[2024-08-10T01:55:13.080Z] Running test renaissance-movie-lens_0 ... [2024-08-10T01:55:13.080Z] =============================================== [2024-08-10T01:55:13.080Z] renaissance-movie-lens_0 Start Time: Fri Aug 9 20:55:12 2024 Epoch Time (ms): 1723254912583 [2024-08-10T01:55:13.080Z] variation: NoOptions [2024-08-10T01:55:13.080Z] JVM_OPTIONS: [2024-08-10T01:55:13.080Z] { \ [2024-08-10T01:55:13.080Z] echo ""; echo "TEST SETUP:"; \ [2024-08-10T01:55:13.080Z] echo "Nothing to be done for setup."; \ [2024-08-10T01:55:13.080Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../TKG/output_1723254269989/renaissance-movie-lens_0"; \ [2024-08-10T01:55:13.080Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../TKG/output_1723254269989/renaissance-movie-lens_0"; \ [2024-08-10T01:55:13.080Z] echo ""; echo "TESTING:"; \ [2024-08-10T01:55:13.080Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux_testList_0/jdkbinary/j2sdk-image/jdk-17.0.13+2/bin/..//bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../TKG/output_1723254269989/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2024-08-10T01:55:13.080Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../TKG/output_1723254269989/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-08-10T01:55:13.080Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-08-10T01:55:13.080Z] echo "Nothing to be done for teardown."; \ [2024-08-10T01:55:13.080Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../TKG/output_1723254269989/TestTargetResult"; [2024-08-10T01:55:13.080Z] [2024-08-10T01:55:13.080Z] TEST SETUP: [2024-08-10T01:55:13.080Z] Nothing to be done for setup. [2024-08-10T01:55:13.080Z] [2024-08-10T01:55:13.080Z] TESTING: [2024-08-10T01:55:15.303Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-08-10T01:55:17.528Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads. [2024-08-10T01:55:20.636Z] Got 100004 ratings from 671 users on 9066 movies. [2024-08-10T01:55:20.636Z] Training: 60056, validation: 20285, test: 19854 [2024-08-10T01:55:20.636Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-08-10T01:55:20.636Z] GC before operation: completed in 53.909 ms, heap usage 114.867 MB -> 37.876 MB. [2024-08-10T01:55:28.320Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T01:55:32.398Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T01:55:35.683Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T01:55:37.957Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T01:55:40.202Z] RMSE (validation) = 1.2218330581874073 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T01:55:41.631Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T01:55:43.864Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T01:55:45.316Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T01:55:45.316Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-10T01:55:45.316Z] The best model improves the baseline by 14.43%. [2024-08-10T01:55:46.011Z] Movies recommended for you: [2024-08-10T01:55:46.011Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T01:55:46.011Z] There is no way to check that no silent failure occurred. [2024-08-10T01:55:46.011Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (24743.589 ms) ====== [2024-08-10T01:55:46.011Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-08-10T01:55:46.011Z] GC before operation: completed in 121.128 ms, heap usage 443.214 MB -> 52.833 MB. [2024-08-10T01:55:49.137Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T01:55:51.377Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T01:55:54.466Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T01:55:57.581Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T01:55:59.010Z] RMSE (validation) = 1.2218330581874073 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T01:56:00.461Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T01:56:01.896Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T01:56:03.340Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T01:56:04.032Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-10T01:56:04.032Z] The best model improves the baseline by 14.43%. [2024-08-10T01:56:04.032Z] Movies recommended for you: [2024-08-10T01:56:04.032Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T01:56:04.032Z] There is no way to check that no silent failure occurred. [2024-08-10T01:56:04.032Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (18163.964 ms) ====== [2024-08-10T01:56:04.032Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-08-10T01:56:04.032Z] GC before operation: completed in 58.169 ms, heap usage 442.662 MB -> 51.801 MB. [2024-08-10T01:56:07.128Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T01:56:09.374Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T01:56:12.486Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T01:56:14.904Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T01:56:16.335Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T01:56:17.771Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T01:56:19.201Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T01:56:21.436Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T01:56:21.436Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-10T01:56:21.436Z] The best model improves the baseline by 14.43%. [2024-08-10T01:56:21.436Z] Movies recommended for you: [2024-08-10T01:56:21.436Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T01:56:21.436Z] There is no way to check that no silent failure occurred. [2024-08-10T01:56:21.436Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (17443.708 ms) ====== [2024-08-10T01:56:21.436Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-08-10T01:56:21.436Z] GC before operation: completed in 78.929 ms, heap usage 422.388 MB -> 52.251 MB. [2024-08-10T01:56:24.578Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T01:56:26.809Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T01:56:29.060Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T01:56:31.290Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T01:56:32.723Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T01:56:34.169Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T01:56:35.615Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T01:56:37.062Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T01:56:37.750Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-10T01:56:37.750Z] The best model improves the baseline by 