[2024-08-16T19:29:21.439Z] Running test renaissance-movie-lens_0 ... [2024-08-16T19:29:22.118Z] =============================================== [2024-08-16T19:29:22.118Z] renaissance-movie-lens_0 Start Time: Fri Aug 16 19:29:21 2024 Epoch Time (ms): 1723836561924 [2024-08-16T19:29:22.441Z] variation: NoOptions [2024-08-16T19:29:22.441Z] JVM_OPTIONS: [2024-08-16T19:29:22.441Z] { \ [2024-08-16T19:29:22.441Z] echo ""; echo "TEST SETUP:"; \ [2024-08-16T19:29:22.441Z] echo "Nothing to be done for setup."; \ [2024-08-16T19:29:22.441Z] mkdir -p "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows_testList_0/aqa-tests/\\TKG\\output_17238356015779\\renaissance-movie-lens_0"; \ [2024-08-16T19:29:22.441Z] cd "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows_testList_0/aqa-tests/\\TKG\\output_17238356015779\\renaissance-movie-lens_0"; \ [2024-08-16T19:29:22.441Z] echo ""; echo "TESTING:"; \ [2024-08-16T19:29:22.441Z] "c:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows_testList_0/jdkbinary/j2sdk-image\\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 "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows_testList_0/aqa-tests///..//jvmtest\\perf\\renaissance\\renaissance.jar" --json ""C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows_testList_0/aqa-tests/\\TKG\\output_17238356015779\\renaissance-movie-lens_0"\\movie-lens.json" movie-lens; \ [2024-08-16T19:29:22.441Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows_testList_0/aqa-tests/; rm -f -r "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows_testList_0/aqa-tests/\\TKG\\output_17238356015779\\renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-08-16T19:29:22.441Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-08-16T19:29:22.441Z] echo "Nothing to be done for teardown."; \ [2024-08-16T19:29:22.441Z] } 2>&1 | tee -a "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows_testList_0/aqa-tests/\\TKG\\output_17238356015779\\TestTargetResult"; [2024-08-16T19:29:22.441Z] [2024-08-16T19:29:22.441Z] TEST SETUP: [2024-08-16T19:29:22.441Z] Nothing to be done for setup. [2024-08-16T19:29:22.441Z] [2024-08-16T19:29:22.441Z] TESTING: [2024-08-16T19:29:33.100Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-08-16T19:29:34.697Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2024-08-16T19:29:37.762Z] Got 100004 ratings from 671 users on 9066 movies. [2024-08-16T19:29:37.762Z] Training: 60056, validation: 20285, test: 19854 [2024-08-16T19:29:37.762Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-08-16T19:29:37.762Z] GC before operation: completed in 50.713 ms, heap usage 57.681 MB -> 37.494 MB. [2024-08-16T19:29:48.554Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-16T19:29:57.290Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-16T19:30:03.033Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-16T19:30:10.196Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-16T19:30:13.856Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-16T19:30:17.668Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-16T19:30:22.314Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-16T19:30:26.042Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-16T19:30:26.042Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-16T19:30:26.042Z] The best model improves the baseline by 14.52%. [2024-08-16T19:30:26.374Z] Movies recommended for you: [2024-08-16T19:30:26.374Z] WARNING: This benchmark provides no result that can be validated. [2024-08-16T19:30:26.374Z] There is no way to check that no silent failure occurred. [2024-08-16T19:30:26.374Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (48449.732 ms) ====== [2024-08-16T19:30:26.374Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-08-16T19:30:26.374Z] GC before operation: completed in 69.107 ms, heap usage 228.562 MB -> 56.499 MB. [2024-08-16T19:30:33.482Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-16T19:30:40.559Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-16T19:30:46.305Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-16T19:30:52.113Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-16T19:30:55.778Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-16T19:30:59.446Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-16T19:31:04.065Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-16T19:31:07.725Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-16T19:31:07.725Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-16T19:31:07.725Z] The best model improves the baseline by 14.52%. [2024-08-16T19:31:08.063Z] Movies recommended for you: [2024-08-16T19:31:08.063Z] WARNING: This benchmark provides no result that can be validated. [2024-08-16T19:31:08.063Z] There is no way to check that no silent failure occurred. [2024-08-16T19:31:08.063Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (41703.585 ms) ====== [2024-08-16T19:31:08.063Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-08-16T19:31:08.063Z] GC before operation: completed in 59.682 ms, heap usage 245.022 MB -> 50.114 MB. [2024-08-16T19:31:15.155Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-16T19:31:20.902Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-16T19:31:26.664Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-16T19:31:33.735Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-16T19:31:36.599Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-16T19:31:40.248Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-16T19:31:43.933Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-16T19:31:46.779Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-16T19:31:47.459Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-16T19:31:47.459Z] The