[2024-11-21T21:55:32.916Z] Running test renaissance-movie-lens_0 ... [2024-11-21T21:55:32.916Z] =============================================== [2024-11-21T21:55:32.916Z] renaissance-movie-lens_0 Start Time: Thu Nov 21 21:55:32 2024 Epoch Time (ms): 1732226132849 [2024-11-21T21:55:33.252Z] variation: NoOptions [2024-11-21T21:55:33.252Z] JVM_OPTIONS: [2024-11-21T21:55:33.252Z] { \ [2024-11-21T21:55:33.252Z] echo ""; echo "TEST SETUP:"; \ [2024-11-21T21:55:33.252Z] echo "Nothing to be done for setup."; \ [2024-11-21T21:55:33.252Z] mkdir -p "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17322248501064\\renaissance-movie-lens_0"; \ [2024-11-21T21:55:33.252Z] cd "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17322248501064\\renaissance-movie-lens_0"; \ [2024-11-21T21:55:33.252Z] echo ""; echo "TESTING:"; \ [2024-11-21T21:55:33.252Z] "c:/jenkins/workspace/Test_openjdk11_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_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests///..//jvmtest\\perf\\renaissance\\renaissance.jar" --json ""C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17322248501064\\renaissance-movie-lens_0"\\movie-lens.json" movie-lens; \ [2024-11-21T21:55:33.252Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/; rm -f -r "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17322248501064\\renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-11-21T21:55:33.252Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-11-21T21:55:33.252Z] echo "Nothing to be done for teardown."; \ [2024-11-21T21:55:33.252Z] } 2>&1 | tee -a "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17322248501064\\TestTargetResult"; [2024-11-21T21:55:33.252Z] [2024-11-21T21:55:33.252Z] TEST SETUP: [2024-11-21T21:55:33.252Z] Nothing to be done for setup. [2024-11-21T21:55:33.252Z] [2024-11-21T21:55:33.252Z] TESTING: [2024-11-21T21:55:43.922Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-11-21T21:55:46.169Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2024-11-21T21:55:49.152Z] Got 100004 ratings from 671 users on 9066 movies. [2024-11-21T21:55:49.152Z] Training: 60056, validation: 20285, test: 19854 [2024-11-21T21:55:49.152Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-11-21T21:55:49.152Z] GC before operation: completed in 63.439 ms, heap usage 99.863 MB -> 36.932 MB. [2024-11-21T21:56:02.381Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-21T21:56:11.169Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-21T21:56:18.343Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-21T21:56:25.517Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-21T21:56:30.202Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-21T21:56:33.942Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-21T21:56:38.625Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-21T21:56:42.329Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-21T21:56:43.064Z] 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. [2024-11-21T21:56:43.064Z] The best model improves the baseline by 14.52%. [2024-11-21T21:56:43.064Z] Movies recommended for you: [2024-11-21T21:56:43.064Z] WARNING: This benchmark provides no result that can be validated. [2024-11-21T21:56:43.064Z] There is no way to check that no silent failure occurred. [2024-11-21T21:56:43.064Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (53898.699 ms) ====== [2024-11-21T21:56:43.064Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-11-21T21:56:43.394Z] GC before operation: completed in 100.308 ms, heap usage 138.049 MB -> 50.825 MB. [2024-11-21T21:56:52.170Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-21T21:56:59.354Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-21T21:57:06.512Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-21T21:57:13.670Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-21T21:57:17.398Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-21T21:57:21.098Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-21T21:57:25.815Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-21T21:57:29.542Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-21T21:57:29.542Z] 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. [2024-11-21T21:57:29.542Z] The best model improves the baseline by 14.52%. [2024-11-21T21:57:29.886Z] Movies recommended for you: [2024-11-21T21:57:29.886Z] WARNING: This benchmark provides no result that can be validated. [2024-11-21T21:57:29.886Z] There is no way to check that no silent failure occurred. [2024-11-21T21:57:29.886Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (46576.896 ms) ====== [2024-11-21T21:57:29.886Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-11-21T21:57:29.886Z] GC before operation: completed in 90.190 ms, heap usage 208.392 MB -> 51.752 MB. [2024-11-21T21:57:38.689Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-21T21:57:44.516Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-21T21:57:51.808Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-21T21:57:59.029Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-21T21:58:02.811Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-21T21:58:07.506Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-21T21:58:11.253Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-21T21:58:14.963Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-21T21:58:15.666Z] 