renaissance-movie-lens_0
[2024-08-02T00:38:36.098Z] Running test renaissance-movie-lens_0 ...
[2024-08-02T00:38:36.098Z] ===============================================
[2024-08-02T00:38:36.098Z] renaissance-movie-lens_0 Start Time: Thu Aug 1 20:20:43 2024 Epoch Time (ms): 1722561643530
[2024-08-02T00:38:36.098Z] variation: NoOptions
[2024-08-02T00:38:36.098Z] JVM_OPTIONS:
[2024-08-02T00:38:36.098Z] { \
[2024-08-02T00:38:36.098Z] echo ""; echo "TEST SETUP:"; \
[2024-08-02T00:38:36.098Z] echo "Nothing to be done for setup."; \
[2024-08-02T00:38:36.098Z] mkdir -p "/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_sparcv9_solaris_testList_0/aqa-tests/TKG/../TKG/output_1722559086619/renaissance-movie-lens_0"; \
[2024-08-02T00:38:36.098Z] cd "/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_sparcv9_solaris_testList_0/aqa-tests/TKG/../TKG/output_1722559086619/renaissance-movie-lens_0"; \
[2024-08-02T00:38:36.098Z] echo ""; echo "TESTING:"; \
[2024-08-02T00:38:36.098Z] "/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_sparcv9_solaris_testList_0/jdkbinary/j2sdk-image/bin/java" -jar "/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_sparcv9_solaris_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_sparcv9_solaris_testList_0/aqa-tests/TKG/../TKG/output_1722559086619/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-02T00:38:36.098Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_sparcv9_solaris_testList_0/aqa-tests/TKG/..; rm -f -r "/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_sparcv9_solaris_testList_0/aqa-tests/TKG/../TKG/output_1722559086619/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-02T00:38:36.098Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-02T00:38:36.098Z] echo "Nothing to be done for teardown."; \
[2024-08-02T00:38:36.098Z] } 2>&1 | tee -a "/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_sparcv9_solaris_testList_0/aqa-tests/TKG/../TKG/output_1722559086619/TestTargetResult";
[2024-08-02T00:38:36.098Z]
[2024-08-02T00:38:36.098Z] TEST SETUP:
[2024-08-02T00:38:36.098Z] Nothing to be done for setup.
[2024-08-02T00:38:36.098Z]
[2024-08-02T00:38:36.098Z] TESTING:
[2024-08-02T00:38:43.305Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-02T00:38:49.086Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2024-08-02T00:39:01.154Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-02T00:39:01.154Z] Training: 60056, validation: 20285, test: 19854
[2024-08-02T00:39:01.154Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-02T00:39:01.770Z] GC before operation: completed in 450.516 ms, heap usage 158.608 MB -> 27.799 MB.
[2024-08-02T00:39:18.727Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T00:39:28.875Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T00:39:39.016Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T00:39:49.246Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T00:39:52.938Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T00:39:57.610Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T00:40:01.953Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T00:40:06.624Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T00:40:06.624Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-08-02T00:40:07.241Z] The best model improves the baseline by 14.52%.
[2024-08-02T00:40:07.241Z] Movies recommended for you:
[2024-08-02T00:40:07.241Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T00:40:07.241Z] There is no way to check that no silent failure occurred.
[2024-08-02T00:40:07.241Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (65706.001 ms) ======
[2024-08-02T00:40:07.241Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-02T00:40:07.858Z] GC before operation: completed in 613.982 ms, heap usage 437.501 MB -> 47.972 MB.
[2024-08-02T00:40:16.342Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T00:40:26.524Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T00:40:36.658Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T00:40:45.131Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T00:40:48.866Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T00:40:53.528Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T00:40:57.216Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T00:41:01.886Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T00:41:02.499Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-08-02T00:41:02.499Z] The best model improves the baseline by 14.52%.
[2024-08-02T00:41:02.499Z] Movies recommended for you:
[2024-08-02T00:41:02.499Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T00:41:02.499Z] There is no way to check that no silent failure occurred.
[2024-08-02T00:41:02.499Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (54658.848 ms) ======
[2024-08-02T00:41:02.499Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-02T00:41:03.113Z] GC before operation: completed in 525.325 ms, heap usage 73.573 MB -> 45.698 MB.
[2024-08-02T00:41:10.064Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T00:41:17.122Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T00:41:22.898Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T00:41:28.706Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T00:41:32.391Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T00:41:37.092Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T00:41:40.780Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T00:41:44.459Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T00:41:44.459Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-08-02T00:41:44.459Z] The best model improves the baseline by 14.52%.
