[2025-02-13T21:58:26.671Z] Running test renaissance-movie-lens_0 ... [2025-02-13T21:58:26.671Z] =============================================== [2025-02-13T21:58:26.671Z] renaissance-movie-lens_0 Start Time: Thu Feb 13 21:58:26 2025 Epoch Time (ms): 1739483906299 [2025-02-13T21:58:26.671Z] variation: NoOptions [2025-02-13T21:58:26.671Z] JVM_OPTIONS: [2025-02-13T21:58:26.671Z] { \ [2025-02-13T21:58:26.671Z] echo ""; echo "TEST SETUP:"; \ [2025-02-13T21:58:26.671Z] echo "Nothing to be done for setup."; \ [2025-02-13T21:58:26.671Z] mkdir -p "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17394829193994/renaissance-movie-lens_0"; \ [2025-02-13T21:58:26.671Z] cd "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17394829193994/renaissance-movie-lens_0"; \ [2025-02-13T21:58:26.671Z] echo ""; echo "TESTING:"; \ [2025-02-13T21:58:26.671Z] "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/jdkbinary/j2sdk-image/bin/java" -jar "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17394829193994/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-02-13T21:58:26.671Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17394829193994/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-02-13T21:58:26.671Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-02-13T21:58:26.671Z] echo "Nothing to be done for teardown."; \ [2025-02-13T21:58:26.671Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17394829193994/TestTargetResult"; [2025-02-13T21:58:26.671Z] [2025-02-13T21:58:26.671Z] TEST SETUP: [2025-02-13T21:58:26.671Z] Nothing to be done for setup. [2025-02-13T21:58:26.671Z] [2025-02-13T21:58:26.671Z] TESTING: [2025-02-13T21:58:29.706Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2025-02-13T21:58:32.744Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads. [2025-02-13T21:58:36.916Z] Got 100004 ratings from 671 users on 9066 movies. [2025-02-13T21:58:36.916Z] Training: 60056, validation: 20285, test: 19854 [2025-02-13T21:58:36.916Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-02-13T21:58:36.916Z] GC before operation: completed in 194.743 ms, heap usage 230.376 MB -> 29.346 MB. [2025-02-13T21:58:43.815Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T21:58:46.848Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T21:58:49.881Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T21:58:52.914Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T21:58:54.879Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T21:58:56.846Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T21:58:58.814Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T21:58:59.771Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T21:59:00.729Z] 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. [2025-02-13T21:59:00.729Z] The best model improves the baseline by 14.43%. [2025-02-13T21:59:00.729Z] Movies recommended for you: [2025-02-13T21:59:00.729Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T21:59:00.729Z] There is no way to check that no silent failure occurred. [2025-02-13T21:59:00.729Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (23810.926 ms) ====== [2025-02-13T21:59:00.729Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-02-13T21:59:00.729Z] GC before operation: completed in 297.550 ms, heap usage 1.094 GB -> 57.091 MB. [2025-02-13T21:59:03.765Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T21:59:06.831Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T21:59:09.862Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T21:59:11.829Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T21:59:13.796Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T21:59:15.764Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T21:59:16.722Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T21:59:18.393Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T21:59:19.352Z] 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. [2025-02-13T21:59:19.352Z] The best model improves the baseline by 14.43%. [2025-02-13T21:59:19.352Z] Movies recommended for you: [2025-02-13T21:59:19.352Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T21:59:19.352Z] There is no way to check that no silent failure occurred. [2025-02-13T21:59:19.352Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (18423.698 ms) ====== [2025-02-13T21:59:19.352Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-02-13T21:59:19.352Z] GC before operation: completed in 235.933 ms, heap usage 251.090 MB -> 45.278 MB. [2025-02-13T21:59:22.388Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T21:59:24.354Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T21:59:27.392Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T21:59:29.356Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T21:59:31.321Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T21:59:33.285Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T21:59:35.254Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T21:59:36.215Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T21:59:36.215Z] 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. [2025-02-13T21:59:37.177Z] The best model improves the baseline by 14.43%. [2025-02-13T21:59:37.177Z] Movies recommended for you: [2025-02-13T21:59:37.177Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T21:59:37.177Z] There is no way to check that no silent failure occurred. [2025-02-13T21:59:37.177Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (17361.407 ms) ====== [2025-02-13T21:59:37.177Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-02-13T21:59:37.177Z] GC before operation: completed in 190.112 ms, heap usage 1.231 GB -> 53.756 MB. [2025-02-13T21:59:39.146Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T21:59:42.222Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T21:59:45.258Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T21:59:47.223Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T21:59:49.186Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T21:59:50.143Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T21:59:52.106Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T21:59:54.074Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T21:59:54.074Z] 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. [2025-02-13T21:59:54.074Z] The best model improves the baseline by 14.43%. [2025-02-13T21:59:54.074Z] Movies recommended for