[2025-02-13T22:16:42.826Z] Running test renaissance-movie-lens_0 ... [2025-02-13T22:16:42.826Z] =============================================== [2025-02-13T22:16:42.826Z] renaissance-movie-lens_0 Start Time: Thu Feb 13 16:16:42 2025 Epoch Time (ms): 1739485002723 [2025-02-13T22:16:42.826Z] variation: NoOptions [2025-02-13T22:16:42.826Z] JVM_OPTIONS: [2025-02-13T22:16:42.826Z] { \ [2025-02-13T22:16:42.826Z] echo ""; echo "TEST SETUP:"; \ [2025-02-13T22:16:42.826Z] echo "Nothing to be done for setup."; \ [2025-02-13T22:16:42.826Z] mkdir -p "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17394841722889/renaissance-movie-lens_0"; \ [2025-02-13T22:16:42.826Z] cd "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17394841722889/renaissance-movie-lens_0"; \ [2025-02-13T22:16:42.826Z] echo ""; echo "TESTING:"; \ [2025-02-13T22:16:42.826Z] "/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_17394841722889/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-02-13T22:16:42.826Z] 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_17394841722889/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-02-13T22:16:42.826Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-02-13T22:16:42.826Z] echo "Nothing to be done for teardown."; \ [2025-02-13T22:16:42.826Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17394841722889/TestTargetResult"; [2025-02-13T22:16:42.826Z] [2025-02-13T22:16:42.826Z] TEST SETUP: [2025-02-13T22:16:42.826Z] Nothing to be done for setup. [2025-02-13T22:16:42.826Z] [2025-02-13T22:16:42.826Z] TESTING: [2025-02-13T22:16:45.364Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2025-02-13T22:16:47.798Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads. [2025-02-13T22:16:51.184Z] Got 100004 ratings from 671 users on 9066 movies. [2025-02-13T22:16:51.962Z] Training: 60056, validation: 20285, test: 19854 [2025-02-13T22:16:51.962Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-02-13T22:16:51.962Z] GC before operation: completed in 405.210 ms, heap usage 63.424 MB -> 28.795 MB. [2025-02-13T22:16:57.562Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:17:00.961Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:17:04.383Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:17:06.845Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:17:08.431Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:17:09.999Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:17:11.585Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:17:13.172Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:17:13.948Z] 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. [2025-02-13T22:17:13.948Z] The best model improves the baseline by 14.43%. [2025-02-13T22:17:13.948Z] Movies recommended for you: [2025-02-13T22:17:13.948Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:17:13.948Z] There is no way to check that no silent failure occurred. [2025-02-13T22:17:13.948Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (21902.561 ms) ====== [2025-02-13T22:17:13.948Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-02-13T22:17:13.948Z] GC before operation: completed in 329.523 ms, heap usage 334.197 MB -> 47.198 MB. [2025-02-13T22:17:16.412Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:17:19.813Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:17:23.739Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:17:25.371Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:17:26.949Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:17:28.551Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:17:30.159Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:17:32.663Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:17:32.663Z] 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. [2025-02-13T22:17:32.663Z] The best model improves the baseline by 14.43%. [2025-02-13T22:17:32.663Z] Movies recommended for you: [2025-02-13T22:17:32.663Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:17:32.663Z] There is no way to check that no silent failure occurred. [2025-02-13T22:17:32.663Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (18408.480 ms) ====== [2025-02-13T22:17:32.663Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-02-13T22:17:32.663Z] GC before operation: completed in 205.252 ms, heap usage 538.561 MB -> 51.725 MB. [2025-02-13T22:17:36.067Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:17:38.534Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:17:40.994Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:17:43.532Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:17:45.103Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:17:46.699Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:17:48.266Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:17:49.839Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:17:49.840Z] 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. [2025-02-13T22:17:49.840Z] The best model improves the baseline by 14.43%. [2025-02-13T22:17:49.840Z] Movies recommended for you: [2025-02-13T22:17:49.840Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:17:49.840Z] There is no way to check that no silent failure occurred. [2025-02-13T22:17:49.840Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (17342.247 ms) ====== [2025-02-13T22:17:49.840Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-02-13T22:17:50.598Z] GC before operation: completed in 213.205 ms, heap usage 422.124 MB -> 57.738 MB. [2025-02-13T22:17:53.061Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:17:54.778Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:17:57.230Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:17:59.681Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:18:01.257Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:18:02.026Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:18:03.597Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:18:05.165Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:18:05.937Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712. [2025-02-13T22:18:05.937Z] The best model improves the baseline by 14.43%. [2025-02-13T22:18:05.937Z] Movies recommended for you: [2025-02-13T22:18:05.937Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:18:05.937Z] There is no way to check