renaissance-movie-lens_0
[2024-09-26T21:38:11.320Z] Running test renaissance-movie-lens_0 ...
[2024-09-26T21:38:11.320Z] ===============================================
[2024-09-26T21:38:11.320Z] renaissance-movie-lens_0 Start Time: Thu Sep 26 21:38:11 2024 Epoch Time (ms): 1727386691157
[2024-09-26T21:38:11.320Z] variation: NoOptions
[2024-09-26T21:38:11.320Z] JVM_OPTIONS:
[2024-09-26T21:38:11.320Z] { \
[2024-09-26T21:38:11.320Z] echo ""; echo "TEST SETUP:"; \
[2024-09-26T21:38:11.320Z] echo "Nothing to be done for setup."; \
[2024-09-26T21:38:11.320Z] mkdir -p "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17273857068101/renaissance-movie-lens_0"; \
[2024-09-26T21:38:11.320Z] cd "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17273857068101/renaissance-movie-lens_0"; \
[2024-09-26T21:38:11.320Z] echo ""; echo "TESTING:"; \
[2024-09-26T21:38:11.320Z] "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64le_linux/jdkbinary/j2sdk-image/bin/java" -jar "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17273857068101/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-09-26T21:38:11.320Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17273857068101/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-09-26T21:38:11.320Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-09-26T21:38:11.320Z] echo "Nothing to be done for teardown."; \
[2024-09-26T21:38:11.320Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17273857068101/TestTargetResult";
[2024-09-26T21:38:11.320Z]
[2024-09-26T21:38:11.320Z] TEST SETUP:
[2024-09-26T21:38:11.320Z] Nothing to be done for setup.
[2024-09-26T21:38:11.320Z]
[2024-09-26T21:38:11.320Z] TESTING:
[2024-09-26T21:38:15.379Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-09-26T21:38:17.298Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2024-09-26T21:38:22.555Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-09-26T21:38:22.555Z] Training: 60056, validation: 20285, test: 19854
[2024-09-26T21:38:22.555Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-09-26T21:38:23.485Z] GC before operation: completed in 231.367 ms, heap usage 69.825 MB -> 25.797 MB.
[2024-09-26T21:38:30.070Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T21:38:33.021Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T21:38:35.977Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T21:38:38.927Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T21:38:40.835Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T21:38:42.747Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T21:38:44.657Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T21:38:45.587Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T21:38:46.517Z] 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.
[2024-09-26T21:38:46.517Z] The best model improves the baseline by 14.52%.
[2024-09-26T21:38:46.517Z] Movies recommended for you:
[2024-09-26T21:38:46.517Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T21:38:46.517Z] There is no way to check that no silent failure occurred.
[2024-09-26T21:38:46.517Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (23400.924 ms) ======
[2024-09-26T21:38:46.517Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-09-26T21:38:46.517Z] GC before operation: completed in 300.560 ms, heap usage 161.727 MB -> 41.649 MB.
[2024-09-26T21:38:49.469Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T21:38:52.419Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T21:38:55.371Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T21:38:57.280Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T21:38:59.191Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T21:39:01.103Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T21:39:04.056Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T21:39:04.056Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T21:39:05.684Z] 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.
[2024-09-26T21:39:05.684Z] The best model improves the baseline by 14.52%.
[2024-09-26T21:39:05.684Z] Movies recommended for you:
[2024-09-26T21:39:05.684Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T21:39:05.684Z] There is no way to check that no silent failure occurred.
[2024-09-26T21:39:05.684Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (17793.699 ms) ======
[2024-09-26T21:39:05.684Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-09-26T21:39:05.684Z] GC before operation: completed in 205.125 ms, heap usage 344.132 MB -> 41.291 MB.
[2024-09-26T21:39:07.816Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T21:39:09.731Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T21:39:12.685Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T21:39:14.604Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T21:39:16.519Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T21:39:17.448Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T21:39:19.361Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T21:39:21.281Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T21:39:21.281Z] 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.
[2024-09-26T21:39:21.281Z] The best model improves the baseline by 14.52%.
[2024-09-26T21:39:21.281Z] Movies recommended for you:
[2024-09-26T21:39:21.281Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T21:39:21.281Z] There is no way to check that no silent failure occurred.
[2024-09-26T21:39:21.281Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (16579.043 ms) ======
[2024-09-26T21:39:21.281Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-09-26T21:39:21.281Z] GC before operation: completed in 217.593 ms, heap usage 120.010 MB -> 51.832 MB.
