[2024-08-29T05:20:11.718Z] Running test renaissance-movie-lens_0 ... [2024-08-29T05:20:11.718Z] =============================================== [2024-08-29T05:20:12.031Z] renaissance-movie-lens_0 Start Time: Thu Aug 29 05:20:11 2024 Epoch Time (ms): 1724908811685 [2024-08-29T05:20:12.341Z] variation: NoOptions [2024-08-29T05:20:12.661Z] JVM_OPTIONS: [2024-08-29T05:20:12.661Z] { \ [2024-08-29T05:20:12.661Z] echo ""; echo "TEST SETUP:"; \ [2024-08-29T05:20:12.661Z] echo "Nothing to be done for setup."; \ [2024-08-29T05:20:12.661Z] mkdir -p "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17249075524958\\renaissance-movie-lens_0"; \ [2024-08-29T05:20:12.661Z] cd "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17249075524958\\renaissance-movie-lens_0"; \ [2024-08-29T05:20:12.661Z] echo ""; echo "TESTING:"; \ [2024-08-29T05:20:12.661Z] "c:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/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_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests///..//jvmtest\\perf\\renaissance\\renaissance.jar" --json ""C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17249075524958\\renaissance-movie-lens_0"\\movie-lens.json" movie-lens; \ [2024-08-29T05:20:12.661Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/; rm -f -r "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17249075524958\\renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-08-29T05:20:12.661Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-08-29T05:20:12.661Z] echo "Nothing to be done for teardown."; \ [2024-08-29T05:20:12.661Z] } 2>&1 | tee -a "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17249075524958\\TestTargetResult"; [2024-08-29T05:20:12.983Z] [2024-08-29T05:20:12.983Z] TEST SETUP: [2024-08-29T05:20:12.983Z] Nothing to be done for setup. [2024-08-29T05:20:12.983Z] [2024-08-29T05:20:12.983Z] TESTING: [2024-08-29T05:20:23.589Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-08-29T05:20:25.187Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2024-08-29T05:20:28.171Z] Got 100004 ratings from 671 users on 9066 movies. [2024-08-29T05:20:28.171Z] Training: 60056, validation: 20285, test: 19854 [2024-08-29T05:20:28.171Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-08-29T05:20:28.171Z] GC before operation: completed in 68.916 ms, heap usage 74.776 MB -> 36.929 MB. [2024-08-29T05:20:41.180Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-29T05:20:49.909Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-29T05:20:57.007Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-29T05:21:04.102Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-29T05:21:08.724Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-29T05:21:12.414Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-29T05:21:17.091Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-29T05:21:20.782Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-29T05:21:21.111Z] 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. [2024-08-29T05:21:21.438Z] The best model improves the baseline by 14.52%. [2024-08-29T05:21:21.438Z] Movies recommended for you: [2024-08-29T05:21:21.438Z] WARNING: This benchmark provides no result that can be validated. [2024-08-29T05:21:21.438Z] There is no way to check that no silent failure occurred. [2024-08-29T05:21:21.438Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (53142.357 ms) ====== [2024-08-29T05:21:21.438Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-08-29T05:21:21.438Z] GC before operation: completed in 101.608 ms, heap usage 168.422 MB -> 48.635 MB. [2024-08-29T05:21:28.619Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-29T05:21:35.721Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-29T05:21:44.448Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-29T05:21:50.214Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-29T05:21:53.908Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-29T05:21:58.548Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-29T05:22:02.209Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-29T05:22:05.893Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-29T05:22:06.214Z] 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. [2024-08-29T05:22:06.214Z] The best model improves the baseline by 14.52%. [2024-08-29T05:22:06.538Z] Movies recommended for you: [2024-08-29T05:22:06.538Z] WARNING: This benchmark provides no result that can be validated. [2024-08-29T05:22:06.538Z] There is no way to check that no silent failure occurred. [2024-08-29T05:22:06.538Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (44936.537 ms) ====== [2024-08-29T05:22:06.538Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-08-29T05:22:06.538Z] GC before operation: completed in 86.173 ms, heap usage 165.728 MB -> 52.704 MB. [2024-08-29T05:22:13.648Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-29T05:22:20.754Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-29T05:22:27.873Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-29T05:22:34.969Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-29T05:22:38.639Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-29T05:22:42.326Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-29T05:22:46.025Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-29T05:22:49.702Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-29T05:22:50.082Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-29T05:22:50.082Z] The