[2024-11-21T16:45:54.467Z] Running test renaissance-movie-lens_0 ... [2024-11-21T16:45:54.467Z] =============================================== [2024-11-21T16:45:54.467Z] renaissance-movie-lens_0 Start Time: Thu Nov 21 08:45:54 2024 Epoch Time (ms): 1732207554195 [2024-11-21T16:45:54.467Z] variation: NoOptions [2024-11-21T16:45:54.467Z] JVM_OPTIONS: [2024-11-21T16:45:54.467Z] { \ [2024-11-21T16:45:54.467Z] echo ""; echo "TEST SETUP:"; \ [2024-11-21T16:45:54.467Z] echo "Nothing to be done for setup."; \ [2024-11-21T16:45:54.467Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17322063229215/renaissance-movie-lens_0"; \ [2024-11-21T16:45:54.467Z] cd "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17322063229215/renaissance-movie-lens_0"; \ [2024-11-21T16:45:54.467Z] echo ""; echo "TESTING:"; \ [2024-11-21T16:45:54.467Z] "/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_17322063229215/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2024-11-21T16:45:54.467Z] 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_17322063229215/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-11-21T16:45:54.467Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-11-21T16:45:54.467Z] echo "Nothing to be done for teardown."; \ [2024-11-21T16:45:54.467Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17322063229215/TestTargetResult"; [2024-11-21T16:45:54.467Z] [2024-11-21T16:45:54.467Z] TEST SETUP: [2024-11-21T16:45:54.467Z] Nothing to be done for setup. [2024-11-21T16:45:54.467Z] [2024-11-21T16:45:54.467Z] TESTING: [2024-11-21T16:46:00.146Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-11-21T16:46:02.837Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 3 (out of 3) threads. [2024-11-21T16:46:08.663Z] Got 100004 ratings from 671 users on 9066 movies. [2024-11-21T16:46:08.663Z] Training: 60056, validation: 20285, test: 19854 [2024-11-21T16:46:08.663Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-11-21T16:46:08.663Z] GC before operation: completed in 102.200 ms, heap usage 153.581 MB -> 36.607 MB. [2024-11-21T16:46:21.081Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-21T16:46:29.490Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-21T16:46:36.418Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-21T16:46:42.842Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-21T16:46:47.476Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-21T16:46:52.044Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-21T16:46:55.587Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-21T16:46:59.308Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-21T16:46:59.779Z] 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. [2024-11-21T16:46:59.779Z] The best model improves the baseline by 14.52%. [2024-11-21T16:46:59.779Z] Movies recommended for you: [2024-11-21T16:46:59.779Z] WARNING: This benchmark provides no result that can be validated. [2024-11-21T16:46:59.779Z] There is no way to check that no silent failure occurred. [2024-11-21T16:46:59.779Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (51104.482 ms) ====== [2024-11-21T16:46:59.779Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-11-21T16:47:00.268Z] GC before operation: completed in 225.319 ms, heap usage 466.027 MB -> 50.624 MB. [2024-11-21T16:47:07.345Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-21T16:47:13.140Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-21T16:47:19.984Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-21T16:47:24.668Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-21T16:47:28.242Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-21T16:47:31.089Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-21T16:47:35.669Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-21T16:47:38.507Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-21T16:47:38.938Z] 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. [2024-11-21T16:47:38.938Z] The best model improves the baseline by 14.52%. [2024-11-21T16:47:38.938Z] Movies recommended for you: [2024-11-21T16:47:38.938Z] WARNING: This benchmark provides no result that can be validated. [2024-11-21T16:47:38.938Z] There is no way to check that no silent failure occurred. [2024-11-21T16:47:38.938Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (38816.999 ms) ====== [2024-11-21T16:47:38.938Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-11-21T16:47:39.410Z] GC before operation: completed in 276.767 ms, heap usage 315.240 MB -> 49.037 MB. [2024-11-21T16:47:46.202Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-21T16:47:53.185Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-21T16:47:59.925Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-21T16:48:07.015Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-21T16:48:09.907Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-21T16:48:13.790Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-21T16:48:18.256Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-21T16:48:22.796Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-21T16:48:22.796Z] 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. [2024-11-21T16:48:22.796Z] The best model improves the baseline by 14.52%. [2024-11-21T16:48:23.226Z] Movies recommended for you: [2024-11-21T16:48:23.226Z] WARNING: This benchmark provides no result that can be