renaissance-movie-lens_0
[2025-02-13T21:47:07.107Z] Running test renaissance-movie-lens_0 ...
[2025-02-13T21:47:07.107Z] ===============================================
[2025-02-13T21:47:07.107Z] renaissance-movie-lens_0 Start Time: Thu Feb 13 21:47:06 2025 Epoch Time (ms): 1739483226005
[2025-02-13T21:47:07.107Z] variation: NoOptions
[2025-02-13T21:47:07.107Z] JVM_OPTIONS:
[2025-02-13T21:47:07.107Z] { \
[2025-02-13T21:47:07.107Z] echo ""; echo "TEST SETUP:"; \
[2025-02-13T21:47:07.107Z] echo "Nothing to be done for setup."; \
[2025-02-13T21:47:07.107Z] mkdir -p "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17394822075452/renaissance-movie-lens_0"; \
[2025-02-13T21:47:07.107Z] cd "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17394822075452/renaissance-movie-lens_0"; \
[2025-02-13T21:47:07.107Z] echo ""; echo "TESTING:"; \
[2025-02-13T21:47:07.107Z] "/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_17394822075452/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-02-13T21:47:07.107Z] 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_17394822075452/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-02-13T21:47:07.107Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-02-13T21:47:07.107Z] echo "Nothing to be done for teardown."; \
[2025-02-13T21:47:07.107Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17394822075452/TestTargetResult";
[2025-02-13T21:47:07.107Z]
[2025-02-13T21:47:07.107Z] TEST SETUP:
[2025-02-13T21:47:07.107Z] Nothing to be done for setup.
[2025-02-13T21:47:07.107Z]
[2025-02-13T21:47:07.107Z] TESTING:
[2025-02-13T21:47:10.129Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2025-02-13T21:47:13.155Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-02-13T21:47:17.304Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-02-13T21:47:18.256Z] Training: 60056, validation: 20285, test: 19854
[2025-02-13T21:47:18.256Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-02-13T21:47:18.256Z] GC before operation: completed in 219.773 ms, heap usage 213.805 MB -> 26.417 MB.
[2025-02-13T21:47:24.956Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-13T21:47:27.972Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-13T21:47:30.992Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-13T21:47:34.009Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-13T21:47:35.968Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-13T21:47:37.920Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-13T21:47:40.918Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-13T21:47:41.870Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-13T21:47:41.870Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-02-13T21:47:41.870Z] The best model improves the baseline by 14.52%.
[2025-02-13T21:47:41.870Z] Movies recommended for you:
[2025-02-13T21:47:41.870Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-13T21:47:41.870Z] There is no way to check that no silent failure occurred.
[2025-02-13T21:47:41.870Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (23848.063 ms) ======
[2025-02-13T21:47:41.870Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-02-13T21:47:42.821Z] GC before operation: completed in 339.743 ms, heap usage 183.632 MB -> 42.201 MB.
[2025-02-13T21:47:44.822Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-13T21:47:47.852Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-13T21:47:50.877Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-13T21:47:52.838Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-13T21:47:54.795Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-13T21:47:56.749Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-13T21:47:57.749Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-13T21:47:59.703Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-13T21:47:59.703Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-02-13T21:47:59.703Z] The best model improves the baseline by 14.52%.
[2025-02-13T21:48:00.655Z] Movies recommended for you:
[2025-02-13T21:48:00.655Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-13T21:48:00.655Z] There is no way to check that no silent failure occurred.
[2025-02-13T21:48:00.655Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (17766.572 ms) ======
[2025-02-13T21:48:00.655Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-02-13T21:48:00.655Z] GC before operation: completed in 242.212 ms, heap usage 293.926 MB -> 41.204 MB.
[2025-02-13T21:48:02.609Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-13T21:48:05.628Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-13T21:48:08.648Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-13T21:48:10.604Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-13T21:48:12.558Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-13T21:48:13.520Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-13T21:48:15.477Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-13T21:48:16.466Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-13T21:48:17.418Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-02-13T21:48:17.418Z] The best model improves the baseline by 14.52%.
[2025-02-13T21:48:17.418Z] Movies recommended for you:
[2025-02-13T21:48:17.418Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-13T21:48:17.418Z] There is no way to check that no silent failure occurred.
[2025-02-13T21:48:17.418Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (16758.731 ms) ======
[2025-02-13T21:48:17.418Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-02-13T21:48:17.418Z] GC before operation: completed in 208.327 ms, heap usage 95.629 MB -> 42.259 MB.
