[2024-11-25T03:13:22.264Z] Running test renaissance-movie-lens_0 ... [2024-11-25T03:13:22.678Z] =============================================== [2024-11-25T03:13:22.678Z] renaissance-movie-lens_0 Start Time: Mon Nov 25 03:13:22 2024 Epoch Time (ms): 1732504402378 [2024-11-25T03:13:22.678Z] variation: NoOptions [2024-11-25T03:13:22.678Z] JVM_OPTIONS: [2024-11-25T03:13:22.678Z] { \ [2024-11-25T03:13:22.678Z] echo ""; echo "TEST SETUP:"; \ [2024-11-25T03:13:22.678Z] echo "Nothing to be done for setup."; \ [2024-11-25T03:13:22.678Z] mkdir -p "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_1732503462773\\renaissance-movie-lens_0"; \ [2024-11-25T03:13:22.678Z] cd "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_1732503462773\\renaissance-movie-lens_0"; \ [2024-11-25T03:13:22.678Z] echo ""; echo "TESTING:"; \ [2024-11-25T03:13:22.678Z] "c:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows/jdkbinary/j2sdk-image\\bin\\java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows/aqa-tests///..//jvmtest\\perf\\renaissance\\renaissance.jar" --json ""C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_1732503462773\\renaissance-movie-lens_0"\\movie-lens.json" movie-lens; \ [2024-11-25T03:13:22.678Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows/aqa-tests/; rm -f -r "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_1732503462773\\renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-11-25T03:13:22.678Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-11-25T03:13:22.678Z] echo "Nothing to be done for teardown."; \ [2024-11-25T03:13:22.678Z] } 2>&1 | tee -a "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_1732503462773\\TestTargetResult"; [2024-11-25T03:13:23.020Z] [2024-11-25T03:13:23.020Z] TEST SETUP: [2024-11-25T03:13:23.020Z] Nothing to be done for setup. [2024-11-25T03:13:23.020Z] [2024-11-25T03:13:23.020Z] TESTING: [2024-11-25T03:13:33.711Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-11-25T03:13:34.417Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2024-11-25T03:13:37.467Z] Got 100004 ratings from 671 users on 9066 movies. [2024-11-25T03:13:37.866Z] Training: 60056, validation: 20285, test: 19854 [2024-11-25T03:13:37.866Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-11-25T03:13:37.866Z] GC before operation: completed in 61.951 ms, heap usage 135.862 MB -> 37.516 MB. [2024-11-25T03:13:48.833Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-25T03:13:57.675Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-25T03:14:04.858Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-25T03:14:10.679Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-25T03:14:15.352Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-25T03:14:19.080Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-25T03:14:22.809Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-25T03:14:26.559Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-25T03:14:26.898Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-11-25T03:14:26.898Z] The best model improves the baseline by 14.52%. [2024-11-25T03:14:27.227Z] Movies recommended for you: [2024-11-25T03:14:27.227Z] WARNING: This benchmark provides no result that can be validated. [2024-11-25T03:14:27.227Z] There is no way to check that no silent failure occurred. [2024-11-25T03:14:27.227Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (49303.914 ms) ====== [2024-11-25T03:14:27.227Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-11-25T03:14:27.227Z] GC before operation: completed in 68.637 ms, heap usage 71.057 MB -> 58.346 MB. [2024-11-25T03:14:34.384Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-25T03:14:41.573Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-25T03:14:48.725Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-25T03:14:54.526Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-25T03:14:57.438Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-25T03:15:01.175Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-25T03:15:05.860Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-25T03:15:08.755Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-25T03:15:09.449Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-11-25T03:15:09.449Z] The best model improves the baseline by 14.52%. [2024-11-25T03:15:09.449Z] Movies recommended for you: [2024-11-25T03:15:09.449Z] WARNING: This benchmark provides no result that can be validated. [2024-11-25T03:15:09.449Z] There is no way to check that no silent failure occurred. [2024-11-25T03:15:09.449Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (42283.363 ms) ====== [2024-11-25T03:15:09.449Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-11-25T03:15:09.450Z] GC before operation: completed in 62.108 ms, heap usage 433.820 MB -> 53.396 MB. [2024-11-25T03:15:16.611Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-25T03:15:22.440Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-25T03:15:29.582Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-25T03:15:35.444Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-25T03:15:39.133Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-25T03:15:42.855Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-25T03:15:46.554Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-25T03:15:50.269Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-25T03:15:50.597Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-11-25T03:15:50.597Z] The