renaissance-movie-lens_0
[2025-01-10T18:25:57.395Z] Running test renaissance-movie-lens_0 ...
[2025-01-10T18:25:57.395Z] ===============================================
[2025-01-10T18:25:57.395Z] renaissance-movie-lens_0 Start Time: Fri Jan 10 18:25:56 2025 Epoch Time (ms): 1736533556223
[2025-01-10T18:25:57.395Z] variation: NoOptions
[2025-01-10T18:25:57.395Z] JVM_OPTIONS:
[2025-01-10T18:25:57.395Z] { \
[2025-01-10T18:25:57.395Z] echo ""; echo "TEST SETUP:"; \
[2025-01-10T18:25:57.395Z] echo "Nothing to be done for setup."; \
[2025-01-10T18:25:57.395Z] mkdir -p "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17365323397586/renaissance-movie-lens_0"; \
[2025-01-10T18:25:57.395Z] cd "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17365323397586/renaissance-movie-lens_0"; \
[2025-01-10T18:25:57.395Z] echo ""; echo "TESTING:"; \
[2025-01-10T18:25:57.395Z] "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/jdkbinary/j2sdk-image/bin/java" -jar "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17365323397586/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-01-10T18:25:57.395Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17365323397586/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-01-10T18:25:57.395Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-01-10T18:25:57.395Z] echo "Nothing to be done for teardown."; \
[2025-01-10T18:25:57.395Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17365323397586/TestTargetResult";
[2025-01-10T18:25:57.395Z]
[2025-01-10T18:25:57.395Z] TEST SETUP:
[2025-01-10T18:25:57.395Z] Nothing to be done for setup.
[2025-01-10T18:25:57.395Z]
[2025-01-10T18:25:57.395Z] TESTING:
[2025-01-10T18:26:00.564Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2025-01-10T18:26:03.744Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-01-10T18:26:08.861Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-01-10T18:26:08.861Z] Training: 60056, validation: 20285, test: 19854
[2025-01-10T18:26:08.861Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-01-10T18:26:08.861Z] GC before operation: completed in 237.867 ms, heap usage 33.597 MB -> 25.746 MB.
[2025-01-10T18:26:16.658Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T18:26:20.919Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T18:26:26.115Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T18:26:30.223Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T18:26:33.436Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T18:26:35.989Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T18:26:38.518Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T18:26:41.038Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T18:26:41.825Z] 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.
[2025-01-10T18:26:41.825Z] The best model improves the baseline by 14.52%.
[2025-01-10T18:26:41.825Z] Movies recommended for you:
[2025-01-10T18:26:41.825Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T18:26:41.825Z] There is no way to check that no silent failure occurred.
[2025-01-10T18:26:41.825Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (32854.660 ms) ======
[2025-01-10T18:26:41.825Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-01-10T18:26:42.206Z] GC before operation: completed in 383.609 ms, heap usage 355.997 MB -> 40.328 MB.
[2025-01-10T18:26:47.402Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T18:26:50.736Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T18:26:54.904Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T18:26:59.149Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T18:27:01.668Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T18:27:03.524Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T18:27:06.008Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T18:27:08.565Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T18:27:08.978Z] 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.
[2025-01-10T18:27:08.978Z] The best model improves the baseline by 14.52%.
[2025-01-10T18:27:08.978Z] Movies recommended for you:
[2025-01-10T18:27:08.978Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T18:27:08.978Z] There is no way to check that no silent failure occurred.
[2025-01-10T18:27:08.978Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (26846.678 ms) ======
[2025-01-10T18:27:08.978Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-01-10T18:27:09.346Z] GC before operation: completed in 288.881 ms, heap usage 71.538 MB -> 44.265 MB.
[2025-01-10T18:27:13.457Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T18:27:17.628Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T18:27:20.883Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T18:27:23.342Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T18:27:25.146Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T18:27:27.075Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T18:27:28.899Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T18:27:30.749Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T18:27:31.117Z] 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.
[2025-01-10T18:27:31.118Z] The best model improves the baseline by 14.52%.
[2025-01-10T18:27:31.118Z] Movies recommended for you:
[2025-01-10T18:27:31.118Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T18:27:31.118Z] There is no way to check that no silent failure occurred.
[2025-01-10T18:27:31.118Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (21736.806 ms) ======
[2025-01-10T18:27:31.118Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-01-10T18:27:31.483Z] GC before operation: completed in 228.236 ms, heap usage 473.903 MB -> 45.276 MB.