[2024-09-26T21:39:24.233Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T21:39:26.146Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T21:39:29.138Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T21:39:31.046Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T21:39:32.955Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T21:39:33.885Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T21:39:35.795Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T21:39:37.706Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T21:39:37.707Z] 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.
[2024-09-26T21:39:37.707Z] The best model improves the baseline by 14.52%.
[2024-09-26T21:39:37.707Z] Movies recommended for you:
[2024-09-26T21:39:37.707Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T21:39:37.707Z] There is no way to check that no silent failure occurred.
[2024-09-26T21:39:37.707Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (16222.346 ms) ======
[2024-09-26T21:39:37.707Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-09-26T21:39:37.707Z] GC before operation: completed in 197.816 ms, heap usage 105.645 MB -> 53.356 MB.
[2024-09-26T21:39:40.659Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T21:39:42.568Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T21:39:45.518Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T21:39:48.466Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T21:39:49.397Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T21:39:51.310Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T21:39:52.240Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T21:39:54.153Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T21:39:54.153Z] 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.
[2024-09-26T21:39:54.153Z] The best model improves the baseline by 14.52%.
[2024-09-26T21:39:54.153Z] Movies recommended for you:
[2024-09-26T21:39:54.153Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T21:39:54.153Z] There is no way to check that no silent failure occurred.
[2024-09-26T21:39:54.153Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (16213.973 ms) ======
[2024-09-26T21:39:54.153Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-09-26T21:39:54.153Z] GC before operation: completed in 231.120 ms, heap usage 276.824 MB -> 70.702 MB.
[2024-09-26T21:39:57.105Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T21:39:59.019Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T21:40:01.970Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T21:40:03.883Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T21:40:04.813Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T21:40:06.724Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T21:40:07.653Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T21:40:09.562Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T21:40:09.562Z] 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.
[2024-09-26T21:40:09.562Z] The best model improves the baseline by 14.52%.
[2024-09-26T21:40:09.562Z] Movies recommended for you:
[2024-09-26T21:40:09.562Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T21:40:09.562Z] There is no way to check that no silent failure occurred.
[2024-09-26T21:40:09.562Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (15368.397 ms) ======
[2024-09-26T21:40:09.562Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-09-26T21:40:10.493Z] GC before operation: completed in 183.705 ms, heap usage 213.290 MB -> 52.438 MB.
[2024-09-26T21:40:12.404Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T21:40:14.316Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T21:40:17.291Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T21:40:19.202Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T21:40:20.133Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T21:40:22.047Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T21:40:22.979Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T21:40:24.892Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T21:40:24.892Z] 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.
[2024-09-26T21:40:24.892Z] The best model improves the baseline by 14.52%.
[2024-09-26T21:40:24.892Z] Movies recommended for you:
[2024-09-26T21:40:24.892Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T21:40:24.892Z] There is no way to check that no silent failure occurred.
[2024-09-26T21:40:24.892Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (14919.546 ms) ======
[2024-09-26T21:40:24.892Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-09-26T21:40:24.892Z] GC before operation: completed in 231.342 ms, heap usage 214.685 MB -> 70.648 MB.
[2024-09-26T21:40:27.845Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T21:40:29.755Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T21:40:31.668Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T21:40:34.620Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T21:40:35.555Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T21:40:36.487Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T21:40:38.397Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T21:40:40.310Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T21:40:40.310Z] 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.
[2024-09-26T21:40:40.310Z] The best model improves the baseline by 14.52%.
[2024-09-26T21:40:40.310Z] Movies recommended for you:
[2024-09-26T21:40:40.310Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T21:40:40.310Z] There is no way to check that no silent failure occurred.
[2024-09-26T21:40:40.310Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (15159.613 ms) ======
[2024-09-26T21:40:40.310Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-09-26T21:40:40.310Z] GC before operation: completed in 221.218 ms, heap usage 240.567 MB -> 45.981 MB.
[2024-09-26T21:40:43.264Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T21:40:45.175Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T21:40:47.087Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T21:40:49.004Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T21:40:50.915Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T21:40:51.846Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T21:40:53.758Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T21:40:54.689Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T21:40:54.689Z] 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.
[2024-09-26T21:40:54.689Z] The best model improves the baseline by 14.52%.
[2024-09-26T21:40:55.618Z] Movies recommended for you:
[2024-09-26T21:40:55.618Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T21:40:55.618Z] There is no way to check that no silent failure occurred.
[2024-09-26T21:40:55.618Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (14662.010 ms) ======
[2024-09-26T21:40:55.618Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-09-26T21:40:55.618Z] GC before operation: completed in 187.801 ms, heap usage 274.476 MB -> 70.876 MB.