best model improves the baseline by 14.52%. [2024-08-16T19:31:47.459Z] Movies recommended for you: [2024-08-16T19:31:47.459Z] WARNING: This benchmark provides no result that can be validated. [2024-08-16T19:31:47.459Z] There is no way to check that no silent failure occurred. [2024-08-16T19:31:47.459Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (39494.930 ms) ====== [2024-08-16T19:31:47.459Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-08-16T19:31:47.459Z] GC before operation: completed in 57.878 ms, heap usage 200.994 MB -> 50.373 MB. [2024-08-16T19:31:54.556Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-16T19:32:00.298Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-16T19:32:07.393Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-16T19:32:13.162Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-16T19:32:16.095Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-16T19:32:19.769Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-16T19:32:23.452Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-16T19:32:27.135Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-16T19:32:27.135Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-16T19:32:27.135Z] The best model improves the baseline by 14.52%. [2024-08-16T19:32:27.135Z] Movies recommended for you: [2024-08-16T19:32:27.135Z] WARNING: This benchmark provides no result that can be validated. [2024-08-16T19:32:27.135Z] There is no way to check that no silent failure occurred. [2024-08-16T19:32:27.135Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (39648.301 ms) ====== [2024-08-16T19:32:27.135Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-08-16T19:32:27.135Z] GC before operation: completed in 59.178 ms, heap usage 232.185 MB -> 50.670 MB. [2024-08-16T19:32:34.239Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-16T19:32:39.999Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-16T19:32:47.103Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-16T19:32:52.870Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-16T19:32:55.726Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-16T19:32:59.398Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-16T19:33:03.050Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-16T19:33:06.709Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-16T19:33:07.110Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-16T19:33:07.110Z] The best model improves the baseline by 14.52%. [2024-08-16T19:33:07.110Z] Movies recommended for you: [2024-08-16T19:33:07.110Z] WARNING: This benchmark provides no result that can be validated. [2024-08-16T19:33:07.110Z] There is no way to check that no silent failure occurred. [2024-08-16T19:33:07.110Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (39891.165 ms) ====== [2024-08-16T19:33:07.110Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-08-16T19:33:07.110Z] GC before operation: completed in 62.851 ms, heap usage 180.682 MB -> 50.867 MB. [2024-08-16T19:33:14.194Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-16T19:33:19.947Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-16T19:33:25.742Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-16T19:33:32.852Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-16T19:33:35.725Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-16T19:33:39.372Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-16T19:33:43.036Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-16T19:33:45.894Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-16T19:33:46.241Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-16T19:33:46.241Z] The best model improves the baseline by 14.52%. [2024-08-16T19:33:46.241Z] Movies recommended for you: [2024-08-16T19:33:46.241Z] WARNING: This benchmark provides no result that can be validated. [2024-08-16T19:33:46.241Z] There is no way to check that no silent failure occurred. [2024-08-16T19:33:46.241Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (39142.316 ms) ====== [2024-08-16T19:33:46.241Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-08-16T19:33:46.567Z] GC before operation: completed in 65.192 ms, heap usage 65.973 MB -> 50.671 MB. [2024-08-16T19:33:52.325Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-16T19:33:59.426Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-16T19:34:05.224Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-16T19:34:10.973Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-16T19:34:14.624Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-16T19:34:18.294Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-16T19:34:21.964Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-16T19:34:25.637Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-16T19:34:25.637Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-16T19:34:25.637Z] The best model improves the baseline by 14.52%. [2024-08-16T19:34:25.637Z] Movies recommended for you: [2024-08-16T19:34:25.637Z] WARNING: This benchmark provides no result that can be validated. [2024-08-16T19:34:25.637Z] There is no way to check that no silent failure