renaissance-movie-lens_0
[2024-09-27T12:40:43.044Z] Running test renaissance-movie-lens_0 ...
[2024-09-27T12:40:43.044Z] ===============================================
[2024-09-27T12:40:43.044Z] renaissance-movie-lens_0 Start Time: Fri Sep 27 12:40:42 2024 Epoch Time (ms): 1727440842627
[2024-09-27T12:40:43.044Z] variation: NoOptions
[2024-09-27T12:40:43.044Z] JVM_OPTIONS:
[2024-09-27T12:40:43.044Z] { \
[2024-09-27T12:40:43.044Z] echo ""; echo "TEST SETUP:"; \
[2024-09-27T12:40:43.044Z] echo "Nothing to be done for setup."; \
[2024-09-27T12:40:43.044Z] mkdir -p "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17274365276368/renaissance-movie-lens_0"; \
[2024-09-27T12:40:43.044Z] cd "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17274365276368/renaissance-movie-lens_0"; \
[2024-09-27T12:40:43.044Z] echo ""; echo "TESTING:"; \
[2024-09-27T12:40:43.044Z] "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_alpine-linux/jdkbinary/j2sdk-image/bin/java" -jar "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17274365276368/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-09-27T12:40:43.044Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17274365276368/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-09-27T12:40:43.044Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-09-27T12:40:43.044Z] echo "Nothing to be done for teardown."; \
[2024-09-27T12:40:43.044Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17274365276368/TestTargetResult";
[2024-09-27T12:40:43.044Z]
[2024-09-27T12:40:43.044Z] TEST SETUP:
[2024-09-27T12:40:43.044Z] Nothing to be done for setup.
[2024-09-27T12:40:43.044Z]
[2024-09-27T12:40:43.044Z] TESTING:
[2024-09-27T12:40:53.452Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-09-27T12:41:08.002Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2024-09-27T12:41:31.056Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-09-27T12:41:31.056Z] Training: 60056, validation: 20285, test: 19854
[2024-09-27T12:41:31.056Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-09-27T12:41:32.205Z] GC before operation: completed in 1463.154 ms, heap usage 47.162 MB -> 27.103 MB.
[2024-09-27T12:42:15.492Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-27T12:42:42.556Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-27T12:43:05.625Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-27T12:43:28.774Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-27T12:43:41.708Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-27T12:43:54.150Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-27T12:44:06.844Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-27T12:44:19.291Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-27T12:44:20.902Z] 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.
[2024-09-27T12:44:20.902Z] The best model improves the baseline by 14.52%.
[2024-09-27T12:44:21.710Z] Movies recommended for you:
[2024-09-27T12:44:21.710Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-27T12:44:21.711Z] There is no way to check that no silent failure occurred.
[2024-09-27T12:44:21.711Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (170117.645 ms) ======
[2024-09-27T12:44:21.711Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-09-27T12:44:24.129Z] GC before operation: completed in 2444.987 ms, heap usage 380.787 MB -> 45.324 MB.
[2024-09-27T12:44:46.164Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-27T12:45:11.925Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-27T12:45:31.371Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-27T12:45:47.488Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-27T12:45:59.141Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-27T12:46:10.909Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-27T12:46:24.578Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-27T12:46:36.555Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-27T12:46:38.151Z] 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.
[2024-09-27T12:46:38.151Z] The best model improves the baseline by 14.52%.
[2024-09-27T12:46:38.151Z] Movies recommended for you:
[2024-09-27T12:46:38.151Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-27T12:46:38.151Z] There is no way to check that no silent failure occurred.
[2024-09-27T12:46:38.151Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (134062.404 ms) ======
[2024-09-27T12:46:38.151Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-09-27T12:46:39.721Z] GC before operation: completed in 1416.138 ms, heap usage 310.271 MB -> 42.384 MB.
[2024-09-27T12:46:59.191Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-27T12:47:18.014Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-27T12:47:37.126Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-27T12:47:56.103Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-27T12:48:06.129Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-27T12:48:16.146Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-27T12:48:27.925Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-27T12:48:38.297Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-27T12:48:39.050Z] 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.
[2024-09-27T12:48:39.050Z] The best model improves the baseline by 14.52%.
[2024-09-27T12:48:39.806Z] Movies recommended for you:
[2024-09-27T12:48:39.806Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-27T12:48:39.806Z] There is no way to check that no silent failure occurred.
[2024-09-27T12:48:39.806Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (120167.172 ms) ======
[2024-09-27T12:48:39.806Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-09-27T12:48:42.238Z] GC before operation: completed in 1777.888 ms, heap usage 500.677 MB -> 46.433 MB.
