[2024-08-23T21:44:38.566Z] Running test renaissance-movie-lens_0 ... [2024-08-23T21:44:38.566Z] =============================================== [2024-08-23T21:44:38.566Z] renaissance-movie-lens_0 Start Time: Fri Aug 23 14:44:38 2024 Epoch Time (ms): 1724449478111 [2024-08-23T21:44:38.566Z] variation: NoOptions [2024-08-23T21:44:38.566Z] JVM_OPTIONS: [2024-08-23T21:44:38.566Z] { \ [2024-08-23T21:44:38.566Z] echo ""; echo "TEST SETUP:"; \ [2024-08-23T21:44:38.566Z] echo "Nothing to be done for setup."; \ [2024-08-23T21:44:38.566Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17244471692534/renaissance-movie-lens_0"; \ [2024-08-23T21:44:38.566Z] cd "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17244471692534/renaissance-movie-lens_0"; \ [2024-08-23T21:44:38.566Z] echo ""; echo "TESTING:"; \ [2024-08-23T21:44:38.566Z] "/Users/admin/workspace/workspace/Test_openjdk11_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_openjdk11_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17244471692534/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2024-08-23T21:44:38.566Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/..; rm -f -r "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17244471692534/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-08-23T21:44:38.566Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-08-23T21:44:38.566Z] echo "Nothing to be done for teardown."; \ [2024-08-23T21:44:38.566Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17244471692534/TestTargetResult"; [2024-08-23T21:44:38.566Z] [2024-08-23T21:44:38.566Z] TEST SETUP: [2024-08-23T21:44:38.566Z] Nothing to be done for setup. [2024-08-23T21:44:38.566Z] [2024-08-23T21:44:38.566Z] TESTING: [2024-08-23T21:44:51.009Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-08-23T21:44:54.885Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 3 (out of 3) threads. [2024-08-23T21:45:05.851Z] Got 100004 ratings from 671 users on 9066 movies. [2024-08-23T21:45:07.712Z] Training: 60056, validation: 20285, test: 19854 [2024-08-23T21:45:07.712Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-08-23T21:45:07.712Z] GC before operation: completed in 412.341 ms, heap usage 52.738 MB -> 36.640 MB. [2024-08-23T21:45:33.091Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-23T21:45:51.856Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-23T21:46:07.431Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-23T21:46:20.407Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-23T21:46:28.131Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-23T21:46:37.054Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-23T21:46:46.061Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-23T21:46:53.404Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-23T21:46:53.404Z] 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. [2024-08-23T21:46:53.404Z] The best model improves the baseline by 14.52%. [2024-08-23T21:46:53.929Z] Movies recommended for you: [2024-08-23T21:46:53.929Z] WARNING: This benchmark provides no result that can be validated. [2024-08-23T21:46:53.929Z] There is no way to check that no silent failure occurred. [2024-08-23T21:46:53.929Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (106136.463 ms) ====== [2024-08-23T21:46:53.929Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-08-23T21:46:54.372Z] GC before operation: completed in 287.192 ms, heap usage 189.748 MB -> 48.560 MB. [2024-08-23T21:47:09.892Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-23T21:47:22.956Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-23T21:47:36.054Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-23T21:47:51.361Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-23T21:47:57.441Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-23T21:48:04.678Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-23T21:48:13.425Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-23T21:48:20.933Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-23T21:48:22.774Z] 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. [2024-08-23T21:48:22.774Z] The best model improves the baseline by 14.52%. [2024-08-23T21:48:23.262Z] Movies recommended for you: [2024-08-23T21:48:23.262Z] WARNING: This benchmark provides no result that can be validated. [2024-08-23T21:48:23.262Z] There is no way to check that no silent failure occurred. [2024-08-23T21:48:23.262Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (88917.202 ms) ====== [2024-08-23T21:48:23.262Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-08-23T21:48:23.772Z] GC before operation: completed in 412.214 ms, heap usage 77.603 MB -> 52.197 MB. [2024-08-23T21:48:39.422Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-23T21:48:50.119Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-23T21:49:05.681Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-23T21:49:18.433Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-23T21:49:24.390Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-23T21:49:31.550Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-23T21:49:40.559Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-23T21:49:49.319Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-23T21:49:49.914Z] 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. [2024-08-23T21:49:49.914Z] The best model improves the baseline by 