renaissance-movie-lens_0
[2024-08-16T16:51:56.144Z] Running test renaissance-movie-lens_0 ...
[2024-08-16T16:51:56.144Z] ===============================================
[2024-08-16T16:51:56.569Z] renaissance-movie-lens_0 Start Time: Fri Aug 16 09:51:56 2024 Epoch Time (ms): 1723827116102
[2024-08-16T16:51:56.569Z] variation: NoOptions
[2024-08-16T16:51:56.569Z] JVM_OPTIONS:
[2024-08-16T16:51:56.569Z] { \
[2024-08-16T16:51:56.569Z] echo ""; echo "TEST SETUP:"; \
[2024-08-16T16:51:56.569Z] echo "Nothing to be done for setup."; \
[2024-08-16T16:51:56.569Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17238249671784/renaissance-movie-lens_0"; \
[2024-08-16T16:51:56.569Z] cd "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17238249671784/renaissance-movie-lens_0"; \
[2024-08-16T16:51:56.569Z] echo ""; echo "TESTING:"; \
[2024-08-16T16:51:56.569Z] "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1/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_x86-64_mac_testList_1/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17238249671784/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-16T16:51:56.569Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/..; rm -f -r "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17238249671784/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-16T16:51:56.569Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-16T16:51:56.569Z] echo "Nothing to be done for teardown."; \
[2024-08-16T16:51:56.569Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17238249671784/TestTargetResult";
[2024-08-16T16:51:56.569Z]
[2024-08-16T16:51:56.569Z] TEST SETUP:
[2024-08-16T16:51:56.569Z] Nothing to be done for setup.
[2024-08-16T16:51:56.569Z]
[2024-08-16T16:51:56.569Z] TESTING:
[2024-08-16T16:52:19.666Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-16T16:52:23.590Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 3 (out of 3) threads.
[2024-08-16T16:52:39.896Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-16T16:52:42.070Z] Training: 60056, validation: 20285, test: 19854
[2024-08-16T16:52:42.070Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-16T16:52:42.474Z] GC before operation: completed in 274.549 ms, heap usage 101.543 MB -> 37.738 MB.
[2024-08-16T16:53:27.061Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T16:53:50.896Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T16:54:17.909Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T16:54:34.637Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T16:54:47.057Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T16:55:01.531Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T16:55:14.792Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T16:55:26.816Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T16:55:28.699Z] 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.
[2024-08-16T16:55:28.699Z] The best model improves the baseline by 14.52%.
[2024-08-16T16:55:29.952Z] Movies recommended for you:
[2024-08-16T16:55:29.952Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T16:55:29.952Z] There is no way to check that no silent failure occurred.
[2024-08-16T16:55:29.952Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (166900.708 ms) ======
[2024-08-16T16:55:29.952Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-16T16:55:29.952Z] GC before operation: completed in 386.987 ms, heap usage 389.250 MB -> 55.162 MB.
[2024-08-16T16:55:54.066Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T16:56:15.157Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T16:56:29.373Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T16:56:49.210Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T16:56:59.176Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T16:57:08.859Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T16:57:18.969Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T16:57:30.265Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T16:57:30.265Z] 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.
[2024-08-16T16:57:30.265Z] The best model improves the baseline by 14.52%.
[2024-08-16T16:57:30.265Z] Movies recommended for you:
[2024-08-16T16:57:30.265Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T16:57:30.265Z] There is no way to check that no silent failure occurred.
[2024-08-16T16:57:30.265Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (120249.188 ms) ======
[2024-08-16T16:57:30.265Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-16T16:57:30.265Z] GC before operation: completed in 194.177 ms, heap usage 103.291 MB -> 52.241 MB.
[2024-08-16T16:57:46.131Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T16:58:02.968Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T16:58:18.914Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T16:58:32.520Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T16:58:40.854Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T16:58:50.828Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T16:59:01.748Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T16:59:10.877Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T16:59:12.961Z] 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.
[2024-08-16T16:59:12.961Z] The best model improves the baseline by 14.52%.
[2024-08-16T16:59:12.961Z] Movies recommended for you:
[2024-08-16T16:59:12.961Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T16:59:12.961Z] There is no way to check that no silent failure occurred.
[2024-08-16T16:59:12.961Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (102686.795 ms) ======
[2024-08-16T16:59:12.961Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-16T16:59:12.961Z] GC before operation: completed in 128.143 ms, heap usage 254.315 MB -> 50.302 MB.
