[2024-08-10T10:16:11.635Z] Running test renaissance-movie-lens_0 ... [2024-08-10T10:16:11.635Z] =============================================== [2024-08-10T10:16:11.635Z] renaissance-movie-lens_0 Start Time: Sat Aug 10 10:16:11 2024 Epoch Time (ms): 1723284971482 [2024-08-10T10:16:11.635Z] variation: NoOptions [2024-08-10T10:16:11.635Z] JVM_OPTIONS: [2024-08-10T10:16:11.635Z] { \ [2024-08-10T10:16:11.635Z] echo ""; echo "TEST SETUP:"; \ [2024-08-10T10:16:11.635Z] echo "Nothing to be done for setup."; \ [2024-08-10T10:16:11.635Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17232836225986/renaissance-movie-lens_0"; \ [2024-08-10T10:16:11.635Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17232836225986/renaissance-movie-lens_0"; \ [2024-08-10T10:16:11.635Z] echo ""; echo "TESTING:"; \ [2024-08-10T10:16:11.635Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux_testList_0/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 "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17232836225986/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2024-08-10T10:16:11.635Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17232836225986/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-08-10T10:16:11.635Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-08-10T10:16:11.635Z] echo "Nothing to be done for teardown."; \ [2024-08-10T10:16:11.635Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17232836225986/TestTargetResult"; [2024-08-10T10:16:11.635Z] [2024-08-10T10:16:11.635Z] TEST SETUP: [2024-08-10T10:16:11.635Z] Nothing to be done for setup. [2024-08-10T10:16:11.635Z] [2024-08-10T10:16:11.635Z] TESTING: [2024-08-10T10:16:14.007Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-08-10T10:16:16.403Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2024-08-10T10:16:19.708Z] Got 100004 ratings from 671 users on 9066 movies. [2024-08-10T10:16:19.708Z] Training: 60056, validation: 20285, test: 19854 [2024-08-10T10:16:19.708Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-08-10T10:16:19.708Z] GC before operation: completed in 43.899 ms, heap usage 95.450 MB -> 37.088 MB. [2024-08-10T10:16:29.330Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T10:16:34.796Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T10:16:41.506Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T10:16:47.487Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T10:16:50.827Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T10:16:54.156Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T10:16:55.687Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T10:16:58.078Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T10:16:58.078Z] 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. [2024-08-10T10:16:58.827Z] The best model improves the baseline by 14.52%. [2024-08-10T10:16:58.827Z] Movies recommended for you: [2024-08-10T10:16:58.827Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T10:16:58.827Z] There is no way to check that no silent failure occurred. [2024-08-10T10:16:58.827Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (38703.417 ms) ====== [2024-08-10T10:16:58.827Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-08-10T10:16:58.827Z] GC before operation: completed in 120.041 ms, heap usage 499.775 MB -> 56.474 MB. [2024-08-10T10:17:02.159Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T10:17:06.500Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T10:17:09.809Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T10:17:14.150Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T10:17:16.530Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T10:17:18.924Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T10:17:21.336Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T10:17:22.874Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T10:17:23.614Z] 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. [2024-08-10T10:17:23.614Z] The best model improves the baseline by 14.52%. [2024-08-10T10:17:23.614Z] Movies recommended for you: [2024-08-10T10:17:23.614Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T10:17:23.614Z] There is no way to check that no silent failure occurred. [2024-08-10T10:17:23.614Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (24822.655 ms) ====== [2024-08-10T10:17:23.614Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-08-10T10:17:23.614Z] GC before operation: completed in 94.213 ms, heap usage 268.504 MB -> 49.692 MB. [2024-08-10T10:17:26.924Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T10:17:31.255Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T10:17:34.851Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T10:17:38.175Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T10:17:40.560Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T10:17:42.097Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T10:17:45.401Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T10:17:47.854Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T10:17:47.855Z] 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. [2024-08-10T10:17:47.855Z] The best model improves the baseline by 14.52%. [2024-08-10T10:17:47.855Z] Movies recommended for you: [2024-08-10T10:17:47.855Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T10:17:47.855Z] There is no way to check that no silent failure occurred. [2024-08-10T10:17:47.855Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (24327.552 ms) ====== [2024-08-10T10:17:47.855Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-08-10T10:17:47.855Z] GC before operation: completed in 147.127 ms, heap usage 333.868 MB -> 50.108 MB. [2024-08-10T10:17:53.291Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T10:17:56.602Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T10:18:00.926Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T10:18:05.262Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T10:18:07.666Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T10:18:10.063Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T10:18:12.454Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T10:18:14.846Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T10:18:15.590Z] 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. [2024-08-10T10:18:15.590Z] The best model improves the baseline by 14.52%. [2024-08-10T10:18:15.590Z] Movies recommended for you: [2024-08-10T10:18:15.590Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T10:18:15.590Z] There