renaissance-movie-lens_0
[2024-09-02T11:39:44.074Z] Running test renaissance-movie-lens_0 ...
[2024-09-02T11:39:44.074Z] ===============================================
[2024-09-02T11:39:44.074Z] renaissance-movie-lens_0 Start Time: Mon Sep 2 07:21:15 2024 Epoch Time (ms): 1725279675542
[2024-09-02T11:39:44.074Z] variation: NoOptions
[2024-09-02T11:39:44.074Z] JVM_OPTIONS:
[2024-09-02T11:39:44.074Z] { \
[2024-09-02T11:39:44.074Z] echo ""; echo "TEST SETUP:"; \
[2024-09-02T11:39:44.074Z] echo "Nothing to be done for setup."; \
[2024-09-02T11:39:44.074Z] mkdir -p "/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_sparcv9_solaris/aqa-tests/TKG/../TKG/output_172527720782/renaissance-movie-lens_0"; \
[2024-09-02T11:39:44.074Z] cd "/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_sparcv9_solaris/aqa-tests/TKG/../TKG/output_172527720782/renaissance-movie-lens_0"; \
[2024-09-02T11:39:44.074Z] echo ""; echo "TESTING:"; \
[2024-09-02T11:39:44.074Z] "/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_172527720782/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-09-02T11:39:44.074Z] 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_172527720782/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-09-02T11:39:44.074Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-09-02T11:39:44.074Z] echo "Nothing to be done for teardown."; \
[2024-09-02T11:39:44.075Z] } 2>&1 | tee -a "/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_sparcv9_solaris/aqa-tests/TKG/../TKG/output_172527720782/TestTargetResult";
[2024-09-02T11:39:44.075Z]
[2024-09-02T11:39:44.075Z] TEST SETUP:
[2024-09-02T11:39:44.075Z] Nothing to be done for setup.
[2024-09-02T11:39:44.075Z]
[2024-09-02T11:39:44.075Z] TESTING:
[2024-09-02T11:39:51.132Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-09-02T11:39:56.934Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2024-09-02T11:40:09.168Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-09-02T11:40:09.168Z] Training: 60056, validation: 20285, test: 19854
[2024-09-02T11:40:09.168Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-09-02T11:40:09.788Z] GC before operation: completed in 548.060 ms, heap usage 123.948 MB -> 27.542 MB.
[2024-09-02T11:40:29.830Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-02T11:40:41.741Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-02T11:40:59.564Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-02T11:41:09.885Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-02T11:41:15.682Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-02T11:41:19.404Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-02T11:41:25.195Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-02T11:41:28.888Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-02T11:41:29.505Z] 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.
[2024-09-02T11:41:29.505Z] The best model improves the baseline by 14.52%.
[2024-09-02T11:41:30.120Z] Movies recommended for you:
[2024-09-02T11:41:30.121Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-02T11:41:30.121Z] There is no way to check that no silent failure occurred.
[2024-09-02T11:41:30.121Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (80224.015 ms) ======
[2024-09-02T11:41:30.121Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-09-02T11:41:30.738Z] GC before operation: completed in 673.184 ms, heap usage 289.199 MB -> 56.599 MB.
[2024-09-02T11:41:37.802Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-02T11:41:44.923Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-02T11:41:51.845Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-02T11:41:58.894Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-02T11:42:02.583Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-02T11:42:06.284Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-02T11:42:11.008Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-02T11:42:14.703Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-02T11:42:15.320Z] 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.
[2024-09-02T11:42:15.936Z] The best model improves the baseline by 14.52%.
[2024-09-02T11:42:15.936Z] Movies recommended for you:
[2024-09-02T11:42:15.936Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-02T11:42:15.936Z] There is no way to check that no silent failure occurred.
[2024-09-02T11:42:15.936Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (45085.453 ms) ======
[2024-09-02T11:42:15.936Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-09-02T11:42:16.553Z] GC before operation: completed in 509.989 ms, heap usage 648.198 MB -> 47.247 MB.
[2024-09-02T11:42:22.341Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-02T11:42:29.397Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-02T11:42:36.446Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-02T11:42:42.242Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-02T11:42:45.052Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-02T11:42:50.130Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-02T11:42:52.943Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-02T11:42:56.661Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-02T11:42:57.277Z] 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.
[2024-09-02T11:42:57.277Z] The best model improves the baseline by 14.52%.
[2024-09-02T11:42:57.277Z] Movies recommended for you:
[2024-09-02T11:42:57.277Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-02T11:42:57.277Z] There is no way to check that no silent failure occurred.
[2024-09-02T11:42:57.277Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (41039.114 ms) ======
[2024-09-02T11:42:57.277Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-09-02T11:42:57.892Z] GC before operation: completed in 528.955 ms, heap usage 597.028 MB -> 47.286 MB.