validated. [2024-11-21T16:48:23.226Z] There is no way to check that no silent failure occurred. [2024-11-21T16:48:23.226Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (43925.942 ms) ====== [2024-11-21T16:48:23.226Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-11-21T16:48:23.226Z] GC before operation: completed in 171.092 ms, heap usage 266.255 MB -> 49.197 MB. [2024-11-21T16:48:31.493Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-21T16:48:39.778Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-21T16:48:46.546Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-21T16:48:53.189Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-21T16:48:56.636Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-21T16:49:00.068Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-21T16:49:03.607Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-21T16:49:07.079Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-21T16:49:07.079Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2024-11-21T16:49:07.079Z] The best model improves the baseline by 14.52%. [2024-11-21T16:49:07.464Z] Movies recommended for you: [2024-11-21T16:49:07.464Z] WARNING: This benchmark provides no result that can be validated. [2024-11-21T16:49:07.464Z] There is no way to check that no silent failure occurred. [2024-11-21T16:49:07.464Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (43975.329 ms) ====== [2024-11-21T16:49:07.464Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-11-21T16:49:07.464Z] GC before operation: completed in 220.280 ms, heap usage 249.793 MB -> 49.545 MB. [2024-11-21T16:49:14.416Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-21T16:49:21.120Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-21T16:49:26.550Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-21T16:49:33.181Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-21T16:49:36.526Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-21T16:49:40.238Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-21T16:49:44.659Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-21T16:49:48.120Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-21T16:49:48.120Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2024-11-21T16:49:48.120Z] The best model improves the baseline by 14.52%. [2024-11-21T16:49:48.120Z] Movies recommended for you: [2024-11-21T16:49:48.120Z] WARNING: This benchmark provides no result that can be validated. [2024-11-21T16:49:48.120Z] There is no way to check that no silent failure occurred. [2024-11-21T16:49:48.120Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (40678.206 ms) ====== [2024-11-21T16:49:48.120Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-11-21T16:49:48.522Z] GC before operation: completed in 140.309 ms, heap usage 189.081 MB -> 49.669 MB. [2024-11-21T16:49:55.194Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-21T16:49:59.588Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-21T16:50:06.425Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-21T16:50:11.938Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-21T16:50:16.436Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-21T16:50:20.946Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-21T16:50:23.777Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-21T16:50:27.473Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-21T16:50:27.960Z] 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. [2024-11-21T16:50:27.960Z] The best model improves the baseline by 14.52%. [2024-11-21T16:50:28.469Z] Movies recommended for you: [2024-11-21T16:50:28.469Z] WARNING: This benchmark provides no result that can be validated. [2024-11-21T16:50:28.469Z] There is no way to check that no silent failure occurred. [2024-11-21T16:50:28.469Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (39898.623 ms) ====== [2024-11-21T16:50:28.469Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-11-21T16:50:28.469Z] GC before operation: completed in 191.314 ms, heap usage 305.051 MB -> 49.732 MB. [2024-11-21T16:50:36.649Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-21T16:50:42.057Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-21T16:50:46.325Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-21T16:50:53.003Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-21T16:50:57.330Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-21T16:51:00.972Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-21T16:51:04.860Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-21T16:51:08.442Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-21T16:51:08.932Z] 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. [2024-11-21T16:51:08.933Z] The best model improves the baseline by 14.52%. [2024-11-21T16:51:08.933Z] Movies recommended for you: [2024-11-21T16:51:08.933Z] WARNING: This benchmark provides no result that can be validated. [2024-11-21T16:51:08.933Z] There is no way to check that no silent failure occurred. [2024-11-21T16:51:08.933Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (40600.587 ms) ====== [2024-11-21T16:51:08.933Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-11-21T16:51:09.421Z] GC before operation: completed in 222.093 ms, heap usage 411.218 MB -> 53.139 