you: [2025-02-13T21:59:54.074Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T21:59:54.074Z] There is no way to check that no silent failure occurred. [2025-02-13T21:59:54.074Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (17267.042 ms) ====== [2025-02-13T21:59:54.074Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-02-13T21:59:54.074Z] GC before operation: completed in 198.955 ms, heap usage 1.214 GB -> 54.086 MB. [2025-02-13T21:59:57.107Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T21:59:59.085Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:00:02.116Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:00:04.080Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:00:06.045Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:00:07.003Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:00:08.969Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:00:09.925Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:00:09.925Z] 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. [2025-02-13T22:00:09.925Z] The best model improves the baseline by 14.43%. [2025-02-13T22:00:10.881Z] Movies recommended for you: [2025-02-13T22:00:10.881Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:00:10.881Z] There is no way to check that no silent failure occurred. [2025-02-13T22:00:10.881Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (15949.456 ms) ====== [2025-02-13T22:00:10.881Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-02-13T22:00:10.881Z] GC before operation: completed in 228.280 ms, heap usage 1.218 GB -> 56.197 MB. [2025-02-13T22:00:12.855Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:00:15.893Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:00:17.858Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:00:19.822Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:00:21.789Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:00:22.747Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:00:24.712Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:00:25.672Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:00:26.628Z] 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. [2025-02-13T22:00:26.628Z] The best model improves the baseline by 14.43%. [2025-02-13T22:00:26.628Z] Movies recommended for you: [2025-02-13T22:00:26.628Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:00:26.628Z] There is no way to check that no silent failure occurred. [2025-02-13T22:00:26.628Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (15770.169 ms) ====== [2025-02-13T22:00:26.628Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-02-13T22:00:26.628Z] GC before operation: completed in 192.617 ms, heap usage 1.240 GB -> 54.347 MB. [2025-02-13T22:00:28.597Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:00:31.632Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:00:33.595Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:00:35.974Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:00:37.940Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:00:38.896Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:00:40.878Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:00:42.846Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:00:42.846Z] 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. [2025-02-13T22:00:42.846Z] The best model improves the baseline by 14.43%. [2025-02-13T22:00:42.846Z] Movies recommended for you: [2025-02-13T22:00:42.846Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:00:42.846Z] There is no way to check that no silent failure occurred. [2025-02-13T22:00:42.846Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (16204.165 ms) ====== [2025-02-13T22:00:42.846Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-02-13T22:00:42.846Z] GC before operation: completed in 200.261 ms, heap usage 1.211 GB -> 54.190 MB. [2025-02-13T22:00:45.915Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:00:47.882Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:00:49.849Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:00:52.890Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:00:53.850Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:00:55.818Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:00:56.775Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:00:58.741Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:00:58.741Z] 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. [2025-02-13T22:00:58.742Z] The best model improves the baseline by 14.43%. [2025-02-13T22:00:58.742Z] Movies recommended for you: [2025-02-13T22:00:58.742Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:00:58.742Z] There is no way to check that no silent failure occurred. [2025-02-13T22:00:58.742Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (15722.570 ms) ====== [2025-02-13T22:00:58.742Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-02-13T22:00:58.742Z] GC before operation: completed in 194.746 ms, heap usage 1.128 GB -> 56.303 MB. [2025-02-13T22:01:01.773Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:01:03.736Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:01:05.701Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:01:08.735Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:01:09.694Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:01:11.658Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:01:12.621Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:01:14.586Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:01:14.586Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712. [2025-02-13T22:01:14.586Z] The best model improves the baseline by 14.43%. [2025-02-13T22:01:14.586Z] Movies recommended for you: [2025-02-13T22:01:14.586Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:01:14.586Z] There is no way to check that no silent failure occurred. [2025-02-13T22:01:14.586Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (15749.546 ms) ====== [2025-02-13T22:01:14.586Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-02-13T22:01:14.586Z] GC before operation: completed in 185.246 ms, heap usage 1.217 GB -> 58.180 