[2025-02-17T18:17:54.405Z] Running test renaissance-movie-lens_0 ... [2025-02-17T18:17:54.405Z] =============================================== [2025-02-17T18:17:54.722Z] renaissance-movie-lens_0 Start Time: Mon Feb 17 18:17:54 2025 Epoch Time (ms): 1739816274448 [2025-02-17T18:17:54.722Z] variation: NoOptions [2025-02-17T18:17:55.068Z] JVM_OPTIONS: [2025-02-17T18:17:55.068Z] { \ [2025-02-17T18:17:55.068Z] echo ""; echo "TEST SETUP:"; \ [2025-02-17T18:17:55.068Z] echo "Nothing to be done for setup."; \ [2025-02-17T18:17:55.068Z] mkdir -p "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17398151574076\\renaissance-movie-lens_0"; \ [2025-02-17T18:17:55.068Z] cd "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17398151574076\\renaissance-movie-lens_0"; \ [2025-02-17T18:17:55.068Z] echo ""; echo "TESTING:"; \ [2025-02-17T18:17:55.068Z] "c:/jenkins/workspace/Test_openjdk17_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_openjdk17_hs_extended.perf_x86-64_windows/aqa-tests///..//jvmtest\\perf\\renaissance\\renaissance.jar" --json ""C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17398151574076\\renaissance-movie-lens_0"\\movie-lens.json" movie-lens; \ [2025-02-17T18:17:55.069Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows/aqa-tests/; rm -f -r "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17398151574076\\renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-02-17T18:17:55.069Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-02-17T18:17:55.069Z] echo "Nothing to be done for teardown."; \ [2025-02-17T18:17:55.069Z] } 2>&1 | tee -a "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17398151574076\\TestTargetResult"; [2025-02-17T18:17:55.069Z] [2025-02-17T18:17:55.069Z] TEST SETUP: [2025-02-17T18:17:55.069Z] Nothing to be done for setup. [2025-02-17T18:17:55.069Z] [2025-02-17T18:17:55.069Z] TESTING: [2025-02-17T18:18:10.798Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2025-02-17T18:18:11.137Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-02-17T18:18:14.917Z] Got 100004 ratings from 671 users on 9066 movies. [2025-02-17T18:18:14.917Z] Training: 60056, validation: 20285, test: 19854 [2025-02-17T18:18:14.917Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-02-17T18:18:14.917Z] GC before operation: completed in 44.622 ms, heap usage 138.416 MB -> 37.441 MB. [2025-02-17T18:18:28.225Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-17T18:18:37.063Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-17T18:18:47.858Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-17T18:18:56.685Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-17T18:19:00.429Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-17T18:19:06.273Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-17T18:19:10.955Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-17T18:19:15.666Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-17T18:19:16.040Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-02-17T18:19:16.040Z] The best model improves the baseline by 14.52%. [2025-02-17T18:19:16.372Z] Movies recommended for you: [2025-02-17T18:19:16.372Z] WARNING: This benchmark provides no result that can be validated. [2025-02-17T18:19:16.372Z] There is no way to check that no silent failure occurred. [2025-02-17T18:19:16.372Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (61353.576 ms) ====== [2025-02-17T18:19:16.372Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-02-17T18:19:16.372Z] GC before operation: completed in 74.476 ms, heap usage 237.102 MB -> 59.571 MB. [2025-02-17T18:19:25.205Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-17T18:19:32.418Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-17T18:19:41.279Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-17T18:19:50.084Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-17T18:19:53.803Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-17T18:19:58.529Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-17T18:20:03.210Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-17T18:20:07.902Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-17T18:20:08.619Z] 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. [2025-02-17T18:20:08.619Z] The best model improves the baseline by 14.52%. [2025-02-17T18:20:08.619Z] Movies recommended for you: [2025-02-17T18:20:08.619Z] WARNING: This benchmark provides no result that can be validated. [2025-02-17T18:20:08.619Z] There is no way to check that no silent failure occurred. [2025-02-17T18:20:08.619Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (52307.705 ms) ====== [2025-02-17T18:20:08.619Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-02-17T18:20:08.957Z] GC before operation: completed in 72.114 ms, heap usage 91.221 MB -> 49.850 MB. [2025-02-17T18:20:17.773Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-17T18:20:24.961Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-17T18:20:33.755Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-17T18:20:40.940Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-17T18:20:45.643Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-17T18:20:50.330Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-17T18:20:55.039Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-17T18:20:58.768Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-17T18:20:59.151Z] 