[2024-09-02T11:43:03.679Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-02T11:43:09.484Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-02T11:43:16.559Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-02T11:43:23.611Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-02T11:43:27.301Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-02T11:43:30.996Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-02T11:43:34.692Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-02T11:43:37.508Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-02T11:43:38.125Z] 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.
[2024-09-02T11:43:38.742Z] The best model improves the baseline by 14.52%.
[2024-09-02T11:43:38.742Z] Movies recommended for you:
[2024-09-02T11:43:38.742Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-02T11:43:38.742Z] There is no way to check that no silent failure occurred.
[2024-09-02T11:43:38.742Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (40713.866 ms) ======
[2024-09-02T11:43:38.742Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-09-02T11:43:39.483Z] GC before operation: completed in 471.820 ms, heap usage 579.058 MB -> 47.454 MB.
[2024-09-02T11:43:45.295Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-02T11:43:51.873Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-02T11:43:57.662Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-02T11:44:04.730Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-02T11:44:07.553Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-02T11:44:11.263Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-02T11:44:14.961Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-02T11:44:18.671Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-02T11:44:19.289Z] 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.
[2024-09-02T11:44:19.289Z] The best model improves the baseline by 14.52%.
[2024-09-02T11:44:19.911Z] Movies recommended for you:
[2024-09-02T11:44:19.911Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-02T11:44:19.911Z] There is no way to check that no silent failure occurred.
[2024-09-02T11:44:19.911Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (40570.192 ms) ======
[2024-09-02T11:44:19.911Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-09-02T11:44:19.911Z] GC before operation: completed in 416.802 ms, heap usage 573.844 MB -> 47.676 MB.
[2024-09-02T11:44:25.718Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-02T11:44:31.539Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-02T11:44:37.372Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-02T11:44:43.174Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-02T11:44:46.021Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-02T11:44:50.284Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-02T11:44:53.193Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-02T11:44:56.903Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-02T11:44:56.903Z] 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.
[2024-09-02T11:44:56.903Z] The best model improves the baseline by 14.52%.
[2024-09-02T11:44:57.525Z] Movies recommended for you:
[2024-09-02T11:44:57.525Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-02T11:44:57.525Z] There is no way to check that no silent failure occurred.
[2024-09-02T11:44:57.525Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (37218.150 ms) ======
[2024-09-02T11:44:57.525Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-09-02T11:44:57.525Z] GC before operation: completed in 371.291 ms, heap usage 566.888 MB -> 47.606 MB.
[2024-09-02T11:45:03.339Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-02T11:45:09.148Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-02T11:45:14.953Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-02T11:45:19.643Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-02T11:45:23.345Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-02T11:45:27.040Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-02T11:45:29.873Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-02T11:45:33.565Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-02T11:45:34.180Z] 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.
[2024-09-02T11:45:34.180Z] The best model improves the baseline by 14.52%.
[2024-09-02T11:45:34.180Z] Movies recommended for you:
[2024-09-02T11:45:34.180Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-02T11:45:34.180Z] There is no way to check that no silent failure occurred.
[2024-09-02T11:45:34.180Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (36393.665 ms) ======
[2024-09-02T11:45:34.180Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-09-02T11:45:34.801Z] GC before operation: completed in 429.955 ms, heap usage 569.641 MB -> 47.779 MB.
[2024-09-02T11:45:40.612Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-02T11:45:45.307Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-02T11:45:51.487Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-02T11:45:57.303Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-02T11:46:00.122Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-02T11:46:03.823Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-02T11:46:07.528Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-02T11:46:10.348Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-02T11:46:10.983Z] 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.
[2024-09-02T11:46:10.983Z] The best model improves the baseline by 14.52%.
[2024-09-02T11:46:10.983Z] Movies recommended for you:
[2024-09-02T11:46:10.983Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-02T11:46:10.983Z] There is no way to check that no silent failure occurred.
[2024-09-02T11:46:10.983Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (36658.570 ms) ======
[2024-09-02T11:46:10.983Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-09-02T11:46:11.602Z] GC before operation: completed in 365.891 ms, heap usage 583.979 MB -> 48.089 MB.
[2024-09-02T11:46:17.429Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-02T11:46:23.235Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-02T11:46:29.037Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-02T11:46:33.722Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-02T11:46:37.432Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-02T11:46:40.245Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-02T11:46:43.945Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-02T11:46:48.138Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-02T11:46:49.117Z] 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.
[2024-09-02T11:46:49.117Z] The best model improves the baseline by 14.52%.
[2024-09-02T11:46:49.117Z] Movies recommended for you:
[2024-09-02T11:46:49.117Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-02T11:46:49.117Z] There is no way to check that no silent failure occurred.
