.219 MB -> 46.043 MB. [2024-10-29T22:06:20.408Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-10-29T22:06:22.930Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-10-29T22:06:26.202Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-10-29T22:06:28.700Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-10-29T22:06:30.571Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-10-29T22:06:31.857Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-10-29T22:06:33.693Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-10-29T22:06:35.551Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-10-29T22:06:35.551Z] 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. [2024-10-29T22:06:35.551Z] The best model improves the baseline by 14.52%. [2024-10-29T22:06:35.551Z] Movies recommended for you: [2024-10-29T22:06:35.551Z] WARNING: This benchmark provides no result that can be validated. [2024-10-29T22:06:35.551Z] There is no way to check that no silent failure occurred. [2024-10-29T22:06:35.551Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (17872.130 ms) ====== [2024-10-29T22:06:35.551Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-10-29T22:06:35.930Z] GC before operation: completed in 149.485 ms, heap usage 393.634 MB -> 46.134 MB. [2024-10-29T22:06:38.410Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-10-29T22:06:41.653Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-10-29T22:06:44.279Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-10-29T22:06:46.848Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-10-29T22:06:48.158Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-10-29T22:06:50.033Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-10-29T22:06:51.893Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-10-29T22:06:53.230Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-10-29T22:06:53.606Z] 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. [2024-10-29T22:06:53.606Z] The best model improves the baseline by 14.52%. [2024-10-29T22:06:53.606Z] Movies recommended for you: [2024-10-29T22:06:53.606Z] WARNING: This benchmark provides no result that can be validated. [2024-10-29T22:06:53.606Z] There is no way to check that no silent failure occurred. [2024-10-29T22:06:53.606Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (17776.432 ms) ====== [2024-10-29T22:06:53.606Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-10-29T22:06:53.606Z] GC before operation: completed in 173.750 ms, heap usage 444.299 MB -> 45.970 MB. [2024-10-29T22:06:56.907Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-10-29T22:06:59.478Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-10-29T22:07:01.979Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-10-29T22:07:04.451Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-10-29T22:07:06.293Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-10-29T22:07:08.142Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-10-29T22:07:09.450Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-10-29T22:07:11.440Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-10-29T22:07:11.906Z] 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. [2024-10-29T22:07:11.906Z] The best model improves the baseline by 14.52%. [2024-10-29T22:07:11.906Z] Movies recommended for you: [2024-10-29T22:07:11.906Z] WARNING: This benchmark provides no result that can be validated. [2024-10-29T22:07:11.906Z] There is no way to check that no silent failure occurred. [2024-10-29T22:07:11.906Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (17972.216 ms) ====== [2024-10-29T22:07:11.906Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-10-29T22:07:11.906Z] GC before operation: completed in 206.632 ms, heap usage 439.139 MB -> 47.961 MB. [2024-10-29T22:07:14.415Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-10-29T22:07:17.731Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-10-29T22:07:20.288Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-10-29T22:07:22.787Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-10-29T22:07:24.119Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-10-29T22:07:25.960Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-10-29T22:07:27.833Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-10-29T22:07:29.160Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-10-29T22:07:29.550Z] 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. [2024-10-29T22:07:29.550Z] The best model improves the baseline by 14.52%. [2024-10-29T22:07:29.550Z] Movies recommended for you: [2024-10-29T22:07:29.550Z] WARNING: This benchmark provides no result that can be validated. [2024-10-29T22:07:29.550Z] There is no way to check that no silent failure occurred. [2024-10-29T22:07:29.550Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (17697.109 ms) ====== [2024-10-29T22:07:29.550Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-10-29T22:07:29.961Z] GC before operation: completed in 156.417 ms, heap usage 522.659 MB -> 45.946 MB. [2024-10-29T22:07:32.481Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-10-29T22:07:34.975Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-10-29T22:07:38.249Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-10-29T22:07:40.767Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-10-29T22:07:42.250Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-10-29T22:07:44.092Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-10-29T22:07:45.417Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-10-29T22:07:47.263Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-10-29T22:07:47.263Z] 