14.52%. [2024-08-23T21:49:49.914Z] Movies recommended for you: [2024-08-23T21:49:49.914Z] WARNING: This benchmark provides no result that can be validated. [2024-08-23T21:49:49.914Z] There is no way to check that no silent failure occurred. [2024-08-23T21:49:49.914Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (86360.782 ms) ====== [2024-08-23T21:49:49.914Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-08-23T21:49:50.434Z] GC before operation: completed in 351.146 ms, heap usage 495.449 MB -> 52.979 MB. [2024-08-23T21:50:03.903Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-23T21:50:16.587Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-23T21:50:31.557Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-23T21:50:40.353Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-23T21:50:48.098Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-23T21:50:55.383Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-23T21:51:02.627Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-23T21:51:08.762Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-23T21:51:09.707Z] 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. [2024-08-23T21:51:09.708Z] The best model improves the baseline by 14.52%. [2024-08-23T21:51:10.263Z] Movies recommended for you: [2024-08-23T21:51:10.263Z] WARNING: This benchmark provides no result that can be validated. [2024-08-23T21:51:10.263Z] There is no way to check that no silent failure occurred. [2024-08-23T21:51:10.263Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (79662.651 ms) ====== [2024-08-23T21:51:10.263Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-08-23T21:51:10.263Z] GC before operation: completed in 355.041 ms, heap usage 388.779 MB -> 52.813 MB. [2024-08-23T21:51:25.591Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-23T21:51:34.524Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-23T21:51:46.967Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-23T21:51:57.193Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-23T21:52:04.474Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-23T21:52:12.397Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-23T21:52:19.733Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-23T21:52:25.747Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-23T21:52:26.679Z] 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. [2024-08-23T21:52:26.679Z] The best model improves the baseline by 14.52%. [2024-08-23T21:52:27.183Z] Movies recommended for you: [2024-08-23T21:52:27.183Z] WARNING: This benchmark provides no result that can be validated. [2024-08-23T21:52:27.183Z] There is no way to check that no silent failure occurred. [2024-08-23T21:52:27.183Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (76670.797 ms) ====== [2024-08-23T21:52:27.183Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-08-23T21:52:27.183Z] GC before operation: completed in 270.596 ms, heap usage 125.001 MB -> 49.570 MB. [2024-08-23T21:52:41.632Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-23T21:52:53.853Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-23T21:53:06.321Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-23T21:53:21.072Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-23T21:53:28.193Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-23T21:53:35.670Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-23T21:53:44.436Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-23T21:53:50.677Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-23T21:53:51.715Z] 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. [2024-08-23T21:53:51.715Z] The best model improves the baseline by 14.52%. [2024-08-23T21:53:52.179Z] Movies recommended for you: [2024-08-23T21:53:52.179Z] WARNING: This benchmark provides no result that can be validated. [2024-08-23T21:53:52.179Z] There is no way to check that no silent failure occurred. [2024-08-23T21:53:52.179Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (85119.708 ms) ====== [2024-08-23T21:53:52.179Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-08-23T21:53:52.785Z] GC before operation: completed in 314.264 ms, heap usage 131.473 MB -> 49.515 MB. [2024-08-23T21:54:05.685Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-23T21:54:18.658Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-23T21:54:31.371Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-23T21:54:43.854Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-23T21:54:52.486Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-23T21:55:00.987Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-23T21:55:07.218Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-23T21:55:15.885Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-23T21:55:15.886Z] 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. [2024-08-23T21:55:15.886Z] The best model improves the baseline by 14.52%. [2024-08-23T21:55:16.304Z] Movies recommended for you: [2024-08-23T21:55:16.304Z] WARNING: This benchmark provides no result that can be validated. [2024-08-23T21:55:16.304Z] There is no way to check that no silent failure occurred. [2024-08-23T21:55:16.304Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (83554.536 ms) ====== [2024-08-23T21:55:16.304Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-08-23T21:55:16.736Z] GC before operation: completed in 350.382 ms, heap usage 382.756 MB -> 53.207 MB. [2024-08-23T21:55:31.740Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-23T21:55:44.372Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-23T21:55:56.754Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-23T21:56:09.099Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-23T21:56:17.327Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-23T21:56:23.466Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-23T21:56:30.589Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-23T21:56:37.710Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-23T21:56:37.710Z] 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. [2024-08-23T21:56:38.211Z] The best model improves the baseline by 14.52%. [2024-08-23T21:56:38.786Z] Movies recommended for you: [2024-08-23T21:56:38.786Z] WARNING: This benchmark provides no result that can be validated. [2024-08-23T21:56:38.786Z] There is no way to check that no silent failure occurred. [2024-08-23T21:56:38.786Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (81781.026 ms) ====== [2024-08-23T21:56:38.786Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-08-23T21:56:38.786Z] GC before operation: completed in 353.943 ms, heap usage 447.405 MB -> 53.443 MB. [2024-08-23T21:56:54.267Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-23T21:57:06.923Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-23T21:57:21.958Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-23T21:57:32.500Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-23T21:57:39.577Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-23T21:57:46.967Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-23T21:57:53.907Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-23T21:57:59.867Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-23T21:58:00.491Z] 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. [2024-08-23T21:58:00.491Z] The best model improves the baseline by 14.52%. [2024-08-23T21:58:00.945Z] Movies recommended for you: [2024-08-23T21:58:00.945Z] WARNING: This benchmark provides no result that can be validated. [2024-08-23T21:58:00.945Z] There is no way to check that no silent failure occurred. [2024-08-23T21:58:00.945Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (81983.048 ms) ====== [2024-08-23T21:58:00.945Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-08-23T21:58:01.332Z] GC before operation: completed in 336.969 ms, heap usage 334.104 MB -> 50.005 MB. [2024-08-23T21:58:16.534Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-23T21:58:26.844Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-23T21:58:41.816Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-23T21:58:52.211Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-23T21:58:59.410Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-23T21:59:06.821Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-23T21:59:14.152Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-23T21:59:22.906Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-23T21:59:23.423Z] 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. [2024-08-23T21:59:23.423Z] The best model improves the baseline by 14.52%. [2024-08-23T21:59:23.423Z] Movies recommended for you: [2024-08-23T21:59:23.423Z] WARNING: This benchmark provides no result that can be validated. [2024-08-23T21:59:23.423Z] There is no way to check that no silent failure occurred. [2024-08-23T21:59:23.423Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (82271.963 ms) ====== [2024-08-23T21:59:23.423Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-08-23T21:59:23.924Z] GC before operation: completed in 371.319 ms, heap usage 114.260 MB -> 50.688 MB. [2024-08-23T21:59:39.463Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-23T21:59:50.432Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-23T22:00:03.063Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-23T22:00:11.755Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-23T22:00:20.230Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-23T22:00:27.130Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-23T22:00:34.310Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-23T22:00:43.154Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-23T22:00:43.154Z] 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. [2024-08-23T22:00:43.154Z] The best model improves the baseline by 14.52%. [2024-08-23T22:00:43.154Z] Movies recommended for you: [2024-08-23T22:00:43.154Z] WARNING: This benchmark provides no result that can be validated. [2024-08-23T22:00:43.154Z] There is no way to check that no silent failure occurred. [2024-08-23T22:00:43.154Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (79417.105 ms) ====== [2024-08-23T22:00:43.154Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-08-23T22:00:43.674Z] GC before operation: completed in 251.633 ms, heap usage 262.901 MB -> 49.773 MB. [2024-08-23T22:00:56.372Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-23T22:01:08.601Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-23T22:01:19.212Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-23T22:01:29.499Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-23T22:01:36.637Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-23T22:01:44.081Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-23T22:01:49.781Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-23T22:01:55.815Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-23T22:01:57.318Z] 