[2025-02-13T21:48:19.377Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-13T21:48:22.393Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-13T21:48:24.347Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-13T21:48:27.362Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-13T21:48:28.316Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-13T21:48:30.271Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-13T21:48:31.224Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-13T21:48:33.177Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-13T21:48:33.177Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-02-13T21:48:33.177Z] The best model improves the baseline by 14.52%.
[2025-02-13T21:48:33.177Z] Movies recommended for you:
[2025-02-13T21:48:33.177Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-13T21:48:33.177Z] There is no way to check that no silent failure occurred.
[2025-02-13T21:48:33.177Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (16213.455 ms) ======
[2025-02-13T21:48:33.177Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-02-13T21:48:34.128Z] GC before operation: completed in 206.069 ms, heap usage 146.584 MB -> 41.540 MB.
[2025-02-13T21:48:36.084Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-13T21:48:38.038Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-13T21:48:41.789Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-13T21:48:43.740Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-13T21:48:44.692Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-13T21:48:46.653Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-13T21:48:47.605Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-13T21:48:49.560Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-13T21:48:49.560Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-02-13T21:48:49.560Z] The best model improves the baseline by 14.52%.
[2025-02-13T21:48:49.560Z] Movies recommended for you:
[2025-02-13T21:48:49.560Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-13T21:48:49.560Z] There is no way to check that no silent failure occurred.
[2025-02-13T21:48:49.560Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (15982.264 ms) ======
[2025-02-13T21:48:49.560Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-02-13T21:48:49.560Z] GC before operation: completed in 173.807 ms, heap usage 69.196 MB -> 41.615 MB.
[2025-02-13T21:48:52.577Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-13T21:48:54.531Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-13T21:48:57.544Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-13T21:48:59.497Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-13T21:49:00.450Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-13T21:49:02.406Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-13T21:49:03.358Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-13T21:49:05.313Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-13T21:49:05.313Z] 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.
[2025-02-13T21:49:05.313Z] The best model improves the baseline by 14.52%.
[2025-02-13T21:49:05.313Z] Movies recommended for you:
[2025-02-13T21:49:05.313Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-13T21:49:05.313Z] There is no way to check that no silent failure occurred.
[2025-02-13T21:49:05.313Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (15475.865 ms) ======
[2025-02-13T21:49:05.313Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-02-13T21:49:05.313Z] GC before operation: completed in 174.664 ms, heap usage 114.847 MB -> 45.072 MB.
[2025-02-13T21:49:08.333Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-13T21:49:10.291Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-13T21:49:12.248Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-13T21:49:15.264Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-13T21:49:16.216Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-13T21:49:17.168Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-13T21:49:19.121Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-13T21:49:20.073Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-13T21:49:21.024Z] 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.
[2025-02-13T21:49:21.024Z] The best model improves the baseline by 14.52%.
[2025-02-13T21:49:21.024Z] Movies recommended for you:
[2025-02-13T21:49:21.024Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-13T21:49:21.024Z] There is no way to check that no silent failure occurred.
[2025-02-13T21:49:21.024Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (15192.992 ms) ======
[2025-02-13T21:49:21.024Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-02-13T21:49:21.024Z] GC before operation: completed in 190.110 ms, heap usage 89.958 MB -> 41.632 MB.
[2025-02-13T21:49:22.977Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-13T21:49:24.929Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-13T21:49:27.944Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-13T21:49:29.898Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-13T21:49:31.854Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-13T21:49:32.805Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-13T21:49:33.757Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-13T21:49:35.714Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-13T21:49:35.714Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-02-13T21:49:35.714Z] The best model improves the baseline by 14.52%.
[2025-02-13T21:49:35.714Z] Movies recommended for you:
[2025-02-13T21:49:35.714Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-13T21:49:35.714Z] There is no way to check that no silent failure occurred.
[2025-02-13T21:49:35.714Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (15129.881 ms) ======
[2025-02-13T21:49:35.714Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-02-13T21:49:36.669Z] GC before operation: completed in 225.094 ms, heap usage 134.982 MB -> 45.510 MB.
[2025-02-13T21:49:39.342Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-13T21:49:40.297Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-13T21:49:43.361Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-13T21:49:45.433Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-13T21:49:46.385Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-13T21:49:48.338Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-13T21:49:49.289Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-13T21:49:51.243Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-13T21:49:51.243Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-02-13T21:49:51.243Z] The best model improves the baseline by 14.52%.
[2025-02-13T21:49:51.243Z] Movies recommended for you:
[2025-02-13T21:49:51.243Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-13T21:49:51.243Z] There is no way to check that no silent failure occurred.
[2025-02-13T21:49:51.243Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (14788.805 ms) ======
[2025-02-13T21:49:51.243Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-02-13T21:49:51.243Z] GC before operation: completed in 220.441 ms, heap usage 410.054 MB -> 64.872 MB.