14.43%. [2024-08-10T01:56:37.750Z] Movies recommended for you: [2024-08-10T01:56:37.750Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T01:56:37.751Z] There is no way to check that no silent failure occurred. [2024-08-10T01:56:37.751Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (16156.342 ms) ====== [2024-08-10T01:56:37.751Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-08-10T01:56:37.751Z] GC before operation: completed in 59.974 ms, heap usage 233.957 MB -> 52.512 MB. [2024-08-10T01:56:39.988Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T01:56:43.095Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T01:56:45.319Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T01:56:48.432Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T01:56:49.882Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T01:56:51.336Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T01:56:52.784Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T01:56:53.488Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T01:56:54.194Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-10T01:56:54.194Z] The best model improves the baseline by 14.43%. [2024-08-10T01:56:54.194Z] Movies recommended for you: [2024-08-10T01:56:54.194Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T01:56:54.194Z] There is no way to check that no silent failure occurred. [2024-08-10T01:56:54.194Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (16429.603 ms) ====== [2024-08-10T01:56:54.194Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-08-10T01:56:54.194Z] GC before operation: completed in 81.110 ms, heap usage 572.710 MB -> 56.187 MB. [2024-08-10T01:56:56.447Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T01:56:59.576Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T01:57:01.819Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T01:57:03.261Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T01:57:04.697Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T01:57:06.125Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T01:57:07.563Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T01:57:09.002Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T01:57:09.889Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-10T01:57:09.889Z] The best model improves the baseline by 14.43%. [2024-08-10T01:57:09.889Z] Movies recommended for you: [2024-08-10T01:57:09.889Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T01:57:09.889Z] There is no way to check that no silent failure occurred. [2024-08-10T01:57:09.890Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (15409.829 ms) ====== [2024-08-10T01:57:09.890Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-08-10T01:57:09.890Z] GC before operation: completed in 77.133 ms, heap usage 488.929 MB -> 56.038 MB. [2024-08-10T01:57:12.127Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T01:57:14.389Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T01:57:17.498Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T01:57:18.960Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T01:57:20.392Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T01:57:21.837Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T01:57:23.362Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T01:57:24.807Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T01:57:24.807Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-10T01:57:24.807Z] The best model improves the baseline by 14.43%. [2024-08-10T01:57:24.807Z] Movies recommended for you: [2024-08-10T01:57:24.807Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T01:57:24.807Z] There is no way to check that no silent failure occurred. [2024-08-10T01:57:24.807Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (15211.132 ms) ====== [2024-08-10T01:57:24.807Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-08-10T01:57:24.807Z] GC before operation: completed in 78.963 ms, heap usage 387.331 MB -> 52.927 MB. [2024-08-10T01:57:27.897Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T01:57:30.153Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T01:57:32.376Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T01:57:34.612Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T01:57:36.048Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T01:57:37.469Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T01:57:38.896Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T01:57:39.588Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T01:57:40.282Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-10T01:57:40.282Z] The best model improves the baseline by 14.43%. [2024-08-10T01:57:40.282Z] Movies recommended for you: [2024-08-10T01:57:40.282Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T01:57:40.282Z] There is no way to check that no silent failure occurred. [2024-08-10T01:57:40.282Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (15141.406 ms) ====== [2024-08-10T01:57:40.282Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-08-10T01:57:40.282Z] GC before operation: completed in 80.975 ms, heap usage 284.246 MB -> 56.291 MB. [2024-08-10T01:57:42.511Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T01:57:44.767Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T01:57:47.006Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T01:57:49.253Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T01:57:50.690Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T01:57:52.144Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T01:57:53.566Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T01:57:54.252Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T01:57:54.942Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-10T01:57:54.942Z] The best model improves the baseline by 14.43%. [2024-08-10T01:57:54.942Z] Movies recommended for you: [2024-08-10T01:57:54.942Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T01:57:54.942Z] There is no way to check that no silent failure occurred. [2024-08-10T01:57:54.942Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (14692.620 ms) ====== [2024-08-10T01:57:54.942Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-08-10T01:57:54.942Z] GC before operation: completed in 59.624 ms, heap usage 294.226 MB -> 52.851 