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. [2024-08-23T22:01:57.318Z] The best model improves the baseline by 14.52%. [2024-08-23T22:01:57.748Z] Movies recommended for you: [2024-08-23T22:01:57.748Z] WARNING: This benchmark provides no result that can be validated. [2024-08-23T22:01:57.748Z] There is no way to check that no silent failure occurred. [2024-08-23T22:01:57.748Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (74159.896 ms) ====== [2024-08-23T22:01:57.749Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-08-23T22:01:57.749Z] GC before operation: completed in 219.012 ms, heap usage 306.453 MB -> 50.029 MB. [2024-08-23T22:02:13.373Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-23T22:02:25.899Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-23T22:02:36.511Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-23T22:02:48.672Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-23T22:02:56.116Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-23T22:03:01.866Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-23T22:03:10.779Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-23T22:03:17.727Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-23T22:03:17.727Z] 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. [2024-08-23T22:03:18.229Z] The best model improves the baseline by 14.52%. [2024-08-23T22:03:18.748Z] Movies recommended for you: [2024-08-23T22:03:18.748Z] WARNING: This benchmark provides no result that can be validated. [2024-08-23T22:03:18.748Z] There is no way to check that no silent failure occurred. [2024-08-23T22:03:18.748Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (80594.545 ms) ====== [2024-08-23T22:03:18.748Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-08-23T22:03:18.748Z] GC before operation: completed in 275.386 ms, heap usage 361.064 MB -> 53.457 MB. [2024-08-23T22:03:31.190Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-23T22:03:43.210Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-23T22:03:53.518Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-23T22:04:04.611Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-23T22:04:11.721Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-23T22:04:17.561Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-23T22:04:23.516Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-23T22:04:30.369Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-23T22:04:31.333Z] 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. [2024-08-23T22:04:31.333Z] The best model improves the baseline by 14.52%. [2024-08-23T22:04:31.775Z] Movies recommended for you: [2024-08-23T22:04:31.775Z] WARNING: This benchmark provides no result that can be validated. [2024-08-23T22:04:31.775Z] There is no way to check that no silent failure occurred. [2024-08-23T22:04:31.775Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (72845.032 ms) ====== [2024-08-23T22:04:31.775Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-08-23T22:04:31.775Z] GC before operation: completed in 350.981 ms, heap usage 137.590 MB -> 49.728 MB. [2024-08-23T22:04:47.004Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-23T22:04:59.694Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-23T22:05:12.134Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-23T22:05:21.171Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-23T22:05:28.377Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-23T22:05:35.463Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-23T22:05:43.110Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-23T22:05:50.163Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-23T22:05:50.628Z] 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. [2024-08-23T22:05:50.628Z] The best model improves the baseline by 14.52%. [2024-08-23T22:05:51.166Z] Movies recommended for you: [2024-08-23T22:05:51.166Z] WARNING: This benchmark provides no result that can be validated. [2024-08-23T22:05:51.166Z] There is no way to check that no silent failure occurred. [2024-08-23T22:05:51.166Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (79220.975 ms) ====== [2024-08-23T22:05:51.166Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-08-23T22:05:51.850Z] GC before operation: completed in 361.764 ms, heap usage 74.177 MB -> 51.084 MB. [2024-08-23T22:06:05.110Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-23T22:06:20.636Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-23T22:06:32.886Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-23T22:06:44.717Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-23T22:06:51.110Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-23T22:06:58.206Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-23T22:07:05.783Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-23T22:07:11.716Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-23T22:07:12.680Z] 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. [2024-08-23T22:07:12.680Z] The best model improves the baseline by 14.52%. [2024-08-23T22:07:13.165Z] Movies recommended for you: [2024-08-23T22:07:13.165Z] WARNING: This benchmark provides no result that can be validated. [2024-08-23T22:07:13.165Z] There is no way to check that no silent failure