[2025-02-13T21:49:53.197Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-13T21:49:56.223Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-13T21:49:58.191Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-13T21:50:00.152Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-13T21:50:02.108Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-13T21:50:03.061Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-13T21:50:05.022Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-13T21:50:05.974Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-13T21:50:05.974Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-02-13T21:50:05.974Z] The best model improves the baseline by 14.52%.
[2025-02-13T21:50:06.936Z] Movies recommended for you:
[2025-02-13T21:50:06.936Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-13T21:50:06.936Z] There is no way to check that no silent failure occurred.
[2025-02-13T21:50:06.937Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (15139.315 ms) ======
[2025-02-13T21:50:06.937Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-02-13T21:50:06.937Z] GC before operation: completed in 252.674 ms, heap usage 144.951 MB -> 63.080 MB.
[2025-02-13T21:50:08.987Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-13T21:50:11.117Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-13T21:50:13.071Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-13T21:50:16.088Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-13T21:50:17.041Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-13T21:50:18.001Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-13T21:50:19.953Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-13T21:50:20.917Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-13T21:50:21.873Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-02-13T21:50:21.873Z] The best model improves the baseline by 14.52%.
[2025-02-13T21:50:21.873Z] Movies recommended for you:
[2025-02-13T21:50:21.873Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-13T21:50:21.873Z] There is no way to check that no silent failure occurred.
[2025-02-13T21:50:21.873Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (14846.483 ms) ======
[2025-02-13T21:50:21.873Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-02-13T21:50:21.873Z] GC before operation: completed in 175.504 ms, heap usage 134.188 MB -> 52.172 MB.
[2025-02-13T21:50:23.831Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-13T21:50:25.803Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-13T21:50:28.819Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-13T21:50:30.775Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-13T21:50:31.727Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-13T21:50:33.680Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-13T21:50:35.693Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-13T21:50:35.693Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-13T21:50:36.647Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-02-13T21:50:36.647Z] The best model improves the baseline by 14.52%.
[2025-02-13T21:50:36.647Z] Movies recommended for you:
[2025-02-13T21:50:36.647Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-13T21:50:36.647Z] There is no way to check that no silent failure occurred.
[2025-02-13T21:50:36.647Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (14609.784 ms) ======
[2025-02-13T21:50:36.647Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-02-13T21:50:36.647Z] GC before operation: completed in 225.896 ms, heap usage 125.682 MB -> 70.408 MB.
[2025-02-13T21:50:38.618Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-13T21:50:40.584Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-13T21:50:43.639Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-13T21:50:45.594Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-13T21:50:46.546Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-13T21:50:48.502Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-13T21:50:49.454Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-13T21:50:51.412Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-13T21:50:51.412Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-02-13T21:50:51.412Z] The best model improves the baseline by 14.52%.
[2025-02-13T21:50:51.412Z] Movies recommended for you:
[2025-02-13T21:50:51.412Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-13T21:50:51.412Z] There is no way to check that no silent failure occurred.
[2025-02-13T21:50:51.412Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (14777.972 ms) ======
[2025-02-13T21:50:51.412Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-02-13T21:50:51.412Z] GC before operation: completed in 154.381 ms, heap usage 142.511 MB -> 52.478 MB.
[2025-02-13T21:50:53.367Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-13T21:50:56.384Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-13T21:50:58.341Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-13T21:51:00.298Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-13T21:51:02.258Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-13T21:51:03.213Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-13T21:51:05.167Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-13T21:51:06.119Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-13T21:51:06.119Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-02-13T21:51:06.119Z] The best model improves the baseline by 14.52%.
[2025-02-13T21:51:06.119Z] Movies recommended for you:
[2025-02-13T21:51:06.119Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-13T21:51:06.119Z] There is no way to check that no silent failure occurred.
[2025-02-13T21:51:06.119Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (14906.362 ms) ======
[2025-02-13T21:51:06.119Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-02-13T21:51:07.079Z] GC before operation: completed in 243.224 ms, heap usage 166.954 MB -> 70.332 MB.
[2025-02-13T21:51:09.034Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-13T21:51:10.988Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-13T21:51:12.959Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-13T21:51:15.977Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-13T21:51:16.930Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-13T21:51:17.883Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-13T21:51:19.839Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-13T21:51:20.792Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-13T21:51:21.743Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-02-13T21:51:21.743Z] The best model improves the baseline by 14.52%.
[2025-02-13T21:51:21.743Z] Movies recommended for you:
[2025-02-13T21:51:21.743Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-13T21:51:21.743Z] There is no way to check that no silent failure occurred.