occurred. [2024-08-16T19:34:25.637Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (39266.791 ms) ====== [2024-08-16T19:34:25.637Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-08-16T19:34:25.637Z] GC before operation: completed in 60.016 ms, heap usage 148.892 MB -> 50.947 MB. [2024-08-16T19:34:32.749Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-16T19:34:38.496Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-16T19:34:44.257Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-16T19:34:50.000Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-16T19:34:53.654Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-16T19:34:57.333Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-16T19:35:00.990Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-16T19:35:04.659Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-16T19:35:04.659Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-16T19:35:04.659Z] The best model improves the baseline by 14.52%. [2024-08-16T19:35:04.659Z] Movies recommended for you: [2024-08-16T19:35:04.659Z] WARNING: This benchmark provides no result that can be validated. [2024-08-16T19:35:04.659Z] There is no way to check that no silent failure occurred. [2024-08-16T19:35:04.659Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (38952.203 ms) ====== [2024-08-16T19:35:04.659Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-08-16T19:35:04.659Z] GC before operation: completed in 58.228 ms, heap usage 347.121 MB -> 51.418 MB. [2024-08-16T19:35:11.749Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-16T19:35:17.516Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-16T19:35:23.297Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-16T19:35:29.025Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-16T19:35:32.688Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-16T19:35:36.345Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-16T19:35:40.003Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-16T19:35:43.657Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-16T19:35:43.657Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-16T19:35:43.657Z] The best model improves the baseline by 14.52%. [2024-08-16T19:35:43.657Z] Movies recommended for you: [2024-08-16T19:35:43.657Z] WARNING: This benchmark provides no result that can be validated. [2024-08-16T19:35:43.657Z] There is no way to check that no silent failure occurred. [2024-08-16T19:35:43.657Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (38916.174 ms) ====== [2024-08-16T19:35:43.657Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-08-16T19:35:43.657Z] GC before operation: completed in 57.467 ms, heap usage 212.086 MB -> 51.137 MB. [2024-08-16T19:35:50.759Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-16T19:35:56.524Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-16T19:36:02.310Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-16T19:36:08.049Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-16T19:36:11.719Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-16T19:36:15.402Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-16T19:36:19.063Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-16T19:36:21.937Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-16T19:36:22.259Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-16T19:36:22.259Z] The best model improves the baseline by 14.52%. [2024-08-16T19:36:22.611Z] Movies recommended for you: [2024-08-16T19:36:22.611Z] WARNING: This benchmark provides no result that can be validated. [2024-08-16T19:36:22.611Z] There is no way to check that no silent failure occurred. [2024-08-16T19:36:22.611Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (38803.083 ms) ====== [2024-08-16T19:36:22.611Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-08-16T19:36:22.611Z] GC before operation: completed in 56.784 ms, heap usage 88.530 MB -> 51.102 MB. [2024-08-16T19:36:28.360Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-16T19:36:35.462Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-16T19:36:41.237Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-16T19:36:46.995Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-16T19:36:49.856Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-16T19:36:53.501Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-16T19:36:57.158Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-16T19:37:00.819Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-16T19:37:00.820Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-16T19:37:00.820Z] The best model improves the baseline by 14.52%. [2024-08-16T19:37:00.820Z] Movies recommended for you: [2024-08-16T19:37:00.820Z] WARNING: This benchmark provides no result that can be validated. [2024-08-16T19:37:00.820Z] There is no way to check that no silent failure occurred. [2024-08-16T19:37:00.820Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (38259.815 ms) ====== [2024-08-16T19:37:00.820Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-08-16T19:37:00.820Z] GC before operation: completed in 58.841 ms, heap usage 202.417 MB -> 50.988 