[2025-03-04T21:52:39.810Z] Running test renaissance-movie-lens_0 ... [2025-03-04T21:52:39.810Z] =============================================== [2025-03-04T21:52:39.810Z] renaissance-movie-lens_0 Start Time: Tue Mar 4 15:52:39 2025 Epoch Time (ms): 1741125159693 [2025-03-04T21:52:39.810Z] variation: NoOptions [2025-03-04T21:52:39.810Z] JVM_OPTIONS: [2025-03-04T21:52:39.810Z] { \ [2025-03-04T21:52:39.810Z] echo ""; echo "TEST SETUP:"; \ [2025-03-04T21:52:39.810Z] echo "Nothing to be done for setup."; \ [2025-03-04T21:52:39.810Z] mkdir -p "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17411243091852/renaissance-movie-lens_0"; \ [2025-03-04T21:52:39.810Z] cd "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17411243091852/renaissance-movie-lens_0"; \ [2025-03-04T21:52:39.810Z] echo ""; echo "TESTING:"; \ [2025-03-04T21:52:39.810Z] "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux/jdkbinary/j2sdk-image/bin/java" -jar "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17411243091852/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-03-04T21:52:39.810Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17411243091852/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-03-04T21:52:39.810Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-03-04T21:52:39.810Z] echo "Nothing to be done for teardown."; \ [2025-03-04T21:52:39.810Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17411243091852/TestTargetResult"; [2025-03-04T21:52:39.810Z] [2025-03-04T21:52:39.810Z] TEST SETUP: [2025-03-04T21:52:39.810Z] Nothing to be done for setup. [2025-03-04T21:52:39.810Z] [2025-03-04T21:52:39.810Z] TESTING: [2025-03-04T21:52:42.898Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2025-03-04T21:52:45.137Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads. [2025-03-04T21:52:48.271Z] Got 100004 ratings from 671 users on 9066 movies. [2025-03-04T21:52:48.986Z] Training: 60056, validation: 20285, test: 19854 [2025-03-04T21:52:48.986Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-03-04T21:52:48.986Z] GC before operation: completed in 276.682 ms, heap usage 115.973 MB -> 28.867 MB. [2025-03-04T21:52:55.429Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-03-04T21:52:58.523Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-03-04T21:53:01.616Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-03-04T21:53:04.735Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-03-04T21:53:06.193Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-03-04T21:53:07.639Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-03-04T21:53:09.189Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-03-04T21:53:10.675Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-03-04T21:53:11.391Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711. [2025-03-04T21:53:11.391Z] The best model improves the baseline by 14.43%. [2025-03-04T21:53:11.391Z] Movies recommended for you: [2025-03-04T21:53:11.391Z] WARNING: This benchmark provides no result that can be validated. [2025-03-04T21:53:11.391Z] There is no way to check that no silent failure occurred. [2025-03-04T21:53:11.391Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (22387.465 ms) ====== [2025-03-04T21:53:11.391Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-03-04T21:53:11.391Z] GC before operation: completed in 337.536 ms, heap usage 465.430 MB -> 44.561 MB. [2025-03-04T21:53:13.651Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-03-04T21:53:16.774Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-03-04T21:53:19.089Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-03-04T21:53:21.702Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-03-04T21:53:23.151Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-03-04T21:53:24.632Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-03-04T21:53:28.815Z] RMSE (validation) = 0.9275717388537592 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-03-04T21:53:28.815Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-03-04T21:53:28.815Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711. [2025-03-04T21:53:29.503Z] The best model improves the baseline by 14.43%. [2025-03-04T21:53:29.503Z] Movies recommended for you: [2025-03-04T21:53:29.503Z] WARNING: This benchmark provides no result that can be validated. [2025-03-04T21:53:29.503Z] There is no way to check that no silent failure occurred. [2025-03-04T21:53:29.503Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (17690.533 ms) ====== [2025-03-04T21:53:29.503Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-03-04T21:53:29.503Z] GC before operation: completed in 235.089 ms, heap usage 361.642 MB -> 45.589 MB. [2025-03-04T21:53:31.861Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-03-04T21:53:34.988Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-03-04T21:53:37.225Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-03-04T21:53:40.333Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-03-04T21:53:41.783Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-03-04T21:53:42.476Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-03-04T21:53:43.917Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-03-04T21:53:45.362Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-03-04T21:53:46.046Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712. [2025-03-04T21:53:46.046Z] The best model improves the baseline by 14.43%. [2025-03-04T21:53:46.046Z] Movies recommended for you: [2025-03-04T21:53:46.046Z] WARNING: This benchmark