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. [2024-10-29T22:07:47.263Z] The best model improves the baseline by 14.52%. [2024-10-29T22:07:47.641Z] Movies recommended for you: [2024-10-29T22:07:47.641Z] WARNING: This benchmark provides no result that can be validated. [2024-10-29T22:07:47.641Z] There is no way to check that no silent failure occurred. [2024-10-29T22:07:47.641Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (17718.276 ms) ====== [2024-10-29T22:07:47.641Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-10-29T22:07:47.641Z] GC before operation: completed in 155.574 ms, heap usage 403.909 MB -> 45.958 MB. [2024-10-29T22:07:50.139Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-10-29T22:07:53.472Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-10-29T22:07:56.038Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-10-29T22:07:59.290Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-10-29T22:08:00.683Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-10-29T22:08:02.578Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-10-29T22:08:03.873Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-10-29T22:08:05.757Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-10-29T22:08:05.757Z] 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. [2024-10-29T22:08:05.757Z] The best model improves the baseline by 14.52%. [2024-10-29T22:08:06.131Z] Movies recommended for you: [2024-10-29T22:08:06.131Z] WARNING: This benchmark provides no result that can be validated. [2024-10-29T22:08:06.131Z] There is no way to check that no silent failure occurred. [2024-10-29T22:08:06.131Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (18370.942 ms) ====== [2024-10-29T22:08:06.131Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-10-29T22:08:06.131Z] GC before operation: completed in 149.063 ms, heap usage 433.953 MB -> 46.172 MB. [2024-10-29T22:08:08.661Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-10-29T22:08:12.051Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-10-29T22:08:14.627Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-10-29T22:08:17.178Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-10-29T22:08:19.108Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-10-29T22:08:20.526Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-10-29T22:08:22.439Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-10-29T22:08:23.799Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-10-29T22:08:24.182Z] 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. [2024-10-29T22:08:24.182Z] The best model improves the baseline by 14.52%. [2024-10-29T22:08:24.182Z] Movies recommended for you: [2024-10-29T22:08:24.182Z] WARNING: This benchmark provides no result that can be validated. [2024-10-29T22:08:24.182Z] There is no way to check that no silent failure occurred. [2024-10-29T22:08:24.182Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (17960.421 ms) ====== [2024-10-29T22:08:24.182Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-10-29T22:08:24.182Z] GC before operation: completed in 147.416 ms, heap usage 404.887 MB -> 45.902 MB. [2024-10-29T22:08:27.510Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-10-29T22:08:30.054Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-10-29T22:08:32.599Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-10-29T22:08:35.168Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-10-29T22:08:37.102Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-10-29T22:08:38.428Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-10-29T22:08:39.941Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-10-29T22:08:41.825Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-10-29T22:08:41.825Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536. [2024-10-29T22:08:41.825Z] The best model improves the baseline by 14.52%. [2024-10-29T22:08:42.207Z] Movies recommended for you: [2024-10-29T22:08:42.207Z] WARNING: This benchmark provides no result that can be validated. [2024-10-29T22:08:42.207Z] There is no way to check that no silent failure occurred. [2024-10-29T22:08:42.207Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (17835.245 ms) ====== [2024-10-29T22:08:42.207Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-10-29T22:08:42.207Z] GC before operation: completed in 156.856 ms, heap usage 409.387 MB -> 46.109 MB. [2024-10-29T22:08:44.781Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-10-29T22:08:48.117Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-10-29T22:08:50.666Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-10-29T22:08:53.215Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-10-29T22:08:54.542Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-10-29T22:08:56.443Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-10-29T22:08:58.370Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-10-29T22:08:59.720Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-10-29T22:09:00.104Z] 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. [2024-10-29T22:09:00.104Z] The best model improves the baseline by 14.52%. [2024-10-29T22:09:00.104Z] Movies recommended for you: [2024-10-29T22:09:00.104Z] WARNING: This benchmark provides no result that can be validated. [2024-10-29T22:09:00.104Z] There is no way to check that no silent failure