MB. [2024-11-21T16:51:16.184Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-21T16:51:24.447Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-21T16:51:28.906Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-21T16:51:35.600Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-21T16:51:46.637Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-21T16:51:46.637Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-21T16:51:46.637Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-21T16:51:50.220Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-21T16:51:50.220Z] 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. [2024-11-21T16:51:50.220Z] The best model improves the baseline by 14.52%. [2024-11-21T16:51:50.689Z] Movies recommended for you: [2024-11-21T16:51:50.689Z] WARNING: This benchmark provides no result that can be validated. [2024-11-21T16:51:50.689Z] There is no way to check that no silent failure occurred. [2024-11-21T16:51:50.689Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (41162.589 ms) ====== [2024-11-21T16:51:50.689Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-11-21T16:51:50.689Z] GC before operation: completed in 170.304 ms, heap usage 353.514 MB -> 50.215 MB. [2024-11-21T16:51:57.422Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-21T16:52:03.020Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-21T16:52:08.446Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-21T16:52:13.944Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-21T16:52:16.669Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-21T16:52:20.102Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-21T16:52:23.511Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-21T16:52:26.259Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-21T16:52:26.700Z] 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. [2024-11-21T16:52:26.700Z] The best model improves the baseline by 14.52%. [2024-11-21T16:52:27.146Z] Movies recommended for you: [2024-11-21T16:52:27.146Z] WARNING: This benchmark provides no result that can be validated. [2024-11-21T16:52:27.146Z] There is no way to check that no silent failure occurred. [2024-11-21T16:52:27.146Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (36306.914 ms) ====== [2024-11-21T16:52:27.146Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-11-21T16:52:27.146Z] GC before operation: completed in 224.148 ms, heap usage 187.618 MB -> 49.884 MB. [2024-11-21T16:52:33.842Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-21T16:52:39.461Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-21T16:52:44.929Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-21T16:52:51.567Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-21T16:52:54.303Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-21T16:52:57.853Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-21T16:53:01.441Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-21T16:53:04.106Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-21T16:53:04.499Z] 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. [2024-11-21T16:53:04.499Z] The best model improves the baseline by 14.52%. [2024-11-21T16:53:04.958Z] Movies recommended for you: [2024-11-21T16:53:04.958Z] WARNING: This benchmark provides no result that can be validated. [2024-11-21T16:53:04.958Z] There is no way to check that no silent failure occurred. [2024-11-21T16:53:04.958Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (37649.359 ms) ====== [2024-11-21T16:53:04.958Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-11-21T16:53:04.958Z] GC before operation: completed in 170.932 ms, heap usage 403.380 MB -> 53.330 MB. [2024-11-21T16:53:11.688Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-21T16:53:17.126Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-21T16:53:22.762Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-21T16:53:28.261Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-21T16:53:32.629Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-21T16:53:34.774Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-21T16:53:38.366Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-21T16:53:41.838Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-21T16:53:42.246Z] 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. [2024-11-21T16:53:42.246Z] The best model improves the baseline by 14.52%. [2024-11-21T16:53:42.659Z] Movies recommended for you: [2024-11-21T16:53:42.659Z] WARNING: This benchmark provides no result that can be validated. [2024-11-21T16:53:42.659Z] There is no way to check that no silent failure occurred. [2024-11-21T16:53:42.659Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (37526.815 ms) ====== [2024-11-21T16:53:42.659Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-11-21T16:53:42.659Z] GC before operation: completed in 163.705 ms, heap usage 262.523 MB -> 49.776 MB. [2024-11-21T16:53:49.441Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-21T16:53:56.040Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-21T16:54:01.691Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-21T16:54:07.244Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-21T16:54:10.012Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-21T16:54:13.631Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-21T16:54:16.364Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-21T16:54:20.681Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-21T16:54:20.681Z] 