is no way to check that no silent failure occurred. [2024-08-10T10:18:15.590Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (27366.288 ms) ====== [2024-08-10T10:18:15.590Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-08-10T10:18:15.590Z] GC before operation: completed in 143.088 ms, heap usage 340.869 MB -> 50.914 MB. [2024-08-10T10:18:19.907Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T10:18:23.379Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T10:18:26.701Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T10:18:30.023Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T10:18:32.409Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T10:18:34.814Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T10:18:37.211Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T10:18:40.520Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T10:18:40.520Z] 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. [2024-08-10T10:18:40.520Z] The best model improves the baseline by 14.52%. [2024-08-10T10:18:40.520Z] Movies recommended for you: [2024-08-10T10:18:40.520Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T10:18:40.520Z] There is no way to check that no silent failure occurred. [2024-08-10T10:18:40.520Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (25021.022 ms) ====== [2024-08-10T10:18:40.520Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-08-10T10:18:41.261Z] GC before operation: completed in 171.585 ms, heap usage 114.535 MB -> 50.674 MB. [2024-08-10T10:18:45.704Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T10:18:50.033Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T10:18:54.371Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T10:18:58.697Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T10:19:01.106Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T10:19:04.449Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T10:19:06.857Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T10:19:09.258Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T10:19:10.001Z] 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. [2024-08-10T10:19:10.001Z] The best model improves the baseline by 14.52%. [2024-08-10T10:19:10.001Z] Movies recommended for you: [2024-08-10T10:19:10.001Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T10:19:10.001Z] There is no way to check that no silent failure occurred. [2024-08-10T10:19:10.001Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (29263.776 ms) ====== [2024-08-10T10:19:10.001Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-08-10T10:19:10.001Z] GC before operation: completed in 149.787 ms, heap usage 312.044 MB -> 50.643 MB. [2024-08-10T10:19:13.847Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T10:19:18.178Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T10:19:22.495Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T10:19:25.808Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T10:19:29.140Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T10:19:30.703Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T10:19:34.019Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T10:19:35.546Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T10:19:36.294Z] 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. [2024-08-10T10:19:36.294Z] The best model improves the baseline by 14.52%. [2024-08-10T10:19:36.294Z] Movies recommended for you: [2024-08-10T10:19:36.294Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T10:19:36.294Z] There is no way to check that no silent failure occurred. [2024-08-10T10:19:36.294Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (26166.882 ms) ====== [2024-08-10T10:19:36.294Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-08-10T10:19:36.294Z] GC before operation: completed in 136.620 ms, heap usage 222.699 MB -> 50.698 MB. [2024-08-10T10:19:40.612Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T10:19:44.971Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T10:19:49.293Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T10:19:52.598Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T10:19:55.020Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T10:19:56.551Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T10:19:57.289Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T10:19:58.833Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T10:19:59.570Z] 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. [2024-08-10T10:19:59.570Z] The best model improves the baseline by 14.52%. [2024-08-10T10:19:59.570Z] Movies recommended for you: [2024-08-10T10:19:59.570Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T10:19:59.570Z] There is no way to check that no silent failure occurred. [2024-08-10T10:19:59.570Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (22773.716 ms) ====== [2024-08-10T10:19:59.570Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-08-10T10:19:59.570Z] GC before operation: completed in 58.879 ms, heap usage 115.715 MB -> 50.947 MB. [2024-08-10T10:20:01.098Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T10:20:03.953Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T10:20:07.247Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T10:20:09.635Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T10:20:11.165Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T10:20:13.551Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T10:20:16.865Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T10:20:19.254Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T10:20:19.254Z] 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. [2024-08-10T10:20:19.254Z] The best model improves the baseline by 14.52%. [2024-08-10T10:20:19.254Z] Movies recommended for you: [2024-08-10T10:20:19.254Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T10:20:19.254Z] There is no way to check that no silent failure occurred. [2024-08-10T10:20:19.254Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (20136.310 ms) ====== [2024-08-10T10:20:19.254Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-08-10T10:20:20.014Z] GC before operation: completed in 138.113 ms, heap usage 80.708 MB -> 53.250 