that no silent failure occurred. [2025-02-13T22:18:05.937Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (15310.061 ms) ====== [2025-02-13T22:18:05.937Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-02-13T22:18:05.937Z] GC before operation: completed in 155.612 ms, heap usage 255.067 MB -> 46.104 MB. [2025-02-13T22:18:08.380Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:18:10.849Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:18:13.341Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:18:14.927Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:18:16.497Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:18:18.073Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:18:19.662Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:18:21.239Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:18:21.239Z] 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. [2025-02-13T22:18:21.239Z] The best model improves the baseline by 14.43%. [2025-02-13T22:18:21.239Z] Movies recommended for you: [2025-02-13T22:18:21.239Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:18:21.239Z] There is no way to check that no silent failure occurred. [2025-02-13T22:18:21.239Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (15450.258 ms) ====== [2025-02-13T22:18:21.239Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-02-13T22:18:21.239Z] GC before operation: completed in 144.432 ms, heap usage 163.367 MB -> 49.636 MB. [2025-02-13T22:18:23.906Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:18:26.367Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:18:28.808Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:18:30.384Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:18:31.981Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:18:33.577Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:18:34.346Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:18:35.913Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:18:36.671Z] 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. [2025-02-13T22:18:36.671Z] The best model improves the baseline by 14.43%. [2025-02-13T22:18:36.671Z] Movies recommended for you: [2025-02-13T22:18:36.671Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:18:36.671Z] There is no way to check that no silent failure occurred. [2025-02-13T22:18:36.671Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (14979.268 ms) ====== [2025-02-13T22:18:36.671Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-02-13T22:18:36.671Z] GC before operation: completed in 155.244 ms, heap usage 260.153 MB -> 47.089 MB. [2025-02-13T22:18:39.135Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:18:40.752Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:18:43.231Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:18:45.681Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:18:47.249Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:18:48.029Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:18:49.614Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:18:51.194Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:18:51.194Z] 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. [2025-02-13T22:18:51.194Z] The best model improves the baseline by 14.43%. [2025-02-13T22:18:51.972Z] Movies recommended for you: [2025-02-13T22:18:51.972Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:18:51.972Z] There is no way to check that no silent failure occurred. [2025-02-13T22:18:51.972Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (15013.498 ms) ====== [2025-02-13T22:18:51.972Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-02-13T22:18:51.972Z] GC before operation: completed in 178.865 ms, heap usage 220.756 MB -> 46.489 MB. [2025-02-13T22:18:53.559Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:18:56.003Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:18:58.443Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:19:00.901Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:19:01.659Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:19:03.260Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:19:04.857Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:19:05.624Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:19:06.398Z] 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. [2025-02-13T22:19:06.398Z] The best model improves the baseline by 14.43%. [2025-02-13T22:19:06.398Z] Movies recommended for you: [2025-02-13T22:19:06.398Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:19:06.398Z] There is no way to check that no silent failure occurred. [2025-02-13T22:19:06.398Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (14508.847 ms) ====== [2025-02-13T22:19:06.398Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-02-13T22:19:06.398Z] GC before operation: completed in 134.543 ms, heap usage 278.054 MB -> 50.467 MB. [2025-02-13T22:19:08.848Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:19:10.418Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:19:12.890Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:19:15.343Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:19:16.910Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:19:18.485Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:19:19.245Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:19:20.835Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:19:20.835Z] 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. [2025-02-13T22:19:20.835Z] The best model improves the baseline by 14.43%. [2025-02-13T22:19:21.625Z] Movies recommended for you: [2025-02-13T22:19:21.625Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:19:21.625Z] There is no way to check that no silent failure occurred. [2025-02-13T22:19:21.625Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (14923.632 ms) ====== [2025-02-13T22:19:21.625Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-02-13T22:19:21.625Z] GC before operation: completed in 126.662 ms, heap usage 300.191 MB -> 46.708 MB. [2025-02-13T22:19:24.083Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:19:25.684Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:19:28.161Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:19:29.973Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:19:31.549Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:19:33.139Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:19:34.713Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:19:35.491Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:19:36.250Z] 