[2025-01-10T18:27:34.673Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T18:27:37.946Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T18:27:40.437Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T18:27:43.715Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T18:27:46.212Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T18:27:48.055Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T18:27:49.336Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T18:27:51.168Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T18:27:51.550Z] 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.
[2025-01-10T18:27:51.550Z] The best model improves the baseline by 14.52%.
[2025-01-10T18:27:51.926Z] Movies recommended for you:
[2025-01-10T18:27:51.926Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T18:27:51.926Z] There is no way to check that no silent failure occurred.
[2025-01-10T18:27:51.926Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (20363.018 ms) ======
[2025-01-10T18:27:51.926Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-01-10T18:27:51.926Z] GC before operation: completed in 209.583 ms, heap usage 418.295 MB -> 45.609 MB.
[2025-01-10T18:27:55.154Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T18:27:58.381Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T18:28:00.876Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T18:28:04.084Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T18:28:05.917Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T18:28:07.750Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T18:28:10.235Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T18:28:12.088Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T18:28:12.454Z] 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.
[2025-01-10T18:28:12.454Z] The best model improves the baseline by 14.52%.
[2025-01-10T18:28:12.454Z] Movies recommended for you:
[2025-01-10T18:28:12.454Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T18:28:12.454Z] There is no way to check that no silent failure occurred.
[2025-01-10T18:28:12.454Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (20562.876 ms) ======
[2025-01-10T18:28:12.454Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-01-10T18:28:12.829Z] GC before operation: completed in 221.372 ms, heap usage 428.140 MB -> 45.834 MB.
[2025-01-10T18:28:16.063Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T18:28:18.561Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T18:28:21.017Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T18:28:24.286Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T18:28:25.560Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T18:28:27.547Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T18:28:29.398Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T18:28:30.677Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T18:28:31.079Z] 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.
[2025-01-10T18:28:31.079Z] The best model improves the baseline by 14.52%.
[2025-01-10T18:28:31.079Z] Movies recommended for you:
[2025-01-10T18:28:31.079Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T18:28:31.079Z] There is no way to check that no silent failure occurred.
[2025-01-10T18:28:31.079Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (18395.598 ms) ======
[2025-01-10T18:28:31.079Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-01-10T18:28:31.447Z] GC before operation: completed in 176.720 ms, heap usage 401.114 MB -> 45.718 MB.
[2025-01-10T18:28:33.925Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T18:28:37.164Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T18:28:39.631Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T18:28:42.088Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T18:28:43.939Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T18:28:45.766Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T18:28:47.584Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T18:28:48.886Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T18:28:49.254Z] 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.
[2025-01-10T18:28:49.254Z] The best model improves the baseline by 14.52%.
[2025-01-10T18:28:49.626Z] Movies recommended for you:
[2025-01-10T18:28:49.626Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T18:28:49.626Z] There is no way to check that no silent failure occurred.
[2025-01-10T18:28:49.626Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (18186.651 ms) ======
[2025-01-10T18:28:49.626Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-01-10T18:28:49.626Z] GC before operation: completed in 204.969 ms, heap usage 414.397 MB -> 45.888 MB.
[2025-01-10T18:28:52.835Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T18:28:55.293Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T18:28:57.836Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T18:29:01.075Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T18:29:02.342Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T18:29:04.176Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T18:29:05.994Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T18:29:07.297Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T18:29:07.664Z] 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.
[2025-01-10T18:29:07.664Z] The best model improves the baseline by 14.52%.
[2025-01-10T18:29:07.664Z] Movies recommended for you:
[2025-01-10T18:29:07.664Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T18:29:07.664Z] There is no way to check that no silent failure occurred.
[2025-01-10T18:29:07.664Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (18051.192 ms) ======
[2025-01-10T18:29:07.664Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-01-10T18:29:08.036Z] GC before operation: completed in 195.231 ms, heap usage 403.896 MB -> 46.254 MB.
[2025-01-10T18:29:10.485Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T18:29:13.681Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T18:29:16.145Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T18:29:18.633Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T18:29:20.450Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T18:29:22.276Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T18:29:24.161Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T18:29:25.459Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T18:29:25.827Z] 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.
[2025-01-10T18:29:25.827Z] The best model improves the baseline by 14.52%.
[2025-01-10T18:29:25.827Z] Movies recommended for you:
[2025-01-10T18:29:25.827Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T18:29:25.827Z] There is no way to check that no silent failure occurred.
[2025-01-10T18:29:25.827Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (17996.364 ms) ======
[2025-01-10T18:29:25.827Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-01-10T18:29:26.192Z] GC before operation: completed in 176.620 ms, heap usage 405.240 MB -> 46.010 MB.