occurred. [2024-08-23T22:07:13.165Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (81555.976 ms) ====== [2024-08-23T22:07:13.165Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-08-23T22:07:13.165Z] GC before operation: completed in 254.983 ms, heap usage 169.169 MB -> 50.051 MB. [2024-08-23T22:07:25.797Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-23T22:07:38.101Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-23T22:07:50.354Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-23T22:08:03.029Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-23T22:08:08.316Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-23T22:08:15.160Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-23T22:08:22.327Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-23T22:08:27.141Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-23T22:08:27.633Z] 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. [2024-08-23T22:08:28.187Z] The best model improves the baseline by 14.52%. [2024-08-23T22:08:28.187Z] Movies recommended for you: [2024-08-23T22:08:28.187Z] WARNING: This benchmark provides no result that can be validated. [2024-08-23T22:08:28.187Z] There is no way to check that no silent failure occurred. [2024-08-23T22:08:28.187Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (74897.556 ms) ====== [2024-08-23T22:08:28.187Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-08-23T22:08:29.147Z] GC before operation: completed in 328.919 ms, heap usage 93.865 MB -> 51.504 MB. [2024-08-23T22:08:44.162Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-23T22:08:56.174Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-23T22:09:07.295Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-23T22:09:20.414Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-23T22:09:26.242Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-23T22:09:33.323Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-23T22:09:40.902Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-23T22:09:48.067Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-23T22:09:48.958Z] 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. [2024-08-23T22:09:48.958Z] The best model improves the baseline by 14.52%. [2024-08-23T22:09:49.436Z] Movies recommended for you: [2024-08-23T22:09:49.436Z] WARNING: This benchmark provides no result that can be validated. [2024-08-23T22:09:49.436Z] There is no way to check that no silent failure occurred. [2024-08-23T22:09:49.436Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (80874.597 ms) ====== [2024-08-23T22:09:49.436Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-08-23T22:09:49.963Z] GC before operation: completed in 434.718 ms, heap usage 410.383 MB -> 53.410 MB. [2024-08-23T22:10:02.521Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-23T22:10:17.417Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-23T22:10:29.932Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-23T22:10:39.137Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-23T22:10:47.691Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-23T22:10:52.586Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-23T22:10:58.372Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-23T22:11:05.529Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-23T22:11:05.950Z] 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. [2024-08-23T22:11:05.950Z] The best model improves the baseline by 14.52%. [2024-08-23T22:11:05.950Z] Movies recommended for you: [2024-08-23T22:11:05.950Z] WARNING: This benchmark provides no result that can be validated. [2024-08-23T22:11:05.950Z] There is no way to check that no silent failure occurred. [2024-08-23T22:11:05.950Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (76301.147 ms) ====== [2024-08-23T22:11:05.950Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-08-23T22:11:06.467Z] GC before operation: completed in 283.944 ms, heap usage 324.815 MB -> 50.286 MB. [2024-08-23T22:11:18.781Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-23T22:11:31.341Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-23T22:11:43.551Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-23T22:11:53.892Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-23T22:11:59.407Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-23T22:12:06.668Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-23T22:12:14.168Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-23T22:12:20.245Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-23T22:12:20.904Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2024-08-23T22:12:20.904Z] The best model improves the baseline by 14.52%. [2024-08-23T22:12:21.384Z] Movies recommended for you: [2024-08-23T22:12:21.384Z] WARNING: This benchmark provides no result that can be validated. [2024-08-23T22:12:21.384Z] There is no way to check that no silent failure occurred. [2024-08-23T22:12:21.384Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (74943.301 ms) ====== [2024-08-23T22:12:22.909Z] ----------------------------------- [2024-08-23T22:12:22.909Z] renaissance-movie-lens_0_PASSED [2024-08-23T22:12:22.909Z] ----------------------------------- [2024-08-23T22:12:22.909Z] [2024-08-23T22:12:22.909Z] TEST TEARDOWN: [2024-08-23T22:12:22.909Z] Nothing to be done for teardown. [2024-08-23T22:12:23.311Z] renaissance-movie-lens_0 Finish Time: Fri Aug 23 15:12:22 2024 Epoch Time (ms): 1724451142619