renaissance-movie-lens_0
[2024-08-16T15:52:49.228Z] Running test renaissance-movie-lens_0 ...
[2024-08-16T15:52:49.228Z] ===============================================
[2024-08-16T15:52:49.228Z] renaissance-movie-lens_0 Start Time: Fri Aug 16 11:52:48 2024 Epoch Time (ms): 1723823568752
[2024-08-16T15:52:49.228Z] variation: NoOptions
[2024-08-16T15:52:49.228Z] JVM_OPTIONS:
[2024-08-16T15:52:49.228Z] { \
[2024-08-16T15:52:49.228Z] echo ""; echo "TEST SETUP:"; \
[2024-08-16T15:52:49.228Z] echo "Nothing to be done for setup."; \
[2024-08-16T15:52:49.228Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac_testList_0/aqa-tests/TKG/../TKG/output_17238232737845/renaissance-movie-lens_0"; \
[2024-08-16T15:52:49.228Z] cd "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac_testList_0/aqa-tests/TKG/../TKG/output_17238232737845/renaissance-movie-lens_0"; \
[2024-08-16T15:52:49.228Z] echo ""; echo "TESTING:"; \
[2024-08-16T15:52:49.228Z] "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac_testList_0/jdkbinary/j2sdk-image/Contents/Home/bin/..//bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac_testList_0/aqa-tests/TKG/../TKG/output_17238232737845/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-16T15:52:49.228Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac_testList_0/aqa-tests/TKG/..; rm -f -r "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac_testList_0/aqa-tests/TKG/../TKG/output_17238232737845/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-16T15:52:49.228Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-16T15:52:49.228Z] echo "Nothing to be done for teardown."; \
[2024-08-16T15:52:49.228Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac_testList_0/aqa-tests/TKG/../TKG/output_17238232737845/TestTargetResult";
[2024-08-16T15:52:49.228Z]
[2024-08-16T15:52:49.228Z] TEST SETUP:
[2024-08-16T15:52:49.228Z] Nothing to be done for setup.
[2024-08-16T15:52:49.228Z]
[2024-08-16T15:52:49.228Z] TESTING:
[2024-08-16T15:52:50.448Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-16T15:52:51.195Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 3 (out of 3) threads.
[2024-08-16T15:52:52.975Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-16T15:52:52.975Z] Training: 60056, validation: 20285, test: 19854
[2024-08-16T15:52:52.975Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-16T15:52:52.975Z] GC before operation: completed in 29.365 ms, heap usage 78.961 MB -> 36.923 MB.
[2024-08-16T15:52:56.192Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T15:52:58.571Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T15:53:00.342Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T15:53:02.125Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T15:53:02.890Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T15:53:03.656Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T15:53:04.949Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T15:53:05.738Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T15:53:06.087Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-16T15:53:06.087Z] The best model improves the baseline by 14.52%.
[2024-08-16T15:53:06.087Z] Movies recommended for you:
[2024-08-16T15:53:06.087Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T15:53:06.087Z] There is no way to check that no silent failure occurred.
[2024-08-16T15:53:06.087Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (13078.840 ms) ======
[2024-08-16T15:53:06.087Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-16T15:53:06.087Z] GC before operation: completed in 51.774 ms, heap usage 225.366 MB -> 52.986 MB.
[2024-08-16T15:53:07.862Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T15:53:09.099Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T15:53:10.910Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T15:53:12.121Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T15:53:12.623Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T15:53:13.643Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T15:53:14.419Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T15:53:14.768Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T15:53:15.120Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-16T15:53:15.120Z] The best model improves the baseline by 14.52%.
[2024-08-16T15:53:15.120Z] Movies recommended for you:
[2024-08-16T15:53:15.120Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T15:53:15.120Z] There is no way to check that no silent failure occurred.
[2024-08-16T15:53:15.120Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (9010.847 ms) ======
[2024-08-16T15:53:15.120Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-16T15:53:15.120Z] GC before operation: completed in 31.968 ms, heap usage 328.286 MB -> 49.389 MB.
[2024-08-16T15:53:16.340Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T15:53:17.587Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T15:53:18.817Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T15:53:19.576Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T15:53:20.324Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T15:53:21.111Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T15:53:21.486Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T15:53:22.273Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T15:53:22.641Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-16T15:53:22.641Z] The best model improves the baseline by 14.52%.
