renaissance-movie-lens_0
[2024-11-20T17:18:51.447Z] Running test renaissance-movie-lens_0 ...
[2024-11-20T17:18:51.447Z] ===============================================
[2024-11-20T17:18:51.447Z] renaissance-movie-lens_0 Start Time: Wed Nov 20 11:58:54 2024 Epoch Time (ms): 1732125534113
[2024-11-20T17:18:51.447Z] variation: NoOptions
[2024-11-20T17:18:51.447Z] JVM_OPTIONS:
[2024-11-20T17:18:51.447Z] { \
[2024-11-20T17:18:51.447Z] echo ""; echo "TEST SETUP:"; \
[2024-11-20T17:18:51.447Z] echo "Nothing to be done for setup."; \
[2024-11-20T17:18:51.447Z] mkdir -p "/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_sparcv9_solaris/aqa-tests/TKG/../TKG/output_17321231409107/renaissance-movie-lens_0"; \
[2024-11-20T17:18:51.447Z] cd "/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_sparcv9_solaris/aqa-tests/TKG/../TKG/output_17321231409107/renaissance-movie-lens_0"; \
[2024-11-20T17:18:51.447Z] echo ""; echo "TESTING:"; \
[2024-11-20T17:18:51.447Z] "/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_sparcv9_solaris/jdkbinary/j2sdk-image/bin/java" -jar "/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_sparcv9_solaris/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_sparcv9_solaris/aqa-tests/TKG/../TKG/output_17321231409107/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-11-20T17:18:51.447Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_sparcv9_solaris/aqa-tests/TKG/..; rm -f -r "/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_sparcv9_solaris/aqa-tests/TKG/../TKG/output_17321231409107/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-11-20T17:18:51.447Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-11-20T17:18:51.447Z] echo "Nothing to be done for teardown."; \
[2024-11-20T17:18:51.447Z] } 2>&1 | tee -a "/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_sparcv9_solaris/aqa-tests/TKG/../TKG/output_17321231409107/TestTargetResult";
[2024-11-20T17:18:51.447Z]
[2024-11-20T17:18:51.447Z] TEST SETUP:
[2024-11-20T17:18:51.447Z] Nothing to be done for setup.
[2024-11-20T17:18:51.447Z]
[2024-11-20T17:18:51.447Z] TESTING:
[2024-11-20T17:19:15.123Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-11-20T17:19:17.952Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2024-11-20T17:19:28.163Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-11-20T17:19:28.789Z] Training: 60056, validation: 20285, test: 19854
[2024-11-20T17:19:28.789Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-11-20T17:19:29.412Z] GC before operation: completed in 444.371 ms, heap usage 48.665 MB -> 27.297 MB.
[2024-11-20T17:19:46.556Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-20T17:19:55.108Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-20T17:20:03.652Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-20T17:20:14.145Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-20T17:20:19.991Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-20T17:20:23.715Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-20T17:20:29.549Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-20T17:20:33.272Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-20T17:20:33.895Z] 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.
[2024-11-20T17:20:33.895Z] The best model improves the baseline by 14.52%.
[2024-11-20T17:20:34.518Z] Movies recommended for you:
[2024-11-20T17:20:34.518Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-20T17:20:34.518Z] There is no way to check that no silent failure occurred.
[2024-11-20T17:20:34.518Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (65197.567 ms) ======
[2024-11-20T17:20:34.518Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-11-20T17:20:35.142Z] GC before operation: completed in 686.340 ms, heap usage 479.160 MB -> 49.021 MB.
[2024-11-20T17:20:42.286Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-20T17:20:52.628Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-20T17:21:02.852Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-20T17:21:11.411Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-20T17:21:16.127Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-20T17:21:19.861Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-20T17:21:24.575Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-20T17:21:29.367Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-20T17:21:30.737Z] 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.
[2024-11-20T17:21:30.737Z] The best model improves the baseline by 14.52%.
