renaissance-movie-lens_0
[2025-01-22T02:51:09.913Z] Running test renaissance-movie-lens_0 ...
[2025-01-22T02:51:09.913Z] ===============================================
[2025-01-22T02:51:09.913Z] renaissance-movie-lens_0 Start Time: Wed Jan 22 02:51:08 2025 Epoch Time (ms): 1737514268602
[2025-01-22T02:51:09.913Z] variation: NoOptions
[2025-01-22T02:51:09.913Z] JVM_OPTIONS:
[2025-01-22T02:51:09.913Z] { \
[2025-01-22T02:51:09.913Z] echo ""; echo "TEST SETUP:"; \
[2025-01-22T02:51:09.913Z] echo "Nothing to be done for setup."; \
[2025-01-22T02:51:09.913Z] mkdir -p "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17375132689573/renaissance-movie-lens_0"; \
[2025-01-22T02:51:09.913Z] cd "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17375132689573/renaissance-movie-lens_0"; \
[2025-01-22T02:51:09.913Z] echo ""; echo "TESTING:"; \
[2025-01-22T02:51:09.913Z] "/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_17375132689573/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-01-22T02:51:09.913Z] 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_17375132689573/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-01-22T02:51:09.913Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-01-22T02:51:09.913Z] echo "Nothing to be done for teardown."; \
[2025-01-22T02:51:09.913Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17375132689573/TestTargetResult";
[2025-01-22T02:51:09.913Z]
[2025-01-22T02:51:09.913Z] TEST SETUP:
[2025-01-22T02:51:09.913Z] Nothing to be done for setup.
[2025-01-22T02:51:09.913Z]
[2025-01-22T02:51:09.913Z] TESTING:
[2025-01-22T02:51:12.927Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2025-01-22T02:51:14.877Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-01-22T02:51:20.250Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-01-22T02:51:20.250Z] Training: 60056, validation: 20285, test: 19854
[2025-01-22T02:51:20.250Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-01-22T02:51:21.204Z] GC before operation: completed in 289.799 ms, heap usage 134.306 MB -> 25.964 MB.
[2025-01-22T02:51:27.323Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-22T02:51:30.349Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-22T02:51:33.364Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-22T02:51:36.394Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-22T02:51:38.380Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-22T02:51:39.338Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-22T02:51:41.290Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-22T02:51:43.242Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-22T02:51:43.242Z] 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.
[2025-01-22T02:51:43.242Z] The best model improves the baseline by 14.52%.
[2025-01-22T02:51:43.242Z] Movies recommended for you:
[2025-01-22T02:51:43.242Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-22T02:51:43.242Z] There is no way to check that no silent failure occurred.
[2025-01-22T02:51:43.242Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (22875.144 ms) ======
[2025-01-22T02:51:43.242Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-01-22T02:51:44.197Z] GC before operation: completed in 337.674 ms, heap usage 82.454 MB -> 41.690 MB.
[2025-01-22T02:51:46.191Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-22T02:51:49.209Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-22T02:51:51.161Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-22T02:51:54.172Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-22T02:51:55.126Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-22T02:51:57.093Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-22T02:51:58.047Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-22T02:52:00.004Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-22T02:52:00.004Z] 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.
[2025-01-22T02:52:00.004Z] The best model improves the baseline by 14.52%.
[2025-01-22T02:52:00.955Z] Movies recommended for you:
[2025-01-22T02:52:00.955Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-22T02:52:00.955Z] There is no way to check that no silent failure occurred.
[2025-01-22T02:52:00.955Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (16578.789 ms) ======
[2025-01-22T02:52:00.955Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-01-22T02:52:00.955Z] GC before operation: completed in 230.175 ms, heap usage 335.963 MB -> 41.238 MB.
[2025-01-22T02:52:02.950Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-22T02:52:04.905Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-22T02:52:07.921Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-22T02:52:09.873Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-22T02:52:11.843Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-22T02:52:12.811Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-22T02:52:13.785Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-22T02:52:15.802Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-22T02:52:15.802Z] 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.
[2025-01-22T02:52:15.802Z] The best model improves the baseline by 14.52%.
[2025-01-22T02:52:15.802Z] Movies recommended for you:
[2025-01-22T02:52:15.802Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-22T02:52:15.802Z] There is no way to check that no silent failure occurred.
[2025-01-22T02:52:15.802Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (15167.490 ms) ======
[2025-01-22T02:52:15.802Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-01-22T02:52:15.802Z] GC before operation: completed in 233.694 ms, heap usage 69.832 MB -> 40.934 MB.
[2025-01-22T02:52:18.827Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-22T02:52:20.831Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-22T02:52:22.823Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-22T02:52:24.840Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-22T02:52:26.798Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-22T02:52:27.750Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-22T02:52:30.294Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-22T02:52:30.294Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-22T02:52:31.246Z] 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.