[2024-09-02T11:46:49.117Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (36625.501 ms) ======
[2024-09-02T11:46:49.117Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-09-02T11:46:49.117Z] GC before operation: completed in 492.000 ms, heap usage 578.871 MB -> 47.863 MB.
[2024-09-02T11:46:53.809Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-02T11:46:59.619Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-02T11:47:05.422Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-02T11:47:11.233Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-02T11:47:14.052Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-02T11:47:17.766Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-02T11:47:21.464Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-02T11:47:24.281Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-02T11:47:24.903Z] 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.
[2024-09-02T11:47:24.903Z] The best model improves the baseline by 14.52%.
[2024-09-02T11:47:24.903Z] Movies recommended for you:
[2024-09-02T11:47:24.903Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-02T11:47:24.903Z] There is no way to check that no silent failure occurred.
[2024-09-02T11:47:24.903Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (36308.403 ms) ======
[2024-09-02T11:47:24.903Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-09-02T11:47:25.520Z] GC before operation: completed in 443.912 ms, heap usage 566.090 MB -> 48.002 MB.
[2024-09-02T11:47:31.325Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-02T11:47:36.016Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-02T11:47:43.091Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-02T11:47:49.195Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-02T11:47:51.205Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-02T11:47:54.904Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-02T11:47:57.713Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-02T11:48:01.413Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-02T11:48:02.031Z] 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.
[2024-09-02T11:48:02.031Z] The best model improves the baseline by 14.52%.
[2024-09-02T11:48:02.031Z] Movies recommended for you:
[2024-09-02T11:48:02.031Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-02T11:48:02.031Z] There is no way to check that no silent failure occurred.
[2024-09-02T11:48:02.031Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (36685.990 ms) ======
[2024-09-02T11:48:02.031Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-09-02T11:48:02.647Z] GC before operation: completed in 386.148 ms, heap usage 607.077 MB -> 50.243 MB.
[2024-09-02T11:48:08.443Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-02T11:48:13.137Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-02T11:48:18.937Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-02T11:48:24.733Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-02T11:48:27.546Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-02T11:48:30.358Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-02T11:48:34.060Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-02T11:48:37.768Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-02T11:48:37.768Z] 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.
[2024-09-02T11:48:38.390Z] The best model improves the baseline by 14.52%.
[2024-09-02T11:48:38.390Z] Movies recommended for you:
[2024-09-02T11:48:38.390Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-02T11:48:38.390Z] There is no way to check that no silent failure occurred.
[2024-09-02T11:48:38.390Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (35713.564 ms) ======
[2024-09-02T11:48:38.390Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-09-02T11:48:38.390Z] GC before operation: completed in 354.354 ms, heap usage 672.026 MB -> 48.468 MB.
[2024-09-02T11:48:44.609Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-02T11:48:49.356Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-02T11:48:55.166Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-02T11:49:00.976Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-02T11:49:04.672Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-02T11:49:08.375Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-02T11:49:11.186Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-02T11:49:14.885Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-02T11:49:15.502Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-09-02T11:49:15.502Z] The best model improves the baseline by 14.52%.
[2024-09-02T11:49:15.502Z] Movies recommended for you:
[2024-09-02T11:49:15.502Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-02T11:49:15.502Z] There is no way to check that no silent failure occurred.
[2024-09-02T11:49:15.502Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (36835.469 ms) ======
[2024-09-02T11:49:15.502Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-09-02T11:49:16.121Z] GC before operation: completed in 358.786 ms, heap usage 636.267 MB -> 48.657 MB.
[2024-09-02T11:49:21.932Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-02T11:49:26.628Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-02T11:49:32.431Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-02T11:49:38.234Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-02T11:49:41.538Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-02T11:49:44.355Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-02T11:49:48.084Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-02T11:49:51.794Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-02T11:49:51.794Z] 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.
[2024-09-02T11:49:51.794Z] The best model improves the baseline by 14.52%.
[2024-09-02T11:49:52.437Z] Movies recommended for you:
[2024-09-02T11:49:52.437Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-02T11:49:52.437Z] There is no way to check that no silent failure occurred.
[2024-09-02T11:49:52.437Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (36340.976 ms) ======
[2024-09-02T11:49:52.437Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-09-02T11:49:52.437Z] GC before operation: completed in 428.445 ms, heap usage 590.566 MB -> 47.845 MB.
[2024-09-02T11:49:58.242Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-02T11:50:03.071Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-02T11:50:08.890Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-02T11:50:14.696Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-02T11:50:17.528Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-02T11:50:21.232Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-02T11:50:24.047Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-02T11:50:27.753Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-02T11:50:28.371Z] 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.
[2024-09-02T11:50:28.371Z] The best model improves the baseline by 14.52%.
[2024-09-02T11:50:28.371Z] Movies recommended for you:
[2024-09-02T11:50:28.371Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-02T11:50:28.371Z] There is no way to check that no silent failure occurred.