MB. [2024-08-10T10:20:24.453Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T10:20:27.956Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T10:20:32.512Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T10:20:36.001Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T10:20:38.538Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T10:20:41.061Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T10:20:43.595Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T10:20:46.123Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T10:20:46.912Z] 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. [2024-08-10T10:20:46.912Z] The best model improves the baseline by 14.52%. [2024-08-10T10:20:46.912Z] Movies recommended for you: [2024-08-10T10:20:46.912Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T10:20:46.912Z] There is no way to check that no silent failure occurred. [2024-08-10T10:20:46.912Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (26933.339 ms) ====== [2024-08-10T10:20:46.912Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-08-10T10:20:46.912Z] GC before operation: completed in 102.222 ms, heap usage 443.315 MB -> 54.280 MB. [2024-08-10T10:20:50.399Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T10:20:55.147Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T10:20:58.664Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T10:21:02.171Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T10:21:03.811Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T10:21:06.333Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T10:21:08.909Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T10:21:10.536Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T10:21:11.321Z] 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. [2024-08-10T10:21:11.321Z] The best model improves the baseline by 14.52%. [2024-08-10T10:21:11.321Z] Movies recommended for you: [2024-08-10T10:21:11.321Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T10:21:11.321Z] There is no way to check that no silent failure occurred. [2024-08-10T10:21:11.321Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (24504.636 ms) ====== [2024-08-10T10:21:11.321Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-08-10T10:21:11.321Z] GC before operation: completed in 74.699 ms, heap usage 139.182 MB -> 50.566 MB. [2024-08-10T10:21:13.838Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T10:21:15.458Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T10:21:18.952Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T10:21:21.482Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T10:21:24.009Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T10:21:26.536Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T10:21:29.071Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T10:21:31.597Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T10:21:32.391Z] 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. [2024-08-10T10:21:32.391Z] The best model improves the baseline by 14.52%. [2024-08-10T10:21:32.391Z] Movies recommended for you: [2024-08-10T10:21:32.391Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T10:21:32.391Z] There is no way to check that no silent failure occurred. [2024-08-10T10:21:32.391Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (20894.132 ms) ====== [2024-08-10T10:21:32.391Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-08-10T10:21:32.391Z] GC before operation: completed in 139.191 ms, heap usage 153.528 MB -> 50.826 MB. [2024-08-10T10:21:36.943Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T10:21:40.453Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T10:21:45.661Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T10:21:49.177Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T10:21:50.811Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T10:21:52.433Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T10:21:54.051Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T10:21:56.575Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T10:21:56.575Z] 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. [2024-08-10T10:21:56.575Z] The best model improves the baseline by 14.52%. [2024-08-10T10:21:57.361Z] Movies recommended for you: [2024-08-10T10:21:57.361Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T10:21:57.361Z] There is no way to check that no silent failure occurred. [2024-08-10T10:21:57.361Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (24671.090 ms) ====== [2024-08-10T10:21:57.361Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-08-10T10:21:57.361Z] GC before operation: completed in 145.501 ms, heap usage 407.554 MB -> 54.384 MB. [2024-08-10T10:22:01.907Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T10:22:06.498Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T10:22:09.986Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T10:22:14.536Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T10:22:17.071Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T10:22:19.618Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T10:22:22.151Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T10:22:24.688Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T10:22:24.688Z] 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. [2024-08-10T10:22:24.688Z] The best model improves the baseline by 14.52%. [2024-08-10T10:22:25.477Z] Movies recommended for you: [2024-08-10T10:22:25.477Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T10:22:25.477Z] There is no way to check that no silent failure occurred. [2024-08-10T10:22:25.477Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (27904.383 ms) ====== [2024-08-10T10:22:25.477Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-08-10T10:22:25.477Z] GC before operation: completed in 98.479 ms, heap usage 340.939 MB -> 50.855 MB. [2024-08-10T10:22:28.970Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T10:22:32.487Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T10:22:37.063Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T10:22:41.217Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T10:22:43.765Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T10:22:46.296Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T10:22:48.829Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T10:22:50.452Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T10:22:51.243Z] 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. [2024-08-10T10:22:51.243Z] The best model improves the baseline by 14.52%. [2024-08-10T10:22:51.243Z] Movies recommended for you: [2024-08-10T10:22:51.243Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T10:22:51.243Z] There