MB. [2024-08-10T01:57:57.162Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T01:57:59.405Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T01:58:01.657Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T01:58:03.873Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T01:58:05.319Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T01:58:07.202Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T01:58:08.650Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T01:58:10.094Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T01:58:10.094Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-10T01:58:10.094Z] The best model improves the baseline by 14.43%. [2024-08-10T01:58:10.094Z] Movies recommended for you: [2024-08-10T01:58:10.094Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T01:58:10.094Z] There is no way to check that no silent failure occurred. [2024-08-10T01:58:10.094Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (15120.804 ms) ====== [2024-08-10T01:58:10.094Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-08-10T01:58:10.094Z] GC before operation: completed in 58.138 ms, heap usage 438.428 MB -> 52.970 MB. [2024-08-10T01:58:12.347Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T01:58:14.583Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T01:58:16.834Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T01:58:19.084Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T01:58:20.525Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T01:58:21.972Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T01:58:23.462Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T01:58:24.893Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T01:58:24.893Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-10T01:58:24.893Z] The best model improves the baseline by 14.43%. [2024-08-10T01:58:24.893Z] Movies recommended for you: [2024-08-10T01:58:24.893Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T01:58:24.893Z] There is no way to check that no silent failure occurred. [2024-08-10T01:58:24.893Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (14952.666 ms) ====== [2024-08-10T01:58:24.893Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-08-10T01:58:24.893Z] GC before operation: completed in 62.128 ms, heap usage 518.145 MB -> 56.057 MB. [2024-08-10T01:58:27.996Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T01:58:30.266Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T01:58:32.498Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T01:58:34.858Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T01:58:36.304Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T01:58:37.743Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T01:58:39.170Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T01:58:40.642Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T01:58:40.642Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-10T01:58:40.642Z] The best model improves the baseline by 14.43%. [2024-08-10T01:58:40.642Z] Movies recommended for you: [2024-08-10T01:58:40.642Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T01:58:40.642Z] There is no way to check that no silent failure occurred. [2024-08-10T01:58:40.642Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (15541.952 ms) ====== [2024-08-10T01:58:40.642Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-08-10T01:58:40.642Z] GC before operation: completed in 65.573 ms, heap usage 251.817 MB -> 52.845 MB. [2024-08-10T01:58:43.777Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T01:58:46.023Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T01:58:48.247Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T01:58:50.478Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T01:58:51.900Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T01:58:53.343Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T01:58:54.763Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T01:58:56.230Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T01:58:56.230Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-10T01:58:56.230Z] The best model improves the baseline by 14.43%. [2024-08-10T01:58:56.230Z] Movies recommended for you: [2024-08-10T01:58:56.230Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T01:58:56.230Z] There is no way to check that no silent failure occurred. [2024-08-10T01:58:56.230Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (15559.716 ms) ====== [2024-08-10T01:58:56.230Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-08-10T01:58:56.230Z] GC before operation: completed in 92.296 ms, heap usage 315.573 MB -> 53.105 MB. [2024-08-10T01:58:59.353Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T01:59:00.800Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T01:59:04.346Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T01:59:05.778Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T01:59:07.213Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T01:59:08.654Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T01:59:10.082Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T01:59:10.784Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T01:59:11.489Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-10T01:59:11.489Z] The best model improves the baseline by 14.43%. [2024-08-10T01:59:11.489Z] Movies recommended for you: [2024-08-10T01:59:11.489Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T01:59:11.489Z] There is no way to check that no silent failure occurred. [2024-08-10T01:59:11.489Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (14964.205 ms) ====== [2024-08-10T01:59:11.489Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-08-10T01:59:11.489Z] GC before operation: completed in 60.255 ms, heap usage 483.672 MB -> 56.234 MB. [2024-08-10T01:59:13.731Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T01:59:15.952Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T01:59:18.208Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T01:59:20.447Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T01:59:21.890Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T01:59:23.348Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T01:59:24.780Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T01:59:26.217Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T01:59:26.217Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-10T01:59:26.217Z] The best model improves the baseline by 14.43%. [2024-08-10T01:59:26.217Z] Movies recommended for you: [2024-08-10T01:59:26.217Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T01:59:26.217Z] There