[2024-09-26T21:40:57.531Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T21:40:59.446Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T21:41:02.398Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T21:41:04.309Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T21:41:05.255Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T21:41:06.186Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T21:41:08.097Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T21:41:09.027Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T21:41:09.027Z] 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.
[2024-09-26T21:41:09.027Z] The best model improves the baseline by 14.52%.
[2024-09-26T21:41:09.956Z] Movies recommended for you:
[2024-09-26T21:41:09.956Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T21:41:09.956Z] There is no way to check that no silent failure occurred.
[2024-09-26T21:41:09.956Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (14091.357 ms) ======
[2024-09-26T21:41:09.956Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-09-26T21:41:09.956Z] GC before operation: completed in 221.082 ms, heap usage 293.890 MB -> 70.834 MB.
[2024-09-26T21:41:11.867Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T21:41:13.778Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T21:41:15.687Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T21:41:17.602Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T21:41:19.514Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T21:41:20.444Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T21:41:21.374Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T21:41:23.286Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T21:41:23.286Z] 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.
[2024-09-26T21:41:23.286Z] The best model improves the baseline by 14.52%.
[2024-09-26T21:41:23.286Z] Movies recommended for you:
[2024-09-26T21:41:23.286Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T21:41:23.286Z] There is no way to check that no silent failure occurred.
[2024-09-26T21:41:23.286Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (13692.398 ms) ======
[2024-09-26T21:41:23.286Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-09-26T21:41:23.286Z] GC before operation: completed in 202.985 ms, heap usage 244.304 MB -> 70.489 MB.
[2024-09-26T21:41:26.239Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T21:41:28.146Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T21:41:30.116Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T21:41:32.045Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T21:41:32.975Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T21:41:34.887Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T21:41:35.819Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T21:41:37.734Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T21:41:37.734Z] 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.
[2024-09-26T21:41:37.734Z] The best model improves the baseline by 14.52%.
[2024-09-26T21:41:37.734Z] Movies recommended for you:
[2024-09-26T21:41:37.734Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T21:41:37.734Z] There is no way to check that no silent failure occurred.
[2024-09-26T21:41:37.734Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (14191.356 ms) ======
[2024-09-26T21:41:37.734Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-09-26T21:41:37.734Z] GC before operation: completed in 159.322 ms, heap usage 188.982 MB -> 46.319 MB.
[2024-09-26T21:41:39.646Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T21:41:42.601Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T21:41:44.511Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T21:41:46.439Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T21:41:47.377Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T21:41:48.485Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T21:41:50.399Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T21:41:51.329Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T21:41:51.329Z] 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.
[2024-09-26T21:41:51.329Z] The best model improves the baseline by 14.52%.
[2024-09-26T21:41:51.329Z] Movies recommended for you:
[2024-09-26T21:41:51.329Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T21:41:51.329Z] There is no way to check that no silent failure occurred.
[2024-09-26T21:41:51.329Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (13756.728 ms) ======
[2024-09-26T21:41:51.329Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-09-26T21:41:52.263Z] GC before operation: completed in 183.615 ms, heap usage 248.121 MB -> 71.113 MB.
[2024-09-26T21:41:54.177Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T21:41:56.089Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T21:41:57.999Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T21:41:59.909Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T21:42:00.837Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T21:42:02.747Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T21:42:03.676Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T21:42:04.607Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T21:42:05.538Z] 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.
[2024-09-26T21:42:05.538Z] The best model improves the baseline by 14.52%.
[2024-09-26T21:42:05.538Z] Movies recommended for you:
[2024-09-26T21:42:05.538Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T21:42:05.538Z] There is no way to check that no silent failure occurred.
[2024-09-26T21:42:05.538Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (13473.129 ms) ======
[2024-09-26T21:42:05.538Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-09-26T21:42:05.538Z] GC before operation: completed in 223.920 ms, heap usage 239.237 MB -> 70.735 MB.
[2024-09-26T21:42:07.448Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T21:42:09.381Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T21:42:12.333Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T21:42:14.244Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T21:42:15.174Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T21:42:17.085Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T21:42:18.027Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T21:42:18.958Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T21:42:19.888Z] 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.
[2024-09-26T21:42:19.889Z] The best model improves the baseline by 14.52%.
[2024-09-26T21:42:19.889Z] Movies recommended for you:
[2024-09-26T21:42:19.889Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T21:42:19.889Z] There is no way to check that no silent failure occurred.