[2024-11-20T17:21:31.360Z] Movies recommended for you:
[2024-11-20T17:21:31.360Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-20T17:21:31.360Z] There is no way to check that no silent failure occurred.
[2024-11-20T17:21:31.360Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (55882.355 ms) ======
[2024-11-20T17:21:31.360Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-11-20T17:21:31.360Z] GC before operation: completed in 506.275 ms, heap usage 161.809 MB -> 42.525 MB.
[2024-11-20T17:21:38.492Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-20T17:21:45.604Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-20T17:21:51.457Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-20T17:21:57.293Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-20T17:22:01.042Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-20T17:22:04.764Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-20T17:22:09.487Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-20T17:22:12.317Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-20T17:22:13.612Z] 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.
[2024-11-20T17:22:13.612Z] The best model improves the baseline by 14.52%.
[2024-11-20T17:22:13.612Z] Movies recommended for you:
[2024-11-20T17:22:13.612Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-20T17:22:13.612Z] There is no way to check that no silent failure occurred.
[2024-11-20T17:22:13.612Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (42026.248 ms) ======
[2024-11-20T17:22:13.612Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-11-20T17:22:14.235Z] GC before operation: completed in 496.504 ms, heap usage 681.729 MB -> 47.407 MB.
[2024-11-20T17:22:20.075Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-20T17:22:25.912Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-20T17:22:33.013Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-20T17:22:40.119Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-20T17:22:42.953Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-20T17:22:46.685Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-20T17:22:50.411Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-20T17:22:54.136Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-20T17:22:54.763Z] 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.
[2024-11-20T17:22:54.763Z] The best model improves the baseline by 14.52%.
[2024-11-20T17:22:54.763Z] Movies recommended for you:
[2024-11-20T17:22:54.763Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-20T17:22:54.763Z] There is no way to check that no silent failure occurred.
[2024-11-20T17:22:54.763Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (40844.777 ms) ======
[2024-11-20T17:22:54.763Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-11-20T17:22:55.385Z] GC before operation: completed in 487.480 ms, heap usage 658.459 MB -> 48.010 MB.
[2024-11-20T17:23:01.357Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-20T17:23:07.245Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-20T17:23:14.347Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-20T17:23:20.195Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-20T17:23:23.948Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-20T17:23:27.670Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-20T17:23:32.395Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-20T17:23:35.232Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-20T17:23:35.855Z] 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.
[2024-11-20T17:23:35.855Z] The best model improves the baseline by 14.52%.
[2024-11-20T17:23:36.476Z] Movies recommended for you:
[2024-11-20T17:23:36.476Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-20T17:23:36.476Z] There is no way to check that no silent failure occurred.
[2024-11-20T17:23:36.476Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (40943.358 ms) ======
[2024-11-20T17:23:36.476Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-11-20T17:23:37.102Z] GC before operation: completed in 437.808 ms, heap usage 653.008 MB -> 48.067 MB.
[2024-11-20T17:23:42.945Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-20T17:23:47.665Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-20T17:23:53.512Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-20T17:23:59.375Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-20T17:24:03.113Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-20T17:24:06.132Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-20T17:24:09.863Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-20T17:24:13.591Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-20T17:24:14.218Z] 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.
[2024-11-20T17:24:14.218Z] The best model improves the baseline by 14.52%.
[2024-11-20T17:24:14.218Z] Movies recommended for you:
[2024-11-20T17:24:14.218Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-20T17:24:14.218Z] There is no way to check that no silent failure occurred.
[2024-11-20T17:24:14.218Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (37567.305 ms) ======
[2024-11-20T17:24:14.218Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-11-20T17:24:14.841Z] GC before operation: completed in 430.027 ms, heap usage 636.414 MB -> 47.975 MB.
[2024-11-20T17:24:20.687Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-20T17:24:26.525Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-20T17:24:32.368Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-20T17:24:37.098Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-20T17:24:40.886Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-20T17:24:44.612Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-20T17:24:47.447Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-20T17:24:51.181Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-20T17:24:51.804Z] 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.