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. [2025-02-13T22:19:36.250Z] The best model improves the baseline by 14.43%. [2025-02-13T22:19:36.250Z] Movies recommended for you: [2025-02-13T22:19:36.250Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:19:36.250Z] There is no way to check that no silent failure occurred. [2025-02-13T22:19:36.250Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (14550.209 ms) ====== [2025-02-13T22:19:36.250Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-02-13T22:19:36.250Z] GC before operation: completed in 211.478 ms, heap usage 168.029 MB -> 48.127 MB. [2025-02-13T22:19:38.709Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:19:40.294Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:19:42.745Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:19:44.348Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:19:45.929Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:19:47.506Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:19:49.076Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:19:50.660Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:19:50.660Z] 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. [2025-02-13T22:19:50.660Z] The best model improves the baseline by 14.43%. [2025-02-13T22:19:50.660Z] Movies recommended for you: [2025-02-13T22:19:50.660Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:19:50.660Z] There is no way to check that no silent failure occurred. [2025-02-13T22:19:50.660Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (14381.127 ms) ====== [2025-02-13T22:19:50.660Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-02-13T22:19:50.660Z] GC before operation: completed in 127.284 ms, heap usage 662.413 MB -> 51.561 MB. [2025-02-13T22:19:53.102Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:19:55.551Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:19:57.140Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:19:59.591Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:20:01.163Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:20:02.738Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:20:03.510Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:20:05.093Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:20:05.093Z] 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. [2025-02-13T22:20:05.093Z] The best model improves the baseline by 14.43%. [2025-02-13T22:20:05.850Z] Movies recommended for you: [2025-02-13T22:20:05.850Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:20:05.850Z] There is no way to check that no silent failure occurred. [2025-02-13T22:20:05.850Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (14821.777 ms) ====== [2025-02-13T22:20:05.850Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-02-13T22:20:05.850Z] GC before operation: completed in 119.075 ms, heap usage 175.403 MB -> 50.369 MB. [2025-02-13T22:20:08.313Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:20:09.891Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:20:12.348Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:20:14.806Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:20:16.384Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:20:17.145Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:20:18.740Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:20:20.328Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:20:21.090Z] 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. [2025-02-13T22:20:21.090Z] The best model improves the baseline by 14.43%. [2025-02-13T22:20:21.090Z] Movies recommended for you: [2025-02-13T22:20:21.090Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:20:21.090Z] There is no way to check that no silent failure occurred. [2025-02-13T22:20:21.090Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (15255.436 ms) ====== [2025-02-13T22:20:21.090Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-02-13T22:20:21.090Z] GC before operation: completed in 165.983 ms, heap usage 597.570 MB -> 51.094 MB. [2025-02-13T22:20:23.547Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:20:25.998Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:20:27.586Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:20:29.683Z] RMSE (validation) = 1.0045407704488025 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:20:31.286Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:20:32.859Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:20:33.628Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:20:35.227Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:20:35.227Z] 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. [2025-02-13T22:20:35.227Z] The best model improves the baseline by 14.43%. [2025-02-13T22:20:35.985Z] Movies recommended for you: [2025-02-13T22:20:35.985Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:20:35.985Z] There is no way to check that no silent failure occurred. [2025-02-13T22:20:35.985Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (14593.420 ms) ====== [2025-02-13T22:20:35.985Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-02-13T22:20:35.985Z] GC before operation: completed in 137.030 ms, heap usage 613.769 MB -> 50.771 MB. [2025-02-13T22:20:38.427Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:20:40.003Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:20:42.476Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:20:44.922Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:20:46.560Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:20:47.319Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:20:48.886Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:20:50.473Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:20:50.473Z] 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. [2025-02-13T22:20:50.473Z] The best model improves the baseline by 14.43%. [2025-02-13T22:20:50.473Z] Movies recommended for you: [2025-02-13T22:20:50.473Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:20:50.473Z] There