[2024-08-02T00:41:45.073Z] Movies recommended for you:
[2024-08-02T00:41:45.073Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T00:41:45.073Z] There is no way to check that no silent failure occurred.
[2024-08-02T00:41:45.073Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (41724.029 ms) ======
[2024-08-02T00:41:45.073Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-02T00:41:45.688Z] GC before operation: completed in 492.650 ms, heap usage 570.634 MB -> 47.057 MB.
[2024-08-02T00:41:51.463Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T00:41:58.495Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T00:42:04.296Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T00:42:10.717Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T00:42:15.410Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T00:42:19.092Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T00:42:23.765Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T00:42:27.441Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T00:42:28.056Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-08-02T00:42:28.056Z] The best model improves the baseline by 14.52%.
[2024-08-02T00:42:28.056Z] Movies recommended for you:
[2024-08-02T00:42:28.056Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T00:42:28.056Z] There is no way to check that no silent failure occurred.
[2024-08-02T00:42:28.056Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (42616.599 ms) ======
[2024-08-02T00:42:28.056Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-02T00:42:28.670Z] GC before operation: completed in 480.867 ms, heap usage 570.583 MB -> 47.488 MB.
[2024-08-02T00:42:34.451Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T00:42:41.511Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T00:42:48.552Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T00:42:54.353Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T00:42:58.039Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T00:43:01.744Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T00:43:06.418Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T00:43:09.270Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T00:43:09.887Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-08-02T00:43:11.572Z] The best model improves the baseline by 14.52%.
[2024-08-02T00:43:11.572Z] Movies recommended for you:
[2024-08-02T00:43:11.572Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T00:43:11.572Z] There is no way to check that no silent failure occurred.
[2024-08-02T00:43:11.572Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (41917.788 ms) ======
[2024-08-02T00:43:11.572Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-02T00:43:12.188Z] GC before operation: completed in 554.547 ms, heap usage 584.187 MB -> 47.691 MB.
[2024-08-02T00:43:16.858Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T00:43:22.635Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T00:43:28.414Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T00:43:34.198Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T00:43:37.880Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T00:43:41.587Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T00:43:45.278Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T00:43:48.962Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T00:43:49.577Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-08-02T00:43:49.577Z] The best model improves the baseline by 14.52%.
[2024-08-02T00:43:49.577Z] Movies recommended for you:
[2024-08-02T00:43:49.577Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T00:43:49.577Z] There is no way to check that no silent failure occurred.
[2024-08-02T00:43:49.577Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (38653.673 ms) ======
[2024-08-02T00:43:49.577Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-02T00:43:50.191Z] GC before operation: completed in 442.231 ms, heap usage 579.833 MB -> 47.629 MB.
[2024-08-02T00:43:55.976Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T00:44:01.754Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T00:44:07.548Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T00:44:13.099Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T00:44:16.780Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T00:44:20.462Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T00:44:24.142Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T00:44:26.938Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T00:44:27.551Z] 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.
[2024-08-02T00:44:27.551Z] The best model improves the baseline by 14.52%.
[2024-08-02T00:44:28.164Z] Movies recommended for you:
[2024-08-02T00:44:28.164Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T00:44:28.164Z] There is no way to check that no silent failure occurred.
[2024-08-02T00:44:28.164Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (37823.307 ms) ======
[2024-08-02T00:44:28.164Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-02T00:44:28.776Z] GC before operation: completed in 411.133 ms, heap usage 579.416 MB -> 47.809 MB.
[2024-08-02T00:44:34.582Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T00:44:40.357Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T00:44:46.126Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T00:44:51.912Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T00:44:55.594Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T00:44:59.274Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T00:45:02.955Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T00:45:05.753Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T00:45:07.030Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-08-02T00:45:07.030Z] The best model improves the baseline by 14.52%.
[2024-08-02T00:45:07.030Z] Movies recommended for you:
[2024-08-02T00:45:07.030Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T00:45:07.030Z] There is no way to check that no silent failure occurred.
[2024-08-02T00:45:07.030Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (38557.189 ms) ======
[2024-08-02T00:45:07.030Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-02T00:45:07.645Z] GC before operation: completed in 431.801 ms, heap usage 572.792 MB -> 48.133 MB.
[2024-08-02T00:45:12.914Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T00:45:19.961Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T00:45:25.758Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T00:45:30.421Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T00:45:34.105Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T00:45:37.798Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T00:45:41.526Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T00:45:44.343Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T00:45:44.958Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-08-02T00:45:44.958Z] The best model improves the baseline by 14.52%.