[2025-01-22T02:52:31.246Z] The best model improves the baseline by 14.52%.
[2025-01-22T02:52:31.246Z] Movies recommended for you:
[2025-01-22T02:52:31.246Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-22T02:52:31.246Z] There is no way to check that no silent failure occurred.
[2025-01-22T02:52:31.246Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (14999.352 ms) ======
[2025-01-22T02:52:31.246Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-01-22T02:52:31.246Z] GC before operation: completed in 164.415 ms, heap usage 95.614 MB -> 43.538 MB.
[2025-01-22T02:52:33.198Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-22T02:52:36.213Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-22T02:52:38.172Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-22T02:52:40.129Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-22T02:52:41.089Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-22T02:52:43.058Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-22T02:52:44.019Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-22T02:52:45.985Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-22T02:52:45.985Z] 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.
[2025-01-22T02:52:45.985Z] The best model improves the baseline by 14.52%.
[2025-01-22T02:52:45.985Z] Movies recommended for you:
[2025-01-22T02:52:45.985Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-22T02:52:45.985Z] There is no way to check that no silent failure occurred.
[2025-01-22T02:52:45.985Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (14665.133 ms) ======
[2025-01-22T02:52:45.985Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-01-22T02:52:45.985Z] GC before operation: completed in 176.097 ms, heap usage 122.542 MB -> 41.719 MB.
[2025-01-22T02:52:47.963Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-22T02:52:49.963Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-22T02:52:53.024Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-22T02:52:54.979Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-22T02:52:55.934Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-22T02:52:56.884Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-22T02:52:58.842Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-22T02:52:59.807Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-22T02:53:00.776Z] 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.
[2025-01-22T02:53:00.776Z] The best model improves the baseline by 14.52%.
[2025-01-22T02:53:00.776Z] Movies recommended for you:
[2025-01-22T02:53:00.776Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-22T02:53:00.776Z] There is no way to check that no silent failure occurred.
[2025-01-22T02:53:00.776Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (14321.866 ms) ======
[2025-01-22T02:53:00.776Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-01-22T02:53:00.776Z] GC before operation: completed in 149.151 ms, heap usage 146.714 MB -> 43.334 MB.
[2025-01-22T02:53:02.753Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-22T02:53:04.707Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-22T02:53:06.662Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-22T02:53:09.692Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-22T02:53:10.642Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-22T02:53:11.593Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-22T02:53:13.583Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-22T02:53:14.542Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-22T02:53:14.542Z] 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.
[2025-01-22T02:53:14.542Z] The best model improves the baseline by 14.52%.
[2025-01-22T02:53:14.542Z] Movies recommended for you:
[2025-01-22T02:53:14.542Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-22T02:53:14.542Z] There is no way to check that no silent failure occurred.
[2025-01-22T02:53:14.542Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (14335.456 ms) ======
[2025-01-22T02:53:14.542Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-01-22T02:53:15.497Z] GC before operation: completed in 183.066 ms, heap usage 122.834 MB -> 41.766 MB.
[2025-01-22T02:53:17.450Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-22T02:53:19.412Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-22T02:53:21.435Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-22T02:53:23.389Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-22T02:53:24.338Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-22T02:53:26.290Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-22T02:53:27.241Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-22T02:53:29.201Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-22T02:53:29.201Z] 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.
[2025-01-22T02:53:29.201Z] The best model improves the baseline by 14.52%.
[2025-01-22T02:53:29.201Z] Movies recommended for you:
[2025-01-22T02:53:29.201Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-22T02:53:29.201Z] There is no way to check that no silent failure occurred.
[2025-01-22T02:53:29.201Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (14078.965 ms) ======
[2025-01-22T02:53:29.201Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-01-22T02:53:29.201Z] GC before operation: completed in 153.659 ms, heap usage 78.283 MB -> 42.030 MB.
[2025-01-22T02:53:31.033Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-22T02:53:32.998Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-22T02:53:36.011Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-22T02:53:37.964Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-22T02:53:38.914Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-22T02:53:39.866Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-22T02:53:41.823Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-22T02:53:42.777Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-22T02:53:42.777Z] 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.
[2025-01-22T02:53:42.777Z] The best model improves the baseline by 14.52%.
[2025-01-22T02:53:42.777Z] Movies recommended for you:
[2025-01-22T02:53:42.777Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-22T02:53:42.777Z] There is no way to check that no silent failure occurred.
[2025-01-22T02:53:42.777Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (13835.647 ms) ======
[2025-01-22T02:53:42.777Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-01-22T02:53:43.733Z] GC before operation: completed in 138.889 ms, heap usage 90.729 MB -> 43.870 MB.