[2024-08-16T15:53:22.641Z] Movies recommended for you:
[2024-08-16T15:53:22.641Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T15:53:22.641Z] There is no way to check that no silent failure occurred.
[2024-08-16T15:53:22.641Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (7448.633 ms) ======
[2024-08-16T15:53:22.641Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-16T15:53:22.641Z] GC before operation: completed in 35.429 ms, heap usage 74.072 MB -> 49.314 MB.
[2024-08-16T15:53:23.891Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T15:53:25.206Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T15:53:26.970Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T15:53:28.188Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T15:53:28.945Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T15:53:29.721Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T15:53:30.480Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T15:53:30.839Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T15:53:30.839Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-16T15:53:30.839Z] The best model improves the baseline by 14.52%.
[2024-08-16T15:53:31.192Z] Movies recommended for you:
[2024-08-16T15:53:31.192Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T15:53:31.192Z] There is no way to check that no silent failure occurred.
[2024-08-16T15:53:31.192Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (8413.145 ms) ======
[2024-08-16T15:53:31.192Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-16T15:53:31.192Z] GC before operation: completed in 32.680 ms, heap usage 330.173 MB -> 50.118 MB.
[2024-08-16T15:53:32.401Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T15:53:33.155Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T15:53:34.376Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T15:53:35.594Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T15:53:36.377Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T15:53:36.742Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T15:53:37.600Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T15:53:38.360Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T15:53:38.360Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-16T15:53:38.360Z] The best model improves the baseline by 14.52%.
[2024-08-16T15:53:38.360Z] Movies recommended for you:
[2024-08-16T15:53:38.360Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T15:53:38.360Z] There is no way to check that no silent failure occurred.
[2024-08-16T15:53:38.360Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (7350.918 ms) ======
[2024-08-16T15:53:38.360Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-16T15:53:38.360Z] GC before operation: completed in 30.632 ms, heap usage 92.939 MB -> 52.305 MB.
[2024-08-16T15:53:39.569Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T15:53:40.788Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T15:53:42.022Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T15:53:43.242Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T15:53:43.996Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T15:53:44.748Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T15:53:45.543Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T15:53:46.297Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T15:53:46.297Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-16T15:53:46.297Z] The best model improves the baseline by 14.52%.
[2024-08-16T15:53:46.297Z] Movies recommended for you:
[2024-08-16T15:53:46.297Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T15:53:46.297Z] There is no way to check that no silent failure occurred.
[2024-08-16T15:53:46.297Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (7853.773 ms) ======
[2024-08-16T15:53:46.297Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-16T15:53:46.297Z] GC before operation: completed in 33.634 ms, heap usage 247.998 MB -> 50.076 MB.
[2024-08-16T15:53:47.507Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T15:53:48.745Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T15:53:49.968Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T15:53:50.718Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T15:53:51.480Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T15:53:52.248Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T15:53:52.998Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T15:53:53.757Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T15:53:53.757Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-16T15:53:53.757Z] The best model improves the baseline by 14.52%.
[2024-08-16T15:53:54.115Z] Movies recommended for you:
[2024-08-16T15:53:54.115Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T15:53:54.115Z] There is no way to check that no silent failure occurred.
[2024-08-16T15:53:54.115Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (7597.279 ms) ======
[2024-08-16T15:53:54.115Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-16T15:53:54.115Z] GC before operation: completed in 32.600 ms, heap usage 74.957 MB -> 50.052 MB.
[2024-08-16T15:53:55.340Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T15:53:56.569Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T15:53:57.325Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T15:53:58.548Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T15:53:59.313Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T15:53:59.662Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T15:54:00.444Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T15:54:01.252Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T15:54:01.252Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-16T15:54:01.252Z] The best model improves the baseline by 14.52%.
[2024-08-16T15:54:01.252Z] Movies recommended for you:
[2024-08-16T15:54:01.252Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T15:54:01.252Z] There is no way to check that no silent failure occurred.
[2024-08-16T15:54:01.252Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (7212.327 ms) ======
[2024-08-16T15:54:01.252Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-16T15:54:01.252Z] GC before operation: completed in 29.778 ms, heap usage 369.276 MB -> 53.984 MB.
[2024-08-16T15:54:02.585Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T15:54:03.805Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T15:54:04.570Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T15:54:05.796Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T15:54:06.559Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T15:54:07.319Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T15:54:08.077Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T15:54:08.834Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T15:54:09.186Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-16T15:54:09.186Z] The best model improves the baseline by 14.52%.
[2024-08-16T15:54:09.186Z] Movies recommended for you:
[2024-08-16T15:54:09.186Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T15:54:09.186Z] There is no way to check that no silent failure occurred.