best model improves the baseline by 14.52%. [2024-11-25T03:15:50.597Z] Movies recommended for you: [2024-11-25T03:15:50.597Z] WARNING: This benchmark provides no result that can be validated. [2024-11-25T03:15:50.597Z] There is no way to check that no silent failure occurred. [2024-11-25T03:15:50.597Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (41067.904 ms) ====== [2024-11-25T03:15:50.597Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-11-25T03:15:50.597Z] GC before operation: completed in 58.081 ms, heap usage 87.753 MB -> 50.326 MB. [2024-11-25T03:15:57.757Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-25T03:16:03.568Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-25T03:16:10.740Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-25T03:16:17.912Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-25T03:16:20.834Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-25T03:16:24.552Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-25T03:16:28.261Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-25T03:16:31.996Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-25T03:16:31.996Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-11-25T03:16:31.996Z] The best model improves the baseline by 14.52%. [2024-11-25T03:16:31.996Z] Movies recommended for you: [2024-11-25T03:16:31.996Z] WARNING: This benchmark provides no result that can be validated. [2024-11-25T03:16:31.996Z] There is no way to check that no silent failure occurred. [2024-11-25T03:16:31.996Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (41410.325 ms) ====== [2024-11-25T03:16:31.996Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-11-25T03:16:31.996Z] GC before operation: completed in 58.850 ms, heap usage 129.329 MB -> 50.650 MB. [2024-11-25T03:16:39.160Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-25T03:16:44.957Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-25T03:16:52.143Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-25T03:16:57.980Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-25T03:17:00.930Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-25T03:17:04.682Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-25T03:17:08.394Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-25T03:17:12.124Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-25T03:17:12.449Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-11-25T03:17:12.449Z] The best model improves the baseline by 14.52%. [2024-11-25T03:17:12.807Z] Movies recommended for you: [2024-11-25T03:17:12.807Z] WARNING: This benchmark provides no result that can be validated. [2024-11-25T03:17:12.807Z] There is no way to check that no silent failure occurred. [2024-11-25T03:17:12.807Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (40581.025 ms) ====== [2024-11-25T03:17:12.807Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-11-25T03:17:12.807Z] GC before operation: completed in 59.149 ms, heap usage 314.300 MB -> 51.016 MB. [2024-11-25T03:17:19.973Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-25T03:17:25.838Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-25T03:17:31.653Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-25T03:17:38.814Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-25T03:17:41.719Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-25T03:17:44.630Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-25T03:17:49.312Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-25T03:17:52.221Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-25T03:17:52.550Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-11-25T03:17:52.550Z] The best model improves the baseline by 14.52%. [2024-11-25T03:17:52.884Z] Movies recommended for you: [2024-11-25T03:17:52.884Z] WARNING: This benchmark provides no result that can be validated. [2024-11-25T03:17:52.884Z] There is no way to check that no silent failure occurred. [2024-11-25T03:17:52.884Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (40035.538 ms) ====== [2024-11-25T03:17:52.884Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-11-25T03:17:52.884Z] GC before operation: completed in 57.262 ms, heap usage 199.254 MB -> 50.844 MB. [2024-11-25T03:18:00.080Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-25T03:18:05.910Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-25T03:18:13.118Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-25T03:18:18.955Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-25T03:18:21.846Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-25T03:18:25.567Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-25T03:18:29.309Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-25T03:18:33.051Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-25T03:18:33.051Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-11-25T03:18:33.051Z] The best model improves the baseline by 14.52%. [2024-11-25T03:18:33.051Z] Movies recommended for you: [2024-11-25T03:18:33.051Z] WARNING: This benchmark provides no result that can be validated. [2024-11-25T03:18:33.051Z] There is no way to check that no silent failure occurred. [2024-11-25T03:18:33.051Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (40265.995 ms) ====== [2024-11-25T03:18:33.051Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-11-25T03:18:33.379Z] GC