best model improves the baseline by 14.52%. [2024-08-29T05:22:50.082Z] Movies recommended for you: [2024-08-29T05:22:50.082Z] WARNING: This benchmark provides no result that can be validated. [2024-08-29T05:22:50.082Z] There is no way to check that no silent failure occurred. [2024-08-29T05:22:50.082Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (43495.353 ms) ====== [2024-08-29T05:22:50.082Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-08-29T05:22:50.082Z] GC before operation: completed in 92.790 ms, heap usage 210.778 MB -> 53.079 MB. [2024-08-29T05:22:57.193Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-29T05:23:04.291Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-29T05:23:11.403Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-29T05:23:18.523Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-29T05:23:22.245Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-29T05:23:25.899Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-29T05:23:29.606Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-29T05:23:33.304Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-29T05:23:33.736Z] 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. [2024-08-29T05:23:33.736Z] The best model improves the baseline by 14.52%. [2024-08-29T05:23:33.736Z] Movies recommended for you: [2024-08-29T05:23:33.736Z] WARNING: This benchmark provides no result that can be validated. [2024-08-29T05:23:33.736Z] There is no way to check that no silent failure occurred. [2024-08-29T05:23:33.737Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (43518.585 ms) ====== [2024-08-29T05:23:33.737Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-08-29T05:23:33.737Z] GC before operation: completed in 90.496 ms, heap usage 125.135 MB -> 53.336 MB. [2024-08-29T05:23:42.491Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-29T05:23:48.269Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-29T05:23:57.007Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-29T05:24:02.804Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-29T05:24:06.523Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-29T05:24:10.265Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-29T05:24:14.918Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-29T05:24:18.626Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-29T05:24:18.626Z] 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. [2024-08-29T05:24:18.626Z] The best model improves the baseline by 14.52%. [2024-08-29T05:24:18.626Z] Movies recommended for you: [2024-08-29T05:24:18.626Z] WARNING: This benchmark provides no result that can be validated. [2024-08-29T05:24:18.626Z] There is no way to check that no silent failure occurred. [2024-08-29T05:24:18.626Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (44936.022 ms) ====== [2024-08-29T05:24:18.627Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-08-29T05:24:18.940Z] GC before operation: completed in 89.694 ms, heap usage 73.402 MB -> 50.196 MB. [2024-08-29T05:24:26.072Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-29T05:24:33.207Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-29T05:24:40.346Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-29T05:24:46.155Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-29T05:24:49.889Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-29T05:24:54.524Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-29T05:24:58.215Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-29T05:25:01.923Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-29T05:25:02.245Z] 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. [2024-08-29T05:25:02.245Z] The best model improves the baseline by 14.52%. [2024-08-29T05:25:02.572Z] Movies recommended for you: [2024-08-29T05:25:02.572Z] WARNING: This benchmark provides no result that can be validated. [2024-08-29T05:25:02.572Z] There is no way to check that no silent failure occurred. [2024-08-29T05:25:02.572Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (43691.178 ms) ====== [2024-08-29T05:25:02.572Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-08-29T05:25:02.572Z] GC before operation: completed in 82.491 ms, heap usage 121.589 MB -> 50.211 MB. [2024-08-29T05:25:09.689Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-29T05:25:16.803Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-29T05:25:23.935Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-29T05:25:29.692Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-29T05:25:34.349Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-29T05:25:38.020Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-29T05:25:42.643Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-29T05:25:45.518Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-29T05:25:46.205Z] 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. [2024-08-29T05:25:46.205Z] The best model improves the baseline by 14.52%. [2024-08-29T05:25:46.206Z] Movies recommended for you: [2024-08-29T05:25:46.206Z] WARNING: This benchmark provides no result that can be validated. [2024-08-29T05:25:46.206Z] There is no way to check that no silent failure occurred. [2024-08-29T05:25:46.206Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (43716.838 ms) ====== [2024-08-29T05:25:46.206Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-08-29T05:25:46.529Z] GC