MB. [2024-08-16T19:37:06.565Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-16T19:37:13.699Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-16T19:37:19.476Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-16T19:37:25.216Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-16T19:37:28.888Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-16T19:37:31.745Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-16T19:37:35.421Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-16T19:37:39.140Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-16T19:37:39.140Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-16T19:37:39.462Z] The best model improves the baseline by 14.52%. [2024-08-16T19:37:39.462Z] Movies recommended for you: [2024-08-16T19:37:39.462Z] WARNING: This benchmark provides no result that can be validated. [2024-08-16T19:37:39.462Z] There is no way to check that no silent failure occurred. [2024-08-16T19:37:39.462Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (38491.861 ms) ====== [2024-08-16T19:37:39.462Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-08-16T19:37:39.462Z] GC before operation: completed in 58.491 ms, heap usage 159.626 MB -> 51.166 MB. [2024-08-16T19:37:46.558Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-16T19:37:52.310Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-16T19:37:58.133Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-16T19:38:03.881Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-16T19:38:07.556Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-16T19:38:11.255Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-16T19:38:14.945Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-16T19:38:17.806Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-16T19:38:18.509Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-16T19:38:18.509Z] The best model improves the baseline by 14.52%. [2024-08-16T19:38:18.509Z] Movies recommended for you: [2024-08-16T19:38:18.509Z] WARNING: This benchmark provides no result that can be validated. [2024-08-16T19:38:18.509Z] There is no way to check that no silent failure occurred. [2024-08-16T19:38:18.509Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (38987.864 ms) ====== [2024-08-16T19:38:18.509Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-08-16T19:38:18.509Z] GC before operation: completed in 58.888 ms, heap usage 268.683 MB -> 51.448 MB. [2024-08-16T19:38:24.284Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-16T19:38:31.368Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-16T19:38:37.131Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-16T19:38:42.873Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-16T19:38:46.538Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-16T19:38:49.390Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-16T19:38:53.065Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-16T19:38:56.750Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-16T19:38:56.750Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-16T19:38:56.750Z] The best model improves the baseline by 14.52%. [2024-08-16T19:38:57.076Z] Movies recommended for you: [2024-08-16T19:38:57.076Z] WARNING: This benchmark provides no result that can be validated. [2024-08-16T19:38:57.076Z] There is no way to check that no silent failure occurred. [2024-08-16T19:38:57.076Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (38464.034 ms) ====== [2024-08-16T19:38:57.076Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-08-16T19:38:57.076Z] GC before operation: completed in 63.690 ms, heap usage 74.014 MB -> 50.948 MB. [2024-08-16T19:39:02.850Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-16T19:39:09.961Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-16T19:39:15.713Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-16T19:39:21.455Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-16T19:39:24.307Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-16T19:39:27.966Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-16T19:39:31.633Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-16T19:39:34.501Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-16T19:39:35.184Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-16T19:39:35.184Z] The best model improves the baseline by 14.52%. [2024-08-16T19:39:35.184Z] Movies recommended for you: [2024-08-16T19:39:35.184Z] WARNING: This benchmark provides no result that can be validated. [2024-08-16T19:39:35.184Z] There is no way to check that no silent failure occurred. [2024-08-16T19:39:35.185Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (38177.542 ms) ====== [2024-08-16T19:39:35.185Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-08-16T19:39:35.185Z] GC before operation: completed in 59.853 ms, heap usage 187.864 MB -> 51.351 MB. [2024-08-16T19:39:42.274Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-16T19:39:48.041Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-16T19:39:53.816Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-16T19:39:59.565Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-16T19:40:03.248Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-16T19:40:06.100Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-16T19:40:10.733Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-16T19:40:13.605Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-16T19:40:13.937Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-16T19:40:13.937Z] The best model improves the baseline by 14.52%. [2024-08-16T19:40:13.937Z] Movies recommended for you: [2024-08-16T19:40:13.938Z] WARNING: This benchmark provides no result that can be validated. [2024-08-16T19:40:13.938Z] There is no