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. [2024-11-21T21:58:15.666Z] The best model improves the baseline by 14.52%. [2024-11-21T21:58:15.666Z] Movies recommended for you: [2024-11-21T21:58:15.666Z] WARNING: This benchmark provides no result that can be validated. [2024-11-21T21:58:15.666Z] There is no way to check that no silent failure occurred. [2024-11-21T21:58:15.666Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (45794.703 ms) ====== [2024-11-21T21:58:15.666Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-11-21T21:58:15.666Z] GC before operation: completed in 91.924 ms, heap usage 71.273 MB -> 49.691 MB. [2024-11-21T21:58:22.871Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-21T21:58:30.055Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-21T21:58:37.219Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-21T21:58:44.414Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-21T21:58:48.159Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-21T21:58:52.823Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-21T21:58:56.530Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-21T21:59:00.243Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-21T21:59:00.602Z] 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. [2024-11-21T21:59:00.602Z] The best model improves the baseline by 14.52%. [2024-11-21T21:59:00.602Z] Movies recommended for you: [2024-11-21T21:59:00.602Z] WARNING: This benchmark provides no result that can be validated. [2024-11-21T21:59:00.602Z] There is no way to check that no silent failure occurred. [2024-11-21T21:59:00.602Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (44869.961 ms) ====== [2024-11-21T21:59:00.602Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-11-21T21:59:00.942Z] GC before operation: completed in 84.368 ms, heap usage 106.522 MB -> 52.290 MB. [2024-11-21T21:59:08.103Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-21T21:59:15.299Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-21T21:59:24.105Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-21T21:59:29.956Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-21T21:59:33.676Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-21T21:59:37.412Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-21T21:59:42.102Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-21T21:59:45.831Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-21T21:59:46.162Z] 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. [2024-11-21T21:59:46.162Z] The best model improves the baseline by 14.52%. [2024-11-21T21:59:46.500Z] Movies recommended for you: [2024-11-21T21:59:46.500Z] WARNING: This benchmark provides no result that can be validated. [2024-11-21T21:59:46.500Z] There is no way to check that no silent failure occurred. [2024-11-21T21:59:46.500Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (45571.945 ms) ====== [2024-11-21T21:59:46.501Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-11-21T21:59:46.501Z] GC before operation: completed in 84.167 ms, heap usage 113.877 MB -> 50.263 MB. [2024-11-21T21:59:53.677Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-21T22:00:00.865Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-21T22:00:08.245Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-21T22:00:15.523Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-21T22:00:19.262Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-21T22:00:23.981Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-21T22:00:27.708Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-21T22:00:31.431Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-21T22:00:31.763Z] 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. [2024-11-21T22:00:32.111Z] The best model improves the baseline by 14.52%. [2024-11-21T22:00:32.111Z] Movies recommended for you: [2024-11-21T22:00:32.111Z] WARNING: This benchmark provides no result that can be validated. [2024-11-21T22:00:32.111Z] There is no way to check that no silent failure occurred. [2024-11-21T22:00:32.111Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (45630.254 ms) ====== [2024-11-21T22:00:32.111Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-11-21T22:00:32.111Z] GC before operation: completed in 91.786 ms, heap usage 201.343 MB -> 50.268 MB. [2024-11-21T22:00:39.288Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-21T22:00:46.534Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-21T22:00:53.737Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-21T22:01:00.873Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-21T22:01:04.590Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-21T22:01:08.307Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-21T22:01:12.971Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-21T22:01:16.705Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-21T22:01:16.705Z] 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. [2024-11-21T22:01:16.705Z] The best model improves the baseline by 14.52%. [2024-11-21T22:01:16.705Z] Movies recommended for you: [2024-11-21T22:01:16.705Z] WARNING: This benchmark provides no result that can be validated. [2024-11-21T22:01:16.705Z] There is no way to check that no silent failure occurred. [2024-11-21T22:01:16.705Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (44652.730 ms) ====== [2024-11-21T22:01:16.705Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-11-21T22:01:17.037Z] GC