[2025-01-22T02:53:45.688Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-22T02:53:47.639Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-22T02:53:49.595Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-22T02:53:51.551Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-22T02:53:53.503Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-22T02:53:54.458Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-22T02:53:55.416Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-22T02:53:56.383Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-22T02:53:57.345Z] 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.
[2025-01-22T02:53:57.345Z] The best model improves the baseline by 14.52%.
[2025-01-22T02:53:57.345Z] Movies recommended for you:
[2025-01-22T02:53:57.345Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-22T02:53:57.345Z] There is no way to check that no silent failure occurred.
[2025-01-22T02:53:57.345Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (13929.471 ms) ======
[2025-01-22T02:53:57.345Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-01-22T02:53:57.345Z] GC before operation: completed in 204.565 ms, heap usage 86.745 MB -> 41.956 MB.
[2025-01-22T02:53:59.315Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-22T02:54:01.267Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-22T02:54:03.305Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-22T02:54:05.305Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-22T02:54:07.275Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-22T02:54:08.246Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-22T02:54:09.204Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-22T02:54:11.157Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-22T02:54:11.157Z] 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.
[2025-01-22T02:54:11.157Z] The best model improves the baseline by 14.52%.
[2025-01-22T02:54:11.157Z] Movies recommended for you:
[2025-01-22T02:54:11.157Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-22T02:54:11.157Z] There is no way to check that no silent failure occurred.
[2025-01-22T02:54:11.158Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (13754.214 ms) ======
[2025-01-22T02:54:11.158Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-01-22T02:54:11.158Z] GC before operation: completed in 148.768 ms, heap usage 300.264 MB -> 42.187 MB.
[2025-01-22T02:54:13.115Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-22T02:54:16.128Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-22T02:54:18.078Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-22T02:54:20.031Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-22T02:54:20.980Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-22T02:54:22.930Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-22T02:54:23.879Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-22T02:54:24.829Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-22T02:54:25.777Z] 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.
[2025-01-22T02:54:25.777Z] The best model improves the baseline by 14.52%.
[2025-01-22T02:54:25.777Z] Movies recommended for you:
[2025-01-22T02:54:25.777Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-22T02:54:25.777Z] There is no way to check that no silent failure occurred.
[2025-01-22T02:54:25.777Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (14084.495 ms) ======
[2025-01-22T02:54:25.777Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-01-22T02:54:25.777Z] GC before operation: completed in 150.826 ms, heap usage 79.295 MB -> 41.828 MB.
[2025-01-22T02:54:27.752Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-22T02:54:30.722Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-22T02:54:31.915Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-22T02:54:33.901Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-22T02:54:34.854Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-22T02:54:36.829Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-22T02:54:37.780Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-22T02:54:38.731Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-22T02:54:39.683Z] 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.
[2025-01-22T02:54:39.683Z] The best model improves the baseline by 14.52%.
[2025-01-22T02:54:39.683Z] Movies recommended for you:
[2025-01-22T02:54:39.683Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-22T02:54:39.683Z] There is no way to check that no silent failure occurred.
[2025-01-22T02:54:39.683Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (13775.400 ms) ======
[2025-01-22T02:54:39.683Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-01-22T02:54:39.683Z] GC before operation: completed in 126.478 ms, heap usage 359.712 MB -> 42.792 MB.
[2025-01-22T02:54:41.635Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-22T02:54:43.587Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-22T02:54:45.546Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-22T02:54:47.498Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-22T02:54:48.448Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-22T02:54:50.400Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-22T02:54:51.358Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-22T02:54:52.318Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-22T02:54:53.303Z] 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.
[2025-01-22T02:54:53.303Z] The best model improves the baseline by 14.52%.
[2025-01-22T02:54:53.303Z] Movies recommended for you:
[2025-01-22T02:54:53.303Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-22T02:54:53.303Z] There is no way to check that no silent failure occurred.
[2025-01-22T02:54:53.303Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (13460.446 ms) ======
[2025-01-22T02:54:53.303Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-01-22T02:54:53.303Z] GC before operation: completed in 147.621 ms, heap usage 131.368 MB -> 41.791 MB.
[2025-01-22T02:54:55.257Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-22T02:54:57.208Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-22T02:54:59.157Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-22T02:55:01.105Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-22T02:55:02.056Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-22T02:55:04.008Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-22T02:55:04.956Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-22T02:55:05.904Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-22T02:55:06.859Z] 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.
[2025-01-22T02:55:06.859Z] The best model improves the baseline by 14.52%.
[2025-01-22T02:55:06.859Z] Movies recommended for you:
[2025-01-22T02:55:06.859Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-22T02:55:06.859Z] There is no way to check that no silent failure occurred.