before operation: completed in 83.411 ms, heap usage 122.611 MB -> 50.355 MB. [2024-08-29T05:25:53.647Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-29T05:26:00.763Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-29T05:26:07.882Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-29T05:26:15.011Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-29T05:26:18.697Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-29T05:26:22.380Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-29T05:26:26.077Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-29T05:26:30.724Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-29T05:26:30.724Z] 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. [2024-08-29T05:26:30.724Z] The best model improves the baseline by 14.52%. [2024-08-29T05:26:30.724Z] Movies recommended for you: [2024-08-29T05:26:30.724Z] WARNING: This benchmark provides no result that can be validated. [2024-08-29T05:26:30.724Z] There is no way to check that no silent failure occurred. [2024-08-29T05:26:30.724Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (44258.079 ms) ====== [2024-08-29T05:26:30.724Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-08-29T05:26:30.724Z] GC before operation: completed in 81.909 ms, heap usage 155.671 MB -> 50.677 MB. [2024-08-29T05:26:37.838Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-29T05:26:44.984Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-29T05:26:52.095Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-29T05:26:59.223Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-29T05:27:02.107Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-29T05:27:05.767Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-29T05:27:10.426Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-29T05:27:14.117Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-29T05:27:14.447Z] 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. [2024-08-29T05:27:14.447Z] The best model improves the baseline by 14.52%. [2024-08-29T05:27:14.447Z] Movies recommended for you: [2024-08-29T05:27:14.447Z] WARNING: This benchmark provides no result that can be validated. [2024-08-29T05:27:14.447Z] There is no way to check that no silent failure occurred. [2024-08-29T05:27:14.447Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (43791.382 ms) ====== [2024-08-29T05:27:14.447Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-08-29T05:27:14.447Z] GC before operation: completed in 82.913 ms, heap usage 94.252 MB -> 50.467 MB. [2024-08-29T05:27:21.556Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-29T05:27:28.666Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-29T05:27:35.775Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-29T05:27:41.550Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-29T05:27:45.250Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-29T05:27:48.969Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-29T05:27:52.654Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-29T05:27:56.334Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-29T05:27:57.025Z] 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. [2024-08-29T05:27:57.025Z] The best model improves the baseline by 14.52%. [2024-08-29T05:27:57.025Z] Movies recommended for you: [2024-08-29T05:27:57.025Z] WARNING: This benchmark provides no result that can be validated. [2024-08-29T05:27:57.025Z] There is no way to check that no silent failure occurred. [2024-08-29T05:27:57.025Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (42481.904 ms) ====== [2024-08-29T05:27:57.025Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-08-29T05:27:57.025Z] GC before operation: completed in 86.214 ms, heap usage 66.582 MB -> 50.495 MB. [2024-08-29T05:28:05.746Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-29T05:28:11.536Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-29T05:28:18.647Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-29T05:28:25.771Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-29T05:28:28.679Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-29T05:28:32.391Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-29T05:28:37.042Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-29T05:28:40.747Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-29T05:28:40.748Z] 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. [2024-08-29T05:28:40.748Z] The best model improves the baseline by 14.52%. [2024-08-29T05:28:40.748Z] Movies recommended for you: [2024-08-29T05:28:40.748Z] WARNING: This benchmark provides no result that can be validated. [2024-08-29T05:28:40.748Z] There is no way to check that no silent failure occurred. [2024-08-29T05:28:40.748Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (43594.152 ms) ====== [2024-08-29T05:28:40.748Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-08-29T05:28:40.748Z] GC before operation: completed in 84.243 ms, heap usage 199.071 MB -> 50.394 MB. [2024-08-29T05:28:47.873Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-29T05:28:54.959Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-29T05:29:02.089Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-29T05:29:07.876Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-29T05:29:11.569Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-29T05:29:15.278Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-29T05:29:18.955Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-29T05:29:22.632Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-29T05:29:22.632Z] 