provides no result that can be validated. [2025-03-04T21:53:46.046Z] There is no way to check that no silent failure occurred. [2025-03-04T21:53:46.046Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (16375.464 ms) ====== [2025-03-04T21:53:46.046Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-03-04T21:53:46.046Z] GC before operation: completed in 196.312 ms, heap usage 138.158 MB -> 47.164 MB. [2025-03-04T21:53:48.283Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-03-04T21:53:50.521Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-03-04T21:53:52.754Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-03-04T21:53:54.988Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-03-04T21:53:56.413Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-03-04T21:53:57.840Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-03-04T21:53:59.382Z] RMSE (validation) = 0.9275717388537592 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-03-04T21:54:01.718Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-03-04T21:54:01.718Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712. [2025-03-04T21:54:01.718Z] The best model improves the baseline by 14.43%. [2025-03-04T21:54:01.718Z] Movies recommended for you: [2025-03-04T21:54:01.718Z] WARNING: This benchmark provides no result that can be validated. [2025-03-04T21:54:01.718Z] There is no way to check that no silent failure occurred. [2025-03-04T21:54:01.718Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (15475.974 ms) ====== [2025-03-04T21:54:01.718Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-03-04T21:54:01.718Z] GC before operation: completed in 173.114 ms, heap usage 504.677 MB -> 51.519 MB. [2025-03-04T21:54:04.955Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-03-04T21:54:10.503Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-03-04T21:54:10.503Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-03-04T21:54:10.503Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-03-04T21:54:18.442Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-03-04T21:54:18.442Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-03-04T21:54:18.442Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-03-04T21:54:18.442Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-03-04T21:54:18.442Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711. [2025-03-04T21:54:18.442Z] The best model improves the baseline by 14.43%. [2025-03-04T21:54:18.442Z] Movies recommended for you: [2025-03-04T21:54:18.442Z] WARNING: This benchmark provides no result that can be validated. [2025-03-04T21:54:18.442Z] There is no way to check that no silent failure occurred. [2025-03-04T21:54:18.442Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (14928.641 ms) ====== [2025-03-04T21:54:18.442Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-03-04T21:54:18.442Z] GC before operation: completed in 197.097 ms, heap usage 440.521 MB -> 51.892 MB. [2025-03-04T21:54:23.302Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-03-04T21:54:23.302Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-03-04T21:54:23.302Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-03-04T21:54:26.108Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-03-04T21:54:26.800Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-03-04T21:54:29.539Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-03-04T21:54:29.540Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-03-04T21:54:30.962Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-03-04T21:54:36.408Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712. [2025-03-04T21:54:36.408Z] The best model improves the baseline by 14.43%. [2025-03-04T21:54:36.408Z] Movies recommended for you: [2025-03-04T21:54:36.408Z] WARNING: This benchmark provides no result that can be validated. [2025-03-04T21:54:36.408Z] There is no way to check that no silent failure occurred. [2025-03-04T21:54:36.408Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (14611.170 ms) ====== [2025-03-04T21:54:36.408Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-03-04T21:54:36.408Z] GC before operation: completed in 151.436 ms, heap usage 239.196 MB -> 47.608 MB. [2025-03-04T21:54:36.408Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-03-04T21:54:36.408Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-03-04T21:54:37.883Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-03-04T21:54:43.800Z] RMSE (validation) = 1.0045407704488025 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-03-04T21:54:43.800Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-03-04T21:54:43.800Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-03-04T21:54:44.488Z] RMSE (validation) = 0.9275717388537592 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-03-04T21:54:51.431Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-03-04T21:54:51.431Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712. [2025-03-04T21:54:51.431Z] The best model improves the baseline by 14.43%. [2025-03-04T21:54:51.431Z] Movies recommended for you: [2025-03-04T21:54:51.431Z] WARNING: This benchmark provides no result that can be validated. [2025-03-04T21:54:51.431Z] There is no way to check that no silent failure occurred. [2025-03-04T21:54:51.431Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (14455.341 ms) ====== [2025-03-04T21:54:51.431Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-03-04T21:54:51.431Z] GC before operation: completed in 159.909 ms, heap usage 287.868 