before operation: completed in 85.471 ms, heap usage 100.618 MB -> 53.676 MB. [2024-11-21T22:01:24.241Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-21T22:01:31.476Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-21T22:01:38.697Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-21T22:01:44.503Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-21T22:01:48.213Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-21T22:01:51.924Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-21T22:01:56.582Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-21T22:02:00.308Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-21T22:02:00.308Z] 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. [2024-11-21T22:02:00.308Z] The best model improves the baseline by 14.52%. [2024-11-21T22:02:00.636Z] Movies recommended for you: [2024-11-21T22:02:00.636Z] WARNING: This benchmark provides no result that can be validated. [2024-11-21T22:02:00.636Z] There is no way to check that no silent failure occurred. [2024-11-21T22:02:00.636Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (43639.922 ms) ====== [2024-11-21T22:02:00.636Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-11-21T22:02:00.636Z] GC before operation: completed in 90.124 ms, heap usage 218.395 MB -> 53.962 MB. [2024-11-21T22:02:07.814Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-21T22:02:14.984Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-21T22:02:22.170Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-21T22:02:29.342Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-21T22:02:34.010Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-21T22:02:37.743Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-21T22:02:41.462Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-21T22:02:46.165Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-21T22:02:46.165Z] 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. [2024-11-21T22:02:46.165Z] The best model improves the baseline by 14.52%. [2024-11-21T22:02:46.165Z] Movies recommended for you: [2024-11-21T22:02:46.165Z] WARNING: This benchmark provides no result that can be validated. [2024-11-21T22:02:46.165Z] There is no way to check that no silent failure occurred. [2024-11-21T22:02:46.165Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (45579.795 ms) ====== [2024-11-21T22:02:46.165Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-11-21T22:02:46.165Z] GC before operation: completed in 92.999 ms, heap usage 139.205 MB -> 53.733 MB. [2024-11-21T22:02:54.973Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-21T22:03:02.202Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-21T22:03:09.406Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-21T22:03:16.580Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-21T22:03:21.268Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-21T22:03:24.164Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-21T22:03:28.848Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-21T22:03:32.580Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-21T22:03:32.580Z] 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. [2024-11-21T22:03:32.580Z] The best model improves the baseline by 14.52%. [2024-11-21T22:03:32.580Z] Movies recommended for you: [2024-11-21T22:03:32.580Z] WARNING: This benchmark provides no result that can be validated. [2024-11-21T22:03:32.580Z] There is no way to check that no silent failure occurred. [2024-11-21T22:03:32.580Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (46368.115 ms) ====== [2024-11-21T22:03:32.580Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-11-21T22:03:32.914Z] GC before operation: completed in 112.250 ms, heap usage 135.104 MB -> 50.593 MB. [2024-11-21T22:03:40.084Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-21T22:03:47.236Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-21T22:03:54.376Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-21T22:04:00.194Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-21T22:04:03.962Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-21T22:04:08.644Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-21T22:04:12.408Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-21T22:04:16.133Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-21T22:04:16.464Z] 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. [2024-11-21T22:04:16.464Z] The best model improves the baseline by 14.52%. [2024-11-21T22:04:16.792Z] Movies recommended for you: [2024-11-21T22:04:16.792Z] WARNING: This benchmark provides no result that can be validated. [2024-11-21T22:04:16.792Z] There is no way to check that no silent failure occurred. [2024-11-21T22:04:16.792Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (43924.962 ms) ====== [2024-11-21T22:04:16.792Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-11-21T22:04:16.792Z] GC before operation: completed in 87.000 ms, heap usage 194.419 MB -> 50.394 MB. [2024-11-21T22:04:23.987Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-21T22:04:31.184Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-21T22:04:38.336Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-21T22:04:44.150Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-21T22:04:48.842Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-21T22:04:52.583Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-21T22:04:57.265Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-21T22:05:01.051Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-21T22:05:01.051Z] 