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. [2025-02-17T18:20:59.485Z] The best model improves the baseline by 14.52%. [2025-02-17T18:20:59.485Z] Movies recommended for you: [2025-02-17T18:20:59.485Z] WARNING: This benchmark provides no result that can be validated. [2025-02-17T18:20:59.485Z] There is no way to check that no silent failure occurred. [2025-02-17T18:20:59.485Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (50667.822 ms) ====== [2025-02-17T18:20:59.485Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-02-17T18:20:59.485Z] GC before operation: completed in 64.719 ms, heap usage 162.762 MB -> 50.292 MB. [2025-02-17T18:21:08.295Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-17T18:21:15.462Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-17T18:21:24.267Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-17T18:21:31.436Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-17T18:21:36.139Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-17T18:21:40.829Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-17T18:21:45.517Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-17T18:21:50.203Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-17T18:21:50.203Z] 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. [2025-02-17T18:21:50.203Z] The best model improves the baseline by 14.52%. [2025-02-17T18:21:50.535Z] Movies recommended for you: [2025-02-17T18:21:50.535Z] WARNING: This benchmark provides no result that can be validated. [2025-02-17T18:21:50.535Z] There is no way to check that no silent failure occurred. [2025-02-17T18:21:50.535Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (50980.446 ms) ====== [2025-02-17T18:21:50.535Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-02-17T18:21:50.535Z] GC before operation: completed in 64.350 ms, heap usage 208.526 MB -> 50.737 MB. [2025-02-17T18:21:57.719Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-17T18:22:06.537Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-17T18:22:15.327Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-17T18:22:22.509Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-17T18:22:26.260Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-17T18:22:30.949Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-17T18:22:35.639Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-17T18:22:40.334Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-17T18:22:40.667Z] 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. [2025-02-17T18:22:40.667Z] The best model improves the baseline by 14.52%. [2025-02-17T18:22:40.667Z] Movies recommended for you: [2025-02-17T18:22:40.667Z] WARNING: This benchmark provides no result that can be validated. [2025-02-17T18:22:40.667Z] There is no way to check that no silent failure occurred. [2025-02-17T18:22:40.667Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (50112.938 ms) ====== [2025-02-17T18:22:40.667Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-02-17T18:22:40.667Z] GC before operation: completed in 70.954 ms, heap usage 293.328 MB -> 50.954 MB. [2025-02-17T18:22:49.473Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-17T18:22:56.668Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-17T18:23:05.475Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-17T18:23:12.656Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-17T18:23:17.336Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-17T18:23:22.028Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-17T18:23:26.718Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-17T18:23:30.437Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-17T18:23:31.145Z] 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. [2025-02-17T18:23:31.145Z] The best model improves the baseline by 14.52%. [2025-02-17T18:23:31.145Z] Movies recommended for you: [2025-02-17T18:23:31.145Z] WARNING: This benchmark provides no result that can be validated. [2025-02-17T18:23:31.145Z] There is no way to check that no silent failure occurred. [2025-02-17T18:23:31.145Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (50439.942 ms) ====== [2025-02-17T18:23:31.145Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-02-17T18:23:31.145Z] GC before operation: completed in 71.811 ms, heap usage 158.685 MB -> 50.804 MB. [2025-02-17T18:23:39.938Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-17T18:23:47.139Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-17T18:23:55.972Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-17T18:24:03.196Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-17T18:24:07.904Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-17T18:24:11.625Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-17T18:24:17.474Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-17T18:24:21.249Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-17T18:24:21.615Z] 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. [2025-02-17T18:24:21.615Z] The best model improves the baseline by 14.52%. [2025-02-17T18:24:21.615Z] Movies recommended for you: [2025-02-17T18:24:21.615Z] WARNING: This benchmark provides no result that can be validated. [2025-02-17T18:24:21.615Z] There is no way to check that no silent failure occurred. [2025-02-17T18:24:21.615Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (50361.903 ms) ====== [2025-02-17T18:24:21.615Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-02-17T18:24:21.615Z] GC