MB -> 52.426 MB. [2025-03-04T21:54:51.431Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-03-04T21:54:55.546Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-03-04T21:54:55.546Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-03-04T21:54:55.546Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-03-04T21:54:56.241Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-03-04T21:54:57.768Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-03-04T21:54:59.308Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-03-04T21:55:00.873Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-03-04T21:55:00.873Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711. [2025-03-04T21:55:00.873Z] The best model improves the baseline by 14.43%. [2025-03-04T21:55:00.873Z] Movies recommended for you: [2025-03-04T21:55:00.873Z] WARNING: This benchmark provides no result that can be validated. [2025-03-04T21:55:00.873Z] There is no way to check that no silent failure occurred. [2025-03-04T21:55:00.873Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (14671.753 ms) ====== [2025-03-04T21:55:00.873Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-03-04T21:55:00.873Z] GC before operation: completed in 155.436 ms, heap usage 167.418 MB -> 50.629 MB. [2025-03-04T21:55:03.132Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-03-04T21:55:05.356Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-03-04T21:55:07.594Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-03-04T21:55:09.844Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-03-04T21:55:11.280Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-03-04T21:55:12.704Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-03-04T21:55:14.131Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-03-04T21:55:15.562Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-03-04T21:55:15.562Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711. [2025-03-04T21:55:15.562Z] The best model improves the baseline by 14.43%. [2025-03-04T21:55:15.562Z] Movies recommended for you: [2025-03-04T21:55:15.562Z] WARNING: This benchmark provides no result that can be validated. [2025-03-04T21:55:15.562Z] There is no way to check that no silent failure occurred. [2025-03-04T21:55:15.562Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (14504.348 ms) ====== [2025-03-04T21:55:15.562Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-03-04T21:55:15.562Z] GC before operation: completed in 150.095 ms, heap usage 235.264 MB -> 50.267 MB. [2025-03-04T21:55:17.792Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-03-04T21:55:20.000Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-03-04T21:55:22.706Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-03-04T21:55:24.130Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-03-04T21:55:25.569Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-03-04T21:55:27.008Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-03-04T21:55:28.428Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-03-04T21:55:29.866Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-03-04T21:55:29.866Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711. [2025-03-04T21:55:29.866Z] The best model improves the baseline by 14.43%. [2025-03-04T21:55:30.552Z] Movies recommended for you: [2025-03-04T21:55:30.552Z] WARNING: This benchmark provides no result that can be validated. [2025-03-04T21:55:30.552Z] There is no way to check that no silent failure occurred. [2025-03-04T21:55:30.552Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (14499.613 ms) ====== [2025-03-04T21:55:30.552Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-03-04T21:55:30.552Z] GC before operation: completed in 170.620 ms, heap usage 163.787 MB -> 46.243 MB. [2025-03-04T21:55:32.777Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-03-04T21:55:35.008Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-03-04T21:55:37.238Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-03-04T21:55:38.659Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-03-04T21:55:40.192Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-03-04T21:55:41.630Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-03-04T21:55:43.066Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-03-04T21:55:44.585Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-03-04T21:55:44.585Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712. [2025-03-04T21:55:44.585Z] The best model improves the baseline by 14.43%. [2025-03-04T21:55:44.585Z] Movies recommended for you: [2025-03-04T21:55:44.585Z] WARNING: This benchmark provides no result that can be validated. [2025-03-04T21:55:44.585Z] There is no way to check that no silent failure occurred. [2025-03-04T21:55:44.585Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (14275.458 ms) ====== [2025-03-04T21:55:44.585Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-03-04T21:55:44.585Z] GC before operation: completed in 129.184 ms, heap usage 654.156 MB -> 52.017 MB. [2025-03-04T21:55:46.922Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-03-04T21:55:49.149Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-03-04T21:55:51.418Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-03-04T21:55:53.770Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-03-04T21:55:55.213Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-03-04T21:55:56.694Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-03-04T21:55:57.401Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-03-04T21:55:58.840Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-03-04T21:55:59.526Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711. [2025-03-04T21:55:59.526Z] The