[2024-09-26T21:42:19.889Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14209.021 ms) ======
[2024-09-26T21:42:19.889Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-09-26T21:42:19.889Z] GC before operation: completed in 205.778 ms, heap usage 260.655 MB -> 70.933 MB.
[2024-09-26T21:42:21.800Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T21:42:24.752Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T21:42:26.666Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T21:42:28.577Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T21:42:29.509Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T21:42:31.424Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T21:42:32.353Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T21:42:34.281Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T21:42:34.281Z] 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.
[2024-09-26T21:42:34.281Z] The best model improves the baseline by 14.52%.
[2024-09-26T21:42:34.281Z] Movies recommended for you:
[2024-09-26T21:42:34.281Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T21:42:34.281Z] There is no way to check that no silent failure occurred.
[2024-09-26T21:42:34.281Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (14176.873 ms) ======
[2024-09-26T21:42:34.281Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-09-26T21:42:34.281Z] GC before operation: completed in 212.369 ms, heap usage 224.196 MB -> 70.839 MB.
[2024-09-26T21:42:36.198Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T21:42:38.110Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T21:42:41.299Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T21:42:42.426Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T21:42:44.340Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T21:42:45.287Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T21:42:47.205Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T21:42:48.137Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T21:42:48.137Z] 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.
[2024-09-26T21:42:48.137Z] The best model improves the baseline by 14.52%.
[2024-09-26T21:42:48.137Z] Movies recommended for you:
[2024-09-26T21:42:48.137Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T21:42:48.137Z] There is no way to check that no silent failure occurred.
[2024-09-26T21:42:48.137Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (13996.527 ms) ======
[2024-09-26T21:42:48.137Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-09-26T21:42:49.073Z] GC before operation: completed in 179.431 ms, heap usage 234.921 MB -> 70.763 MB.
[2024-09-26T21:42:50.983Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T21:42:52.896Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T21:42:54.808Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T21:42:56.723Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T21:42:58.650Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T21:42:59.580Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T21:43:00.511Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T21:43:02.426Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T21:43:02.426Z] 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.
[2024-09-26T21:43:02.426Z] The best model improves the baseline by 14.52%.
[2024-09-26T21:43:02.426Z] Movies recommended for you:
[2024-09-26T21:43:02.426Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T21:43:02.426Z] There is no way to check that no silent failure occurred.
[2024-09-26T21:43:02.426Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (13778.897 ms) ======
[2024-09-26T21:43:02.426Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-09-26T21:43:02.426Z] GC before operation: completed in 195.250 ms, heap usage 244.251 MB -> 71.012 MB.
[2024-09-26T21:43:04.338Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T21:43:07.290Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T21:43:09.201Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T21:43:11.113Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T21:43:12.043Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T21:43:12.975Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T21:43:14.886Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T21:43:15.818Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T21:43:15.818Z] 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.
[2024-09-26T21:43:15.818Z] The best model improves the baseline by 14.52%.
[2024-09-26T21:43:15.818Z] Movies recommended for you:
[2024-09-26T21:43:15.818Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T21:43:15.818Z] There is no way to check that no silent failure occurred.
[2024-09-26T21:43:15.818Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (13544.154 ms) ======
[2024-09-26T21:43:15.818Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-09-26T21:43:16.748Z] GC before operation: completed in 192.528 ms, heap usage 215.909 MB -> 70.864 MB.
[2024-09-26T21:43:18.659Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T21:43:20.575Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T21:43:22.487Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T21:43:24.400Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T21:43:26.309Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T21:43:27.239Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T21:43:28.170Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T21:43:30.125Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T21:43:30.125Z] 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.
[2024-09-26T21:43:30.125Z] The best model improves the baseline by 14.52%.
[2024-09-26T21:43:30.125Z] Movies recommended for you:
[2024-09-26T21:43:30.125Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T21:43:30.125Z] There is no way to check that no silent failure occurred.
[2024-09-26T21:43:30.125Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (13682.735 ms) ======
[2024-09-26T21:43:30.125Z] -----------------------------------
[2024-09-26T21:43:30.125Z] renaissance-movie-lens_0_PASSED
[2024-09-26T21:43:30.125Z] -----------------------------------
[2024-09-26T21:43:31.056Z]
[2024-09-26T21:43:31.056Z] TEST TEARDOWN:
[2024-09-26T21:43:31.056Z] Nothing to be done for teardown.
[2024-09-26T21:43:31.056Z] renaissance-movie-lens_0 Finish Time: Thu Sep 26 21:43:30 2024 Epoch Time (ms): 1727387010077