[2024-11-20T17:24:51.804Z] The best model improves the baseline by 14.52%.
[2024-11-20T17:24:51.804Z] Movies recommended for you:
[2024-11-20T17:24:51.804Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-20T17:24:51.804Z] There is no way to check that no silent failure occurred.
[2024-11-20T17:24:51.805Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (37148.072 ms) ======
[2024-11-20T17:24:51.805Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-11-20T17:24:52.432Z] GC before operation: completed in 397.159 ms, heap usage 625.048 MB -> 48.041 MB.
[2024-11-20T17:24:58.270Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-20T17:25:03.242Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-20T17:25:10.341Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-20T17:25:15.056Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-20T17:25:18.785Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-20T17:25:21.614Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-20T17:25:25.341Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-20T17:25:29.101Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-20T17:25:29.722Z] 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.
[2024-11-20T17:25:29.722Z] The best model improves the baseline by 14.52%.
[2024-11-20T17:25:29.722Z] Movies recommended for you:
[2024-11-20T17:25:29.722Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-20T17:25:29.722Z] There is no way to check that no silent failure occurred.
[2024-11-20T17:25:29.722Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (37430.129 ms) ======
[2024-11-20T17:25:29.722Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-11-20T17:25:30.344Z] GC before operation: completed in 392.915 ms, heap usage 639.018 MB -> 48.485 MB.
[2024-11-20T17:25:36.178Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-20T17:25:42.022Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-20T17:25:47.854Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-20T17:25:52.578Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-20T17:25:56.302Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-20T17:25:59.149Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-20T17:26:02.885Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-20T17:26:05.853Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-20T17:26:06.478Z] 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.
[2024-11-20T17:26:07.100Z] The best model improves the baseline by 14.52%.
[2024-11-20T17:26:07.100Z] Movies recommended for you:
[2024-11-20T17:26:07.100Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-20T17:26:07.100Z] There is no way to check that no silent failure occurred.
[2024-11-20T17:26:07.100Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (36872.643 ms) ======
[2024-11-20T17:26:07.100Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-11-20T17:26:07.772Z] GC before operation: completed in 520.727 ms, heap usage 634.643 MB -> 48.250 MB.
[2024-11-20T17:26:13.609Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-20T17:26:18.344Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-20T17:26:25.453Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-20T17:26:30.174Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-20T17:26:33.896Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-20T17:26:36.728Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-20T17:26:40.452Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-20T17:26:44.183Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-20T17:26:44.806Z] 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.
[2024-11-20T17:26:44.806Z] The best model improves the baseline by 14.52%.
[2024-11-20T17:26:44.806Z] Movies recommended for you:
[2024-11-20T17:26:44.806Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-20T17:26:44.806Z] There is no way to check that no silent failure occurred.
[2024-11-20T17:26:44.806Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (37321.219 ms) ======
[2024-11-20T17:26:44.806Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-11-20T17:26:45.432Z] GC before operation: completed in 474.407 ms, heap usage 627.171 MB -> 48.243 MB.
[2024-11-20T17:26:51.266Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-20T17:26:55.984Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-20T17:27:03.092Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-20T17:27:07.436Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-20T17:27:11.189Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-20T17:27:14.925Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-20T17:27:18.643Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-20T17:27:21.478Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-20T17:27:22.101Z] 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.
[2024-11-20T17:27:22.101Z] The best model improves the baseline by 14.52%.
[2024-11-20T17:27:22.101Z] Movies recommended for you:
[2024-11-20T17:27:22.101Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-20T17:27:22.101Z] There is no way to check that no silent failure occurred.
[2024-11-20T17:27:22.101Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (37016.537 ms) ======
[2024-11-20T17:27:22.101Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-11-20T17:27:22.722Z] GC before operation: completed in 363.808 ms, heap usage 631.282 MB -> 47.932 MB.