[2024-08-16T16:59:32.913Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T16:59:44.258Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T17:00:00.940Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T17:00:21.395Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T17:00:29.229Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T17:00:38.902Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T17:00:50.335Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T17:01:02.120Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T17:01:03.368Z] 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.
[2024-08-16T17:01:03.369Z] The best model improves the baseline by 14.52%.
[2024-08-16T17:01:04.917Z] Movies recommended for you:
[2024-08-16T17:01:04.917Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T17:01:04.917Z] There is no way to check that no silent failure occurred.
[2024-08-16T17:01:04.917Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (111890.402 ms) ======
[2024-08-16T17:01:04.917Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-16T17:01:05.327Z] GC before operation: completed in 280.572 ms, heap usage 172.490 MB -> 50.563 MB.
[2024-08-16T17:01:26.815Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T17:01:40.356Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T17:01:57.736Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T17:02:16.282Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T17:02:28.465Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T17:02:36.331Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T17:02:47.113Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T17:02:56.939Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T17:02:58.267Z] 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.
[2024-08-16T17:02:58.267Z] The best model improves the baseline by 14.52%.
[2024-08-16T17:02:59.207Z] Movies recommended for you:
[2024-08-16T17:02:59.207Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T17:02:59.207Z] There is no way to check that no silent failure occurred.
[2024-08-16T17:02:59.207Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (113657.326 ms) ======
[2024-08-16T17:02:59.207Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-16T17:02:59.207Z] GC before operation: completed in 315.056 ms, heap usage 312.802 MB -> 50.916 MB.
[2024-08-16T17:03:21.358Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T17:03:38.298Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T17:03:57.487Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T17:04:14.332Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T17:04:21.735Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T17:04:30.807Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T17:04:42.581Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T17:04:51.644Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T17:04:53.222Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-16T17:04:53.222Z] The best model improves the baseline by 14.52%.
[2024-08-16T17:04:53.645Z] Movies recommended for you:
[2024-08-16T17:04:53.645Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T17:04:53.645Z] There is no way to check that no silent failure occurred.
[2024-08-16T17:04:53.645Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (114597.208 ms) ======
[2024-08-16T17:04:53.645Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-16T17:04:54.106Z] GC before operation: completed in 131.763 ms, heap usage 209.775 MB -> 50.708 MB.
[2024-08-16T17:05:12.668Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T17:05:28.729Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T17:05:47.954Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T17:06:01.142Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T17:06:10.209Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T17:06:19.109Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T17:06:32.081Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T17:06:43.352Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T17:06:43.811Z] 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.
[2024-08-16T17:06:44.290Z] The best model improves the baseline by 14.52%.
[2024-08-16T17:06:44.290Z] Movies recommended for you:
[2024-08-16T17:06:44.290Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T17:06:44.290Z] There is no way to check that no silent failure occurred.
[2024-08-16T17:06:44.290Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (110402.439 ms) ======
[2024-08-16T17:06:44.290Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-16T17:06:44.865Z] GC before operation: completed in 356.706 ms, heap usage 492.590 MB -> 54.385 MB.
[2024-08-16T17:07:03.751Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T17:07:23.200Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T17:07:39.363Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T17:08:01.675Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T17:08:13.294Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T17:08:22.690Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T17:08:31.493Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T17:08:42.983Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T17:08:42.983Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-16T17:08:42.983Z] The best model improves the baseline by 14.52%.
[2024-08-16T17:08:42.983Z] Movies recommended for you:
[2024-08-16T17:08:42.983Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T17:08:42.983Z] There is no way to check that no silent failure occurred.
[2024-08-16T17:08:42.983Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (118293.959 ms) ======
[2024-08-16T17:08:42.983Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-16T17:08:43.354Z] GC before operation: completed in 251.593 ms, heap usage 121.160 MB -> 54.554 MB.
[2024-08-16T17:09:02.293Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T17:09:15.523Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T17:09:30.974Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T17:09:46.355Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T17:09:53.387Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T17:10:04.411Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T17:10:11.815Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T17:10:21.496Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T17:10:21.882Z] 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.
[2024-08-16T17:10:21.882Z] The best model improves the baseline by 14.52%.
[2024-08-16T17:10:22.392Z] Movies recommended for you:
[2024-08-16T17:10:22.392Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T17:10:22.392Z] There is no way to check that no silent failure occurred.
[2024-08-16T17:10:22.392Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (99238.339 ms) ======
[2024-08-16T17:10:22.392Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-16T17:10:22.929Z] GC before operation: completed in 135.330 ms, heap usage 140.776 MB -> 50.956 MB.