MB. [2025-02-13T22:01:17.620Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:01:19.601Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:01:22.640Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:01:24.609Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:01:25.588Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:01:27.577Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:01:29.544Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:01:30.503Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:01:30.503Z] 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. [2025-02-13T22:01:30.503Z] The best model improves the baseline by 14.43%. [2025-02-13T22:01:30.503Z] Movies recommended for you: [2025-02-13T22:01:30.503Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:01:30.503Z] There is no way to check that no silent failure occurred. [2025-02-13T22:01:30.503Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (15932.898 ms) ====== [2025-02-13T22:01:30.503Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-02-13T22:01:31.462Z] GC before operation: completed in 234.707 ms, heap usage 1.249 GB -> 54.578 MB. [2025-02-13T22:01:33.442Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:01:35.409Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:01:38.446Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:01:40.415Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:01:42.385Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:01:43.344Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:01:45.446Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:01:46.404Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:01:46.404Z] 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. [2025-02-13T22:01:46.404Z] The best model improves the baseline by 14.43%. [2025-02-13T22:01:47.365Z] Movies recommended for you: [2025-02-13T22:01:47.365Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:01:47.365Z] There is no way to check that no silent failure occurred. [2025-02-13T22:01:47.365Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (15876.334 ms) ====== [2025-02-13T22:01:47.365Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-02-13T22:01:47.365Z] GC before operation: completed in 213.703 ms, heap usage 1.188 GB -> 54.067 MB. [2025-02-13T22:01:49.331Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:01:52.014Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:01:55.073Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:01:57.059Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:01:59.028Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:01:59.987Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:02:01.954Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:02:03.089Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:02:04.046Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711. [2025-02-13T22:02:04.046Z] The best model improves the baseline by 14.43%. [2025-02-13T22:02:04.046Z] Movies recommended for you: [2025-02-13T22:02:04.046Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:02:04.046Z] There is no way to check that no silent failure occurred. [2025-02-13T22:02:04.046Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (16845.808 ms) ====== [2025-02-13T22:02:04.046Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-02-13T22:02:04.046Z] GC before operation: completed in 189.637 ms, heap usage 1.246 GB -> 59.548 MB. [2025-02-13T22:02:07.154Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:02:10.260Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:02:12.227Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:02:15.265Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:02:16.225Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:02:17.185Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:02:18.143Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:02:20.110Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:02:20.110Z] 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. [2025-02-13T22:02:20.110Z] The best model improves the baseline by 14.43%. [2025-02-13T22:02:20.110Z] Movies recommended for you: [2025-02-13T22:02:20.110Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:02:20.110Z] There is no way to check that no silent failure occurred. [2025-02-13T22:02:20.110Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (15926.138 ms) ====== [2025-02-13T22:02:20.110Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-02-13T22:02:20.110Z] GC before operation: completed in 200.698 ms, heap usage 1.296 GB -> 54.940 MB. [2025-02-13T22:02:22.078Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:02:24.044Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:02:27.078Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:02:28.038Z] RMSE (validation) = 1.0045407704488025 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:02:30.006Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:02:30.965Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:02:31.924Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:02:33.893Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:02:33.893Z] 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. [2025-02-13T22:02:33.893Z] The best model improves the baseline by 14.43%. [2025-02-13T22:02:33.893Z] Movies recommended for you: [2025-02-13T22:02:33.893Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:02:33.893Z] There is no way to check that no silent failure occurred. [2025-02-13T22:02:33.893Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (13449.959 ms) ====== [2025-02-13T22:02:33.893Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-02-13T22:02:33.893Z] GC before operation: completed in 179.649 ms, heap usage 1.210 GB -> 56.193 MB. [2025-02-13T22:02:35.862Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:02:37.829Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:02:40.867Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:02:41.824Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:02:43.823Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:02:44.781Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:02:45.739Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:02:47.706Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:02:47.706Z] 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. [2025-02-13T22:02:47.706Z] The best model improves the baseline by 14.43%. [2025-02-13T22:02:47.706Z] Movies recommended for you: [2025-02-13T22:02:47.706Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:02:47.706Z] There is no way to check that no silent failure