[2025-01-10T18:29:28.644Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T18:29:31.885Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T18:29:34.368Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T18:29:36.823Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T18:29:38.653Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T18:29:40.487Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T18:29:41.777Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T18:29:43.609Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T18:29:43.989Z] 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.
[2025-01-10T18:29:43.989Z] The best model improves the baseline by 14.52%.
[2025-01-10T18:29:43.989Z] Movies recommended for you:
[2025-01-10T18:29:43.989Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T18:29:43.989Z] There is no way to check that no silent failure occurred.
[2025-01-10T18:29:43.989Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (17844.449 ms) ======
[2025-01-10T18:29:43.989Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-01-10T18:29:44.354Z] GC before operation: completed in 220.315 ms, heap usage 408.804 MB -> 46.145 MB.
[2025-01-10T18:29:46.801Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T18:29:50.064Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T18:29:52.518Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T18:29:54.988Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T18:29:56.804Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T18:29:58.636Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T18:29:59.923Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T18:30:01.798Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T18:30:02.222Z] 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.
[2025-01-10T18:30:02.222Z] The best model improves the baseline by 14.52%.
[2025-01-10T18:30:02.222Z] Movies recommended for you:
[2025-01-10T18:30:02.222Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T18:30:02.222Z] There is no way to check that no silent failure occurred.
[2025-01-10T18:30:02.222Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (17998.855 ms) ======
[2025-01-10T18:30:02.222Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-01-10T18:30:02.222Z] GC before operation: completed in 167.024 ms, heap usage 423.177 MB -> 45.799 MB.
[2025-01-10T18:30:05.454Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T18:30:07.912Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T18:30:11.123Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T18:30:13.571Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T18:30:14.838Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T18:30:16.665Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T18:30:18.577Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T18:30:19.850Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T18:30:20.245Z] 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.
[2025-01-10T18:30:20.245Z] The best model improves the baseline by 14.52%.
[2025-01-10T18:30:20.623Z] Movies recommended for you:
[2025-01-10T18:30:20.623Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T18:30:20.623Z] There is no way to check that no silent failure occurred.
[2025-01-10T18:30:20.623Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (18136.153 ms) ======
[2025-01-10T18:30:20.623Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-01-10T18:30:20.623Z] GC before operation: completed in 158.791 ms, heap usage 416.290 MB -> 42.722 MB.
[2025-01-10T18:30:23.088Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T18:30:26.327Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T18:30:29.512Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T18:30:31.982Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T18:30:33.305Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T18:30:35.126Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T18:30:36.947Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T18:30:38.815Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T18:30:38.815Z] 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.
[2025-01-10T18:30:38.815Z] The best model improves the baseline by 14.52%.
[2025-01-10T18:30:39.180Z] Movies recommended for you:
[2025-01-10T18:30:39.180Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T18:30:39.180Z] There is no way to check that no silent failure occurred.
[2025-01-10T18:30:39.180Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (18426.503 ms) ======
[2025-01-10T18:30:39.180Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-01-10T18:30:39.180Z] GC before operation: completed in 151.431 ms, heap usage 444.766 MB -> 46.292 MB.
[2025-01-10T18:30:42.394Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T18:30:44.940Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T18:30:47.454Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T18:30:49.975Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T18:30:51.932Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T18:30:53.775Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T18:30:55.630Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T18:30:56.928Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T18:30:57.321Z] 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.
[2025-01-10T18:30:57.321Z] The best model improves the baseline by 14.52%.
[2025-01-10T18:30:57.321Z] Movies recommended for you:
[2025-01-10T18:30:57.321Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T18:30:57.321Z] There is no way to check that no silent failure occurred.
[2025-01-10T18:30:57.321Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (18182.337 ms) ======
[2025-01-10T18:30:57.321Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-01-10T18:30:57.694Z] GC before operation: completed in 145.530 ms, heap usage 394.927 MB -> 45.948 MB.
[2025-01-10T18:31:00.138Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T18:31:03.356Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T18:31:05.842Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T18:31:08.324Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T18:31:10.147Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T18:31:12.064Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T18:31:13.393Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T18:31:15.261Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T18:31:15.650Z] 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.
[2025-01-10T18:31:15.650Z] The best model improves the baseline by 14.52%.
[2025-01-10T18:31:15.650Z] Movies recommended for you:
[2025-01-10T18:31:15.650Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T18:31:15.650Z] There is no way to check that no silent failure occurred.