[2024-08-16T15:54:09.186Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (7853.663 ms) ======
[2024-08-16T15:54:09.186Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-16T15:54:09.186Z] GC before operation: completed in 32.230 ms, heap usage 206.192 MB -> 50.399 MB.
[2024-08-16T15:54:10.404Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T15:54:11.630Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T15:54:12.390Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T15:54:13.612Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T15:54:14.372Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T15:54:14.720Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T15:54:15.482Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T15:54:16.234Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T15:54:16.234Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-16T15:54:16.234Z] The best model improves the baseline by 14.52%.
[2024-08-16T15:54:16.234Z] Movies recommended for you:
[2024-08-16T15:54:16.234Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T15:54:16.234Z] There is no way to check that no silent failure occurred.
[2024-08-16T15:54:16.234Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (7162.986 ms) ======
[2024-08-16T15:54:16.234Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-16T15:54:16.234Z] GC before operation: completed in 30.418 ms, heap usage 94.052 MB -> 52.272 MB.
[2024-08-16T15:54:17.487Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T15:54:18.253Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T15:54:19.517Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T15:54:20.276Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T15:54:21.034Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T15:54:21.385Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T15:54:22.143Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T15:54:22.496Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T15:54:22.852Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-16T15:54:22.852Z] The best model improves the baseline by 14.52%.
[2024-08-16T15:54:22.852Z] Movies recommended for you:
[2024-08-16T15:54:22.852Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T15:54:22.852Z] There is no way to check that no silent failure occurred.
[2024-08-16T15:54:22.852Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (6462.742 ms) ======
[2024-08-16T15:54:22.852Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-16T15:54:22.852Z] GC before operation: completed in 30.792 ms, heap usage 330.515 MB -> 50.327 MB.
[2024-08-16T15:54:24.058Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T15:54:25.285Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T15:54:26.048Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T15:54:27.293Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T15:54:27.731Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T15:54:28.504Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T15:54:28.876Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T15:54:29.649Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T15:54:29.649Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-16T15:54:29.649Z] The best model improves the baseline by 14.52%.
[2024-08-16T15:54:29.649Z] Movies recommended for you:
[2024-08-16T15:54:29.649Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T15:54:29.649Z] There is no way to check that no silent failure occurred.
[2024-08-16T15:54:29.649Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (6961.757 ms) ======
[2024-08-16T15:54:29.649Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-16T15:54:29.649Z] GC before operation: completed in 33.827 ms, heap usage 89.898 MB -> 52.544 MB.
[2024-08-16T15:54:30.891Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T15:54:31.639Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T15:54:32.867Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T15:54:34.108Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T15:54:34.457Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T15:54:35.211Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T15:54:35.574Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T15:54:36.333Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T15:54:36.333Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-16T15:54:36.333Z] The best model improves the baseline by 14.52%.
[2024-08-16T15:54:36.333Z] Movies recommended for you:
[2024-08-16T15:54:36.333Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T15:54:36.333Z] There is no way to check that no silent failure occurred.
[2024-08-16T15:54:36.333Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (6660.576 ms) ======
[2024-08-16T15:54:36.333Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-16T15:54:36.333Z] GC before operation: completed in 30.056 ms, heap usage 198.922 MB -> 51.779 MB.
[2024-08-16T15:54:37.578Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T15:54:38.343Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T15:54:39.572Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T15:54:40.324Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T15:54:41.076Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T15:54:41.885Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T15:54:42.233Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T15:54:43.037Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T15:54:43.037Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-16T15:54:43.037Z] The best model improves the baseline by 14.52%.
[2024-08-16T15:54:43.037Z] Movies recommended for you:
[2024-08-16T15:54:43.037Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T15:54:43.037Z] There is no way to check that no silent failure occurred.
[2024-08-16T15:54:43.037Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (6652.886 ms) ======
[2024-08-16T15:54:43.037Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-16T15:54:43.037Z] GC before operation: completed in 30.073 ms, heap usage 72.229 MB -> 50.327 MB.
[2024-08-16T15:54:44.251Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T15:54:45.457Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T15:54:46.675Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T15:54:47.885Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T15:54:48.647Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T15:54:48.995Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T15:54:49.753Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T15:54:50.520Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T15:54:50.520Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-16T15:54:50.520Z] The best model improves the baseline by 14.52%.
[2024-08-16T15:54:50.520Z] Movies recommended for you:
[2024-08-16T15:54:50.520Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T15:54:50.520Z] There is no way to check that no silent failure occurred.