[2025-01-22T02:55:06.859Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (13471.939 ms) ======
[2025-01-22T02:55:06.859Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-01-22T02:55:06.859Z] GC before operation: completed in 125.878 ms, heap usage 141.473 MB -> 43.911 MB.
[2025-01-22T02:55:08.812Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-22T02:55:10.763Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-22T02:55:12.719Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-22T02:55:14.673Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-22T02:55:15.628Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-22T02:55:17.580Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-22T02:55:18.531Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-22T02:55:19.480Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-22T02:55:20.430Z] 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.
[2025-01-22T02:55:20.430Z] The best model improves the baseline by 14.52%.
[2025-01-22T02:55:20.430Z] Movies recommended for you:
[2025-01-22T02:55:20.430Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-22T02:55:20.430Z] There is no way to check that no silent failure occurred.
[2025-01-22T02:55:20.430Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (13550.110 ms) ======
[2025-01-22T02:55:20.430Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-01-22T02:55:20.430Z] GC before operation: completed in 140.032 ms, heap usage 79.020 MB -> 41.989 MB.
[2025-01-22T02:55:22.384Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-22T02:55:24.344Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-22T02:55:26.308Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-22T02:55:28.268Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-22T02:55:30.978Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-22T02:55:30.979Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-22T02:55:32.959Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-22T02:55:33.940Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-22T02:55:33.940Z] 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.
[2025-01-22T02:55:33.940Z] The best model improves the baseline by 14.52%.
[2025-01-22T02:55:33.940Z] Movies recommended for you:
[2025-01-22T02:55:33.940Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-22T02:55:33.940Z] There is no way to check that no silent failure occurred.
[2025-01-22T02:55:33.940Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (13681.243 ms) ======
[2025-01-22T02:55:33.940Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-01-22T02:55:33.940Z] GC before operation: completed in 130.760 ms, heap usage 127.963 MB -> 42.670 MB.
[2025-01-22T02:55:35.938Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-22T02:55:37.890Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-22T02:55:39.840Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-22T02:55:41.816Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-22T02:55:43.811Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-22T02:55:44.767Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-22T02:55:45.731Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-22T02:55:47.683Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-22T02:55:47.683Z] 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.
[2025-01-22T02:55:47.683Z] The best model improves the baseline by 14.52%.
[2025-01-22T02:55:47.683Z] Movies recommended for you:
[2025-01-22T02:55:47.683Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-22T02:55:47.683Z] There is no way to check that no silent failure occurred.
[2025-01-22T02:55:47.683Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (13510.345 ms) ======
[2025-01-22T02:55:47.683Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-01-22T02:55:47.683Z] GC before operation: completed in 148.508 ms, heap usage 139.157 MB -> 45.834 MB.
[2025-01-22T02:55:49.632Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-22T02:55:51.606Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-22T02:55:53.557Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-22T02:55:55.513Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-22T02:55:57.463Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-22T02:55:58.412Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-22T02:55:59.361Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-22T02:56:01.310Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-22T02:56:01.310Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-01-22T02:56:01.310Z] The best model improves the baseline by 14.52%.
[2025-01-22T02:56:01.310Z] Movies recommended for you:
[2025-01-22T02:56:01.310Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-22T02:56:01.310Z] There is no way to check that no silent failure occurred.
[2025-01-22T02:56:01.310Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (13564.796 ms) ======
[2025-01-22T02:56:01.310Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-01-22T02:56:01.310Z] GC before operation: completed in 152.438 ms, heap usage 74.883 MB -> 42.097 MB.
[2025-01-22T02:56:03.261Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-22T02:56:05.210Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-22T02:56:08.221Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-22T02:56:09.171Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-22T02:56:11.121Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-22T02:56:12.072Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-22T02:56:13.026Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-22T02:56:14.977Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-22T02:56:14.977Z] 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.
[2025-01-22T02:56:14.977Z] The best model improves the baseline by 14.52%.
[2025-01-22T02:56:14.977Z] Movies recommended for you:
[2025-01-22T02:56:14.977Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-22T02:56:14.977Z] There is no way to check that no silent failure occurred.
[2025-01-22T02:56:14.977Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (13500.011 ms) ======
[2025-01-22T02:56:15.933Z] -----------------------------------
[2025-01-22T02:56:15.933Z] renaissance-movie-lens_0_PASSED
[2025-01-22T02:56:15.933Z] -----------------------------------
[2025-01-22T02:56:15.933Z]
[2025-01-22T02:56:15.933Z] TEST TEARDOWN:
[2025-01-22T02:56:15.933Z] Nothing to be done for teardown.
[2025-01-22T02:56:15.933Z] renaissance-movie-lens_0 Finish Time: Wed Jan 22 02:56:15 2025 Epoch Time (ms): 1737514575085