before operation: completed in 66.543 ms, heap usage 340.836 MB -> 51.158 MB. [2025-02-17T18:24:30.433Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-17T18:24:37.606Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-17T18:24:46.412Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-17T18:24:53.604Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-17T18:24:57.316Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-17T18:25:02.010Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-17T18:25:06.703Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-17T18:25:11.396Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-17T18:25:11.756Z] 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. [2025-02-17T18:25:11.756Z] The best model improves the baseline by 14.52%. [2025-02-17T18:25:11.756Z] Movies recommended for you: [2025-02-17T18:25:11.756Z] WARNING: This benchmark provides no result that can be validated. [2025-02-17T18:25:11.756Z] There is no way to check that no silent failure occurred. [2025-02-17T18:25:11.756Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (50152.632 ms) ====== [2025-02-17T18:25:11.756Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-02-17T18:25:11.756Z] GC before operation: completed in 66.349 ms, heap usage 186.975 MB -> 51.302 MB. [2025-02-17T18:25:20.571Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-17T18:25:27.745Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-17T18:25:36.535Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-17T18:25:43.729Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-17T18:25:48.421Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-17T18:25:53.087Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-17T18:25:56.836Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-17T18:26:01.520Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-17T18:26:01.520Z] 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. [2025-02-17T18:26:01.520Z] The best model improves the baseline by 14.52%. [2025-02-17T18:26:01.861Z] Movies recommended for you: [2025-02-17T18:26:01.861Z] WARNING: This benchmark provides no result that can be validated. [2025-02-17T18:26:01.861Z] There is no way to check that no silent failure occurred. [2025-02-17T18:26:01.861Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (49845.420 ms) ====== [2025-02-17T18:26:01.861Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-02-17T18:26:01.861Z] GC before operation: completed in 66.650 ms, heap usage 350.125 MB -> 51.216 MB. [2025-02-17T18:26:09.029Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-17T18:26:17.807Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-17T18:26:24.984Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-17T18:26:33.772Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-17T18:26:37.498Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-17T18:26:41.222Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-17T18:26:45.905Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-17T18:26:50.586Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-17T18:26:50.586Z] 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. [2025-02-17T18:26:50.586Z] The best model improves the baseline by 14.52%. [2025-02-17T18:26:50.935Z] Movies recommended for you: [2025-02-17T18:26:50.935Z] WARNING: This benchmark provides no result that can be validated. [2025-02-17T18:26:50.935Z] There is no way to check that no silent failure occurred. [2025-02-17T18:26:50.935Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (48975.320 ms) ====== [2025-02-17T18:26:50.935Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-02-17T18:26:50.935Z] GC before operation: completed in 68.503 ms, heap usage 214.164 MB -> 51.235 MB. [2025-02-17T18:26:58.104Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-17T18:27:06.889Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-17T18:27:14.057Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-17T18:27:21.238Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-17T18:27:25.952Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-17T18:27:30.653Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-17T18:27:35.362Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-17T18:27:39.078Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-17T18:27:39.412Z] 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. [2025-02-17T18:27:39.750Z] The best model improves the baseline by 14.52%. [2025-02-17T18:27:39.750Z] Movies recommended for you: [2025-02-17T18:27:39.750Z] WARNING: This benchmark provides no result that can be validated. [2025-02-17T18:27:39.750Z] There is no way to check that no silent failure occurred. [2025-02-17T18:27:39.750Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (48937.198 ms) ====== [2025-02-17T18:27:39.750Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-02-17T18:27:39.750Z] GC before operation: completed in 65.288 ms, heap usage 127.753 MB -> 50.892 MB. [2025-02-17T18:27:48.531Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-17T18:27:55.724Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-17T18:28:04.503Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-17T18:28:11.729Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-17T18:28:15.469Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-17T18:28:20.163Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-17T18:28:24.855Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-17T18:28:28.590Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-17T18:28:29.290Z] 