is no way to check that no silent failure occurred. [2024-08-10T10:22:51.243Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (25788.526 ms) ====== [2024-08-10T10:22:51.243Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-08-10T10:22:51.243Z] GC before operation: completed in 92.500 ms, heap usage 96.284 MB -> 50.818 MB. [2024-08-10T10:22:53.770Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T10:22:57.277Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T10:23:01.838Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T10:23:04.374Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T10:23:06.005Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T10:23:07.638Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T10:23:10.304Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T10:23:11.933Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T10:23:11.933Z] 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. [2024-08-10T10:23:11.933Z] The best model improves the baseline by 14.52%. [2024-08-10T10:23:11.933Z] Movies recommended for you: [2024-08-10T10:23:11.933Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T10:23:11.933Z] There is no way to check that no silent failure occurred. [2024-08-10T10:23:11.933Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (21056.402 ms) ====== [2024-08-10T10:23:11.933Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-08-10T10:23:11.933Z] GC before operation: completed in 95.155 ms, heap usage 108.513 MB -> 50.914 MB. [2024-08-10T10:23:15.431Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T10:23:18.927Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T10:23:22.434Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T10:23:25.948Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T10:23:28.471Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T10:23:31.589Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T10:23:33.227Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T10:23:35.783Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T10:23:36.575Z] 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. [2024-08-10T10:23:36.575Z] The best model improves the baseline by 14.52%. [2024-08-10T10:23:36.575Z] Movies recommended for you: [2024-08-10T10:23:36.575Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T10:23:36.575Z] There is no way to check that no silent failure occurred. [2024-08-10T10:23:36.575Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (24137.289 ms) ====== [2024-08-10T10:23:36.575Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-08-10T10:23:36.575Z] GC before operation: completed in 168.025 ms, heap usage 97.905 MB -> 53.198 MB. [2024-08-10T10:23:41.141Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T10:23:44.787Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T10:23:49.382Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T10:23:52.910Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T10:23:55.447Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T10:23:57.975Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T10:24:00.509Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T10:24:02.145Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T10:24:02.938Z] 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. [2024-08-10T10:24:02.938Z] The best model improves the baseline by 14.52%. [2024-08-10T10:24:02.938Z] Movies recommended for you: [2024-08-10T10:24:02.938Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T10:24:02.938Z] There is no way to check that no silent failure occurred. [2024-08-10T10:24:02.938Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (26318.347 ms) ====== [2024-08-10T10:24:02.938Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-08-10T10:24:02.938Z] GC before operation: completed in 172.444 ms, heap usage 442.355 MB -> 54.310 MB. [2024-08-10T10:24:07.493Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T10:24:11.014Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T10:24:15.586Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T10:24:19.084Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T10:24:20.713Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T10:24:22.337Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T10:24:24.518Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T10:24:26.141Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T10:24:26.141Z] 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. [2024-08-10T10:24:26.141Z] The best model improves the baseline by 14.52%. [2024-08-10T10:24:26.925Z] Movies recommended for you: [2024-08-10T10:24:26.925Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T10:24:26.925Z] There is no way to check that no silent failure occurred. [2024-08-10T10:24:26.925Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (23588.823 ms) ====== [2024-08-10T10:24:26.925Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-08-10T10:24:26.925Z] GC before operation: completed in 99.424 ms, heap usage 118.268 MB -> 51.052 MB. [2024-08-10T10:24:30.437Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T10:24:33.938Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T10:24:37.460Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T10:24:42.034Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T10:24:44.563Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T10:24:46.198Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T10:24:48.739Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T10:24:51.272Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T10:24:52.059Z] 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. [2024-08-10T10:24:52.059Z] The best model improves the baseline by 14.52%. [2024-08-10T10:24:52.059Z] Movies recommended for you: [2024-08-10T10:24:52.059Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T10:24:52.059Z] There is no way to check that no silent failure occurred. [2024-08-10T10:24:52.059Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (25558.441 ms) ====== [2024-08-10T10:24:53.687Z] ----------------------------------- [2024-08-10T10:24:53.687Z] renaissance-movie-lens_0_PASSED [2024-08-10T10:24:53.687Z] ----------------------------------- [2024-08-10T10:24:53.687Z] [2024-08-10T10:24:53.687Z] TEST TEARDOWN: [2024-08-10T10:24:53.687Z] Nothing to be done for teardown. [2024-08-10T10:24:53.687Z] renaissance-movie-lens_0 Finish Time: Sat Aug 10 10:24:52 2024 Epoch Time (ms): 1723285492863