[2024-09-27T12:49:01.295Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-27T12:49:19.991Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-27T12:49:38.899Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-27T12:49:57.621Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-27T12:50:09.330Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-27T12:50:20.969Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-27T12:50:30.775Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-27T12:50:40.801Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-27T12:50:41.566Z] 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.
[2024-09-27T12:50:41.566Z] The best model improves the baseline by 14.52%.
[2024-09-27T12:50:42.322Z] Movies recommended for you:
[2024-09-27T12:50:42.323Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-27T12:50:42.323Z] There is no way to check that no silent failure occurred.
[2024-09-27T12:50:42.323Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (120156.756 ms) ======
[2024-09-27T12:50:42.323Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-09-27T12:50:43.079Z] GC before operation: completed in 936.771 ms, heap usage 469.354 MB -> 46.869 MB.
[2024-09-27T12:51:01.979Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-27T12:51:23.998Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-27T12:51:43.650Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-27T12:52:02.834Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-27T12:52:14.364Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-27T12:52:24.131Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-27T12:52:35.772Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-27T12:52:45.664Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-27T12:52:46.427Z] 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.
[2024-09-27T12:52:46.427Z] The best model improves the baseline by 14.52%.
[2024-09-27T12:52:47.199Z] Movies recommended for you:
[2024-09-27T12:52:47.199Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-27T12:52:47.199Z] There is no way to check that no silent failure occurred.
[2024-09-27T12:52:47.199Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (124110.550 ms) ======
[2024-09-27T12:52:47.199Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-09-27T12:52:47.959Z] GC before operation: completed in 1173.095 ms, heap usage 451.841 MB -> 47.083 MB.
[2024-09-27T12:53:07.522Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-27T12:53:26.383Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-27T12:53:45.334Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-27T12:54:01.427Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-27T12:54:11.344Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-27T12:54:27.443Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-27T12:54:39.598Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-27T12:54:47.758Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-27T12:54:49.328Z] 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.
[2024-09-27T12:54:49.328Z] The best model improves the baseline by 14.52%.
[2024-09-27T12:54:50.091Z] Movies recommended for you:
[2024-09-27T12:54:50.091Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-27T12:54:50.091Z] There is no way to check that no silent failure occurred.
[2024-09-27T12:54:50.091Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (121761.482 ms) ======
[2024-09-27T12:54:50.091Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-09-27T12:54:50.854Z] GC before operation: completed in 812.859 ms, heap usage 441.318 MB -> 46.903 MB.
[2024-09-27T12:55:07.115Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-27T12:55:23.259Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-27T12:55:42.003Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-27T12:55:55.649Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-27T12:56:05.513Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-27T12:56:15.256Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-27T12:56:25.025Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-27T12:56:34.882Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-27T12:56:36.510Z] 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.
[2024-09-27T12:56:36.510Z] The best model improves the baseline by 14.52%.
[2024-09-27T12:56:36.510Z] Movies recommended for you:
[2024-09-27T12:56:36.510Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-27T12:56:36.510Z] There is no way to check that no silent failure occurred.
[2024-09-27T12:56:36.510Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (106008.103 ms) ======
[2024-09-27T12:56:36.510Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-09-27T12:56:37.265Z] GC before operation: completed in 780.670 ms, heap usage 445.104 MB -> 47.097 MB.
[2024-09-27T12:56:55.986Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-27T12:57:14.819Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-27T12:57:30.915Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-27T12:57:49.585Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-27T12:57:59.323Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-27T12:58:09.213Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-27T12:58:20.915Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-27T12:58:30.766Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-27T12:58:31.521Z] 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.
[2024-09-27T12:58:31.521Z] The best model improves the baseline by 14.52%.
[2024-09-27T12:58:32.287Z] Movies recommended for you:
[2024-09-27T12:58:32.287Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-27T12:58:32.287Z] There is no way to check that no silent failure occurred.
[2024-09-27T12:58:32.287Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (114422.450 ms) ======
[2024-09-27T12:58:32.287Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-09-27T12:58:33.051Z] GC before operation: completed in 1194.323 ms, heap usage 444.076 MB -> 47.516 MB.
[2024-09-27T12:58:51.914Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-27T12:59:08.623Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-27T12:59:27.359Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-27T12:59:43.476Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-27T12:59:55.217Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-27T13:00:04.992Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-27T13:00:16.586Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-27T13:00:26.640Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-27T13:00:27.399Z] 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.
[2024-09-27T13:00:27.399Z] The best model improves the baseline by 14.52%.
[2024-09-27T13:00:28.141Z] Movies recommended for you:
[2024-09-27T13:00:28.141Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-27T13:00:28.141Z] There is no way to check that no silent failure occurred.
[2024-09-27T13:00:28.141Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (114908.912 ms) ======
[2024-09-27T13:00:28.141Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-09-27T13:00:28.902Z] GC before operation: completed in 770.741 ms, heap usage 441.552 MB -> 47.168 MB.