[2024-09-02T11:50:28.371Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (35730.319 ms) ======
[2024-09-02T11:50:28.371Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-09-02T11:50:28.992Z] GC before operation: completed in 365.765 ms, heap usage 569.334 MB -> 48.052 MB.
[2024-09-02T11:50:33.688Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-02T11:50:39.792Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-02T11:50:45.603Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-02T11:50:50.298Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-02T11:50:54.003Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-02T11:50:56.823Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-02T11:51:01.514Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-02T11:51:04.335Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-02T11:51:04.953Z] 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.
[2024-09-02T11:51:04.953Z] The best model improves the baseline by 14.52%.
[2024-09-02T11:51:04.953Z] Movies recommended for you:
[2024-09-02T11:51:04.953Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-02T11:51:04.953Z] There is no way to check that no silent failure occurred.
[2024-09-02T11:51:04.953Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (36420.076 ms) ======
[2024-09-02T11:51:04.953Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-09-02T11:51:05.572Z] GC before operation: completed in 396.191 ms, heap usage 579.145 MB -> 48.109 MB.
[2024-09-02T11:51:11.390Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-02T11:51:16.086Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-02T11:51:21.918Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-02T11:51:27.724Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-02T11:51:30.560Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-02T11:51:33.378Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-02T11:51:37.565Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-02T11:51:40.384Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-02T11:51:41.007Z] 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.
[2024-09-02T11:51:41.007Z] The best model improves the baseline by 14.52%.
[2024-09-02T11:51:41.007Z] Movies recommended for you:
[2024-09-02T11:51:41.007Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-02T11:51:41.007Z] There is no way to check that no silent failure occurred.
[2024-09-02T11:51:41.007Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (35718.312 ms) ======
[2024-09-02T11:51:41.007Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-09-02T11:51:41.625Z] GC before operation: completed in 477.602 ms, heap usage 540.168 MB -> 47.896 MB.
[2024-09-02T11:51:47.432Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-02T11:51:53.257Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-02T11:51:59.067Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-02T11:52:03.769Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-02T11:52:06.583Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-02T11:52:10.288Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-02T11:52:13.988Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-02T11:52:16.805Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-02T11:52:17.424Z] 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.
[2024-09-02T11:52:17.424Z] The best model improves the baseline by 14.52%.
[2024-09-02T11:52:17.424Z] Movies recommended for you:
[2024-09-02T11:52:17.424Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-02T11:52:17.424Z] There is no way to check that no silent failure occurred.
[2024-09-02T11:52:17.424Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (35856.998 ms) ======
[2024-09-02T11:52:17.424Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-09-02T11:52:18.043Z] GC before operation: completed in 481.194 ms, heap usage 545.014 MB -> 47.932 MB.
[2024-09-02T11:52:23.846Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-02T11:52:28.548Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-02T11:52:34.962Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-02T11:52:39.649Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-02T11:52:43.354Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-02T11:52:46.168Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-02T11:52:49.868Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-02T11:52:52.687Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-02T11:52:53.357Z] 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.
[2024-09-02T11:52:53.357Z] The best model improves the baseline by 14.52%.
[2024-09-02T11:52:53.975Z] Movies recommended for you:
[2024-09-02T11:52:53.975Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-02T11:52:53.975Z] There is no way to check that no silent failure occurred.
[2024-09-02T11:52:53.975Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (35762.235 ms) ======
[2024-09-02T11:52:53.975Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-09-02T11:52:53.975Z] GC before operation: completed in 383.547 ms, heap usage 538.243 MB -> 48.144 MB.
[2024-09-02T11:52:59.890Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-02T11:53:04.577Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-02T11:53:10.383Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-02T11:53:16.191Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-02T11:53:19.006Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-02T11:53:22.709Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-02T11:53:25.570Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-02T11:53:29.427Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-02T11:53:30.046Z] 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.
[2024-09-02T11:53:30.046Z] The best model improves the baseline by 14.52%.
[2024-09-02T11:53:30.046Z] Movies recommended for you:
[2024-09-02T11:53:30.046Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-02T11:53:30.046Z] There is no way to check that no silent failure occurred.
[2024-09-02T11:53:30.046Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (35832.075 ms) ======
[2024-09-02T11:53:30.665Z] -----------------------------------
[2024-09-02T11:53:30.665Z] renaissance-movie-lens_0_PASSED
[2024-09-02T11:53:30.665Z] -----------------------------------
[2024-09-02T11:53:31.284Z]
[2024-09-02T11:53:31.284Z] TEST TEARDOWN:
[2024-09-02T11:53:31.284Z] Nothing to be done for teardown.
[2024-09-02T11:53:31.284Z] renaissance-movie-lens_0 Finish Time: Mon Sep 2 07:35:04 2024 Epoch Time (ms): 1725280504921