before operation: completed in 58.464 ms, heap usage 68.324 MB -> 51.074 MB. [2024-11-25T03:18:39.252Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-25T03:18:46.428Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-25T03:18:52.258Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-25T03:18:58.085Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-25T03:19:01.807Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-25T03:19:05.528Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-25T03:19:09.271Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-25T03:19:13.031Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-25T03:19:13.031Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-11-25T03:19:13.031Z] The best model improves the baseline by 14.52%. [2024-11-25T03:19:13.031Z] Movies recommended for you: [2024-11-25T03:19:13.031Z] WARNING: This benchmark provides no result that can be validated. [2024-11-25T03:19:13.031Z] There is no way to check that no silent failure occurred. [2024-11-25T03:19:13.031Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (39916.709 ms) ====== [2024-11-25T03:19:13.031Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-11-25T03:19:13.031Z] GC before operation: completed in 60.161 ms, heap usage 104.377 MB -> 51.268 MB. [2024-11-25T03:19:20.201Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-25T03:19:26.020Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-25T03:19:31.842Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-25T03:19:39.042Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-25T03:19:41.947Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-25T03:19:44.859Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-25T03:19:48.594Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-25T03:19:52.312Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-25T03:19:52.655Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-11-25T03:19:52.655Z] The best model improves the baseline by 14.52%. [2024-11-25T03:19:52.655Z] Movies recommended for you: [2024-11-25T03:19:52.655Z] WARNING: This benchmark provides no result that can be validated. [2024-11-25T03:19:52.655Z] There is no way to check that no silent failure occurred. [2024-11-25T03:19:52.655Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (39499.904 ms) ====== [2024-11-25T03:19:52.655Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-11-25T03:19:52.655Z] GC before operation: completed in 61.932 ms, heap usage 79.579 MB -> 53.557 MB. [2024-11-25T03:19:59.851Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-25T03:20:05.708Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-25T03:20:11.552Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-25T03:20:17.386Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-25T03:20:21.109Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-25T03:20:24.838Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-25T03:20:28.559Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-25T03:20:31.466Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-25T03:20:32.179Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-11-25T03:20:32.179Z] The best model improves the baseline by 14.52%. [2024-11-25T03:20:32.179Z] Movies recommended for you: [2024-11-25T03:20:32.179Z] WARNING: This benchmark provides no result that can be validated. [2024-11-25T03:20:32.179Z] There is no way to check that no silent failure occurred. [2024-11-25T03:20:32.179Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (39396.182 ms) ====== [2024-11-25T03:20:32.179Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-11-25T03:20:32.179Z] GC before operation: completed in 61.271 ms, heap usage 369.607 MB -> 51.439 MB. [2024-11-25T03:20:38.008Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-25T03:20:45.184Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-25T03:20:51.016Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-25T03:20:56.857Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-25T03:21:00.576Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-25T03:21:04.292Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-25T03:21:08.005Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-25T03:21:11.713Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-25T03:21:12.063Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-11-25T03:21:12.063Z] The best model improves the baseline by 14.52%. [2024-11-25T03:21:12.063Z] Movies recommended for you: [2024-11-25T03:21:12.063Z] WARNING: This benchmark provides no result that can be validated. [2024-11-25T03:21:12.063Z] There is no way to check that no silent failure occurred. [2024-11-25T03:21:12.063Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (39947.689 ms) ====== [2024-11-25T03:21:12.063Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-11-25T03:21:12.063Z] GC before operation: completed in 58.293 ms, heap usage 173.793 MB -> 51.110 MB. [2024-11-25T03:21:19.245Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-25T03:21:25.062Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-25T03:21:30.892Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-25T03:21:36.705Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-25T03:21:40.423Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-25T03:21:44.135Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-25T03:21:47.047Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-25T03:21:50.768Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-25T03:21:51.095Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-11-25T03:21:51.095Z] The