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. [2024-08-29T05:29:22.632Z] The best model improves the baseline by 14.52%. [2024-08-29T05:29:22.953Z] Movies recommended for you: [2024-08-29T05:29:22.953Z] WARNING: This benchmark provides no result that can be validated. [2024-08-29T05:29:22.953Z] There is no way to check that no silent failure occurred. [2024-08-29T05:29:22.953Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (42019.621 ms) ====== [2024-08-29T05:29:22.953Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-08-29T05:29:22.953Z] GC before operation: completed in 88.535 ms, heap usage 175.049 MB -> 53.865 MB. [2024-08-29T05:29:30.076Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-29T05:29:37.189Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-29T05:29:44.289Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-29T05:29:50.033Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-29T05:29:53.778Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-29T05:29:57.424Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-29T05:30:01.108Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-29T05:30:04.789Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-29T05:30:05.203Z] 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. [2024-08-29T05:30:05.203Z] The best model improves the baseline by 14.52%. [2024-08-29T05:30:05.203Z] Movies recommended for you: [2024-08-29T05:30:05.203Z] WARNING: This benchmark provides no result that can be validated. [2024-08-29T05:30:05.203Z] There is no way to check that no silent failure occurred. [2024-08-29T05:30:05.203Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (42218.326 ms) ====== [2024-08-29T05:30:05.203Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-08-29T05:30:05.203Z] GC before operation: completed in 90.731 ms, heap usage 261.714 MB -> 53.996 MB. [2024-08-29T05:30:12.350Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-29T05:30:19.477Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-29T05:30:26.596Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-29T05:30:32.388Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-29T05:30:36.103Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-29T05:30:39.788Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-29T05:30:44.407Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-29T05:30:48.116Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-29T05:30:48.116Z] 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. [2024-08-29T05:30:48.116Z] The best model improves the baseline by 14.52%. [2024-08-29T05:30:48.116Z] Movies recommended for you: [2024-08-29T05:30:48.116Z] WARNING: This benchmark provides no result that can be validated. [2024-08-29T05:30:48.116Z] There is no way to check that no silent failure occurred. [2024-08-29T05:30:48.116Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (42958.702 ms) ====== [2024-08-29T05:30:48.116Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-08-29T05:30:48.463Z] GC before operation: completed in 84.132 ms, heap usage 204.593 MB -> 50.483 MB. [2024-08-29T05:30:55.569Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-29T05:31:01.355Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-29T05:31:08.461Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-29T05:31:15.612Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-29T05:31:18.470Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-29T05:31:23.095Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-29T05:31:26.759Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-29T05:31:30.447Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-29T05:31:30.447Z] 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. [2024-08-29T05:31:30.447Z] The best model improves the baseline by 14.52%. [2024-08-29T05:31:30.769Z] Movies recommended for you: [2024-08-29T05:31:30.769Z] WARNING: This benchmark provides no result that can be validated. [2024-08-29T05:31:30.769Z] There is no way to check that no silent failure occurred. [2024-08-29T05:31:30.769Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (42309.039 ms) ====== [2024-08-29T05:31:30.769Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-08-29T05:31:30.769Z] GC before operation: completed in 87.674 ms, heap usage 65.781 MB -> 50.517 MB. [2024-08-29T05:31:37.879Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-29T05:31:44.990Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-29T05:31:52.085Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-29T05:31:59.222Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-29T05:32:02.092Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-29T05:32:05.762Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-29T05:32:10.396Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-29T05:32:14.076Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-29T05:32:14.076Z] 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. [2024-08-29T05:32:14.076Z] The best model improves the baseline by 14.52%. [2024-08-29T05:32:14.076Z] Movies recommended for you: [2024-08-29T05:32:14.076Z] WARNING: This benchmark provides no result that can be validated. [2024-08-29T05:32:14.076Z] There is no way to check that no silent failure