[2024-08-16T17:10:45.205Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T17:11:01.210Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T17:11:19.665Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T17:11:38.163Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T17:11:47.558Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T17:11:56.697Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T17:12:07.847Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T17:12:13.598Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T17:12:16.072Z] 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.
[2024-08-16T17:12:16.072Z] The best model improves the baseline by 14.52%.
[2024-08-16T17:12:16.537Z] Movies recommended for you:
[2024-08-16T17:12:16.537Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T17:12:16.537Z] There is no way to check that no silent failure occurred.
[2024-08-16T17:12:16.537Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (113779.312 ms) ======
[2024-08-16T17:12:16.537Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-16T17:12:16.537Z] GC before operation: completed in 230.883 ms, heap usage 422.186 MB -> 54.713 MB.
[2024-08-16T17:12:35.860Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T17:12:54.017Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T17:13:10.514Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T17:13:26.896Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T17:13:38.251Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T17:13:46.371Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T17:13:59.471Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T17:14:06.958Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T17:14:09.752Z] 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.
[2024-08-16T17:14:09.752Z] The best model improves the baseline by 14.52%.
[2024-08-16T17:14:10.197Z] Movies recommended for you:
[2024-08-16T17:14:10.197Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T17:14:10.197Z] There is no way to check that no silent failure occurred.
[2024-08-16T17:14:10.197Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (113464.990 ms) ======
[2024-08-16T17:14:10.197Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-16T17:14:10.197Z] GC before operation: completed in 137.834 ms, heap usage 95.383 MB -> 52.260 MB.
[2024-08-16T17:14:31.809Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T17:14:47.947Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T17:15:06.490Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T17:15:22.262Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T17:15:35.428Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T17:15:44.250Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T17:15:53.392Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T17:16:02.298Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T17:16:03.276Z] 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.
[2024-08-16T17:16:03.276Z] The best model improves the baseline by 14.52%.
[2024-08-16T17:16:03.775Z] Movies recommended for you:
[2024-08-16T17:16:03.775Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T17:16:03.775Z] There is no way to check that no silent failure occurred.
[2024-08-16T17:16:03.775Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (113358.897 ms) ======
[2024-08-16T17:16:03.775Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-16T17:16:03.775Z] GC before operation: completed in 183.849 ms, heap usage 156.989 MB -> 51.193 MB.
[2024-08-16T17:16:26.245Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T17:16:37.964Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T17:16:56.221Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T17:17:13.147Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T17:17:22.058Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T17:17:31.421Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T17:17:43.035Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T17:17:51.951Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T17:17:53.269Z] 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.
[2024-08-16T17:17:53.269Z] The best model improves the baseline by 14.52%.
[2024-08-16T17:17:54.978Z] Movies recommended for you:
[2024-08-16T17:17:54.978Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T17:17:54.978Z] There is no way to check that no silent failure occurred.
[2024-08-16T17:17:54.978Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (111211.893 ms) ======
[2024-08-16T17:17:54.978Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-16T17:17:55.381Z] GC before operation: completed in 314.716 ms, heap usage 234.557 MB -> 51.378 MB.
[2024-08-16T17:18:13.840Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T17:18:33.231Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T17:18:46.717Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T17:19:01.972Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T17:19:11.502Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T17:19:20.426Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T17:19:32.177Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T17:19:43.490Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T17:19:45.040Z] 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.
[2024-08-16T17:19:45.040Z] The best model improves the baseline by 14.52%.
[2024-08-16T17:19:45.040Z] Movies recommended for you:
[2024-08-16T17:19:45.040Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T17:19:45.040Z] There is no way to check that no silent failure occurred.
[2024-08-16T17:19:45.040Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (109796.326 ms) ======
[2024-08-16T17:19:45.040Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-16T17:19:45.570Z] GC before operation: completed in 272.334 ms, heap usage 286.552 MB -> 51.274 MB.
[2024-08-16T17:20:04.323Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T17:20:19.180Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T17:20:38.019Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T17:20:50.993Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T17:20:58.249Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T17:21:07.407Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T17:21:16.529Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T17:21:26.164Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T17:21:28.082Z] 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.
[2024-08-16T17:21:28.082Z] The best model improves the baseline by 14.52%.
[2024-08-16T17:21:28.082Z] Movies recommended for you:
[2024-08-16T17:21:28.082Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T17:21:28.082Z] There is no way to check that no silent failure occurred.