[2024-11-20T17:27:28.559Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-20T17:27:33.278Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-20T17:27:39.114Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-20T17:27:45.149Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-20T17:27:47.983Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-20T17:27:51.701Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-20T17:27:55.425Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-20T17:27:58.257Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-20T17:27:58.881Z] 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.
[2024-11-20T17:27:58.881Z] The best model improves the baseline by 14.52%.
[2024-11-20T17:27:59.505Z] Movies recommended for you:
[2024-11-20T17:27:59.505Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-20T17:27:59.505Z] There is no way to check that no silent failure occurred.
[2024-11-20T17:27:59.505Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (36537.212 ms) ======
[2024-11-20T17:27:59.505Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-11-20T17:27:59.505Z] GC before operation: completed in 431.877 ms, heap usage 645.314 MB -> 48.294 MB.
[2024-11-20T17:28:05.472Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-20T17:28:11.313Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-20T17:28:17.159Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-20T17:28:21.897Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-20T17:28:25.623Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-20T17:28:29.349Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-20T17:28:32.185Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-20T17:28:35.910Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-20T17:28:36.532Z] 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.
[2024-11-20T17:28:37.155Z] The best model improves the baseline by 14.52%.
[2024-11-20T17:28:37.155Z] Movies recommended for you:
[2024-11-20T17:28:37.155Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-20T17:28:37.155Z] There is no way to check that no silent failure occurred.
[2024-11-20T17:28:37.155Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (37401.284 ms) ======
[2024-11-20T17:28:37.155Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-11-20T17:28:37.829Z] GC before operation: completed in 498.728 ms, heap usage 648.702 MB -> 48.574 MB.
[2024-11-20T17:28:43.664Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-20T17:28:48.386Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-20T17:28:54.220Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-20T17:29:00.066Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-20T17:29:03.787Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-20T17:29:06.999Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-20T17:29:10.748Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-20T17:29:13.580Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-20T17:29:14.203Z] 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.
[2024-11-20T17:29:14.203Z] The best model improves the baseline by 14.52%.
[2024-11-20T17:29:14.827Z] Movies recommended for you:
[2024-11-20T17:29:14.827Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-20T17:29:14.827Z] There is no way to check that no silent failure occurred.
[2024-11-20T17:29:14.827Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (36954.869 ms) ======
[2024-11-20T17:29:14.827Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-11-20T17:29:14.827Z] GC before operation: completed in 389.366 ms, heap usage 628.324 MB -> 48.025 MB.
[2024-11-20T17:29:20.662Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-20T17:29:25.380Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-20T17:29:31.241Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-20T17:29:37.083Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-20T17:29:40.807Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-20T17:29:43.640Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-20T17:29:47.372Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-20T17:29:50.205Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-20T17:29:50.830Z] 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.
[2024-11-20T17:29:50.830Z] The best model improves the baseline by 14.52%.
[2024-11-20T17:29:51.455Z] Movies recommended for you:
[2024-11-20T17:29:51.455Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-20T17:29:51.455Z] There is no way to check that no silent failure occurred.
[2024-11-20T17:29:51.455Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (36264.733 ms) ======
[2024-11-20T17:29:51.455Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-11-20T17:29:51.455Z] GC before operation: completed in 417.547 ms, heap usage 636.834 MB -> 48.415 MB.
[2024-11-20T17:29:57.298Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-20T17:30:03.169Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-20T17:30:09.126Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-20T17:30:13.846Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-20T17:30:17.569Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-20T17:30:20.415Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-20T17:30:24.137Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-20T17:30:27.870Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-20T17:30:28.493Z] 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.
[2024-11-20T17:30:28.493Z] The best model improves the baseline by 14.52%.
[2024-11-20T17:30:28.493Z] Movies recommended for you:
[2024-11-20T17:30:28.493Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-20T17:30:28.493Z] There is no way to check that no silent failure occurred.