[2024-09-27T13:00:47.714Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-27T13:01:03.672Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-27T13:01:22.413Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-27T13:01:36.135Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-27T13:01:45.990Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-27T13:01:54.919Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-27T13:02:04.912Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-27T13:02:16.580Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-27T13:02:17.353Z] 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.
[2024-09-27T13:02:17.353Z] The best model improves the baseline by 14.52%.
[2024-09-27T13:02:17.353Z] Movies recommended for you:
[2024-09-27T13:02:17.353Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-27T13:02:17.353Z] There is no way to check that no silent failure occurred.
[2024-09-27T13:02:17.353Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (108818.560 ms) ======
[2024-09-27T13:02:17.353Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-09-27T13:02:18.923Z] GC before operation: completed in 1445.782 ms, heap usage 444.387 MB -> 47.321 MB.
[2024-09-27T13:02:37.691Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-27T13:02:53.634Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-27T13:03:12.348Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-27T13:03:31.693Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-27T13:03:41.607Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-27T13:03:51.415Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-27T13:04:03.186Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-27T13:04:13.114Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-27T13:04:13.863Z] 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.
[2024-09-27T13:04:14.623Z] The best model improves the baseline by 14.52%.
[2024-09-27T13:04:14.623Z] Movies recommended for you:
[2024-09-27T13:04:14.623Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-27T13:04:14.623Z] There is no way to check that no silent failure occurred.
[2024-09-27T13:04:14.623Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (115561.119 ms) ======
[2024-09-27T13:04:14.623Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-09-27T13:04:15.382Z] GC before operation: completed in 1008.846 ms, heap usage 455.500 MB -> 47.054 MB.
[2024-09-27T13:04:34.126Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-27T13:04:50.838Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-27T13:05:09.542Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-27T13:05:25.467Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-27T13:05:35.499Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-27T13:05:45.387Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-27T13:05:55.217Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-27T13:06:05.155Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-27T13:06:06.832Z] 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.
[2024-09-27T13:06:06.832Z] The best model improves the baseline by 14.52%.
[2024-09-27T13:06:06.832Z] Movies recommended for you:
[2024-09-27T13:06:06.832Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-27T13:06:06.832Z] There is no way to check that no silent failure occurred.
[2024-09-27T13:06:06.832Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (111477.590 ms) ======
[2024-09-27T13:06:06.832Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-09-27T13:06:08.460Z] GC before operation: completed in 1270.771 ms, heap usage 454.119 MB -> 44.308 MB.
[2024-09-27T13:06:27.838Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-27T13:06:43.794Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-27T13:07:02.534Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-27T13:07:18.505Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-27T13:07:28.328Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-27T13:07:38.167Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-27T13:07:48.530Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-27T13:08:00.217Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-27T13:08:00.217Z] 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.
[2024-09-27T13:08:00.217Z] The best model improves the baseline by 14.52%.
[2024-09-27T13:08:00.969Z] Movies recommended for you:
[2024-09-27T13:08:00.969Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-27T13:08:00.969Z] There is no way to check that no silent failure occurred.
[2024-09-27T13:08:00.969Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (112441.730 ms) ======
[2024-09-27T13:08:00.969Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-09-27T13:08:02.610Z] GC before operation: completed in 1948.457 ms, heap usage 469.704 MB -> 43.659 MB.
[2024-09-27T13:08:21.462Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-27T13:08:35.149Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-27T13:08:51.093Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-27T13:09:04.789Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-27T13:09:15.097Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-27T13:09:23.249Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-27T13:09:33.102Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-27T13:09:41.295Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-27T13:09:42.863Z] 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.
[2024-09-27T13:09:42.863Z] The best model improves the baseline by 14.52%.
[2024-09-27T13:09:43.627Z] Movies recommended for you:
[2024-09-27T13:09:43.627Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-27T13:09:43.627Z] There is no way to check that no silent failure occurred.
[2024-09-27T13:09:43.627Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (100517.615 ms) ======
[2024-09-27T13:09:43.627Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-09-27T13:09:45.171Z] GC before operation: completed in 1602.706 ms, heap usage 468.129 MB -> 43.152 MB.
[2024-09-27T13:10:01.207Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-27T13:10:14.943Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-27T13:10:33.736Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-27T13:10:47.389Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-27T13:10:54.973Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-27T13:11:03.499Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-27T13:11:13.650Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-27T13:11:22.175Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-27T13:11:22.992Z] 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.
[2024-09-27T13:11:22.992Z] The best model improves the baseline by 14.52%.
[2024-09-27T13:11:23.789Z] Movies recommended for you:
[2024-09-27T13:11:23.789Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-27T13:11:23.789Z] There is no way to check that no silent failure occurred.