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. [2024-11-21T22:05:01.051Z] The best model improves the baseline by 14.52%. [2024-11-21T22:05:01.051Z] Movies recommended for you: [2024-11-21T22:05:01.051Z] WARNING: This benchmark provides no result that can be validated. [2024-11-21T22:05:01.051Z] There is no way to check that no silent failure occurred. [2024-11-21T22:05:01.051Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (44360.422 ms) ====== [2024-11-21T22:05:01.051Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-11-21T22:05:01.383Z] GC before operation: completed in 84.941 ms, heap usage 102.954 MB -> 50.493 MB. [2024-11-21T22:05:08.587Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-21T22:05:15.773Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-21T22:05:22.957Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-21T22:05:28.778Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-21T22:05:33.489Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-21T22:05:37.196Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-21T22:05:40.902Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-21T22:05:44.624Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-21T22:05:45.324Z] 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. [2024-11-21T22:05:45.324Z] The best model improves the baseline by 14.52%. [2024-11-21T22:05:45.324Z] Movies recommended for you: [2024-11-21T22:05:45.324Z] WARNING: This benchmark provides no result that can be validated. [2024-11-21T22:05:45.324Z] There is no way to check that no silent failure occurred. [2024-11-21T22:05:45.324Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (44172.459 ms) ====== [2024-11-21T22:05:45.324Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-11-21T22:05:45.669Z] GC before operation: completed in 85.805 ms, heap usage 231.753 MB -> 50.737 MB. [2024-11-21T22:05:52.857Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-21T22:06:00.018Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-21T22:06:07.216Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-21T22:06:14.376Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-21T22:06:18.089Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-21T22:06:21.812Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-21T22:06:25.562Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-21T22:06:29.306Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-21T22:06:29.679Z] 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. [2024-11-21T22:06:29.679Z] The best model improves the baseline by 14.52%. [2024-11-21T22:06:29.679Z] Movies recommended for you: [2024-11-21T22:06:29.679Z] WARNING: This benchmark provides no result that can be validated. [2024-11-21T22:06:29.679Z] There is no way to check that no silent failure occurred. [2024-11-21T22:06:29.679Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (44282.964 ms) ====== [2024-11-21T22:06:29.679Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-11-21T22:06:30.020Z] GC before operation: completed in 88.887 ms, heap usage 119.489 MB -> 53.723 MB. [2024-11-21T22:06:37.204Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-21T22:06:44.387Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-21T22:06:51.550Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-21T22:06:57.374Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-21T22:07:02.069Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-21T22:07:05.822Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-21T22:07:09.540Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-21T22:07:13.253Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-21T22:07:13.581Z] 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. [2024-11-21T22:07:13.581Z] The best model improves the baseline by 14.52%. [2024-11-21T22:07:13.581Z] Movies recommended for you: [2024-11-21T22:07:13.581Z] WARNING: This benchmark provides no result that can be validated. [2024-11-21T22:07:13.581Z] There is no way to check that no silent failure occurred. [2024-11-21T22:07:13.581Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (43790.028 ms) ====== [2024-11-21T22:07:13.581Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-11-21T22:07:13.912Z] GC before operation: completed in 87.776 ms, heap usage 261.078 MB -> 53.953 MB. [2024-11-21T22:07:21.086Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-21T22:07:28.259Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-21T22:07:35.461Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-21T22:07:41.270Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-21T22:07:44.996Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-21T22:07:48.730Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-21T22:07:53.444Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-21T22:07:56.368Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-21T22:07:56.698Z] 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. [2024-11-21T22:07:56.698Z] The best model improves the baseline by 14.52%. [2024-11-21T22:07:57.027Z] Movies recommended for you: [2024-11-21T22:07:57.027Z] WARNING: This benchmark provides no result that can be validated. [2024-11-21T22:07:57.027Z] There is no way to check that no silent failure