is no way to check that no silent failure occurred. [2025-02-13T22:20:50.473Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14858.671 ms) ====== [2025-02-13T22:20:50.473Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-02-13T22:20:50.473Z] GC before operation: completed in 157.626 ms, heap usage 670.603 MB -> 62.959 MB. [2025-02-13T22:20:52.939Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:20:55.407Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:20:57.869Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:20:59.443Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:21:01.023Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:21:02.615Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:21:04.200Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:21:04.965Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:21:05.736Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711. [2025-02-13T22:21:05.736Z] The best model improves the baseline by 14.43%. [2025-02-13T22:21:05.736Z] Movies recommended for you: [2025-02-13T22:21:05.736Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:21:05.736Z] There is no way to check that no silent failure occurred. [2025-02-13T22:21:05.736Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (14838.657 ms) ====== [2025-02-13T22:21:05.736Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-02-13T22:21:05.736Z] GC before operation: completed in 151.998 ms, heap usage 164.101 MB -> 46.346 MB. [2025-02-13T22:21:08.223Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:21:09.789Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:21:12.236Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:21:14.688Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:21:16.278Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:21:17.049Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:21:18.625Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:21:20.198Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:21:20.198Z] 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. [2025-02-13T22:21:20.198Z] The best model improves the baseline by 14.43%. [2025-02-13T22:21:20.198Z] Movies recommended for you: [2025-02-13T22:21:20.198Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:21:20.198Z] There is no way to check that no silent failure occurred. [2025-02-13T22:21:20.198Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (14547.699 ms) ====== [2025-02-13T22:21:20.198Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-02-13T22:21:20.198Z] GC before operation: completed in 123.771 ms, heap usage 173.404 MB -> 48.651 MB. [2025-02-13T22:21:22.698Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:21:25.172Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:21:27.627Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:21:30.077Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:21:30.835Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:21:32.930Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:21:33.692Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:21:35.275Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:21:35.275Z] 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. [2025-02-13T22:21:35.275Z] The best model improves the baseline by 14.43%. [2025-02-13T22:21:35.275Z] Movies recommended for you: [2025-02-13T22:21:35.275Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:21:35.275Z] There is no way to check that no silent failure occurred. [2025-02-13T22:21:35.275Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (15023.700 ms) ====== [2025-02-13T22:21:35.275Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-02-13T22:21:36.039Z] GC before operation: completed in 130.230 ms, heap usage 324.104 MB -> 46.856 MB. [2025-02-13T22:21:37.607Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:21:40.057Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:21:42.506Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:21:44.240Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:21:45.814Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:21:47.406Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:21:48.987Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:21:50.587Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:21:50.587Z] 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. [2025-02-13T22:21:50.587Z] The best model improves the baseline by 14.43%. [2025-02-13T22:21:50.587Z] Movies recommended for you: [2025-02-13T22:21:50.587Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:21:50.587Z] There is no way to check that no silent failure occurred. [2025-02-13T22:21:50.587Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (14927.904 ms) ====== [2025-02-13T22:21:50.587Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-02-13T22:21:50.587Z] GC before operation: completed in 135.762 ms, heap usage 411.824 MB -> 50.951 MB. [2025-02-13T22:21:53.033Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:21:55.486Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:21:57.082Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:21:59.539Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:22:01.109Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:22:01.874Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:22:03.445Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:22:05.031Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:22:05.031Z] 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. [2025-02-13T22:22:05.031Z] The best model improves the baseline by 14.43%. [2025-02-13T22:22:05.031Z] Movies recommended for you: [2025-02-13T22:22:05.031Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:22:05.031Z] There is no way to check that no silent failure occurred. [2025-02-13T22:22:05.031Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (14448.059 ms) ====== [2025-02-13T22:22:06.604Z] ----------------------------------- [2025-02-13T22:22:06.604Z] renaissance-movie-lens_0_PASSED [2025-02-13T22:22:06.604Z] ----------------------------------- [2025-02-13T22:22:06.604Z] [2025-02-13T22:22:06.604Z] TEST TEARDOWN: [2025-02-13T22:22:06.604Z] Nothing to be done for teardown. [2025-02-13T22:22:06.604Z] renaissance-movie-lens_0 Finish Time: Thu Feb 13 16:22:06 2025 Epoch Time (ms): 1739485326098