[2024-11-20T17:30:28.493Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (36833.559 ms) ======
[2024-11-20T17:30:28.493Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-11-20T17:30:29.118Z] GC before operation: completed in 360.086 ms, heap usage 636.843 MB -> 48.497 MB.
[2024-11-20T17:30:34.955Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-20T17:30:39.675Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-20T17:30:45.523Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-20T17:30:51.355Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-20T17:30:54.187Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-20T17:30:57.916Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-20T17:31:00.747Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-20T17:31:04.471Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-20T17:31:05.094Z] 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.
[2024-11-20T17:31:05.094Z] The best model improves the baseline by 14.52%.
[2024-11-20T17:31:05.094Z] Movies recommended for you:
[2024-11-20T17:31:05.094Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-20T17:31:05.094Z] There is no way to check that no silent failure occurred.
[2024-11-20T17:31:05.094Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (36319.641 ms) ======
[2024-11-20T17:31:05.094Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-11-20T17:31:05.730Z] GC before operation: completed in 544.850 ms, heap usage 638.286 MB -> 48.343 MB.
[2024-11-20T17:31:11.582Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-20T17:31:17.420Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-20T17:31:23.258Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-20T17:31:27.977Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-20T17:31:31.715Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-20T17:31:34.553Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-20T17:31:38.279Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-20T17:31:42.000Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-20T17:31:42.000Z] 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.
[2024-11-20T17:31:42.000Z] The best model improves the baseline by 14.52%.
[2024-11-20T17:31:42.622Z] Movies recommended for you:
[2024-11-20T17:31:42.622Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-20T17:31:42.622Z] There is no way to check that no silent failure occurred.
[2024-11-20T17:31:42.622Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (36704.737 ms) ======
[2024-11-20T17:31:42.622Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-11-20T17:31:43.245Z] GC before operation: completed in 502.538 ms, heap usage 651.577 MB -> 48.463 MB.
[2024-11-20T17:31:47.965Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-20T17:31:53.800Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-20T17:31:59.636Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-20T17:32:04.351Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-20T17:32:08.222Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-20T17:32:11.952Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-20T17:32:14.785Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-20T17:32:18.515Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-20T17:32:19.136Z] 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.
[2024-11-20T17:32:19.136Z] The best model improves the baseline by 14.52%.
[2024-11-20T17:32:19.136Z] Movies recommended for you:
[2024-11-20T17:32:19.136Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-20T17:32:19.136Z] There is no way to check that no silent failure occurred.
[2024-11-20T17:32:19.136Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (36246.422 ms) ======
[2024-11-20T17:32:19.136Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-11-20T17:32:19.764Z] GC before operation: completed in 362.313 ms, heap usage 652.896 MB -> 48.686 MB.
[2024-11-20T17:32:24.480Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-20T17:32:30.314Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-20T17:32:36.148Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-20T17:32:42.026Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-20T17:32:44.857Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-20T17:32:47.747Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-20T17:32:51.465Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-20T17:32:55.193Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-20T17:32:55.193Z] 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.
[2024-11-20T17:32:55.815Z] The best model improves the baseline by 14.52%.
[2024-11-20T17:32:55.815Z] Movies recommended for you:
[2024-11-20T17:32:55.815Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-20T17:32:55.815Z] There is no way to check that no silent failure occurred.
[2024-11-20T17:32:55.815Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (36179.309 ms) ======
[2024-11-20T17:32:56.438Z] -----------------------------------
[2024-11-20T17:32:56.438Z] renaissance-movie-lens_0_PASSED
[2024-11-20T17:32:56.438Z] -----------------------------------
[2024-11-20T17:32:56.438Z]
[2024-11-20T17:32:56.438Z] TEST TEARDOWN:
[2024-11-20T17:32:56.438Z] Nothing to be done for teardown.
[2024-11-20T17:32:56.438Z] renaissance-movie-lens_0 Finish Time: Wed Nov 20 12:12:59 2024 Epoch Time (ms): 1732126379345