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. [2025-02-17T18:28:29.290Z] The best model improves the baseline by 14.52%. [2025-02-17T18:28:29.290Z] Movies recommended for you: [2025-02-17T18:28:29.290Z] WARNING: This benchmark provides no result that can be validated. [2025-02-17T18:28:29.290Z] There is no way to check that no silent failure occurred. [2025-02-17T18:28:29.290Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (49388.518 ms) ====== [2025-02-17T18:28:29.290Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-02-17T18:28:29.290Z] GC before operation: completed in 68.269 ms, heap usage 290.658 MB -> 51.256 MB. [2025-02-17T18:28:38.082Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-17T18:28:45.249Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-17T18:28:52.469Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-17T18:28:59.651Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-17T18:29:04.331Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-17T18:29:09.009Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-17T18:29:13.701Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-17T18:29:17.423Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-17T18:29:17.766Z] 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. [2025-02-17T18:29:18.111Z] The best model improves the baseline by 14.52%. [2025-02-17T18:29:18.111Z] Movies recommended for you: [2025-02-17T18:29:18.111Z] WARNING: This benchmark provides no result that can be validated. [2025-02-17T18:29:18.111Z] There is no way to check that no silent failure occurred. [2025-02-17T18:29:18.111Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (48732.834 ms) ====== [2025-02-17T18:29:18.111Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-02-17T18:29:18.111Z] GC before operation: completed in 65.826 ms, heap usage 189.399 MB -> 51.350 MB. [2025-02-17T18:29:25.336Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-17T18:29:34.182Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-17T18:29:41.405Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-17T18:29:48.596Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-17T18:29:53.308Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-17T18:29:57.083Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-17T18:30:01.765Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-17T18:30:06.483Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-17T18:30:06.483Z] 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. [2025-02-17T18:30:06.483Z] The best model improves the baseline by 14.52%. [2025-02-17T18:30:06.483Z] Movies recommended for you: [2025-02-17T18:30:06.483Z] WARNING: This benchmark provides no result that can be validated. [2025-02-17T18:30:06.483Z] There is no way to check that no silent failure occurred. [2025-02-17T18:30:06.483Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (48407.549 ms) ====== [2025-02-17T18:30:06.483Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-02-17T18:30:06.483Z] GC before operation: completed in 66.230 ms, heap usage 182.817 MB -> 52.268 MB. [2025-02-17T18:30:15.285Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-17T18:30:22.471Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-17T18:30:31.270Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-17T18:30:38.453Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-17T18:30:43.143Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-17T18:30:46.874Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-17T18:30:51.563Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-17T18:30:55.337Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-17T18:30:55.337Z] 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. [2025-02-17T18:30:55.337Z] The best model improves the baseline by 14.52%. [2025-02-17T18:30:55.337Z] Movies recommended for you: [2025-02-17T18:30:55.337Z] WARNING: This benchmark provides no result that can be validated. [2025-02-17T18:30:55.337Z] There is no way to check that no silent failure occurred. [2025-02-17T18:30:55.337Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (48816.926 ms) ====== [2025-02-17T18:30:55.337Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-02-17T18:30:55.657Z] GC before operation: completed in 72.856 ms, heap usage 134.988 MB -> 51.176 MB. [2025-02-17T18:31:02.856Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-17T18:31:10.032Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-17T18:31:18.829Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-17T18:31:24.699Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-17T18:31:29.387Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-17T18:31:33.116Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-17T18:31:37.817Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-17T18:31:41.539Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-17T18:31:42.256Z] 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. [2025-02-17T18:31:42.256Z] The best model improves the baseline by 14.52%. [2025-02-17T18:31:42.256Z] Movies recommended for you: [2025-02-17T18:31:42.256Z] WARNING: This benchmark provides no result that can be validated. [2025-02-17T18:31:42.256Z] There is no way to check that no silent failure