best model improves the baseline by 14.43%. [2025-03-04T21:55:59.526Z] Movies recommended for you: [2025-03-04T21:55:59.526Z] WARNING: This benchmark provides no result that can be validated. [2025-03-04T21:55:59.526Z] There is no way to check that no silent failure occurred. [2025-03-04T21:55:59.526Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (14464.275 ms) ====== [2025-03-04T21:55:59.526Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-03-04T21:55:59.526Z] GC before operation: completed in 127.014 ms, heap usage 435.587 MB -> 55.555 MB. [2025-03-04T21:56:01.749Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-03-04T21:56:03.982Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-03-04T21:56:06.225Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-03-04T21:56:08.535Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-03-04T21:56:09.997Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-03-04T21:56:10.783Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-03-04T21:56:12.213Z] RMSE (validation) = 0.9275717388537592 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-03-04T21:56:13.635Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-03-04T21:56:13.635Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712. [2025-03-04T21:56:13.635Z] The best model improves the baseline by 14.43%. [2025-03-04T21:56:14.335Z] Movies recommended for you: [2025-03-04T21:56:14.335Z] WARNING: This benchmark provides no result that can be validated. [2025-03-04T21:56:14.335Z] There is no way to check that no silent failure occurred. [2025-03-04T21:56:14.335Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (14613.210 ms) ====== [2025-03-04T21:56:14.335Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-03-04T21:56:14.335Z] GC before operation: completed in 116.269 ms, heap usage 302.089 MB -> 48.749 MB. [2025-03-04T21:56:16.560Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-03-04T21:56:18.807Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-03-04T21:56:21.028Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-03-04T21:56:23.261Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-03-04T21:56:23.948Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-03-04T21:56:25.387Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-03-04T21:56:26.814Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-03-04T21:56:28.725Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-03-04T21:56:28.725Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711. [2025-03-04T21:56:28.725Z] The best model improves the baseline by 14.43%. [2025-03-04T21:56:28.725Z] Movies recommended for you: [2025-03-04T21:56:28.725Z] WARNING: This benchmark provides no result that can be validated. [2025-03-04T21:56:28.725Z] There is no way to check that no silent failure occurred. [2025-03-04T21:56:28.725Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (14480.550 ms) ====== [2025-03-04T21:56:28.725Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-03-04T21:56:28.725Z] GC before operation: completed in 141.049 ms, heap usage 598.581 MB -> 54.179 MB. [2025-03-04T21:56:30.953Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-03-04T21:56:33.244Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-03-04T21:56:35.598Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-03-04T21:56:37.864Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-03-04T21:56:38.563Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-03-04T21:56:40.088Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-03-04T21:56:41.527Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-03-04T21:56:42.999Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-03-04T21:56:42.999Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711. [2025-03-04T21:56:42.999Z] The best model improves the baseline by 14.43%. [2025-03-04T21:56:43.721Z] Movies recommended for you: [2025-03-04T21:56:43.721Z] WARNING: This benchmark provides no result that can be validated. [2025-03-04T21:56:43.721Z] There is no way to check that no silent failure occurred. [2025-03-04T21:56:43.721Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14564.188 ms) ====== [2025-03-04T21:56:43.721Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-03-04T21:56:43.721Z] GC before operation: completed in 125.400 ms, heap usage 585.153 MB -> 52.215 MB. [2025-03-04T21:56:46.008Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-03-04T21:56:48.244Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-03-04T21:56:50.466Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-03-04T21:56:52.755Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-03-04T21:56:53.468Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-03-04T21:56:54.916Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-03-04T21:56:56.351Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-03-04T21:56:57.785Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-03-04T21:56:58.520Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712. [2025-03-04T21:56:58.520Z] The best model improves the baseline by 14.43%. [2025-03-04T21:56:58.520Z] Movies recommended for you: [2025-03-04T21:56:58.520Z] WARNING: This benchmark provides no result that can be validated. [2025-03-04T21:56:58.520Z] There is no way to check that no silent failure