occurred. [2024-11-21T22:07:57.027Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (43175.579 ms) ====== [2024-11-21T22:07:57.027Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-11-21T22:07:57.027Z] GC before operation: completed in 101.179 ms, heap usage 210.021 MB -> 53.920 MB. [2024-11-21T22:08:04.180Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-21T22:08:11.352Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-21T22:08:18.549Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-21T22:08:25.723Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-21T22:08:28.634Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-21T22:08:33.301Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-21T22:08:37.038Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-21T22:08:40.808Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-21T22:08:40.808Z] 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. [2024-11-21T22:08:40.808Z] The best model improves the baseline by 14.52%. [2024-11-21T22:08:40.808Z] Movies recommended for you: [2024-11-21T22:08:40.808Z] WARNING: This benchmark provides no result that can be validated. [2024-11-21T22:08:40.808Z] There is no way to check that no silent failure occurred. [2024-11-21T22:08:40.808Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (43879.451 ms) ====== [2024-11-21T22:08:40.808Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-11-21T22:08:41.136Z] GC before operation: completed in 98.957 ms, heap usage 166.696 MB -> 52.740 MB. [2024-11-21T22:08:48.316Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-21T22:08:55.497Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-21T22:09:02.670Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-21T22:09:08.476Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-21T22:09:13.183Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-21T22:09:16.105Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-21T22:09:20.797Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-21T22:09:24.536Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-21T22:09:24.536Z] 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. [2024-11-21T22:09:24.536Z] The best model improves the baseline by 14.52%. [2024-11-21T22:09:24.536Z] Movies recommended for you: [2024-11-21T22:09:24.536Z] WARNING: This benchmark provides no result that can be validated. [2024-11-21T22:09:24.536Z] There is no way to check that no silent failure occurred. [2024-11-21T22:09:24.536Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (43515.809 ms) ====== [2024-11-21T22:09:24.536Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-11-21T22:09:24.536Z] GC before operation: completed in 93.161 ms, heap usage 242.216 MB -> 53.902 MB. [2024-11-21T22:09:31.716Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-21T22:09:38.872Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-21T22:09:46.064Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-21T22:09:53.222Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-21T22:09:56.119Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-21T22:10:00.821Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-21T22:10:04.557Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-21T22:10:08.276Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-21T22:10:08.683Z] 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. [2024-11-21T22:10:08.683Z] The best model improves the baseline by 14.52%. [2024-11-21T22:10:09.024Z] Movies recommended for you: [2024-11-21T22:10:09.024Z] WARNING: This benchmark provides no result that can be validated. [2024-11-21T22:10:09.024Z] There is no way to check that no silent failure occurred. [2024-11-21T22:10:09.024Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (44167.553 ms) ====== [2024-11-21T22:10:09.024Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-11-21T22:10:09.024Z] GC before operation: completed in 101.121 ms, heap usage 270.290 MB -> 54.158 MB. [2024-11-21T22:10:16.177Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-21T22:10:23.350Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-21T22:10:30.537Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-21T22:10:36.385Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-21T22:10:41.063Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-21T22:10:43.985Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-21T22:10:48.662Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-21T22:10:52.399Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-21T22:10:52.399Z] 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. [2024-11-21T22:10:52.723Z] The best model improves the baseline by 14.52%. [2024-11-21T22:10:52.723Z] Movies recommended for you: [2024-11-21T22:10:52.723Z] WARNING: This benchmark provides no result that can be validated. [2024-11-21T22:10:52.723Z] There is no way to check that no silent failure occurred. [2024-11-21T22:10:52.723Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (43804.317 ms) ====== [2024-11-21T22:10:53.048Z] ----------------------------------- [2024-11-21T22:10:53.048Z] renaissance-movie-lens_0_PASSED [2024-11-21T22:10:53.048Z] ----------------------------------- [2024-11-21T22:10:53.728Z] [2024-11-21T22:10:53.728Z] TEST TEARDOWN: [2024-11-21T22:10:53.728Z] Nothing to be done for teardown. [2024-11-21T22:10:54.042Z] renaissance-movie-lens_0 Finish Time: Thu Nov 21 22:10:53 2024 Epoch Time (ms): 1732227053753