occurred. [2024-10-29T22:09:00.104Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (17809.809 ms) ====== [2024-10-29T22:09:00.104Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-10-29T22:09:00.104Z] GC before operation: completed in 162.612 ms, heap usage 426.321 MB -> 46.196 MB. [2024-10-29T22:09:02.699Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-10-29T22:09:06.028Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-10-29T22:09:08.185Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-10-29T22:09:10.755Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-10-29T22:09:12.685Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-10-29T22:09:14.014Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-10-29T22:09:15.901Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-10-29T22:09:17.790Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-10-29T22:09:17.790Z] 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. [2024-10-29T22:09:17.790Z] The best model improves the baseline by 14.52%. [2024-10-29T22:09:17.790Z] Movies recommended for you: [2024-10-29T22:09:17.790Z] WARNING: This benchmark provides no result that can be validated. [2024-10-29T22:09:17.790Z] There is no way to check that no silent failure occurred. [2024-10-29T22:09:17.790Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (17590.801 ms) ====== [2024-10-29T22:09:17.790Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-10-29T22:09:18.176Z] GC before operation: completed in 155.072 ms, heap usage 405.467 MB -> 46.036 MB. [2024-10-29T22:09:20.729Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-10-29T22:09:23.307Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-10-29T22:09:25.884Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-10-29T22:09:29.206Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-10-29T22:09:30.560Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-10-29T22:09:31.877Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-10-29T22:09:33.790Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-10-29T22:09:35.150Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-10-29T22:09:35.545Z] 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. [2024-10-29T22:09:35.545Z] The best model improves the baseline by 14.52%. [2024-10-29T22:09:35.545Z] Movies recommended for you: [2024-10-29T22:09:35.545Z] WARNING: This benchmark provides no result that can be validated. [2024-10-29T22:09:35.545Z] There is no way to check that no silent failure occurred. [2024-10-29T22:09:35.545Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (17630.913 ms) ====== [2024-10-29T22:09:35.545Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-10-29T22:09:35.931Z] GC before operation: completed in 170.287 ms, heap usage 436.180 MB -> 46.039 MB. [2024-10-29T22:09:38.602Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-10-29T22:09:41.147Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-10-29T22:09:43.733Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-10-29T22:09:47.069Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-10-29T22:09:48.407Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-10-29T22:09:49.744Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-10-29T22:09:51.687Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-10-29T22:09:53.044Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-10-29T22:09:53.464Z] 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. [2024-10-29T22:09:53.464Z] The best model improves the baseline by 14.52%. [2024-10-29T22:09:53.464Z] Movies recommended for you: [2024-10-29T22:09:53.464Z] WARNING: This benchmark provides no result that can be validated. [2024-10-29T22:09:53.464Z] There is no way to check that no silent failure occurred. [2024-10-29T22:09:53.464Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (17799.349 ms) ====== [2024-10-29T22:09:53.464Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-10-29T22:09:53.849Z] GC before operation: completed in 169.824 ms, heap usage 396.051 MB -> 46.305 MB. [2024-10-29T22:09:56.404Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-10-29T22:09:58.950Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-10-29T22:10:01.551Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-10-29T22:10:04.864Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-10-29T22:10:06.412Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-10-29T22:10:07.808Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-10-29T22:10:09.156Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-10-29T22:10:11.152Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-10-29T22:10:11.152Z] 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. [2024-10-29T22:10:11.152Z] The best model improves the baseline by 14.52%. [2024-10-29T22:10:11.531Z] Movies recommended for you: [2024-10-29T22:10:11.531Z] WARNING: This benchmark provides no result that can be validated. [2024-10-29T22:10:11.531Z] There is no way to check that no silent failure occurred. [2024-10-29T22:10:11.531Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (17668.973 ms) ====== [2024-10-29T22:10:12.359Z] ----------------------------------- [2024-10-29T22:10:12.359Z] renaissance-movie-lens_0_PASSED [2024-10-29T22:10:12.359Z] ----------------------------------- [2024-10-29T22:10:12.359Z] [2024-10-29T22:10:12.359Z] TEST TEARDOWN: [2024-10-29T22:10:12.359Z] Nothing to be done for teardown. [2024-10-29T22:10:12.359Z] renaissance-movie-lens_0 Finish Time: Tue Oct 29 22:10:11 2024 Epoch Time (ms): 1730239811987