occurred. [2025-03-04T21:56:58.520Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (14961.589 ms) ====== [2025-03-04T21:56:58.520Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-03-04T21:56:58.520Z] GC before operation: completed in 180.177 ms, heap usage 670.219 MB -> 64.196 MB. [2025-03-04T21:57:00.753Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-03-04T21:57:02.991Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-03-04T21:57:05.225Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-03-04T21:57:07.449Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-03-04T21:57:08.890Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-03-04T21:57:10.312Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-03-04T21:57:11.752Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-03-04T21:57:12.475Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-03-04T21:57:13.166Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711. [2025-03-04T21:57:13.166Z] The best model improves the baseline by 14.43%. [2025-03-04T21:57:13.166Z] Movies recommended for you: [2025-03-04T21:57:13.166Z] WARNING: This benchmark provides no result that can be validated. [2025-03-04T21:57:13.166Z] There is no way to check that no silent failure occurred. [2025-03-04T21:57:13.166Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (14605.275 ms) ====== [2025-03-04T21:57:13.166Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-03-04T21:57:13.166Z] GC before operation: completed in 141.277 ms, heap usage 134.589 MB -> 48.557 MB. [2025-03-04T21:57:15.401Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-03-04T21:57:17.618Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-03-04T21:57:19.844Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-03-04T21:57:22.078Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-03-04T21:57:23.514Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-03-04T21:57:24.938Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-03-04T21:57:26.372Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-03-04T21:57:27.832Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-03-04T21:57:27.832Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711. [2025-03-04T21:57:27.832Z] The best model improves the baseline by 14.43%. [2025-03-04T21:57:27.832Z] Movies recommended for you: [2025-03-04T21:57:27.832Z] WARNING: This benchmark provides no result that can be validated. [2025-03-04T21:57:27.832Z] There is no way to check that no silent failure occurred. [2025-03-04T21:57:27.832Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (14474.959 ms) ====== [2025-03-04T21:57:27.832Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-03-04T21:57:27.832Z] GC before operation: completed in 127.041 ms, heap usage 276.520 MB -> 50.130 MB. [2025-03-04T21:57:30.155Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-03-04T21:57:32.396Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-03-04T21:57:34.773Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-03-04T21:57:36.231Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-03-04T21:57:37.715Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-03-04T21:57:39.414Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-03-04T21:57:40.869Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-03-04T21:57:42.298Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-03-04T21:57:42.298Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711. [2025-03-04T21:57:42.298Z] The best model improves the baseline by 14.43%. [2025-03-04T21:57:42.298Z] Movies recommended for you: [2025-03-04T21:57:42.298Z] WARNING: This benchmark provides no result that can be validated. [2025-03-04T21:57:42.298Z] There is no way to check that no silent failure occurred. [2025-03-04T21:57:42.298Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (14375.684 ms) ====== [2025-03-04T21:57:42.298Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-03-04T21:57:42.298Z] GC before operation: completed in 128.076 ms, heap usage 93.176 MB -> 49.941 MB. [2025-03-04T21:57:44.519Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-03-04T21:57:46.772Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-03-04T21:57:48.995Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-03-04T21:57:51.214Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-03-04T21:57:52.638Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-03-04T21:57:54.070Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-03-04T21:57:55.502Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-03-04T21:57:56.946Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-03-04T21:57:56.946Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712. [2025-03-04T21:57:56.946Z] The best model improves the baseline by 14.43%. [2025-03-04T21:57:56.946Z] Movies recommended for you: [2025-03-04T21:57:56.946Z] WARNING: This benchmark provides no result that can be validated. [2025-03-04T21:57:56.946Z] There is no way to check that no silent failure occurred. [2025-03-04T21:57:56.946Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (14525.920 ms) ====== [2025-03-04T21:57:58.368Z] ----------------------------------- [2025-03-04T21:57:58.368Z] renaissance-movie-lens_0_PASSED [2025-03-04T21:57:58.368Z] ----------------------------------- [2025-03-04T21:57:58.368Z] [2025-03-04T21:57:58.368Z] TEST TEARDOWN: [2025-03-04T21:57:58.368Z] Nothing to be done for teardown. [2025-03-04T21:57:58.368Z] renaissance-movie-lens_0 Finish Time: Tue Mar 4 15:57:58 2025 Epoch Time (ms): 1741125478083