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. [2024-11-21T16:54:20.681Z] The best model improves the baseline by 14.52%. [2024-11-21T16:54:21.066Z] Movies recommended for you: [2024-11-21T16:54:21.066Z] WARNING: This benchmark provides no result that can be validated. [2024-11-21T16:54:21.066Z] There is no way to check that no silent failure occurred. [2024-11-21T16:54:21.066Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (38267.620 ms) ====== [2024-11-21T16:54:21.066Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-11-21T16:54:21.066Z] GC before operation: completed in 196.678 ms, heap usage 61.836 MB -> 52.351 MB. [2024-11-21T16:54:27.666Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-21T16:54:34.336Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-21T16:54:41.076Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-21T16:54:46.551Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-21T16:54:49.387Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-21T16:54:52.934Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-21T16:54:56.559Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-21T16:55:00.150Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-21T16:55:00.605Z] 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. [2024-11-21T16:55:00.605Z] The best model improves the baseline by 14.52%. [2024-11-21T16:55:00.605Z] Movies recommended for you: [2024-11-21T16:55:00.605Z] WARNING: This benchmark provides no result that can be validated. [2024-11-21T16:55:00.605Z] There is no way to check that no silent failure occurred. [2024-11-21T16:55:00.605Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (39579.729 ms) ====== [2024-11-21T16:55:00.605Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-11-21T16:55:01.051Z] GC before operation: completed in 156.212 ms, heap usage 536.798 MB -> 53.576 MB. [2024-11-21T16:55:06.746Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-21T16:55:13.530Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-21T16:55:19.118Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-21T16:55:24.553Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-21T16:55:28.076Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-21T16:55:32.378Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-21T16:55:35.088Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-21T16:55:38.598Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-21T16:55:38.598Z] 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. [2024-11-21T16:55:38.598Z] The best model improves the baseline by 14.52%. [2024-11-21T16:55:39.000Z] Movies recommended for you: [2024-11-21T16:55:39.000Z] WARNING: This benchmark provides no result that can be validated. [2024-11-21T16:55:39.000Z] There is no way to check that no silent failure occurred. [2024-11-21T16:55:39.000Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (38020.655 ms) ====== [2024-11-21T16:55:39.000Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-11-21T16:55:39.000Z] GC before operation: completed in 180.493 ms, heap usage 488.737 MB -> 53.306 MB. [2024-11-21T16:55:45.811Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-21T16:55:52.466Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-21T16:55:58.034Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-21T16:56:03.698Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-21T16:56:06.410Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-21T16:56:09.913Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-21T16:56:13.374Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-21T16:56:16.150Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-21T16:56:16.150Z] 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. [2024-11-21T16:56:16.150Z] The best model improves the baseline by 14.52%. [2024-11-21T16:56:16.581Z] Movies recommended for you: [2024-11-21T16:56:16.581Z] WARNING: This benchmark provides no result that can be validated. [2024-11-21T16:56:16.581Z] There is no way to check that no silent failure occurred. [2024-11-21T16:56:16.581Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (37474.425 ms) ====== [2024-11-21T16:56:16.581Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-11-21T16:56:16.581Z] GC before operation: completed in 147.486 ms, heap usage 404.877 MB -> 53.344 MB. [2024-11-21T16:56:24.684Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-21T16:56:30.161Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-21T16:56:35.638Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-21T16:56:41.209Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-21T16:56:43.990Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-21T16:56:46.858Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-21T16:56:51.175Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-21T16:56:54.606Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-21T16:56:55.549Z] 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. [2024-11-21T16:56:55.549Z] The best model improves the baseline by 14.52%. [2024-11-21T16:56:55.549Z] Movies recommended for you: [2024-11-21T16:56:55.549Z] WARNING: This benchmark provides no result that can be validated. [2024-11-21T16:56:55.549Z] There is no way to check that no silent failure occurred. [2024-11-21T16:56:55.549Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (38873.088 