[2024-08-02T00:45:45.573Z] Movies recommended for you:
[2024-08-02T00:45:45.573Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T00:45:45.573Z] There is no way to check that no silent failure occurred.
[2024-08-02T00:45:45.573Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (38027.050 ms) ======
[2024-08-02T00:45:45.573Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-02T00:45:45.573Z] GC before operation: completed in 381.223 ms, heap usage 568.167 MB -> 47.869 MB.
[2024-08-02T00:45:51.356Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T00:45:57.160Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T00:46:03.080Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T00:46:09.011Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T00:46:12.542Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T00:46:17.933Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T00:46:22.605Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T00:46:25.414Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T00:46:26.028Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-08-02T00:46:26.028Z] The best model improves the baseline by 14.52%.
[2024-08-02T00:46:26.644Z] Movies recommended for you:
[2024-08-02T00:46:26.644Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T00:46:26.644Z] There is no way to check that no silent failure occurred.
[2024-08-02T00:46:26.644Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (40627.035 ms) ======
[2024-08-02T00:46:26.644Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-02T00:46:27.259Z] GC before operation: completed in 468.688 ms, heap usage 552.331 MB -> 47.875 MB.
[2024-08-02T00:46:33.084Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T00:46:38.916Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T00:46:44.715Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T00:46:50.494Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T00:46:54.198Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T00:46:57.035Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T00:47:00.726Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T00:47:04.410Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T00:47:05.025Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-08-02T00:47:05.025Z] The best model improves the baseline by 14.52%.
[2024-08-02T00:47:05.639Z] Movies recommended for you:
[2024-08-02T00:47:05.640Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T00:47:05.640Z] There is no way to check that no silent failure occurred.
[2024-08-02T00:47:05.640Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (38413.935 ms) ======
[2024-08-02T00:47:05.640Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-02T00:47:05.640Z] GC before operation: completed in 406.249 ms, heap usage 575.786 MB -> 47.699 MB.
[2024-08-02T00:47:12.932Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T00:47:17.609Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T00:47:23.408Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T00:47:29.193Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T00:47:31.994Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T00:47:35.679Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T00:47:39.364Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T00:47:43.090Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T00:47:43.090Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-08-02T00:47:43.090Z] The best model improves the baseline by 14.52%.
[2024-08-02T00:47:43.703Z] Movies recommended for you:
[2024-08-02T00:47:43.703Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T00:47:43.703Z] There is no way to check that no silent failure occurred.
[2024-08-02T00:47:43.703Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (37825.767 ms) ======
[2024-08-02T00:47:43.703Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-02T00:47:44.315Z] GC before operation: completed in 437.558 ms, heap usage 629.771 MB -> 50.646 MB.
[2024-08-02T00:47:50.087Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T00:47:55.866Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T00:48:01.648Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T00:48:07.470Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T00:48:10.275Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T00:48:14.211Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T00:48:17.897Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T00:48:21.583Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T00:48:22.199Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-08-02T00:48:22.199Z] The best model improves the baseline by 14.52%.
[2024-08-02T00:48:22.814Z] Movies recommended for you:
[2024-08-02T00:48:22.814Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T00:48:22.814Z] There is no way to check that no silent failure occurred.
[2024-08-02T00:48:22.814Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (38455.798 ms) ======
[2024-08-02T00:48:22.814Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-02T00:48:22.814Z] GC before operation: completed in 419.244 ms, heap usage 626.956 MB -> 48.509 MB.
[2024-08-02T00:48:28.596Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T00:48:34.381Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T00:48:40.285Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T00:48:46.071Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T00:48:49.760Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T00:48:53.445Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T00:48:57.132Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T00:48:59.937Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T00:49:01.217Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-08-02T00:49:01.217Z] The best model improves the baseline by 14.52%.
[2024-08-02T00:49:01.217Z] Movies recommended for you:
[2024-08-02T00:49:01.217Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T00:49:01.217Z] There is no way to check that no silent failure occurred.
[2024-08-02T00:49:01.217Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (38336.060 ms) ======
[2024-08-02T00:49:01.217Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-02T00:49:01.853Z] GC before operation: completed in 370.536 ms, heap usage 569.303 MB -> 47.798 MB.
[2024-08-02T00:49:07.641Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T00:49:13.869Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T00:49:18.540Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T00:49:24.320Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T00:49:28.012Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T00:49:30.813Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T00:49:34.502Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T00:49:38.193Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T00:49:38.810Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-08-02T00:49:38.810Z] The best model improves the baseline by 14.52%.