occurred. [2025-02-13T22:02:47.706Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (13545.503 ms) ====== [2025-02-13T22:02:47.706Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-02-13T22:02:47.706Z] GC before operation: completed in 197.130 ms, heap usage 1.209 GB -> 54.534 MB. [2025-02-13T22:02:49.682Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:02:51.647Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:02:53.617Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:02:55.585Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:02:56.544Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:02:58.510Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:02:59.469Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:03:00.427Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:03:00.427Z] 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. [2025-02-13T22:03:00.427Z] The best model improves the baseline by 14.43%. [2025-02-13T22:03:00.427Z] Movies recommended for you: [2025-02-13T22:03:00.427Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:03:00.427Z] There is no way to check that no silent failure occurred. [2025-02-13T22:03:00.427Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (13159.084 ms) ====== [2025-02-13T22:03:00.427Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-02-13T22:03:01.384Z] GC before operation: completed in 199.495 ms, heap usage 1.161 GB -> 54.356 MB. [2025-02-13T22:03:03.350Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:03:05.320Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:03:07.286Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:03:09.966Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:03:09.966Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:03:11.933Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:03:12.895Z] RMSE (validation) = 0.9275717388537592 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:03:13.852Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:03:13.852Z] 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. [2025-02-13T22:03:13.852Z] The best model improves the baseline by 14.43%. [2025-02-13T22:03:13.852Z] Movies recommended for you: [2025-02-13T22:03:13.852Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:03:13.852Z] There is no way to check that no silent failure occurred. [2025-02-13T22:03:13.852Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (13125.730 ms) ====== [2025-02-13T22:03:13.852Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-02-13T22:03:14.810Z] GC before operation: completed in 207.633 ms, heap usage 1.112 GB -> 57.115 MB. [2025-02-13T22:03:16.776Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:03:18.745Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:03:20.721Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:03:22.687Z] RMSE (validation) = 1.0045407704488025 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:03:23.644Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:03:24.600Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:03:25.558Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:03:27.523Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:03:27.523Z] 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. [2025-02-13T22:03:27.523Z] The best model improves the baseline by 14.43%. [2025-02-13T22:03:27.523Z] Movies recommended for you: [2025-02-13T22:03:27.523Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:03:27.523Z] There is no way to check that no silent failure occurred. [2025-02-13T22:03:27.523Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (12894.780 ms) ====== [2025-02-13T22:03:27.523Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-02-13T22:03:27.523Z] GC before operation: completed in 213.620 ms, heap usage 1.199 GB -> 55.059 MB. [2025-02-13T22:03:29.489Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:03:32.523Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:03:34.489Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:03:36.458Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:03:37.416Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:03:39.384Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:03:40.342Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:03:41.300Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:03:41.300Z] 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. [2025-02-13T22:03:41.300Z] The best model improves the baseline by 14.43%. [2025-02-13T22:03:42.263Z] Movies recommended for you: [2025-02-13T22:03:42.263Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:03:42.263Z] There is no way to check that no silent failure occurred. [2025-02-13T22:03:42.263Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (14284.635 ms) ====== [2025-02-13T22:03:42.263Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-02-13T22:03:42.263Z] GC before operation: completed in 176.616 ms, heap usage 1.280 GB -> 55.226 MB. [2025-02-13T22:03:44.236Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:03:46.204Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:03:48.173Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:03:50.139Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:03:51.097Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:03:53.064Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:03:54.055Z] RMSE (validation) = 0.9275717388537592 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:03:55.013Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:03:55.973Z] 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. [2025-02-13T22:03:55.973Z] The best model improves the baseline by 14.43%. [2025-02-13T22:03:55.973Z] Movies recommended for you: [2025-02-13T22:03:55.973Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:03:55.973Z] There is no way to check that no silent failure occurred. [2025-02-13T22:03:55.973Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (13873.410 ms) ====== [2025-02-13T22:03:57.938Z] ----------------------------------- [2025-02-13T22:03:57.938Z] renaissance-movie-lens_0_PASSED [2025-02-13T22:03:57.938Z] ----------------------------------- [2025-02-13T22:03:57.938Z] [2025-02-13T22:03:57.938Z] TEST TEARDOWN: [2025-02-13T22:03:57.938Z] Nothing to be done for teardown. [2025-02-13T22:03:57.938Z] renaissance-movie-lens_0 Finish Time: Thu Feb 13 22:03:57 2025 Epoch Time (ms): 1739484237045