occurred. [2025-02-17T18:31:42.256Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (46728.806 ms) ====== [2025-02-17T18:31:42.256Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-02-17T18:31:42.256Z] GC before operation: completed in 70.735 ms, heap usage 310.242 MB -> 51.388 MB. [2025-02-17T18:31:49.446Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-17T18:31:58.244Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-17T18:32:05.433Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-17T18:32:12.619Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-17T18:32:16.336Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-17T18:32:21.041Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-17T18:32:24.767Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-17T18:32:29.463Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-17T18:32:29.796Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-02-17T18:32:29.796Z] The best model improves the baseline by 14.52%. [2025-02-17T18:32:29.796Z] Movies recommended for you: [2025-02-17T18:32:29.796Z] WARNING: This benchmark provides no result that can be validated. [2025-02-17T18:32:29.796Z] There is no way to check that no silent failure occurred. [2025-02-17T18:32:29.796Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (47549.145 ms) ====== [2025-02-17T18:32:29.796Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-02-17T18:32:29.796Z] GC before operation: completed in 63.191 ms, heap usage 146.610 MB -> 51.094 MB. [2025-02-17T18:32:38.585Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-17T18:32:45.788Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-17T18:32:52.966Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-17T18:33:00.132Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-17T18:33:03.874Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-17T18:33:08.569Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-17T18:33:13.253Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-17T18:33:16.977Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-17T18:33:17.307Z] 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. [2025-02-17T18:33:17.307Z] The best model improves the baseline by 14.52%. [2025-02-17T18:33:17.656Z] Movies recommended for you: [2025-02-17T18:33:17.656Z] WARNING: This benchmark provides no result that can be validated. [2025-02-17T18:33:17.656Z] There is no way to check that no silent failure occurred. [2025-02-17T18:33:17.656Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (47597.997 ms) ====== [2025-02-17T18:33:17.656Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-02-17T18:33:17.656Z] GC before operation: completed in 66.982 ms, heap usage 137.897 MB -> 51.202 MB. [2025-02-17T18:33:24.838Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-17T18:33:33.643Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-17T18:33:40.805Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-17T18:33:48.008Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-17T18:33:51.720Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-17T18:33:56.406Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-17T18:34:01.117Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-17T18:34:04.830Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-17T18:34:05.158Z] 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. [2025-02-17T18:34:05.158Z] The best model improves the baseline by 14.52%. [2025-02-17T18:34:05.493Z] Movies recommended for you: [2025-02-17T18:34:05.494Z] WARNING: This benchmark provides no result that can be validated. [2025-02-17T18:34:05.494Z] There is no way to check that no silent failure occurred. [2025-02-17T18:34:05.494Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (47807.959 ms) ====== [2025-02-17T18:34:05.494Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-02-17T18:34:05.494Z] GC before operation: completed in 72.597 ms, heap usage 280.318 MB -> 51.462 MB. [2025-02-17T18:34:14.273Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-17T18:34:21.522Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-17T18:34:28.744Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-17T18:34:35.908Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-17T18:34:40.607Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-17T18:34:45.282Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-17T18:34:49.981Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-17T18:34:53.701Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-17T18:34:54.036Z] 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. [2025-02-17T18:34:54.037Z] The best model improves the baseline by 14.52%. [2025-02-17T18:34:54.356Z] Movies recommended for you: [2025-02-17T18:34:54.356Z] WARNING: This benchmark provides no result that can be validated. [2025-02-17T18:34:54.356Z] There is no way to check that no silent failure occurred. [2025-02-17T18:34:54.356Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (48721.044 ms) ====== [2025-02-17T18:34:54.691Z] ----------------------------------- [2025-02-17T18:34:54.691Z] renaissance-movie-lens_0_PASSED [2025-02-17T18:34:54.691Z] ----------------------------------- [2025-02-17T18:34:55.401Z] [2025-02-17T18:34:55.401Z] TEST TEARDOWN: [2025-02-17T18:34:55.401Z] Nothing to be done for teardown. [2025-02-17T18:34:55.401Z] renaissance-movie-lens_0 Finish Time: Mon Feb 17 18:34:55 2025 Epoch Time (ms): 1739817295201