[2024-08-02T00:49:38.810Z] Movies recommended for you:
[2024-08-02T00:49:38.810Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T00:49:38.810Z] There is no way to check that no silent failure occurred.
[2024-08-02T00:49:38.810Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (37351.236 ms) ======
[2024-08-02T00:49:38.810Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-02T00:49:39.426Z] GC before operation: completed in 384.640 ms, heap usage 570.511 MB -> 48.001 MB.
[2024-08-02T00:49:45.206Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T00:49:51.002Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T00:49:56.789Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T00:50:02.571Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T00:50:06.256Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T00:50:09.064Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T00:50:13.489Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T00:50:16.291Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T00:50:16.906Z] 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.
[2024-08-02T00:50:16.906Z] The best model improves the baseline by 14.52%.
[2024-08-02T00:50:17.522Z] Movies recommended for you:
[2024-08-02T00:50:17.522Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T00:50:17.522Z] There is no way to check that no silent failure occurred.
[2024-08-02T00:50:17.522Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (37999.149 ms) ======
[2024-08-02T00:50:17.522Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-02T00:50:17.522Z] GC before operation: completed in 420.495 ms, heap usage 564.915 MB -> 48.081 MB.
[2024-08-02T00:50:23.306Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T00:50:29.080Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T00:50:34.926Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T00:50:40.726Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T00:50:44.410Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T00:50:48.094Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T00:50:51.795Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T00:50:54.594Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T00:50:55.208Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-08-02T00:50:55.208Z] The best model improves the baseline by 14.52%.
[2024-08-02T00:50:55.823Z] Movies recommended for you:
[2024-08-02T00:50:55.823Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T00:50:55.823Z] There is no way to check that no silent failure occurred.
[2024-08-02T00:50:55.823Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (37847.615 ms) ======
[2024-08-02T00:50:55.823Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-02T00:50:55.823Z] GC before operation: completed in 367.116 ms, heap usage 568.100 MB -> 47.928 MB.
[2024-08-02T00:51:01.607Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T00:51:07.386Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T00:51:14.249Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T00:51:18.919Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T00:51:22.728Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T00:51:26.417Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T00:51:30.104Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T00:51:32.924Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T00:51:33.553Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-08-02T00:51:33.553Z] The best model improves the baseline by 14.52%.
[2024-08-02T00:51:34.167Z] Movies recommended for you:
[2024-08-02T00:51:34.167Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T00:51:34.167Z] There is no way to check that no silent failure occurred.
[2024-08-02T00:51:34.167Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (37938.334 ms) ======
[2024-08-02T00:51:34.167Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-02T00:51:34.167Z] GC before operation: completed in 422.778 ms, heap usage 568.593 MB -> 47.989 MB.
[2024-08-02T00:51:39.961Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T00:51:45.746Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T00:51:51.534Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T00:51:57.329Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T00:52:01.062Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T00:52:04.021Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T00:52:07.710Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T00:52:11.399Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T00:52:12.014Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-08-02T00:52:12.014Z] The best model improves the baseline by 14.52%.
[2024-08-02T00:52:12.631Z] Movies recommended for you:
[2024-08-02T00:52:12.631Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T00:52:12.631Z] There is no way to check that no silent failure occurred.
[2024-08-02T00:52:12.631Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (37937.654 ms) ======
[2024-08-02T00:52:12.631Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-02T00:52:12.631Z] GC before operation: completed in 375.555 ms, heap usage 559.283 MB -> 48.177 MB.
[2024-08-02T00:52:18.418Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T00:52:24.208Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T00:52:29.999Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T00:52:35.782Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T00:52:38.586Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T00:52:42.322Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T00:52:46.013Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T00:52:49.697Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T00:52:49.697Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-08-02T00:52:49.697Z] The best model improves the baseline by 14.52%.
[2024-08-02T00:52:50.312Z] Movies recommended for you:
[2024-08-02T00:52:50.312Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T00:52:50.312Z] There is no way to check that no silent failure occurred.
[2024-08-02T00:52:50.312Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (37459.175 ms) ======
[2024-08-02T00:52:50.928Z] -----------------------------------
[2024-08-02T00:52:50.928Z] renaissance-movie-lens_0_PASSED
[2024-08-02T00:52:50.928Z] -----------------------------------
[2024-08-02T00:52:50.928Z]
[2024-08-02T00:52:50.928Z] TEST TEARDOWN:
[2024-08-02T00:52:50.928Z] Nothing to be done for teardown.
[2024-08-02T00:52:50.928Z] renaissance-movie-lens_0 Finish Time: Thu Aug 1 20:34:59 2024 Epoch Time (ms): 1722562499555