occurred. [2024-08-29T05:32:14.076Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (43434.916 ms) ====== [2024-08-29T05:32:14.076Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-08-29T05:32:14.076Z] GC before operation: completed in 86.905 ms, heap usage 215.655 MB -> 50.758 MB. [2024-08-29T05:32:21.181Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-29T05:32:28.275Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-29T05:32:35.391Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-29T05:32:41.158Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-29T05:32:44.862Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-29T05:32:48.532Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-29T05:32:53.153Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-29T05:32:56.814Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-29T05:32:56.814Z] 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. [2024-08-29T05:32:56.814Z] The best model improves the baseline by 14.52%. [2024-08-29T05:32:56.814Z] Movies recommended for you: [2024-08-29T05:32:56.814Z] WARNING: This benchmark provides no result that can be validated. [2024-08-29T05:32:56.814Z] There is no way to check that no silent failure occurred. [2024-08-29T05:32:56.814Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (42596.279 ms) ====== [2024-08-29T05:32:56.814Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-08-29T05:32:56.814Z] GC before operation: completed in 88.508 ms, heap usage 188.977 MB -> 50.582 MB. [2024-08-29T05:33:03.920Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-29T05:33:11.012Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-29T05:33:18.088Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-29T05:33:23.896Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-29T05:33:27.603Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-29T05:33:31.275Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-29T05:33:34.960Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-29T05:33:38.625Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-29T05:33:38.958Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-29T05:33:38.958Z] The best model improves the baseline by 14.52%. [2024-08-29T05:33:38.958Z] Movies recommended for you: [2024-08-29T05:33:38.958Z] WARNING: This benchmark provides no result that can be validated. [2024-08-29T05:33:38.958Z] There is no way to check that no silent failure occurred. [2024-08-29T05:33:38.958Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (42128.038 ms) ====== [2024-08-29T05:33:38.958Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-08-29T05:33:39.290Z] GC before operation: completed in 84.391 ms, heap usage 85.904 MB -> 50.502 MB. [2024-08-29T05:33:46.385Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-29T05:33:52.149Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-29T05:33:59.269Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-29T05:34:06.430Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-29T05:34:10.103Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-29T05:34:13.786Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-29T05:34:17.463Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-29T05:34:21.130Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-29T05:34:21.488Z] 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. [2024-08-29T05:34:21.488Z] The best model improves the baseline by 14.52%. [2024-08-29T05:34:21.488Z] Movies recommended for you: [2024-08-29T05:34:21.488Z] WARNING: This benchmark provides no result that can be validated. [2024-08-29T05:34:21.488Z] There is no way to check that no silent failure occurred. [2024-08-29T05:34:21.488Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (42463.952 ms) ====== [2024-08-29T05:34:21.488Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-08-29T05:34:21.806Z] GC before operation: completed in 87.642 ms, heap usage 240.687 MB -> 54.044 MB. [2024-08-29T05:34:28.905Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-29T05:34:34.657Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-29T05:34:41.791Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-29T05:34:48.892Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-29T05:34:51.768Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-29T05:34:55.439Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-29T05:34:59.131Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-29T05:35:02.792Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-29T05:35:02.792Z] 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. [2024-08-29T05:35:03.115Z] The best model improves the baseline by 14.52%. [2024-08-29T05:35:03.115Z] Movies recommended for you: [2024-08-29T05:35:03.115Z] WARNING: This benchmark provides no result that can be validated. [2024-08-29T05:35:03.115Z] There is no way to check that no silent failure occurred. [2024-08-29T05:35:03.115Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (41423.513 ms) ====== [2024-08-29T05:35:03.789Z] ----------------------------------- [2024-08-29T05:35:03.789Z] renaissance-movie-lens_0_PASSED [2024-08-29T05:35:03.789Z] ----------------------------------- [2024-08-29T05:35:04.108Z] [2024-08-29T05:35:04.108Z] TEST TEARDOWN: [2024-08-29T05:35:04.108Z] Nothing to be done for teardown. [2024-08-29T05:35:04.427Z] renaissance-movie-lens_0 Finish Time: Thu Aug 29 05:35:04 2024 Epoch Time (ms): 1724909704165