is no way to check that no silent failure occurred. [2024-08-10T01:59:26.217Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14909.672 ms) ====== [2024-08-10T01:59:26.217Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-08-10T01:59:26.217Z] GC before operation: completed in 54.433 ms, heap usage 355.740 MB -> 53.081 MB. [2024-08-10T01:59:29.344Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T01:59:30.900Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T01:59:33.142Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T01:59:35.379Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T01:59:36.832Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T01:59:38.261Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T01:59:39.701Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T01:59:41.127Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T01:59:41.127Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-10T01:59:41.127Z] The best model improves the baseline by 14.43%. [2024-08-10T01:59:41.820Z] Movies recommended for you: [2024-08-10T01:59:41.820Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T01:59:41.820Z] There is no way to check that no silent failure occurred. [2024-08-10T01:59:41.820Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (15104.309 ms) ====== [2024-08-10T01:59:41.820Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-08-10T01:59:41.820Z] GC before operation: completed in 81.825 ms, heap usage 308.591 MB -> 53.116 MB. [2024-08-10T01:59:44.067Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T01:59:46.299Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T01:59:48.530Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T01:59:50.765Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T01:59:52.199Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T01:59:53.628Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T01:59:55.060Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T01:59:55.758Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T01:59:56.445Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-10T01:59:56.445Z] The best model improves the baseline by 14.43%. [2024-08-10T01:59:56.445Z] Movies recommended for you: [2024-08-10T01:59:56.445Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T01:59:56.445Z] There is no way to check that no silent failure occurred. [2024-08-10T01:59:56.445Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (14750.732 ms) ====== [2024-08-10T01:59:56.445Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-08-10T01:59:56.445Z] GC before operation: completed in 83.229 ms, heap usage 847.601 MB -> 56.941 MB. [2024-08-10T01:59:58.684Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T02:00:01.346Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T02:00:03.608Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T02:00:05.869Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T02:00:07.298Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T02:00:08.735Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T02:00:10.160Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T02:00:11.615Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T02:00:11.615Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-10T02:00:11.615Z] The best model improves the baseline by 14.43%. [2024-08-10T02:00:11.615Z] Movies recommended for you: [2024-08-10T02:00:11.615Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T02:00:11.615Z] There is no way to check that no silent failure occurred. [2024-08-10T02:00:11.615Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (15200.652 ms) ====== [2024-08-10T02:00:11.615Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-08-10T02:00:11.615Z] GC before operation: completed in 60.028 ms, heap usage 649.228 MB -> 58.354 MB. [2024-08-10T02:00:13.872Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T02:00:16.102Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T02:00:18.353Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T02:00:20.600Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T02:00:22.022Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T02:00:23.469Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T02:00:24.900Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T02:00:26.359Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T02:00:26.360Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-10T02:00:26.360Z] The best model improves the baseline by 14.43%. [2024-08-10T02:00:26.360Z] Movies recommended for you: [2024-08-10T02:00:26.360Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T02:00:26.360Z] There is no way to check that no silent failure occurred. [2024-08-10T02:00:26.360Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (14795.331 ms) ====== [2024-08-10T02:00:26.360Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-08-10T02:00:26.360Z] GC before operation: completed in 71.729 ms, heap usage 584.126 MB -> 56.606 MB. [2024-08-10T02:00:29.459Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T02:00:31.728Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T02:00:33.979Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T02:00:35.423Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T02:00:36.860Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T02:00:38.306Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T02:00:39.747Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T02:00:41.171Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T02:00:41.171Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-10T02:00:41.171Z] The best model improves the baseline by 14.43%. [2024-08-10T02:00:41.171Z] Movies recommended for you: [2024-08-10T02:00:41.171Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T02:00:41.171Z] There is no way to check that no silent failure occurred. [2024-08-10T02:00:41.171Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (14778.066 ms) ====== [2024-08-10T02:00:42.628Z] ----------------------------------- [2024-08-10T02:00:42.628Z] renaissance-movie-lens_0_PASSED [2024-08-10T02:00:42.628Z] ----------------------------------- [2024-08-10T02:00:42.628Z] [2024-08-10T02:00:42.628Z] TEST TEARDOWN: [2024-08-10T02:00:42.628Z] Nothing to be done for teardown. [2024-08-10T02:00:42.628Z] renaissance-movie-lens_0 Finish Time: Fri Aug 9 21:00:42 2024 Epoch Time (ms): 1723255242210