[2024-08-16T17:21:28.082Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (102715.175 ms) ======
[2024-08-16T17:21:28.082Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-16T17:21:28.082Z] GC before operation: completed in 200.846 ms, heap usage 209.347 MB -> 51.416 MB.
[2024-08-16T17:21:44.349Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T17:21:59.554Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T17:22:14.792Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T17:22:28.117Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T17:22:37.401Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T17:22:44.075Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T17:22:52.879Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T17:23:02.029Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T17:23:02.556Z] 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.
[2024-08-16T17:23:03.053Z] The best model improves the baseline by 14.52%.
[2024-08-16T17:23:03.512Z] Movies recommended for you:
[2024-08-16T17:23:03.512Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T17:23:03.512Z] There is no way to check that no silent failure occurred.
[2024-08-16T17:23:03.512Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (95316.816 ms) ======
[2024-08-16T17:23:03.512Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-16T17:23:03.955Z] GC before operation: completed in 133.185 ms, heap usage 331.761 MB -> 51.480 MB.
[2024-08-16T17:23:19.117Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T17:23:32.361Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T17:23:48.932Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T17:24:04.103Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T17:24:09.137Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T17:24:19.682Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T17:24:28.763Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T17:24:37.365Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T17:24:37.365Z] 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.
[2024-08-16T17:24:37.365Z] The best model improves the baseline by 14.52%.
[2024-08-16T17:24:37.365Z] Movies recommended for you:
[2024-08-16T17:24:37.365Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T17:24:37.365Z] There is no way to check that no silent failure occurred.
[2024-08-16T17:24:37.365Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (93475.452 ms) ======
[2024-08-16T17:24:37.365Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-16T17:24:37.365Z] GC before operation: completed in 185.861 ms, heap usage 94.183 MB -> 51.270 MB.
[2024-08-16T17:24:56.414Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T17:25:12.077Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T17:25:31.109Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T17:25:49.196Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T17:25:58.286Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T17:26:07.588Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T17:26:16.955Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T17:26:24.188Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T17:26:24.730Z] 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.
[2024-08-16T17:26:25.325Z] The best model improves the baseline by 14.52%.
[2024-08-16T17:26:26.903Z] Movies recommended for you:
[2024-08-16T17:26:26.903Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T17:26:26.903Z] There is no way to check that no silent failure occurred.
[2024-08-16T17:26:26.903Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (108648.478 ms) ======
[2024-08-16T17:26:26.903Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-16T17:26:26.903Z] GC before operation: completed in 426.342 ms, heap usage 213.249 MB -> 51.244 MB.
[2024-08-16T17:26:42.100Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T17:26:57.070Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T17:27:12.356Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T17:27:27.899Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T17:27:37.222Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T17:27:44.077Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T17:27:53.197Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T17:28:02.233Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T17:28:02.233Z] 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.
[2024-08-16T17:28:02.233Z] The best model improves the baseline by 14.52%.
[2024-08-16T17:28:02.963Z] Movies recommended for you:
[2024-08-16T17:28:02.963Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T17:28:02.963Z] There is no way to check that no silent failure occurred.
[2024-08-16T17:28:02.963Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (96079.091 ms) ======
[2024-08-16T17:28:02.963Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-16T17:28:03.938Z] GC before operation: completed in 1083.339 ms, heap usage 77.929 MB -> 54.656 MB.
[2024-08-16T17:28:19.477Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T17:28:38.110Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T17:28:51.263Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T17:29:07.062Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T17:29:14.272Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T17:29:23.368Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T17:29:32.587Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T17:29:41.932Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T17:29:42.386Z] 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.
[2024-08-16T17:29:42.386Z] The best model improves the baseline by 14.52%.
[2024-08-16T17:29:42.386Z] Movies recommended for you:
[2024-08-16T17:29:42.386Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T17:29:42.386Z] There is no way to check that no silent failure occurred.
[2024-08-16T17:29:42.386Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (98844.749 ms) ======
[2024-08-16T17:29:46.339Z] -----------------------------------
[2024-08-16T17:29:46.339Z] renaissance-movie-lens_0_PASSED
[2024-08-16T17:29:46.339Z] -----------------------------------
[2024-08-16T17:29:46.339Z]
[2024-08-16T17:29:46.339Z] TEST TEARDOWN:
[2024-08-16T17:29:46.339Z] Nothing to be done for teardown.
[2024-08-16T17:29:46.808Z] renaissance-movie-lens_0 Finish Time: Fri Aug 16 10:29:46 2024 Epoch Time (ms): 1723829386279