[2024-08-16T15:54:50.520Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (7246.421 ms) ======
[2024-08-16T15:54:50.520Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-16T15:54:50.520Z] GC before operation: completed in 32.282 ms, heap usage 349.837 MB -> 53.949 MB.
[2024-08-16T15:54:51.731Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T15:54:52.577Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T15:54:53.334Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T15:54:54.701Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T15:54:55.060Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T15:54:55.824Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T15:54:56.586Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T15:54:56.988Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T15:54:57.347Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-16T15:54:57.347Z] The best model improves the baseline by 14.52%.
[2024-08-16T15:54:57.347Z] Movies recommended for you:
[2024-08-16T15:54:57.347Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T15:54:57.347Z] There is no way to check that no silent failure occurred.
[2024-08-16T15:54:57.347Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (6801.293 ms) ======
[2024-08-16T15:54:57.347Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-16T15:54:57.347Z] GC before operation: completed in 37.047 ms, heap usage 216.262 MB -> 50.576 MB.
[2024-08-16T15:54:58.565Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T15:54:59.789Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T15:55:01.021Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T15:55:02.267Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T15:55:02.621Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T15:55:03.374Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T15:55:04.125Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T15:55:04.489Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T15:55:04.838Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-16T15:55:04.838Z] The best model improves the baseline by 14.52%.
[2024-08-16T15:55:04.838Z] Movies recommended for you:
[2024-08-16T15:55:04.838Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T15:55:04.838Z] There is no way to check that no silent failure occurred.
[2024-08-16T15:55:04.838Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (7411.934 ms) ======
[2024-08-16T15:55:04.838Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-16T15:55:04.838Z] GC before operation: completed in 31.544 ms, heap usage 235.867 MB -> 50.452 MB.
[2024-08-16T15:55:05.600Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T15:55:06.825Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T15:55:07.577Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T15:55:08.797Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T15:55:09.167Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T15:55:09.927Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T15:55:10.685Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T15:55:11.459Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T15:55:11.459Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-16T15:55:11.459Z] The best model improves the baseline by 14.52%.
[2024-08-16T15:55:11.459Z] Movies recommended for you:
[2024-08-16T15:55:11.459Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T15:55:11.459Z] There is no way to check that no silent failure occurred.
[2024-08-16T15:55:11.459Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (6701.479 ms) ======
[2024-08-16T15:55:11.459Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-16T15:55:11.459Z] GC before operation: completed in 33.443 ms, heap usage 227.841 MB -> 50.662 MB.
[2024-08-16T15:55:12.712Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T15:55:13.954Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T15:55:15.752Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T15:55:17.000Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T15:55:17.859Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T15:55:18.609Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T15:55:19.368Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T15:55:20.134Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T15:55:20.502Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-16T15:55:20.502Z] The best model improves the baseline by 14.52%.
[2024-08-16T15:55:20.502Z] Movies recommended for you:
[2024-08-16T15:55:20.502Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T15:55:20.502Z] There is no way to check that no silent failure occurred.
[2024-08-16T15:55:20.502Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (8984.518 ms) ======
[2024-08-16T15:55:20.502Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-16T15:55:20.502Z] GC before operation: completed in 40.081 ms, heap usage 61.895 MB -> 50.593 MB.
[2024-08-16T15:55:21.726Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T15:55:23.475Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T15:55:24.695Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T15:55:25.930Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T15:55:26.688Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T15:55:27.502Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T15:55:28.737Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T15:55:29.489Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T15:55:29.489Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-16T15:55:29.489Z] The best model improves the baseline by 14.52%.
[2024-08-16T15:55:29.489Z] Movies recommended for you:
[2024-08-16T15:55:29.489Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T15:55:29.489Z] There is no way to check that no silent failure occurred.
[2024-08-16T15:55:29.489Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (8964.747 ms) ======
[2024-08-16T15:55:29.838Z] -----------------------------------
[2024-08-16T15:55:29.838Z] renaissance-movie-lens_0_PASSED
[2024-08-16T15:55:29.838Z] -----------------------------------
[2024-08-16T15:55:29.838Z]
[2024-08-16T15:55:29.838Z] TEST TEARDOWN:
[2024-08-16T15:55:29.838Z] Nothing to be done for teardown.
[2024-08-16T15:55:29.838Z] renaissance-movie-lens_0 Finish Time: Fri Aug 16 11:55:29 2024 Epoch Time (ms): 1723823729492