[2025-01-10T18:31:15.650Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (18054.148 ms) ======
[2025-01-10T18:31:15.650Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-01-10T18:31:15.650Z] GC before operation: completed in 159.375 ms, heap usage 397.637 MB -> 46.154 MB.
[2025-01-10T18:31:18.852Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T18:31:21.324Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T18:31:23.916Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T18:31:27.193Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T18:31:28.545Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T18:31:29.832Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T18:31:31.705Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T18:31:33.538Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T18:31:33.904Z] 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.
[2025-01-10T18:31:33.904Z] The best model improves the baseline by 14.52%.
[2025-01-10T18:31:33.904Z] Movies recommended for you:
[2025-01-10T18:31:33.904Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T18:31:33.904Z] There is no way to check that no silent failure occurred.
[2025-01-10T18:31:33.904Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (18112.660 ms) ======
[2025-01-10T18:31:33.904Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-01-10T18:31:34.268Z] GC before operation: completed in 211.727 ms, heap usage 425.279 MB -> 46.229 MB.
[2025-01-10T18:31:36.724Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T18:31:39.935Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T18:31:42.388Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T18:31:44.817Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T18:31:46.631Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T18:31:48.517Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T18:31:50.356Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T18:31:51.639Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T18:31:52.010Z] 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.
[2025-01-10T18:31:52.010Z] The best model improves the baseline by 14.52%.
[2025-01-10T18:31:52.010Z] Movies recommended for you:
[2025-01-10T18:31:52.010Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T18:31:52.010Z] There is no way to check that no silent failure occurred.
[2025-01-10T18:31:52.010Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (17961.238 ms) ======
[2025-01-10T18:31:52.010Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-01-10T18:31:52.378Z] GC before operation: completed in 214.965 ms, heap usage 435.105 MB -> 46.077 MB.
[2025-01-10T18:31:54.824Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T18:31:58.045Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T18:32:00.540Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T18:32:03.009Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T18:32:04.852Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T18:32:06.127Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T18:32:07.981Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T18:32:09.807Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T18:32:09.807Z] 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.
[2025-01-10T18:32:10.178Z] The best model improves the baseline by 14.52%.
[2025-01-10T18:32:10.178Z] Movies recommended for you:
[2025-01-10T18:32:10.178Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T18:32:10.178Z] There is no way to check that no silent failure occurred.
[2025-01-10T18:32:10.178Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (17859.983 ms) ======
[2025-01-10T18:32:10.178Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-01-10T18:32:10.178Z] GC before operation: completed in 217.232 ms, heap usage 395.942 MB -> 46.066 MB.
[2025-01-10T18:32:13.508Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T18:32:16.035Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T18:32:18.547Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T18:32:21.172Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T18:32:23.000Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T18:32:24.285Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T18:32:26.144Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T18:32:27.975Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T18:32:27.975Z] 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.
[2025-01-10T18:32:27.975Z] The best model improves the baseline by 14.52%.
[2025-01-10T18:32:28.346Z] Movies recommended for you:
[2025-01-10T18:32:28.346Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T18:32:28.346Z] There is no way to check that no silent failure occurred.
[2025-01-10T18:32:28.346Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (17853.961 ms) ======
[2025-01-10T18:32:28.346Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-01-10T18:32:28.346Z] GC before operation: completed in 149.612 ms, heap usage 455.954 MB -> 48.699 MB.
[2025-01-10T18:32:30.822Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T18:32:34.026Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T18:32:36.514Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T18:32:38.966Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T18:32:40.776Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T18:32:42.627Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T18:32:43.921Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T18:32:45.766Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T18:32:46.135Z] 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.
[2025-01-10T18:32:46.135Z] The best model improves the baseline by 14.52%.
[2025-01-10T18:32:46.135Z] Movies recommended for you:
[2025-01-10T18:32:46.135Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T18:32:46.135Z] There is no way to check that no silent failure occurred.
[2025-01-10T18:32:46.135Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (17839.162 ms) ======
[2025-01-10T18:32:47.029Z] -----------------------------------
[2025-01-10T18:32:47.029Z] renaissance-movie-lens_0_PASSED
[2025-01-10T18:32:47.029Z] -----------------------------------
[2025-01-10T18:32:47.029Z]
[2025-01-10T18:32:47.029Z] TEST TEARDOWN:
[2025-01-10T18:32:47.029Z] Nothing to be done for teardown.
[2025-01-10T18:32:47.029Z] renaissance-movie-lens_0 Finish Time: Fri Jan 10 18:32:46 2025 Epoch Time (ms): 1736533966686