[2024-09-27T13:11:23.789Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (98775.283 ms) ======
[2024-09-27T13:11:23.789Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-09-27T13:11:24.619Z] GC before operation: completed in 674.975 ms, heap usage 491.107 MB -> 44.507 MB.
[2024-09-27T13:11:38.628Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-27T13:11:55.087Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-27T13:12:09.757Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-27T13:12:26.254Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-27T13:12:33.525Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-27T13:12:42.111Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-27T13:12:52.279Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-27T13:13:00.865Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-27T13:13:01.667Z] 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.
[2024-09-27T13:13:01.667Z] The best model improves the baseline by 14.52%.
[2024-09-27T13:13:01.667Z] Movies recommended for you:
[2024-09-27T13:13:01.667Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-27T13:13:01.667Z] There is no way to check that no silent failure occurred.
[2024-09-27T13:13:01.667Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (97509.572 ms) ======
[2024-09-27T13:13:01.667Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-09-27T13:13:02.458Z] GC before operation: completed in 573.069 ms, heap usage 468.545 MB -> 42.798 MB.
[2024-09-27T13:13:19.125Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-27T13:13:33.961Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-27T13:13:50.390Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-27T13:14:04.743Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-27T13:14:13.246Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-27T13:14:20.408Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-27T13:14:30.545Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-27T13:14:39.113Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-27T13:14:39.911Z] 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.
[2024-09-27T13:14:40.711Z] The best model improves the baseline by 14.52%.
[2024-09-27T13:14:40.711Z] Movies recommended for you:
[2024-09-27T13:14:40.711Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-27T13:14:40.711Z] There is no way to check that no silent failure occurred.
[2024-09-27T13:14:40.711Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (98184.282 ms) ======
[2024-09-27T13:14:40.711Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-09-27T13:14:41.513Z] GC before operation: completed in 1032.992 ms, heap usage 440.195 MB -> 43.231 MB.
[2024-09-27T13:14:56.173Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-27T13:15:12.701Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-27T13:15:26.785Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-27T13:15:38.761Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-27T13:15:47.347Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-27T13:15:54.405Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-27T13:16:02.980Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-27T13:16:10.032Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-27T13:16:11.243Z] 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.
[2024-09-27T13:16:11.243Z] The best model improves the baseline by 14.52%.
[2024-09-27T13:16:11.243Z] Movies recommended for you:
[2024-09-27T13:16:11.243Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-27T13:16:11.243Z] There is no way to check that no silent failure occurred.
[2024-09-27T13:16:11.243Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (89682.233 ms) ======
[2024-09-27T13:16:11.243Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-09-27T13:16:12.034Z] GC before operation: completed in 615.140 ms, heap usage 429.559 MB -> 43.256 MB.
[2024-09-27T13:16:26.182Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-27T13:16:38.317Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-27T13:16:52.505Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-27T13:17:06.578Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-27T13:17:13.649Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-27T13:17:21.010Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-27T13:17:28.480Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-27T13:17:37.136Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-27T13:17:37.136Z] 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.
[2024-09-27T13:17:37.136Z] The best model improves the baseline by 14.52%.
[2024-09-27T13:17:37.925Z] Movies recommended for you:
[2024-09-27T13:17:37.925Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-27T13:17:37.925Z] There is no way to check that no silent failure occurred.
[2024-09-27T13:17:37.925Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (85771.701 ms) ======
[2024-09-27T13:17:37.925Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-09-27T13:17:38.737Z] GC before operation: completed in 842.154 ms, heap usage 455.106 MB -> 43.558 MB.
[2024-09-27T13:17:50.704Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-27T13:18:04.881Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-27T13:18:16.860Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-27T13:18:28.919Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-27T13:18:36.183Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-27T13:18:45.529Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-27T13:18:52.633Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-27T13:19:01.230Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-27T13:19:01.231Z] 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.
[2024-09-27T13:19:02.046Z] The best model improves the baseline by 14.52%.
[2024-09-27T13:19:02.046Z] Movies recommended for you:
[2024-09-27T13:19:02.046Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-27T13:19:02.046Z] There is no way to check that no silent failure occurred.
[2024-09-27T13:19:02.046Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (83337.853 ms) ======
[2024-09-27T13:19:04.701Z] -----------------------------------
[2024-09-27T13:19:04.701Z] renaissance-movie-lens_0_PASSED
[2024-09-27T13:19:04.701Z] -----------------------------------
[2024-09-27T13:19:04.701Z]
[2024-09-27T13:19:04.701Z] TEST TEARDOWN:
[2024-09-27T13:19:04.701Z] Nothing to be done for teardown.
[2024-09-27T13:19:04.701Z] renaissance-movie-lens_0 Finish Time: Fri Sep 27 13:19:03 2024 Epoch Time (ms): 1727443143809