best model improves the baseline by 14.52%. [2024-11-25T03:21:51.095Z] Movies recommended for you: [2024-11-25T03:21:51.095Z] WARNING: This benchmark provides no result that can be validated. [2024-11-25T03:21:51.095Z] There is no way to check that no silent failure occurred. [2024-11-25T03:21:51.095Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (38901.697 ms) ====== [2024-11-25T03:21:51.095Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-11-25T03:21:51.095Z] GC before operation: completed in 66.801 ms, heap usage 103.194 MB -> 51.139 MB. [2024-11-25T03:21:58.258Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-25T03:22:04.096Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-25T03:22:09.923Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-25T03:22:17.136Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-25T03:22:20.032Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-25T03:22:23.746Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-25T03:22:27.463Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-25T03:22:30.368Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-25T03:22:30.695Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-11-25T03:22:30.695Z] The best model improves the baseline by 14.52%. [2024-11-25T03:22:31.025Z] Movies recommended for you: [2024-11-25T03:22:31.025Z] WARNING: This benchmark provides no result that can be validated. [2024-11-25T03:22:31.025Z] There is no way to check that no silent failure occurred. [2024-11-25T03:22:31.025Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (39760.600 ms) ====== [2024-11-25T03:22:31.025Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-11-25T03:22:31.025Z] GC before operation: completed in 59.214 ms, heap usage 328.444 MB -> 51.576 MB. [2024-11-25T03:22:36.843Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-25T03:22:44.042Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-25T03:22:49.862Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-25T03:22:55.693Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-25T03:22:59.420Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-25T03:23:02.330Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-25T03:23:06.058Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-25T03:23:09.838Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-25T03:23:09.838Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-11-25T03:23:09.838Z] The best model improves the baseline by 14.52%. [2024-11-25T03:23:10.167Z] Movies recommended for you: [2024-11-25T03:23:10.167Z] WARNING: This benchmark provides no result that can be validated. [2024-11-25T03:23:10.167Z] There is no way to check that no silent failure occurred. [2024-11-25T03:23:10.167Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (38954.247 ms) ====== [2024-11-25T03:23:10.167Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-11-25T03:23:10.167Z] GC before operation: completed in 60.498 ms, heap usage 155.432 MB -> 51.111 MB. [2024-11-25T03:23:15.984Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-25T03:23:23.160Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-25T03:23:28.976Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-25T03:23:34.808Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-25T03:23:38.553Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-25T03:23:41.464Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-25T03:23:45.190Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-25T03:23:48.916Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-25T03:23:48.916Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-11-25T03:23:48.916Z] The best model improves the baseline by 14.52%. [2024-11-25T03:23:49.263Z] Movies recommended for you: [2024-11-25T03:23:49.263Z] WARNING: This benchmark provides no result that can be validated. [2024-11-25T03:23:49.263Z] There is no way to check that no silent failure occurred. [2024-11-25T03:23:49.263Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (39064.837 ms) ====== [2024-11-25T03:23:49.263Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-11-25T03:23:49.263Z] GC before operation: completed in 58.450 ms, heap usage 276.071 MB -> 51.405 MB. [2024-11-25T03:23:55.078Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-25T03:24:02.257Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-25T03:24:08.063Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-25T03:24:13.901Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-25T03:24:17.595Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-25T03:24:21.295Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-25T03:24:25.023Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-25T03:24:27.947Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-25T03:24:28.319Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-11-25T03:24:28.319Z] The best model improves the baseline by 14.52%. [2024-11-25T03:24:28.646Z] Movies recommended for you: [2024-11-25T03:24:28.646Z] WARNING: This benchmark provides no result that can be validated. [2024-11-25T03:24:28.646Z] There is no way to check that no silent failure