way to check that no silent failure occurred. [2024-08-16T19:40:13.938Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (38749.446 ms) ====== [2024-08-16T19:40:13.938Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-08-16T19:40:14.260Z] GC before operation: completed in 62.727 ms, heap usage 344.668 MB -> 51.559 MB. [2024-08-16T19:40:20.029Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-16T19:40:25.808Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-16T19:40:32.901Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-16T19:40:38.639Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-16T19:40:41.484Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-16T19:40:45.137Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-16T19:40:48.831Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-16T19:40:52.552Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-16T19:40:52.552Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-16T19:40:52.552Z] The best model improves the baseline by 14.52%. [2024-08-16T19:40:52.552Z] Movies recommended for you: [2024-08-16T19:40:52.552Z] WARNING: This benchmark provides no result that can be validated. [2024-08-16T19:40:52.552Z] There is no way to check that no silent failure occurred. [2024-08-16T19:40:52.552Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (38548.401 ms) ====== [2024-08-16T19:40:52.552Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-08-16T19:40:52.876Z] GC before operation: completed in 62.482 ms, heap usage 210.197 MB -> 51.209 MB. [2024-08-16T19:40:58.620Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-16T19:41:05.745Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-16T19:41:11.488Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-16T19:41:17.235Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-16T19:41:20.894Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-16T19:41:24.568Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-16T19:41:28.247Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-16T19:41:31.105Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-16T19:41:31.426Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-16T19:41:31.745Z] The best model improves the baseline by 14.52%. [2024-08-16T19:41:31.745Z] Movies recommended for you: [2024-08-16T19:41:31.745Z] WARNING: This benchmark provides no result that can be validated. [2024-08-16T19:41:31.745Z] There is no way to check that no silent failure occurred. [2024-08-16T19:41:31.745Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (39041.442 ms) ====== [2024-08-16T19:41:31.745Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-08-16T19:41:31.745Z] GC before operation: completed in 59.284 ms, heap usage 133.543 MB -> 51.216 MB. [2024-08-16T19:41:37.597Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-16T19:41:44.677Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-16T19:41:50.417Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-16T19:41:56.164Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-16T19:41:59.837Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-16T19:42:03.484Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-16T19:42:07.142Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-16T19:42:10.006Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-16T19:42:10.688Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-16T19:42:10.688Z] The best model improves the baseline by 14.52%. [2024-08-16T19:42:10.688Z] Movies recommended for you: [2024-08-16T19:42:10.688Z] WARNING: This benchmark provides no result that can be validated. [2024-08-16T19:42:10.688Z] There is no way to check that no silent failure occurred. [2024-08-16T19:42:10.688Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (38834.355 ms) ====== [2024-08-16T19:42:10.688Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-08-16T19:42:10.688Z] GC before operation: completed in 60.559 ms, heap usage 276.953 MB -> 51.505 MB. [2024-08-16T19:42:16.467Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-16T19:42:23.576Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-16T19:42:29.328Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-16T19:42:35.089Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-16T19:42:38.767Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-16T19:42:42.423Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-16T19:42:46.082Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-16T19:42:48.932Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-16T19:42:49.272Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-16T19:42:49.272Z] The best model improves the baseline by 14.52%. [2024-08-16T19:42:49.592Z] Movies recommended for you: [2024-08-16T19:42:49.592Z] WARNING: This benchmark provides no result that can be validated. [2024-08-16T19:42:49.592Z] There is no way to check that no silent failure occurred. [2024-08-16T19:42:49.592Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (38725.829 ms) ====== [2024-08-16T19:42:49.916Z] ----------------------------------- [2024-08-16T19:42:49.916Z] renaissance-movie-lens_0_PASSED [2024-08-16T19:42:49.916Z] ----------------------------------- [2024-08-16T19:42:50.245Z] [2024-08-16T19:42:50.245Z] TEST TEARDOWN: [2024-08-16T19:42:50.245Z] Nothing to be done for teardown. [2024-08-16T19:42:50.923Z] renaissance-movie-lens_0 Finish Time: Fri Aug 16 19:42:50 2024 Epoch Time (ms): 1723837370616