ms) ====== [2024-11-21T16:56:55.549Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-11-21T16:56:55.991Z] GC before operation: completed in 208.625 ms, heap usage 288.169 MB -> 50.269 MB. [2024-11-21T16:57:02.742Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-21T16:57:09.517Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-21T16:57:15.208Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-21T16:57:23.356Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-21T16:57:26.834Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-21T16:57:29.672Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-21T16:57:33.229Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-21T16:57:37.751Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-21T16:57:37.751Z] 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. [2024-11-21T16:57:37.751Z] The best model improves the baseline by 14.52%. [2024-11-21T16:57:38.156Z] Movies recommended for you: [2024-11-21T16:57:38.156Z] WARNING: This benchmark provides no result that can be validated. [2024-11-21T16:57:38.156Z] There is no way to check that no silent failure occurred. [2024-11-21T16:57:38.156Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (42333.082 ms) ====== [2024-11-21T16:57:38.156Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-11-21T16:57:38.156Z] GC before operation: completed in 181.392 ms, heap usage 127.522 MB -> 50.539 MB. [2024-11-21T16:57:45.116Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-21T16:57:53.590Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-21T16:58:00.335Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-21T16:58:08.633Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-21T16:58:12.250Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-21T16:58:15.762Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-21T16:58:19.269Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-21T16:58:22.779Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-21T16:58:23.714Z] 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. [2024-11-21T16:58:23.714Z] The best model improves the baseline by 14.52%. [2024-11-21T16:58:24.119Z] Movies recommended for you: [2024-11-21T16:58:24.119Z] WARNING: This benchmark provides no result that can be validated. [2024-11-21T16:58:24.119Z] There is no way to check that no silent failure occurred. [2024-11-21T16:58:24.119Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (45573.455 ms) ====== [2024-11-21T16:58:24.119Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-11-21T16:58:24.119Z] GC before operation: completed in 169.853 ms, heap usage 229.245 MB -> 50.048 MB. [2024-11-21T16:58:32.330Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-21T16:58:36.801Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-21T16:58:43.532Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-21T16:58:47.998Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-21T16:58:52.340Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-21T16:58:55.744Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-21T16:58:59.445Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-21T16:59:03.211Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-21T16:59:03.211Z] 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. [2024-11-21T16:59:03.211Z] The best model improves the baseline by 14.52%. [2024-11-21T16:59:03.642Z] Movies recommended for you: [2024-11-21T16:59:03.642Z] WARNING: This benchmark provides no result that can be validated. [2024-11-21T16:59:03.642Z] There is no way to check that no silent failure occurred. [2024-11-21T16:59:03.642Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (39473.031 ms) ====== [2024-11-21T16:59:03.642Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-11-21T16:59:03.642Z] GC before operation: completed in 131.482 ms, heap usage 564.554 MB -> 53.745 MB. [2024-11-21T16:59:10.495Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-21T16:59:17.303Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-21T16:59:23.918Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-21T16:59:29.391Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-21T16:59:32.910Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-21T16:59:35.685Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-21T16:59:39.322Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-21T16:59:42.797Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-21T16:59:43.226Z] 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. [2024-11-21T16:59:43.624Z] The best model improves the baseline by 14.52%. [2024-11-21T16:59:43.624Z] Movies recommended for you: [2024-11-21T16:59:43.624Z] WARNING: This benchmark provides no result that can be validated. [2024-11-21T16:59:43.624Z] There is no way to check that no silent failure occurred. [2024-11-21T16:59:43.624Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (39915.096 ms) ====== [2024-11-21T16:59:45.615Z] ----------------------------------- [2024-11-21T16:59:45.615Z] renaissance-movie-lens_0_PASSED [2024-11-21T16:59:45.615Z] ----------------------------------- [2024-11-21T16:59:45.615Z] [2024-11-21T16:59:45.615Z] TEST TEARDOWN: [2024-11-21T16:59:45.615Z] Nothing to be done for teardown. [2024-11-21T16:59:45.615Z] renaissance-movie-lens_0 Finish Time: Thu Nov 21 08:59:45 2024 Epoch Time (ms): 1732208385264