[2025-02-13T21:51:21.743Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14719.697 ms) ======
[2025-02-13T21:51:21.743Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-02-13T21:51:21.743Z] GC before operation: completed in 254.589 ms, heap usage 190.925 MB -> 70.537 MB.
[2025-02-13T21:51:23.696Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-13T21:51:25.655Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-13T21:51:28.673Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-13T21:51:30.630Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-13T21:51:32.638Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-13T21:51:33.590Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-13T21:51:34.542Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-13T21:51:36.502Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-13T21:51:36.502Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-02-13T21:51:36.502Z] The best model improves the baseline by 14.52%.
[2025-02-13T21:51:36.502Z] Movies recommended for you:
[2025-02-13T21:51:36.502Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-13T21:51:36.502Z] There is no way to check that no silent failure occurred.
[2025-02-13T21:51:36.502Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (14876.793 ms) ======
[2025-02-13T21:51:36.502Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-02-13T21:51:36.502Z] GC before operation: completed in 252.972 ms, heap usage 181.562 MB -> 70.698 MB.
[2025-02-13T21:51:39.522Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-13T21:51:41.477Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-13T21:51:43.431Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-13T21:51:45.408Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-13T21:51:47.364Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-13T21:51:48.316Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-13T21:51:50.274Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-13T21:51:51.227Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-13T21:51:51.227Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-02-13T21:51:51.227Z] The best model improves the baseline by 14.52%.
[2025-02-13T21:51:52.180Z] Movies recommended for you:
[2025-02-13T21:51:52.180Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-13T21:51:52.180Z] There is no way to check that no silent failure occurred.
[2025-02-13T21:51:52.180Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (14956.905 ms) ======
[2025-02-13T21:51:52.180Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-02-13T21:51:52.180Z] GC before operation: completed in 161.294 ms, heap usage 122.706 MB -> 48.818 MB.
[2025-02-13T21:51:54.192Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-13T21:51:56.146Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-13T21:51:58.099Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-13T21:52:01.162Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-13T21:52:02.117Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-13T21:52:03.069Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-13T21:52:05.025Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-13T21:52:05.986Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-13T21:52:06.942Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-02-13T21:52:06.942Z] The best model improves the baseline by 14.52%.
[2025-02-13T21:52:06.942Z] Movies recommended for you:
[2025-02-13T21:52:06.942Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-13T21:52:06.942Z] There is no way to check that no silent failure occurred.
[2025-02-13T21:52:06.942Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (14714.965 ms) ======
[2025-02-13T21:52:06.942Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-02-13T21:52:06.942Z] GC before operation: completed in 228.345 ms, heap usage 166.428 MB -> 70.351 MB.
[2025-02-13T21:52:08.895Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-13T21:52:10.850Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-13T21:52:13.870Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-13T21:52:16.697Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-13T21:52:17.649Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-13T21:52:18.606Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-13T21:52:19.559Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-13T21:52:21.525Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-13T21:52:21.525Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-02-13T21:52:21.525Z] The best model improves the baseline by 14.52%.
[2025-02-13T21:52:21.525Z] Movies recommended for you:
[2025-02-13T21:52:21.525Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-13T21:52:21.525Z] There is no way to check that no silent failure occurred.
[2025-02-13T21:52:21.525Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (14719.678 ms) ======
[2025-02-13T21:52:21.525Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-02-13T21:52:21.525Z] GC before operation: completed in 207.585 ms, heap usage 161.361 MB -> 70.683 MB.
[2025-02-13T21:52:24.544Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-13T21:52:26.502Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-13T21:52:28.456Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-13T21:52:30.418Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-13T21:52:32.370Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-13T21:52:33.321Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-13T21:52:35.275Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-13T21:52:36.227Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-13T21:52:36.227Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-02-13T21:52:36.227Z] The best model improves the baseline by 14.52%.
[2025-02-13T21:52:36.227Z] Movies recommended for you:
[2025-02-13T21:52:36.227Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-13T21:52:36.227Z] There is no way to check that no silent failure occurred.
[2025-02-13T21:52:36.227Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (14792.366 ms) ======
[2025-02-13T21:52:37.178Z] -----------------------------------
[2025-02-13T21:52:37.178Z] renaissance-movie-lens_0_PASSED
[2025-02-13T21:52:37.178Z] -----------------------------------
[2025-02-13T21:52:37.178Z]
[2025-02-13T21:52:37.178Z] TEST TEARDOWN:
[2025-02-13T21:52:37.178Z] Nothing to be done for teardown.
[2025-02-13T21:52:37.178Z] renaissance-movie-lens_0 Finish Time: Thu Feb 13 21:52:36 2025 Epoch Time (ms): 1739483556766