occurred. [2024-11-25T03:24:28.646Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (39290.484 ms) ====== [2024-11-25T03:24:28.646Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-11-25T03:24:28.646Z] GC before operation: completed in 60.654 ms, heap usage 201.323 MB -> 51.462 MB. [2024-11-25T03:24:34.479Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-25T03:24:41.648Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-25T03:24:47.497Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-25T03:24:53.319Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-25T03:24:58.013Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-25T03:25:00.918Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-25T03:25:04.618Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-25T03:25:08.334Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-25T03:25:08.334Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-11-25T03:25:08.781Z] The best model improves the baseline by 14.52%. [2024-11-25T03:25:08.781Z] Movies recommended for you: [2024-11-25T03:25:08.781Z] WARNING: This benchmark provides no result that can be validated. [2024-11-25T03:25:08.781Z] There is no way to check that no silent failure occurred. [2024-11-25T03:25:08.781Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (40177.565 ms) ====== [2024-11-25T03:25:08.781Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-11-25T03:25:08.781Z] GC before operation: completed in 62.365 ms, heap usage 124.791 MB -> 51.228 MB. [2024-11-25T03:25:14.588Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-25T03:25:21.765Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-25T03:25:27.621Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-25T03:25:33.434Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-25T03:25:37.168Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-25T03:25:40.064Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-25T03:25:43.794Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-25T03:25:47.516Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-25T03:25:47.885Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-11-25T03:25:47.885Z] The best model improves the baseline by 14.52%. [2024-11-25T03:25:47.885Z] Movies recommended for you: [2024-11-25T03:25:47.885Z] WARNING: This benchmark provides no result that can be validated. [2024-11-25T03:25:47.885Z] There is no way to check that no silent failure occurred. [2024-11-25T03:25:47.885Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (39258.787 ms) ====== [2024-11-25T03:25:47.885Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-11-25T03:25:48.214Z] GC before operation: completed in 60.997 ms, heap usage 263.193 MB -> 51.526 MB. [2024-11-25T03:25:54.039Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-25T03:26:01.220Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-25T03:26:07.051Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-25T03:26:12.842Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-25T03:26:16.558Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-25T03:26:19.480Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-25T03:26:23.192Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-25T03:26:26.907Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-25T03:26:27.263Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-11-25T03:26:27.263Z] The best model improves the baseline by 14.52%. [2024-11-25T03:26:27.263Z] Movies recommended for you: [2024-11-25T03:26:27.263Z] WARNING: This benchmark provides no result that can be validated. [2024-11-25T03:26:27.263Z] There is no way to check that no silent failure occurred. [2024-11-25T03:26:27.263Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (39316.389 ms) ====== [2024-11-25T03:26:27.263Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-11-25T03:26:27.594Z] GC before operation: completed in 60.162 ms, heap usage 116.756 MB -> 51.466 MB. [2024-11-25T03:26:33.416Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-25T03:26:40.617Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-25T03:26:46.437Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-25T03:26:52.236Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-25T03:26:55.966Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-25T03:26:58.891Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-25T03:27:02.608Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-25T03:27:06.331Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-25T03:27:06.662Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-11-25T03:27:06.662Z] The best model improves the baseline by 14.52%. [2024-11-25T03:27:06.991Z] Movies recommended for you: [2024-11-25T03:27:06.991Z] WARNING: This benchmark provides no result that can be validated. [2024-11-25T03:27:06.991Z] There is no way to check that no silent failure occurred. [2024-11-25T03:27:06.991Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (39461.884 ms) ====== [2024-11-25T03:27:07.318Z] ----------------------------------- [2024-11-25T03:27:07.318Z] renaissance-movie-lens_0_PASSED [2024-11-25T03:27:07.318Z] ----------------------------------- [2024-11-25T03:27:08.004Z] [2024-11-25T03:27:08.004Z] TEST TEARDOWN: [2024-11-25T03:27:08.004Z] Nothing to be done for teardown. [2024-11-25T03:27:08.004Z] renaissance-movie-lens_0 Finish Time: Mon Nov 25 03:27:07 2024 Epoch Time (ms): 1732505227926